Analyses on condom evidence: Condom brand profiling via HS-SPME-GC-MS and temperature-brand effect on condom fingerprint development
by
Amanda Patrick, B.S.
A Thesis
In
Forensic Sciences
Submitted to the Graduate Faculty of Texas Tech University in Partial Fulfillment of the Requirements for the Degree of
MASTER OF SCIENCES
Approved
Paola Prada, Ph. D. Chair of Committee
Kathy Sperry, Ph. D.
Megan Thoen, Ph. D.
Mark Sheridan, Ph. D. Dean of the Graduate School
December, 2018
© 2018, Amanda Patrick
Texas Tech University, Amanda Patrick, December 2018
Acknowledgments
The authors of this study would like to thank the participants who made this study possible.
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TABLE OF CONTENTS ABSTRACT ...... vi
LIST OF TABLES ...... viii
LIST OF FIGURES ...... ix
LIST OF ABREVIATIONS ...... xi
1. Introduction ...... 1
1.1.Statement of Objectives ...... 2
1.1.1. Fingerprints on Condoms ...... 2 1.1.2. Condom Brand Identification...... 3
2. Literature Review ...... 5
2.1.Impact of Evidence in Sexual Assault Cases ...... 5
2.1.1. Limitations in Investigation ...... 6 2.1.2. Forensic Evidence ...... 16 2.2.Basic Condom Production ...... 22
2.3.Substrate effect on Fingerprint Development ...... 23
2.3.1. Challenging Substrates ...... 24 2.3.2. Variation of Developmental Methods ...... 24 2.3.3. Challenges with Single Types of Substrates ...... 27 2.3.4. Environmental Conditions & Development with Powders ...... 31 2.4.Chemical Characterization of Condoms ...... 32
2.4.1. Previous Methods Used for Identifying Condom Brands and Lubricants ...... 32 2.4.2. Gas Chromatography-Mass Spectrometry ...... 35 2.4.3. Solid Phase Microextraction ...... 39 2.4.4. SPME and Plastics ...... 42 2.4.5. Principle Component Analysis...... 46 2.5.Hypotheses ...... 49
2.5.1. Temperature Variation on Fingerprint Development ...... 49 2.5.2. Condom Brand Identification...... 50
3. Methods ...... 52
3.1.Temperature Effect on Fingerprint Development ...... 52
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3.1.1. Materials ...... 52 3.1.2. Experimental Procedures ...... 53 3.1.3. Inter-person Variability ...... 57 3.1.4. Dye Staining ─ Rhodamine 6G ...... 58 3.2.Condom Brand Identification using HS-SPME ...... 58
3.2.1. Materials and Standard Instrumental Procedures ...... 58 3.2.2. Experimental Procedures ...... 60 3.3.Data Collection and Analyses ...... 63
3.3.1. Condom Brand SPME Profiling ...... 63 3.3.2. Fingerprint Development ─ Temperature Effect ...... 63
4. Results ...... 64
4.1.Temperature-Brand Effect on Fingerprint Development ...... 64
4.1.1. Magnetic Powder ...... 64 4.1.2. Inter-person Variability ─ Magnetic Powder ...... 67 4.1.3. Rhodamine 6G ...... 69 4.1.4. Inter-person Variability-Rhodamine 6G ...... 73 4.2.Condom Brand Identification via HS-SPME-GC-MS ...... 75
4.2.1. Fiber and Sampling Time ...... 75 4.2.2. Brand identification ...... 78
5. Discussion ...... 82
5.1.Temperature analysis on Fingerprint Development ...... 82
5.2.Identification of Condom Brands ...... 85
5.3.Conclusion ...... 88
References ...... 91
Appendix I: Photographs and Scores of Developed Fingerprints ...... 98
Magnetic Power ...... 99
15ºC ...... 99
24ºC ...... 101
40ºC ...... 103
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Magnetic Powder ─ Population ...... 106
Rhodamine 6G ...... 111
15ºC ...... 111
24ºC ...... 113
40ºC ...... 115
Rhodamine 6G ─ Population ...... 118
Appendix II: Compound Data and Chromatograms ...... 123
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ABSTRACT
Condoms are a challenging substrate as an evidentiary item since they do not
hold a determined shape and fundamental composition may vary depending on the
brand. Developmental variables in regard to condoms substrates were investigated to
optimize latent print methodologies. Fingerprints were deposited onto condoms of
various brands, exposed to different temperatures, and developed with superglue
fuming, magnetic powder, and Rhodamine 6G (R6G). For magnetic powder, results indicated that the highest average fingerprint score was obtained on condoms stored in
15°C temperatures. With R6G, the average fingerprint score was higher for Durex brand condoms processed at an elevated temperature of 40°C. Fingerprint development scores were the lowest on Crown brand condoms, but out of all the tested brands, development with R6G after stored in cool temperature had the highest average score. These differences indicate that optimal fingerprint development is achieved by using the method that regards substrate and environment conditions.
As indicated by differences in fingerprint development on different brands of condoms, brand details can be relative information not only as an artifact of information to a case but as a variable of analytical interest when applying forensic methodologies to these substrates. To make condom brand profiling more practical, methods that involve relatively fewer procedural steps and less manipulation of the sample should be evaluated. Condoms were sampled using a simple sampling procedure, solid phase microextraction (SPME), and analyzed using gas chromatography-mass spectrometry (GC-MS). Sampling conditions were tested by sampling a single brand of condoms with various SPME fibers: PA, PDMS,
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DVB/PDMS, CAR/PDMS, and DVB/CAR/PDMS - and different sampling times: 1 hr., 3 hrs., 6 hrs., 12 hrs., and 24 hrs. Other sampling conditions including exposure to
temperatures, 35ºC and 70ºC, were also tested. DVB/CAR/PDMS at 12 hrs. was the sampling condition that achieved the greatest number of unique compounds with the least sampling time. Using these sampling conditions, condom brands, Durex,
LifeStyles, and Crown were sampled. Using principle component analysis and hierarchical clustering with the chemical profile of each sample, the brands were able to be discriminated.
KEYWORDS: Latent Fingerprints, Development, Condoms, Solid-Phase Microextraction, Brands, Discriminate
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LIST OF TABLES
Table 2.3.1. Plastic substrates and their variable chemical structures ...... 30
Table 3.1.1 Condoms brands tested ...... 53
Table 3.1.2 Fingerprint Development Scoring with Description [74] ...... 57
Table 3.2.1 Supelco® SPME fibers...... 59
Table 3.2.2 Conditioning parameters for each fiber ...... 59
Table 3.2.3 Combination of variables tested at room temperature for sampling optimization. .... 60
Table 3.2.4. Additional variables tested at varying temperatures ...... 61
Table 3.2.5. Gas chromatogram-mass spectrometry parameters (Adapted from [6]) ...... 62
Table 4.1.1. Overall averages per temperature-brand combination ...... 67
Table 4.1.2. Averages for each temperature-brand combination after subsequent development with R6G ...... 73
Table 4.2.1. Coordinates indicating relationship between each principle component ...... 79
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LIST OF FIGURES
Figure 2.3.1.Variables involved in the fingerprint development quality ...... 24
Figure 2.4.1. Electron Impact ionization (left) [59], and atom ionization illustration (right) [60]...... 38
Figure 2.4.2. Fiber rod in normal state (1) and in injection mode (2)...... 40
Figure 2.4.3. Principle Component Analysis Results Interpretation ...... 49
Figure 3.1.1. Condoms after superglue fuming being prepared for powdering ...... 54
Figure 3.1.2. White light source and thin flexible wire utilized for visualization and photographing developed fingerprints after development with superglue fuming and magnetic powder ...... 56
Figure 3.2.1. Sampling headspace of condom substrates with various fibers: PA, PDMS, DVB/PDMS, CAR/PDMS, and DVB/CAR/PDMS ...... 61
Figure 4.1.1. Overall averages per storage temperature after superglue fuming and magnetic powdering...... 65
Figure 4.1.2. Overall averages per brand after development with superglue fuming and magnetic powder ...... 66
Figure 4.1.3. Prints developed on Lifestyles stored in 40ºC after development with superglue fuming and magnetic powdering ...... 66
Figure 4.1.4. Box and whisker plot of five-print averages from deposits of N = 20 males, stored in 15ºC, and developed with superglue fuming and magnetic powder ...... 68
Figure 4.1.5. Distribution of five-print average sores among N = 20 sample after processing with superglue fuming and magnetic powder ...... 69
Figure 4.1.6. Highest scored prints from a population study (N = 20 males) on LifeStyles which was stored in 15ºC and subsequently developed with superglue fuming and magnetic powder ...... 69
Figure 4.1.7. Fingerprint development with the highest five-print averages after development with superglue fuming, magnetic powder, and rhodamine 6G...... 70
Figure 4.1.8. Overall averages per storage temperature after subsequent rhodamine staining ..... 71
Figure 4.1.9. Overall averages per brand after subsequent development with rhodamine 6G...... 72
Figure 4.1.10. Box and Whisker plot of deposits of N = 20 males, stored in 15ºC, and developed subsequently with Rhodamine 6G...... 74
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Figure 4.1.11. Distribution of five-print average scores among N = 20 sample after subsequent processing with Rhodamine 6G...... 74
Figure 4.2.1. Relative abundances of select compounds detected in LifeStyles for each fiber sampled at 1 hr., 3 hrs., 6 hrs., 12 hrs., and 24 hrs...... 76
Figure 4.2.2. Relative abundances of select compounds detected from LifeStyles for each fiber sampled for 0.5 hrs. at 35ºC and 70ºC ...... 77
Figure 4.2.6. Number of compounds detected for each fiber after 1 hr., 3 hrs., 6 hrs., 12 hrs., and 24 hrs. sampling times ...... 78
Figure 4.2.7. Principle component analysis of condoms brands according to relative abundances of different compounds detected ...... 79
Figure 4.2.8. Heat map and dendrogram of compounds and condom brands ...... 81
Figure 5.2.1. Chemical structure of N,N-dibutyl-formamide [77] ...... 85
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LIST OF ABREVIATIONS
SPME Solid-Phase Microextraction
CAR Carboxen
DVB Divinylbenzene
PDMS Polydimethylsiloxane
GC-MS Gas Chromatography-Mass Spectrometry
PCA Principle Component Analysis
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1. Introduction
The ramifications of sexual assault crimes have caused question on how the criminal justice system should respond to increase awareness, deterrence, and effectivity of forensic evidence [1]. Forensic evidence found in sexual assault scenes consists of typical evidence including fingerprints, broken glass, or hair to more sophisticated evidence including saliva, semen, or DNA. To piece together a comprehensive investigation, all types of evidence should be considered, so if any target evidence is misconstrued, other evidence can be used to supplement evidence that deduces possible events. Unfortunately, in sexual assault cases, non-DNA trace evidence, such as evidence like lubricants, are frequently overlooked [2].
Methods for collecting and analyzing forensic evidence are not generally standardized in order to appropriately minimize discrepancy, and as a result, research has been implemented to formulate established protocols in all forensic science disciplines
[3]. Optimistically, improvements would include finding new methods that are time efficient and accurate with minimum destruction of evidence. That is, one forensic method should not alter the evidence rendering it unusable for another possible method.
There have been studies delineated the need to improve analytical methods. For example, the Paul Coverdell National Forensic Sciences Improvement Act [4] discussed the need for improving forensic science methods with regard to upbringing DNA evidence. This act approaches some of the problems with the forensic applications of DNA including
DNA backlogs in computer systems, lack of funding, and quality of forensic practices.
While information deducted from other forensic disciplines may not be as seemingly prevailing as DNA, these can have just as much probative value in their own right.
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The FBI reported that an estimated 90,185 rape cases were reported to law enforcement in 2015 which was 6.3 % higher than what was estimated for 2014. For
2017 this number has increased to 121,745 rape cases which is 3.5% higher than rape cases reported for 2016 [5]. While some offenders of rape may carelessly leave behind biological fluids or expose themselves to sexually transmitted deceases, other offenders may be more proactive in mitigating these factors. One of the easiest ways to mitigate is by using a condom. As more offenders implement this, the prevalence of the use of condoms by an offender may be increased. Condoms may be found in non-sexually related circumstances or sexually related circumstances. Non-sexually related circumstances can include situations involving the utilization of condoms for unconventional purposes (e.g., packaging of controlled substance). Sexually related circumstances can include rape or attempted rape. In all circumstances, non-DNA analysis may be needed to optimize amount of obtained information. If biological fluids are found, DNA analysis would be possible. However, in circumstances that DNA is too degraded or biological fluids are absent, then other analyses would have to be implemented. Information pertaining to brand of condom and latent fingerprints would be useful in providing a more comprehensive, time effective means to gather evidence.
1.1. Statement of Objectives
1.1.1. Fingerprints on Condoms
Fingerprints are a traditional means of identification that has procedural advantages over other means of identification with regards to time and cost. Though the use of fingerprints as evidence has been around for so long, the need for research and methodology improvement in their use is crucial for optimizing the practicality of this
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evidence in the field and avoiding unnecessary misleads or stalling in criminal investigations. The development of fingerprints at crime scenes involves knowing what fingerprint development method is best for each environmental and substrate condition.
With so many variations in substrates and possible development techniques, the decision for the best methodology is usually at the discretion of fingerprint analysts. They make those decisions based on training, experience, and research. Condoms, in particular, are a challenging substrate since they do not hold a determined shape and fundamental components may vary depending on the brand. Accordingly, developmental variables in regard to condoms substrates should be investigated.
1.1.2. Condom Brand Identification
Research on determining condom brands has involved varying techniques in extracting compounds from known condoms [2] and using different instruments to separate and identify the compounds [6]. Though there are previously explored methods for identifying condom brands [6], they include limitations such as practicality since they are either time consuming or relatively expensive. In general, extracting compounds from a sample can be laborious and time consuming since it requires multiple time-consuming steps that can require altering all or part of the original sample. This has spurred an initiative to find more practical ways to extract and identify condoms constituent compounds that are just as effective as the traditional methods. This initiative has led to the emergence of new techniques that simplify the extraction and sample preparation steps. One example of these techniques is solid phase microextraction (SPME), introduced in the 1990s [7]. This technique utilizes the compounds that are released or volatized from the sample. SPME extracts these released components with a polymer and
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can be released out of the polymer for analyzation. This technique requires less preparation steps than other traditional extraction methods. As a result, the applications of
SPME are being explored and are being utilized in forensic sciences [6, 8-14]. Due to the challenging nature of the substrate of condoms, SPME application in the forensic analysis of identifying condom brands needs to be investigated.
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2. Literature Review
2.1. Impact of Evidence in Sexual Assault Cases
Sommers and Baskin [15] state that “rape is one of the most frequently committed
violent felonies…however, it is also one of the most underreported” (p. 314). With the limitation of available information in rape cases, optimizing procedures utilized for evidence collection is imperative to execute due diligence in uncovering the truth. The more probative information obtained, the more likely that a correct and efficient pool of suspects can be acquired.
Sommers and Baskin [7] contend that the belief that advancing scientific technology will increase the likelihood of conviction is unsubstantiated with the little research there is on the impact of evidence in sexual assault cases. Inductively, the dependency of new scientific methodologies to overcome the shortcomings of sexual assault cases will not commensurate for consequences caused by present insufficient protocols (i.e., improper utilization in court or faulty forensic judgments). According to
Sommers and Baskin [15], studies on rape cases have supported that to move cases forward to the trial stage, legal factors including weapons, injuries, and forensic evidence are generally more essential than the characteristics of the victim or assailant, but the influence of these factors will depend on the processing stage. In processing rape cases, the authors state that the value of forensic evidence varies. To determine how forensic evidence plays a role in sexual assault cases, scientific aspects of the forensic evidence should be examined as well as the impression the evidence has on the police, lawyers, and potential juries. For comprehensive understanding of the effect of forensic evidence,
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the significance of the evidence at each stage of case process have to be accounted for
[15].
2.1.1. Limitations in Investigation
2.1.1.1. Nature of Cases
Sexual assault refers to a wide range of sexual offenses that includes penetrative
offenses (i.e., rape) and nonpenetrative offenses [16]. A sexual offense can include no
touch offenses. Hence, a sexual offense is not necessarily a sexual assault, and a sexual
assault is not necessarily rape. As with all types of cases, sexual assault cases follow a
funnel effect where out of many cases only a few reach the conviction stage [15].
Variables including victim and suspect circumstances, legal factors, sociological
circumstances, and the amount of available evidence can help shape the nature of the case
and, accordingly, affect whether these types of cases proceed.
The vast amount of cases that can be classified as sexual assault are not defined
under in a consistent manner. Capers [17] articulates that the varying definitions of rape is a problem because of the effect on the variations of reporting. Daly and Bouhours [16]
point out that the reported rates of rape convictions are widely variable, and this can be
attributed to the varying definitions of rape that have been affected by social and political
factors. Policies that define how sexual assault cases are handled can be affected by
current incentives. As these incentives are pushed, the way cases are reported can change,
and this, in turn, can change the way sexual assault data are perceived. Daly and
Boubours state that laws and legal procedures have been affected by declining conviction
rates, questionable investigations, and poor treatment of victims. If sexual assaults are not
being processed effectively through the criminal justice system, then offenders will less
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likely be convicted. If victims are not being treated fairly, then victims will feel less
incentive to report crimes. Conviction and attrition estimates of sexual assault cases will depend on location, offense type and the age of the victim [16]. How cases are sustained from the police to the court will depend on the context of the case, and not every state, police department, or lawyer will process cases the same way.
2.1.1.2. Case Processing
Factors associated with sexual assault cases include the victim’s character, the
victim’s credibility, the length of time between the incident and the report, and the
relationship between the victim and alleged offender [16]. According Sommers and
Baskin [15], credibly can be dependent on the victim’s age and the relationship of the
victim to the assailant. Conviction and level of uncertainty will depend on how credible the witnesses appear and how the alleged perpetrator appears to have been able to commit the crime [15]. Sommers and Baskin [15] studied outcomes (i.e., arrest, referral to prosecutor, charge, and/or conviction) of 381 sexual assault cases in Los Angeles and
Indianapolis in 2003. All the victims were female, and all suspects were male. Within the
victims-44%, 41%, and 31% were Black, White, and Latino, respectively. They found
that in situations where the victim knew the perpetrator, the mean time from the incident
to the report was four days and mean time from the report to the arrest was three days. In
situations where the victim did not know the perpetrator, the mean time from the incident to the report was nine days, and mean time from the report to the arrest was 42 days. The
authors contend that the lawyers’ perceptions of likelihood of conviction is a likely reason for the decrease in cases that make it to the prosecution stage.
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Sommers and Baskin [15] demonstrate the gatekeeper roles of police officers in the process of referring a case to the district attorney (DA). They articulate three decisions police officers make in sexual assault. The decisions are “whether the rape incident is substantiated”, “whether they are going to use formal social control and arrest the suspect”, and whether “to refer the case to the DA” (p. 330). The results in their study suggested that the reasons why officers did not refer the cases studied was related with victim cooperation, availability of the victim and the amount of evidence that corroborated the report. The case referral process was hindered by factors including victims uncooperating in 24% of cases, victim unavailability in 26% cases, and lack of evidence in 45% of cases (p. 330). It was concluded that perceptions of the case being real or being serious would likely directly influence referral and indirectly influence referral if the victim decided to no longer cooperate. Victim credibly was suggested to be dependent on presence of injuries that corroborate the report, because these injuries could help “counteract juror skepticism” (p. 330). Data did not support that there was an association between victim-suspect relationships and whether the cases were being charged, but data did support relationship with regard whether the suspect was arrested.
The authors suggested that this could be a result of the suspect being more easily identified.
In another study, victimization surveys were utilized to determine case processing factors. Daly and Bouhours [16] studied victimization surveys in five areas (Australia,
Canada, England and Wales, Scotland, and the United States) over three decades, results showed that 14% of victims reported sexual violence. Of the 14% of case reported, 30% lead to a prosecution (p. 538). The United States and Scotland were the only countries
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shown to not have a decline in conviction rate. The authors suggested that for the United
States, this could be attributed to plea bargaining practices. For children and youth
victims, rate of conviction was 6.5% greater than adults which was 12%. The authors
stated out of all the cases that reached the prosecutor’s office that one-third of cases were
dropped because of reasons that included doubt that the case will win or the
unwillingness or inability for the victim to be a participate as a witness.
2.1.1.3. Stigmatizations
Stereotypes or stigmatizations can affect how the cases are processed and how they are presented in court. Some stigmatizations include how rape can be automatically perceived as being a false allegation, how fear of assault is used as a technique in the legal system, and how male rape is viewed indifferently. Philip [18] asserts that false
allegations is a problem, because it diverts “attention from genuine victims and may help
to create a dangerous skepticism among criminal justice professionals to all allegations of
rape” (p. 130). False rape allegations have had a considerable influence the criminal
justice system and, more particularly, trial proceedings [18]. The predetermination of
false accusations of rape has spurred legal policy that attempts to protect accused
defendants if, for example, evidence is not corroborated. While protecting the suspect
from being falsely accused is important, ignoring allegations solely because of lack of
evidence is not justified, because this condones the inclination for victims to not report
these types of offenses. This has also raised into question of the amount cases that police
have determined to be “unfounding”, and which of those cases were unjustly ignored
[18]. This indicates that evidence that infers false allegations needs to be addressed so
that police and courts can accurately address rape allegations.
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Capers [17] points out male rape (i.e., victim is male) is used strategically as a defense (known as a “gay panic” defense) or as “trash talk” by prosecutors or law enforcement. The gay panic defense consists of the defendant claiming to have enacted the crime because of panic caused by being around an individual with a perceptively abnormal sexual preference. This happened in State v. McKinney (1999), where
McKinney alleged that he murdered the victim, Matthew Shepard, because Shepard was making sexual advances at him. This also happened in Schick v. Indiana (1991), where
Schick killed Stephen Lamie by stomping him to death, because Lamie allegedly tried to touch him in a sexual manner. Accordingly, Schick was charged with voluntary manslaughter instead of murder. Capers [17] contends that this homicide could not have been committed the way it was contended, in the ”heat of passion”, because of the fact that Schick stole Lamie’s watch and wiped his fingerprints off the car. The author also pointed out that this kind of defense suggests that deadly force is a somewhat excusable response to sexual advances, even though, ironically, cases of male victim sexual assault seem to be handled in a less serious manner.
Another salient type of stigmatization in the legal process are stereotypes of sexual assault in prison. This has been condoned by social entities including social media and law enforcement [17]. Police using “trash talk” in reference to sexual assault can infer that the police, while conducting an interrogation, threatens that a stereotypical prison sexual assault could happen to them if they do not tell the truth [17] (p. 1285). For example, when a suspect is being interrogated, the interrogator may threaten that the suspect may have to spend time with “Bubba” in prison if they do not tell what happened.
Capers (pp. 1286-1287) states that this sort of interrogation violates due process, because
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threatening that a suspect is going to get sexually assaulted in prison is technically
threatening the use of force which was barred in Brown v. Mississippi [19]. This might
raise into question of whether information gained from these types of interrogations or if
information gained from the result of probable cause that resulted from such an
interrogation should be allowed in trial.
2.1.1.4. Male Victims
Capers [17] contends that male victimization happens daily, and it is not taken as
serious as it should. Not mentioning male-victim rape just because victims are mostly women is not justified, because the challenges of reporting male victims have to be considered along with the fact that sexual assault crimes are generally unreported for both males and females. Capers points out rape has been historically downplayed by using the
example of State v. Gounagias (1915) where case reporters “erased” the act of rape from
the case. In the case, Gounagias, a Greek immigrant, killed a countryman who raped him
while unconscious at a celebration. In the case report, the assault in the case was written
as being an unmentionable crime instead of rape.
The definition of rape is geared toward female victims substantiating the
indifference towards male victims. Accordingly, readjusting laws and social constructs to
make rape more gender neutral would force social and political groups to readjust their
thinking of rape as not just being solely a way that males marginalize women [17]. Even
so, gender neutral laws do not eliminate rape prosecutions that are stigmatized by gender,
because the stigma decreases the chances of the crime being reported in the first place.
Even if jurors do not likely want to convict on cases based on male victimization, the
acceptance of gender bias sexual assault is still not acceptable and prosecutors still need
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to forego prosecution. Capers [17] states that the increase of prosecutions would help destigmatize rape as being only a female victim crime by shifting expectations, and that expectations of force or resistance in rape cases for both male and females could improve if jurors knew that “even ‘real men’ often fail to resist” (p. 1306).
Capers contends that male rape victimization can be stigmatized to mostly be an occurrence in prisons or something that only happens to gay men, and when most male rape victims want to file a suit, they often do not have the resources. Even though crimes in prisons may not be considered as critical to society as those outside of prisons, crimes involving male victimization outside of prisons are viewed indifferently. Capers points out that the likelihood of becoming a victim of rape in prisons could be considered as a factor when deciding the length of sentences. That is, for example, a perpetrator of a white-collar crime might be sentenced for a shorter time if the likelihood of him being raped is taken into consideration. He also points out the controversy and concerns of this giving too much discretion to judges and establishing sentencing uncertainty but contends that these problems would push prison officials to make better policies that deter prison rapes. To implement this, racial disparity would have to be in check to make sure that white victim stigmatism is not causing a bias in black sentencing. He also contends that reduction of prison rape should be a priority to help address the problem of recidivism since exposing individuals to “lawless zones” (i.e., prisons) before releasing them would increase the chances of them reoffending (p. 1305).
For reasons including lack of reporting and disbelief, the occurrence of male victimization is likely underestimated [17]. Data collected for female rape victims are also highly variable, so how male victim cases are handled are not only affect by general
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problems women also have to face but also the stigmatism and bias of being a male. This
affects how they are reported. How they are reported could also be affected by conflicting
thoughts caused by being a male victim of a crime that is supposed to only happen to
women which can cause a male victim to report the sexual assault as a regular assault or,
in the case of prison rap, this can be caused by pressure caused by being stuck in the
same facility as the offender after reporting. Capers contends that correction officers
might also be more dismissive of the victim if he is gay or bisexual.
2.1.1.5.Eyewitness Testimony
Eyewitness testimony is direct evidence and can have substantiating effect if other
types of evidence corroborates it. Without corroborating evidence, eyewitness testimony
can still have a profound impact on the case, but it will not necessarily be helpful in
establishing facts since the current methodologies used have a high error rate. Eyewitness
identifications, depending on the nature of the sexual assault crime, can implement
different challenges in conducting valid methodologies. Memory reliability is inherent in
determining the accuracy of a witness’s account of an event and in making an
identification of an alleged perpetrator. Memory is complex; It can involve processes
such as encoding, consolidating, and retrieving [20], and it can be affected by many variables such as length of time that has passed, who the individual is recalling the memory to, and interfering new experiences. Memory illusions describe how an individual can misremember small details of events or even misremember an entire event, and these can be caused from reasons within the individual (endogenously) or reasons outside the individual (exogenously) [20, 21]. Such misinformation is termed as false memory. Despite the known insufficiencies of memory in the scientific community, there
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are some judicial employees who are ignorant of the science of memory, and this has led to misguided protocols that deal with memory practiced by law enforcement and the court.
Witness misidentification is a potential result of faulty memory accounts that can be guided by biased questioning and erroneous lineup procedures [22]. This has implemented an incentive to identify erroneous protocols such as the misguided interviewing techniques and the vague jury instructions about the reliability of eyewitness evidence. The method of identification and memory account is just as important as the information deduced. Wise and Safer [22] contend that an evaluation method should be used in order to determine if bias occurred during identification procedures. Furthermore, guidelines can help establish better instructions about eyewitness testimony to the jury.
Even though eyewitness testimony may be inevitable to help determine facts of a case, an established protocol based on research will help reduced the number of false convictions that are caused by eyewitness error.
Some exigent situations that involve testimony in sexual assault cases are when the witness is a child or when the witness is trying to remember events from a substantial length of time. Howe and Knott [20] demonstrate how three forensic contexts which include children as eyewitnesses, historic sexual abuse (HAS), and eyewitness misidentification have been associated with false memories of sexual assault. Children as eyewitnesses is an important context that involves memory, because some of the most heinous crimes are those that involve children. Howe and Knott explain that there can be a language barrier when interviewing children. Children can be more susceptible to suggestion, and accordingly, this can cause a potential for more inaccuracy especially if
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interviewing questions are nonobjective and are guided by the predetermined believes of the interviewer. Children also will not necessarily be able to interpret or report to another person if the interviewer is coercing them to give a certain answer which can result in misleading investigations [20].
In the study done by Vrij, Akehurst, Soukara and Bull [23], CBCA was used to compare children and adults (age groups: 5-6 years, 10-11 years, 14-15 years, and undergraduates with mean age of 22.37 years) who were lying and telling the truth about a simulated event. Higher scores indicated a higher level of credibility. Results showed that CBCA scores increased with age. CBCA scores were between liars and truth tellers were significantly different for children 5 and 6 years old and undergraduates.
Participants who were informed about CBCA obtained significantly higher scores than those uninformed indicating the possibility for informed liars to beat the test. This implies that for methods that employ criteria based analysis, younger participants scores should be expected to be lower, and higher scores are not necessarily a result from telling the truth since higher scores can be obtained if a liar knows about how the test works.
Howe and Knott use the McMartin Preschool case and the Wee Care Nursery case to demonstrate the erroneous protocols dealing with memory and identification. The
McMartin case involved allegations of preschool employees bringing preschool children to satanic rituals and abusing them [24], and the Wee Care Nursery case involved allegations of a women named Kelly Michaels sexually abusing preschool children (State v. Michaels, 1988). Both of these cases involved interviewing possibly involved children.
In both of these cases, none of the alleged perpetrators were convicted due to erroneous interviewing. The children were susceptible to reinforcement, question repetition, co-
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witness information, inviting speculation, and introducing new information. This rendered the investigations to be erroneous and inadmissible.
Historic sexual abuse (HAS) is another important context [20]. Cases of HAS have implemented questioning of the ability of a witness to recall childhood memories in adult terms, the ability to recover repressed memories, and the possibility of false memory implantation when implementing memory recovery techniques. Two cases that involved HSA were Borawick v. Shay [25] and Franklin v. Stevenson [26]. The first case involved a woman named Joan Borawick. She was uncovering memories by hypnosis.
The hypnosis resulted in her remembering a sexual assault while being forced into taking part into ritual acts by her relatives in the past. Franklin v. Stevenson involved a woman named Cherese Franklin recovering memories of her older cousin abusing her. Both cases ended up being dismissed due to lack of credibility of the memory retrieval techniques.
2.1.2. Forensic Evidence
2.1.2.1. Prevalence of Evidence
Not all evidence makes it to trial. Evidence that makes it to trial will depend on how it was prioritized through the system from collection to the laboratory and to the prosecution. In the study by Sommers and Baskin [15], where 381 sexual assault cases in
2003 in Los Angeles and Indianapolis were analyzed, results indicated that forensic evidence had more of an “auxiliary, occasional, and non-determinative” role in most sexual assault case (p. 331). Of all the cases, 45% involved intimate relationships or family, 35% involved friends or acquaintances, and 19.2 % involved strangers. Within all the cases, 63.5% received medical treatment, and 49% had the victim participate in investigations.
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Forensic evidence was collected in about 60% of the all the cases. Biological evidence (sexual assault kit, blood, semen, DNA, or saliva) made up 46.7% of all the cases that had evidence. Natural or Synthetic materials such as clothes, bedding, carpet, and binding were in 38.8%. Trace evidence which included hair, paper, glass, cigarettes, plastic, metal, or soil were in 4.5% of cases. Fingerprints were in 5%. Drugs were in
0.5%.
Out of all the evidence collected, about 70% were submitted to the laboratory, and out of those submitted to the laboratory, about 53.5% were examined. This could have been a result from evidence backlogs or insufficiencies of the evidence. Data also revealed that cases with forensic evidence were more likely to lead to an arrest. Presence of forensic evidence did not seem to effect whether cases were more likely to be referred to the district attorney. Of all cases that were referred, 54% of cases with forensic evidence lead to a charge while only 28% of cases without evidence lead to a charge.
Whether the victim received medical treatment and length of time between the incident and the arrest was shown to have a great effect on whether the suspect was charged.
Arrests that occurred within 10 minutes of the incident were more likely to be charged.
Out of all the rape dispositions 70% resulted in a plea bargain and 23% by trial. Of the cases that went to trial, 92.3% included forensic evidence. Whether the victim received medical treatment seemed to have a large effect on whether the case was plea-bargained or went to trial.
Of all the 19.2 % stranger-rape cases, 65.8% had forensic evidence. Conviction rate was 10.4%, and none of the cases that lacked forensic evidence led to a conviction.
These rape cases were 24 times more likely to lead to an arrest if forensic evidence was
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present (p. 328). Overall, the results indicated the case outcomes did not necessarily
depend on presence of forensic evidence since out of all the six cases where evidence
linked the suspect and victim, only one resulted in a conviction (p. 331).
2.1.2.2. Documentation
In court, the defense may seek to gain access to documentation concerning the victim. This can consist of notes from therapists, social workers, doctors, and other examiners [27]. The defense may use information gained from documents to try to discredit the victim. This can be a problem if this deters victims from seeking treatment for fear of being ridiculed. This also concerns ethical responsibilities of mental health specialists whose goals might conflict with the goals of the court [28]. Temkin [27]
contends that rape counselling records are generally not material, because the record
focuses on “the client’s state of mind, her feeling, her distress”. Such a record contains
what the therapist interpreted and does not necessarily contain a reliable depiction of
what occurred at the scene. If the victim is having mental conflictions that result in them
blaming themselves, then the report may be misleading, because such information will
not be necessarily representative of external reality [27].
2.1.2.3. Individual Evidence
Individual evidence constitutes evidence that can characterized as coming from
one source. This type of evidence in sexual assault cases can include DNA and
fingerprints. The Paul Coverdell National Forensic Sciences Improvement Act (2000)
established the need for improvements and the important upbringing DNA evidence. This
act approaches some of the problems with the forensic applications of DNA including
DNA backlogs in computer systems, lack of funding, and quality of forensic practices.
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In a study by Baskin and Sommers [29] that surveyed registered voters in
California, results indicated 89.5% respondents believed that DNA evidence was the
most reliable. Fingerprints were considered the second most reliable followed by medical
expert testimony, police testimony, victim testimony, and expert testimony. Without
scientific evidence, more than half of the respondents said they would still convict for a
rape or murder case. Baskin and Sommers state that this is directly related to their crime
show viewing habits, and that attorneys and judges will need to consider these
predispositions. The impact of conviction despite the lack of evidence potentially could
include convicting innocent people.
Every method and type of evidence involves limitations. Page, Taylor and
Blenkin [30] state that instances where experts contend that their method is extremely reliable can result in their testimony being excluded, as such reliability is unrealistic for certain procedures. Studies have been done to evaluate the factors contributing to the weight of fingerprint evidence in order to bring more transparency and help courts be able to more properly evaluate the evidence since the reliability of fingerprint evidence has been brought into question [31]. Neumann et. al. [31] suggest that a quantitative
method would be helpful in determining the weight.
2.1.2.4. Class Evidence
Class evidence constitutes evidence that can be associated with a group of other
things. Some important types of class evidence in sexual assault cases include drugs and
trace evidence. Drugs are particularly important in drug-rape cases. The detection of date-
rape drugs will depend on the other contaminates in the sample, and the sensitivity of the
test [32]. Just because a test result is negative does not necessarily mean that drugs were
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not present just that the instrument was unable to detect them. In addition, the amount of time between intake and testing also affects the instrument’s ability to detect drugs.
Jenkins and Schuller [32] contend that with the increasing concern for drug-facilitated sexual assaults, factors such as expert testimony, victim intoxication, the absent forensic evidence (i.e., negative test results) affect the jury. These factors have to be taken into account along with the challenges of when forensic evidence is unavailable, there are no physical injuries, or if the victim does not have a clear memory of the event.
The study by Jenkins and Schuller [32] used 171 undergraduate students from 18 to 51 years old where 41% personally knew a sexual assault victim, 6% knew a drug facilitated sexual assault (DFSA) victim, and 7% has been a victim of sexual assault were presented with one of six sexual assault reports that differed in the presence of forensic evidence, whether an expert testified and whether the victim consumed alcohol. The report that the participants reviewed consisted of a description of events that took place according to a male defendant and a female victim. The dispute was whether the victim was drugged and whether nonconsensual sex occurred. Out of all participants, 80% found the defendant not guilty. Results indicated that regardless of whether the victim was known to drink alcohol or not, those who received the forensic report but no expert testimony were less likely to find the defendant guilty. Women were estimated to be more likely to choose guilty, and men were more likely to choose not guilty.
Trace evidence can be helpful in establishing objective facts in which subjective information can be interpreted. Trace evidence in sexual assault cases can include hair, fibers, and other substrates that may be present during a sexual assault. As sex offenders become more aware of the likelihood of catching sexually transmitted diseases or the
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ability of forensic scientists to connect them to a crime by DNA analysis by collecting biological fluids, they may be more likely to use condoms when committing a sexual crime [2].
2.1.2.5. Value of Circumstantial Evidence
Physical evidence generally constitutes another class of evidence known as circumstantial evidence which requires inference to prove a fact. Physical evidence is crucial in cases involving stranger rape cases, because the victim is not familiar with the perpetrator and accordingly will not as likely be able to identify the perpetrator. Forensic evidence found in sexual assault scenes can range from typical evidence including fingerprints, broken glass, or hair to more sophisticated evidence including saliva, semen or DNA [2]. Any type of forensic evidence is usually at its most optimal state of worth when it is corroborated by other evidence. Cases can get complicated when they are based on a single piece of evidence, because there is not as much objective information to substantiate or refute theories. Unless that evidence is DNA, there are many variables to consider that otherwise indicate reasonable doubt. Different types of evidence differ in strength and accordingly, should not be pushed to fit the case. The presentation of evidence should not deceive others in its reliability, and standards of admissibility should require that limitations be presented along with the evidence.
Physical evidence found at a sexual assault crime scene depend on the circumstances of the case. It can be of value, especially when it supports or refutes a suspect’s allegations. Sommers and Baskin [15] state that in cases that involve two strangers, forensic evidence will have greater potential in identifying the assailant. They also state that cases will more likely move forward to trial if there is corroborating
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evidence, where credibility, cooperation, and culpability is not hindered. It was suggested that victim-suspect relationship should be used in deciding which types of forensic evidence to prioritize since, evidence linking the suspect and victim is not always going to decisively prove sexual assault. For example, DNA evidence is not going to be as probative in cases where the victim was having conceptual relationship with the suspect.
2.2. Basic Condom Production
Condoms which are among other potential types of physical evidence in a sexually related scene may provide information that may provide leads or corroborative information. Information about how these substrates are made will be useful in determining what physical state a condom can be expected to be found in. Condoms are made from many different manufacturers including secure socket layer (SSL)
Manufacturing, limited company (Ltd.) in Thailand, Sagami Rubber Industries Company
(Co), Ltd. in Japan, Suretex, Ltd. in Thailand, Suretex Prophylactics (I), Ltd. in India, and
Church and Dwight Co. Inc. in the United States [33]. Each condom brands’ manufacture can be found at the U.S. Food and Drug Administration website search engine using
Product Code: HIS, and Establishment Type: Manufacturer. Different condom brands are all made roughly the same way. The general steps in condom production include retrieving rubber material, chemical additions, vulcanization, fine powder coating, lubrication and packaging [34]. The rubber material may originate from natural resources to make latex (e.g., polyisoprene from Hevea brasiliensis) [35, 36], or other starting materials such as polyurethane film or synthetic elastomers to make non-latex condoms
[37]. Slomkowski et. al. [36] mention that natural latex is the dispersed phase of a plant that is milky and sticky. Depending on the brand or sub-brand of the condom, the types
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and concentrations of chemicals added in each step will differ. Two general categories of condoms are latex or non-latex. Non-latex materials can include polyurethane, polyisoprene or lambskin. In the powdering stage, cornstarch, polyethylene, lycopodium spores, talc, and silica are substances that may be deposited on the condom [38].
Polydimethylsiloxane (PDMS), a dry type fluid or polyethylene glycol (PEG), a wet type fluid, may be added a lubricant [39]. Maynard et. al. [2] notes that these lubricants help preserve the condom and prevent it from sticking to itself. Most condoms are lubricated with PDMS, and few are lubricated with PEG [2]. Some sub-brands of condoms may have other various chemicals added such as spermicide or other substances that add flavor or color. If a spermicide is added, nonoxynol-9 (N-9) is usually the spermicide used [2]. The addition of chemicals and alterations of chemicals of the condom alters the overall chemical makeup. The variation of chemical makeup for each condom should indicate how the condom was made and furthermore, aid in identifying the brand.
2.3. Substrate effect on Fingerprint Development
Fingerprint development is challenging, because there are complex variables associated with each substrate that affect the result of the developmental method (
Figure 2.3.1) Fingerprint development includes two basic steps. Initially, the substrates characteristics have to be analyzed. Then, using known factors of the substrate, the best method of development is deduced. Some of these difficult substrates include those made of a variation of polymers. Plastics are an example of a substrate that encompasses different chemical compositions and polymer arrangement that can affect the result of fingerprint development. Prospectively, these fingerprint development results can impact the analysts’ conclusions which can affect progress of crime investigation.
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Figure 2.3.1.Variables involved in the fingerprint development quality
2.3.1. Challenging Substrates
Fingerprint development involves many challenges, and one of the issues in developing fingerprints involves how the substrate from which the fingerprints are being developed reacts with the developmental method. These challenges include that there are many types of existing developmental methods for different substrates and external factors such as deterioration. Sometimes unconventional methods are necessary for more specific types of substrates. Other times, there is a lack of standard protocols for more specific types of substrates.
2.3.2. Variation of Developmental Methods
Even though there are many methods for developing fingerprints, there does not exist a single method that works for all surfaces or substrates in all circumstances, and as a result, many fingerprints are left undetected [40]. Generally, developmental methods are not robust enough to be expanded to all substrates or even different categories of the same substrate. Diverse nature of developmental methods causes a higher chance of not
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producing optimal results; one method can be mistakenly used for a substrate that is not chemically the same as the class of substrates the method was intended for.
The methods can be divided either by the substrates from which they can develop or by the underlying development mechanisms that develop the print. There are two general types of substrates: porous and nonporous. Porous is usually the most difficult, because porous materials can absorb fingerprint residues. Because of this, a chemical method, rather than a physical method, is employed by targeting specific components such as amino acids or fats that constitute fingerprint residues. Albeit residues on nonporous substrates do not absorb [41] , there are still some difficulties deciphering which method is best, because certain types of nonporous substrates require alterations in the method in order to accommodate for the surface differences of the substrate. For nonporous substrates, there are many methods to choose from including various luminescent, metallic or regular powders [42], cyanoacrylate fuming, vacuum metal disposition (VMD) [40], and rhodamine 6G. A typical method combination for a non- porous substrate is cyanoacrylate fuming and rhodamine 6G [40]. This fluorescence dye has an absorption maximum at 525 nm and an emission maximum at 555 nm.
Accordingly, after applying this dye visualization is done under a laser using an orange filter. The quality of the developed fingerprint depends on how well the substances of the residual fingerprint physically or chemically react to the ingredients of the developmental method. It also depends on how well the fingerprint can be differentiated from the background (i.e. sufficient contrast between the substrate and fingerprint). The chemical composition and physical qualities of the substrate has to be taken into account to verify the ingredients of the developmental method will not react with both the substrate and the
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ridge residue in which the result produces no distinction between the two, and that the ingredients will react appropriately so that the detail of the residue will be able to be detected.
Furthermore, many substrates require either multiple or even untraditional
fingerprinting techniques [41]. If the ingredients of one method are unable to sufficiently
react with the fingerprint residues, then the fingerprint details may be hard or impossible
to observe. Sometimes using another method subsequently or beforehand may be
required to better develop the fingerprints. On the other hand, traditional techniques nor a
combination of traditional techniques may not be adequate for optimal development.
There are some common plastic substrates such as adhesive tapes and other plastics that
require more nontraditional techniques, because the traditional techniques are unable to
provide quality fingerprint development [41].
2.3.2.1. External Factors
Other factors including environmental conditions (e.g., sun exposure and
temperature) and quality of the latent ridges when they were initially deposited affect the
longevity of print as time increases before being discovered. The type of substrate along
with these other factors influences how the fingerprint deteriorates. Depending on the
environmental condition a fingerprint is exposed to, fingerprints on different substrates
can have different rates of deterioration [43]. The longer fingerprint residues are left
exposed to the environment, the least likely the fingerprint will persist on the substrate in
its original form; the liquid in fingerprint residues evaporate and leave the fingerprint in
thicker more viscous state, and this can make development difficult since the viscosity of
the residue will make its adhesion more difficult [42]. If a substrate is known to have
been exposed to non-optimal conditions, a more sensitive development method will be
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required. However, if the substrate’s effects are considered as well as environmental
conditions, more sensitive methods may still need to be employed for substrates that have
even been exposed to optimal conditions.
2.3.2.2. Subtypes of Substrates
With variation of fingerprint quality even on the same substrate by varying
environmental conditions and application quality, the additional variation of the chemical
structures of the same class of substrate make determining the best developmental
method even more difficult. Even though there exist some standard protocols for broad
classifications of substrates, a more detailed classification system is needed since there
are enough differences between substrates of the same group to affect developmental quality [44]. Variation within the same class of substrate suggest that a more detailed method protocol needs to be established. However, a more detailed protocol requires further analysis of the substrate beyond just recognizing the substrate as being a certain general material, and this may make fingerprint development take more time.
2.3.3. Challenges with Single Types of Substrates
2.3.3.1. Plastics
Slomkowski et. al. [36] define latex as a “colloidal dispersion of polymer particles
in a liquid”, where those particles may be organic or inorganic (p. 2231). Plastics are an
example of a single type of substrate that are also characterized by the type of polymer(s)
that constitute it. They are among the most common substrates suspected to have latent
prints at a crime scene [45]. Many types of evidence, depending on the crime, include
plastic shopping bags, garbage bags and plastic bottles are made up of plastic and
polymer substrates [40], and other potential pieces of evidence made of this class of
substrate include condoms and tape.
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2.3.3.2. Developmental Methods
For a single type of substrate such as plastics, some traditional methods such as powdering may be able to be utilized, but sometimes these methods produce low quality or no results for this common substrate [41]. Due to the variances among this type of substrate, untraditional methods including vacuum metal deposition, iron oxide powder suspension and conformal columnar thin film development have been utilized [44, 46,
47]. Each method utilizes complex chemical and physical properties of specific reactants and fingerprint residues on these substrates.
2.3.3.3. Chemical Composition
Development on plastic substrates encompasses many challenges due to their variations in chemical composition and the way the polymers within the substrate are arranged. Different plastics with the same polymer base can have different required development conditions [48]. In general, plastics are made up of repeating units of the same chemical structures known generally as monomers. Plastics differ depending on the monomer identity and arrangement (Table 2.3.1).
Polymers can be classified into different categories based on the way they are synthesized or based on their thermal properties. The categories based on synthetization are addition polymers, condensation polymers, and cross-linked polymers, and the categories based on thermal properties are thermal plastics and thermoset plastics [49].
Polymers that can be softened by heat are known as thermal plastics while polymers that become “permanently hardened” by heat are known as thermoset plastics [49]. Some common industry made polymers including polyethylene (PE) and polypropylene (PP) are addition polymers [49]. These types of polymers are synthesized by adding monomers in a linear or branched-like manner. PE is made up of repeating units of
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ethylene, and PP is made up repeating units of polypropylene with a methyl group branched on every other carbon. PE that has ethylene arranged linearly are more rigid.
These structures are referred to as high density polyethylene (HDPE) [49]. PE that has
“branched-chain molecules, with cross-linking” is more flexible and these are referred to as low density polyethylene (LDPE) [49]. Other types of common plastic include polyvinyl chloride (PVC) and terephthalate (PET). PVC and PET are made of repeating units of vinyl chloride and ethylene terephthalate, respectively. PVC is an addition polymer branched with a methyl group. Other types of polymers can be more complex with three repeating monomers such as acrylonitrile, butadiene, and styrene in acrylonitrile butadiene styrene (ABS) [50]. PE, PP, PVC, PET and ABS are able to be softened by reheating them, so they can also be referred to as thermoplastics. Other plastics, like formica, are not softened, so they are referred to as thermoset plastics [49].
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Table 2.3.1. Plastic substrates and their variable chemical structures
Polyethylene (PE)
Polypropylene (PP)
Polyvinyl chloride (PVC)
Polyethylene terephthalate (PET)
Acrylonitrile butadiene styrene (ABS)
, where n,m,o ϵ
Source for PE, PP, PVC, and PET: Pavia [49], and source for ABS: Abenojar et al. [51].
2.3.3.4. Additional Factors
Changes in plastic composition or addition of additives can also alter optimal fingerprint developing conditions [48]. If manufacturers change the way they produce plastic products by adding different materials, a certain developmental method may react differently to it, and a new or altered method may have to be employed. As a result, the chemical composition of the substrate may need to be verified even though the substrate may have been successfully developed by a certain method previously.
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2.3.4. Environmental Conditions & Development with Powders
A study by Alcaraz-Fossoul and colleagues [52] studied the degradation of fingerprints that are subjected to variables including substrate, fingerprint residue type, and environmental condition. Both sebaceous and eccrine fingerprint residues were deposited on glass and polystyrene substrates. Each of the substrates were placed in closed environments in different indoor conditions including direct exposure to sunlight, indirect exposure to sunlight (penumbra), and no exposure to sunlight for 6 months. In each environment, temperature, humidity, daylight exposure, and light intensity were recorded. The fingerprint residues were developed with white-colored titanium dioxide- based powder. Results indicated that the temperature between the all locations were significantly different. The location with no sunlight exposure had at least variability in temperature throughout time. Insolation between the locations were also significantly different. The fingerprints recovered from glass were overall better quality than the ones recovered on polystyrene. For the sebaceous depositions on the polystyrene substrate, more quality fingerprints were able to be developed in the location with no light exposure after 170 days. For the eccrine depositions, though on day 49 more identifiable fingerprints (4 - 6 fingerprints) were recovered in the location with direct light, all the residues were still poor, and they deteriorated over time until none could be identified on day 170. The fingerprints recovered from the location with no sunlight seemed to deteriorate the most. Accordingly, the author noted that the type of fingerprint residue
(i.e., sebaceous or eccrine) was a major contributing factor to fingerprint development, and that contrary to what they hypothesized, the fingerprints exposed to more solar radiation did not necessarily have the most deterioration.
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A study by Fieldhouse [53] investigated the effect of storage temperature of fingerprint residues deposited on different types of surfaces including glass, enameled metal paint, textured plastic, smooth plastic, and varnished wood over time. The fingerprints were stored to periods up to 52 weeks each in different temperatures between
-10ºC and 37ºC. After storage, each fingerprint was developed with either aluminum powder or cyanoacrylate fuming. Overall, aluminum powder produced the best results when considering all the data. However, cyanoacrylate was shown to be better on the textured and smooth plastic surfaces, and at 37ºC, cyanoacrylate fuming produced better results for all surfaces. Furthermore, lower temperatures were shown to improve fingerprint quality for both methods when combining the grades of all surface types except for between -10ºC and 0ºC where fingerprints stored at 0ºC had better grades than the ones stored at -10ºC. Increase in storage time was correlated with the decrease in the fingerprint quality. Although there was not significant difference in quality up to 2 weeks for aluminum powder and up to 4 weeks for cyanoacrylate fuming.
2.4. Chemical Characterization of Condoms
2.4.1. Previous Methods Used for Identifying Condom Brands and Lubricants
A study by Maynard et. al. [2] attempted identification of lubricants by a number of methods including fluorescence examination, Fourier Transform Infrared
Spectrometry, Gas Chromatography-Mass Spectrometry (GC-MS), Liquid
Chromatography–Tandem MS, and Pyrolysis GC-MS. A total of 50 lubricants that were available in Australia were analyzed. In this study, it was noted that there are four categories that lubricants can be classified under: silicon-based, PEG-based, water-based, and oil-based. The silicon-based includes PDMS lubricant that is used on most condoms.
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The water-based and oil-based are not used for condoms. Only 11 lubricant samples were able to be uniquely identified by extraction using two solvents, but the rest were only able to be grouped. It was noted that the identity of the grouped lubrications could be determined with other instruments, but in order to identify the rest of the condoms more specific instrumentation would be required.
Musah, Cody, Dane, Vuong and Shepard [54] identified condom evidence by using Direct Analysis in Real Time Mass Spectrometry (DART-MS). An advantage to using DART-MS was that it required no sample preparation, and signature profiles were successfully made for all brands of condoms. The authors determined that DART-MS was a useful instrument for forensic analysis for condoms since the condoms, and lubricants swabbed from the condoms, were able to be identified in their native state.
DART has some advantages over GC, because DART allows the samples to be tested directly without destroying the sample. In GC-MS, the samples are not reusable after analysis. Albeit, DART-MS has already worked to distinguish brands in previous methods, a relatively less destructive GC-MS methodology should be tested, because
GC-MS is a common instrument that many laboratories may already be employing for other forensically established protocols.
Another study attempted to identify oil and glycerol- based lubricants on pig skins that were exposed to different environmental conditions [55]. Pig skins with different lubricants on them were placed in three environments: indoors, outdoors in direct sunlight, and outdoors away from sunlight. The samples placed outdoors were placed in a wire cage to prevent scavengers from getting to the samples. Every 24 hours the skins were swabbed, and the swabs were placed in glass test tubes with appropriate solvent.
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Then the solvent was injected into the Gas Chromatogram-Mass Spectrometer (GC-MS).
The results showed that the oil-based lubricants, but not the glycerol-based lubricants, were able to be individually distinguished. Over time, the oil-based had greater persistence than the glycerol for all three environments. For both the oil and glycerol- based lubricants, the persistence on the skin decreased more in the direct sunlight. This study is more comparable to forensic analysis of lubricants that are found on skin since the lubricant samples were applied on skin in the experiment. However, the results indicated that further experimentation is required to find a more versatile method that will be able to differentiate all lubricants.
Another study identified six condoms by their chemical composition by using Ion
Electrospray Ionization-Mass Spectrometry (DESI-MS) [34]. Latent prints that were contaminated with each condom residue were sampled and analyzed using DESI-MS.
Polymers including PDMS, PEG, N-9, and other additives were able to be identified in each sample each with different intensities for the chemicals. Different types of condoms of the same brand were also able to be distinguished by the different chemical intensities that were present in each one. It was determined that the method could be improved and could be more applicable to forensic science if the instrumentation could be made portable. Portability is a desired aspect of instrumentation, because it allows the instrument to be transported more easily which can help samples to be processed quicker.
A similar study used multiple methods, including SPME, to identify 10 different types of condoms [6] . In the SPME methodology, condoms were rinsed with buffer, and the extract from this was diluted. The solution was sampled using SPME for 30 minutes and the sample was inserted into a GS-MS and analyzed. This was done using different
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SPME fibers and solvents for each condom so that each combination could be tested to identify which worked the best. For the PDMS fiber, the results indicated only slight differences for all brands. The PDMS/DVB and PA fibers produced results that indicated distinct results for all major brands of condoms, but some of the sub-brands were not able to be distinguished. A similar procedure was done with swabbed samples of the condoms to try to implement a procedure for evidence that would most likely be submitted to a crime laboratory. The condoms were swabbed, and the cotton containing the condom material was put into a solution and vortexed. This solution was extracted using SPME and analyzed. Some of the results for the swabbing samples produced results of little or no peaks.
2.4.2. Gas Chromatography-Mass Spectrometry
Skoog, Holler and Crouch [56] describe the Gas Chromatogram–Mass
Spectrometer (GC-MS) as “one of the most powerful tools available” for analyzing organic mixtures (p. 582). The GC-MS was first commercialized for laboratory use in the
1950s, and by the 1980s, the instrument had improved features including better temperature control, flow rates, and sample injection. Due to the numerous application, it has been sold in a variety of several hundred models by the millions from $10,000 to greater than $50,000 each [56].
GC-MS is used to analyze volatile or semi-volatile organic compounds [57].
Basic parts of GC-MS include inlet, column, and oven for the GC section. The MS section includes a direct insertion probe, ion source, mass analyzer, ion detector, and data system, where the ion source, mass analyzer, and ion detector work under a high vacuum system to prevent air from interfering with ion reactions. As noted by Skoog et. al. [56],
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the mobile phase in GC-MS does not interact with the analytes like in other separation methods. Helium, argon, nitrogen, and hydrogen can be used to move the analytes through the system. The GC analyzes by separating the chemicals via gas-liquid chromatography [56]. GC components that can affect flow rate include pressure regulators, gauges, and flow meters. The gas cylinder has a two-stage pressure regulator.
The GC has a pressure or flow regulator. The pressure in the inlet can lead to flow rates of 1-25 mL/min. One important feature of the GC helps with efficient separation is the open tubular material being inert at various temperatures [56]. Other features that effect separation is the stationary phase being applied uniformly along the tubular material, having low volatility (i.e., having a boiling point maximum operating temperature + ≥
100°C), having thermal stability, having chemical inertness, and having solvent characteristics that allow analytes to be resolved (i.e., separation factor : α large enough and peak width small enough so that peak resolution: Rs > 1) [58]. Typically, the length of the column can be 3 – 5 m. It is made out of fused silica, but can also be made out of stainless steel, glass, or Teflon. For fused silica, the inside diameter can be 0.1 - 0.3 mm in diameter [56]. Efficiency plates, which is affected by time, longitudinal diffusion, and mass transfer, can be 2000 – 4000. Sample size can be 10 – 75 ng. The tubes with polyimide coating cause the column to be flexible which increases its durability.
The movement of the mobile phase gas carries the compounds through column.
The compounds separated according to their degree of attraction to the liquid stationary phase. The more attracted a chemical is to the stationary phase, the longer amount of time the chemical will stay in the GC. Thus, a chemical with less attraction to the stationary phase will have a shorter retention time (Rt), and a chemical with more attraction will
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have a longer Rt. This is represented by a chromatogram. In the chromatogram, compounds are represented by Gaussian shaped curves (which are a product of diffusion), and each curve is separated according to their chemical’s respective Rt values
(product of the time spent in the column).
Mass spectrometry in GC-MS essentially includes mechanisms to create, separate, and detect ions created from molecules separated by GC. Organic volatiles that come elute first are those who are less attracted to the stationary phase of GC. These are typically those with less mass and higher volatility. In contrast, those eluding last are higher masses and lower volatility. The molecules transferred to the MS, by direct insertion, are first ionized. This can be done by soft ionization or hard ionization. A type of hard ionization is electron impact.
Electron impact consists of fragmenting the molecule with a high energy (70 electron volt) beam of electrons that are coming from a filament. This is done through a process known as thermionic emission where the filament is heated causing a flow of charge carriers (in this case, electrons) to bombard the molecule with energy higher than the ionization energy of the molecule. The beam of electrons disassociates parts of the atom into fragments of charged atoms (i.e., ions) by applying kinetic energy, or more particularly electron impact energy, to cause electrons to disassociate from the parent molecule. The removal of electrons causes the initial molecule to have a positive net charge. Thus, the result is a positive ion and the dissociated electrons. The reaction,
demonstrates the ionization of the parent molecule into a cation by electron impact, where M is the parent molecule of neutral charge, e- is an electron, M+∙is the molecular
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ion, and 2e- is the product of electrons from the beam and the molecule. Ionization energy
refers to the energy required to remove an electron from a molecule. For a neutral
molecule this is referred to as the first ionization energy. For an already ionized molecule,
an energy of higher magnitude is required to remove electrons. The required energies for
further ionization are called second ionization energy, third ionization energy and so on.
Figure 2.4.1. Electron Impact ionization (left) [59], and atom ionization illustration (right) [60]. After ionization, a repeller electrode moves the cations to the mass analyzer. In
the mass analyzer the ions are separated. The process of separation depends on the type
of mass analyzer incorporated into the MS. Typical mass analyzers include quadrupole,
time-of-flight, and ion traps.
In the detector, the relative abundance of each ion according to their mass to
charge ratio is measured. The separated ions are recorded on a spectrum according to
their values. The response produced on the chromatograph is dependent on the 𝑚𝑚 transducer𝑧𝑧 that converts beams of ions into an electrical signal [56]. Those with the
relatively highest mass and/or relatively lower charge will generally has the highest mass
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to charge ratio. Those with the relatively lowest mass and/or relatively highest charge will generally have the lowest mass to charge ratio.
Skoog et. al. [56] point out that the optimal column temperature equals or is slightly above the average boiling point of the analyte, but this increases the elution time which increases the analysis time. Analytes tend to diffuse the longer they are in the column since it is thermodynamically more favorable; it takes less energy for the molecules to spread out than it does for them to stay together. The spreading of the analytes (i.e., diffusion) broadens the peaks. Increase in peak broadening affects resolution and plate height [58]. Therefore, peaks with longer retention times tend to be fatter.
2.4.3. Solid Phase Microextraction
2.4.3.1.Theory
In SPME, the amount of analytes extracted are those that satisfy equilibrium between the fiber and its surroundings [61]. When the sample is a solid, there is equilibrium taking place between the solid and the headspace and the headspace and the fiber. As the sampling time increases, the amount of analytes absorbed into the fiber should increase until equilibrium is achieved. This is where change in the amount of analyte over time reaches zero. Wercinski [61] states that highly volatile analytes should be maximized in in shorter periods and those with low volatility will increase more steadily.
2.4.3.2. Sampling Process
The solid phase extraction (SPME) apparatus is small and analogous to a syringe. It is composed of a plunger, barrel, fiber sheath and fiber attachment rod. A chosen fiber is
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screwed into the apparatus. The needle is made of fused-silica and is coated with a sorbent layer that allows chemicals sorb onto it. The type of fiber and thickness required depends on the type of compounds targeted. The needle is attached to the syringe pump, so after the fiber allows chemicals to sorb, it can be retracted into the SPME syringe and saved for later analysis.
Figure 2.4.2. Fiber rod in normal state (1) and in injection mode (2).
Generally, the sampling process includes placing a sample into a closed container
(e.g., a vial), injecting the SPME fiber, and letting the fiber absorb the compounds emitting from the sample. The sample can be a solution or a solid. After sampling for a set amount of time, the fiber is pulled out of the vial, and the fiber is inserted into an analytical instrument where the analytes are desorbed. In the GC, the analytes are desorbed from the fiber into the injection liner and are refocused into the column [61].
SPME can be used incorporating different commercially available fibers.
Wercinski [61] points out that the affinity of the fiber is important in sampling since the fiber and the surroundings of the analyte are competing for the analytes. Commercial fibers available include a variety of organic polar and nonpolar polymers including
DVB/CAR/PDMS, CAR/PDMS, DVB/PDMS, PA, PDMS. Each fiber includes one or more polymers that have an affinity for different types of analytes. Wercinski [61] points
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out two fundamental processes involved are the partitioning of analytes between the fiber and the sample and the analytes that were concentrated onto the fiber desorbing into a chosen analytical instrument.
The PDMS fiber is nonpolar, so it is used to extract other non-polar compounds, and PA is good with polar compounds since its polar [62]. Determining the best fiber type to extract a sample may require preliminarily testing each fiber on the same sample.
The fiber used that produced the most ideal results, depending on the experiment, would be selected as the best fiber to use. For differentiating between samples, where the chemical composition or chemical quantities are unknown, the ideal fiber would be the one that produced results that are the easiest to contrast (i.e. the fiber that extracts the compounds(s) that differs the most in each sample).
For compounds in condom substrates, different types of fibers would be tested to determine which type is able to adsorb an appropriate amount of target compounds.
Targeted compounds on a particular substrate will depend on the materials utilized in manufacturing the substrate and the type of analytical method used to identify the components in the substrate. For example, in the case of headspace–SPME and GC, targeted compounds would be organic volatiles. Hence, the compounds analyzed in the condom substrate, only organic compounds would be analyzed. To find the best fiber for discriminating purposes, each different kind of fiber would have to be tested on the desired sample to be discriminated, and the fiber that produced data that contrasted the samples the most would be the best fiber.
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2.4.4. SPME and Plastics
Lattuati-Derieux et al. [63] demonstrated that plastics of different polymer families (e.g., styrenics, polyolefins, acrylics, and polyamides) could be differentiated by specific volatile organic compounds (VOCs) which are referred to as the compounds that represent the nature of the polymer. The VOCs of twelve different plastics including polystyrene (PS), low density polyethylene (LDPE), homo-polymethylmethacrylate
(homo-PMMA), and celluloïd were sampled via headspace solid-phase microextraction
(SPME) using a Divinylbenzene/Carboxen/Polydimethylsiloxane (DVB/CAR/PDMS) fiber and compounds were injected in the GC-MS. The samples were placed into 20 mL vials. Sampling was done for each type of plastic in two different temperatures which were room temperature and 60 ºC. For the samples in room temperature the SPME fiber was allowed to sample the objects for 15 days. For the heated samples the SPME fiber was exposed to the objects for one hour. The results between the temperatures were checked and provided similar data. The results constituted of more than 200 different
VOCs. Furthermore, aged museum objects made of plastics were also analyzed, and the chemical components of the objects were able to be characterized.
Research by Curran et al. [64] demonstrated the effects of SPME method variables (i.e., fiber coating, sampling time, temperature, and sample preparation) when sampling historical plastics and rubber materials. Different types of plastics where studied for different variables of the method. The fibers that were tested in this study was
DVB/CAR/PDMS and Carboxen/PDMS (CAR/PDMS). The plastics used to study the fibers were polystyrene (PS), cellulose acetate (CA), and polyethylene (PE).
DVB/CAR/PDMS was shown to produce a more effective since it could adsorb a broader
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range of analytes. Accumulation time (i.e., the time the sample was allowed to sit in the vials) was studied using pieces of natural rubber (NR), cellulose acetate (CA), polyurethane (PUR), and polystyrene (PS). Out of the accumulation times tested (1, 2, 7,
14, 21, and 28 days), 7 days was determined to be optimal. For determining temperature, polyethylene terephthalate glycol-modified (PETG), glass reinforced polyester (GRP),
Poly(methyl methacrylate) (PMMA), and phenol formaldehyde (PF) were the plastics analyzed. The temperatures tested were room temperature and 40 ºC, and results indicated that an increase of temperature did not significantly increase the peak areas. For sampling time PE, PS, and CA were used, and out of the sampling times tested (5, 30, 60, and 120 min.), 60 minutes was determined to be the most suitable. Sampling time of 120 minutes increased the change of analytes carrying over when repeating the use of the fiber. Various historic objects made of plastic materials were tested nondestructively, and results indicated that by sampling objects nondestructively, sufficient detailed information about the composition of the objects are able to be obtained.
Research by Hakkarainen and others [65] encompassed the isolation of degradation products in polyethylene (PE) films. Three PE films varying in thickness which contained the additives iron dimethyldithiocarbamate, iron dimethldithiocarbamate, carbon black, and nickel dibutldithiocarbamate were used in addition to low density polyethylene which contained no additives for comparison. The plastics were exposed to UV radiation and heat to determine how the additives degraded.
The plastic films were analyzed by both HS-SPME-GC-MS and HS-GC-MS. For SPME, the fibers used were PDMS and Carbowax (CW), and the samples were sampled for 30 min. at 80 ºC. The results indicated that SPME-GC-MS was more suitable in extracting
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analytes from these plastics than HS-GC-MS; SPME was able to extract less volatile products. Results also indicated which additives were degraded more quickly when exposed to the different conditions (i.e., UV radiation and heat).
Other research by Hakkarainen et al. [66] demonstrated the use of HS-SPME for the analysis of other polymeric materials including recycled polyamide 6.6, virgin thermo-oxidized polyamide 6.6, nitrile rubber (NBR), and LDPE. The samples were placed into 20 mL vials. The NBR samples were aged for different times in the vials before sampling. The LDPE was exposed to UV radiation and aged for five weeks while heated at 80 ºC. PDMS/DVB was used to sample the recycled and virgin polyamide 6.6.
Polyacrylate (PA) was used to sample the NBR. PDMS and CW/DVB were both used to sample the LDPE. The results in this research were also compared to HS-GC-MS, and the results still indicated that HS-SPME was able to detect more analytes. Several degradation products were analyzed indicating that determining degradation patterns is possible for plastics. The degradation product patterns indicated that the recycled polyamide and virgin polyamide were able to be differentiated. For NBR, the results demonstrated the migration of additives including the plasticizer (tris(2- buotoxyethyl)phosphate) during aging. Accordingly, the author noted the potential of
SPME for the characterization and assessment of polymer and plastic materials. Pure
LDPE was used as a control.
Research by Khabbaz et al. [67] consisted of testing PE films for chemical changes after being exposed to thermo-oxidation. Different types of starch filled LDPE and photosensitized LDPE were studied. The different types of starch filled LDPE were
LDPE modified with 20% masterbatch (LDPE-MB) which was made up of linear low
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density polyethylene (LLDPE), corn starch, styrene-butadiene copolymer, and manganese stearate, LDPE modified with a prooxidant system (LDPE-PO), and 7.7% corn starch (LDPE-Starch). The different types of photosensitized LDPE were LDPE films made up of different additives including iron dimethyldithiocarbamate, iron dimethyldithiocarbamate and 0.8% carbon black, and iron dimethyldithiocarbamate nickel dibutyldithiocarbamate. Each type of plastic was placed into a vial and allowed to sit for 14 days while exposed to heat. The samples were analyzed for different properties using different analytical methods including HS-SPME. For HS-SPME the analytes from the samples were extracted using PDMS and CW/DVB. The fibers were allowed to sample analytes for 30 min. at 60 ºC. For the GC, a DB-5 column was used for samples extracted with PDMS, and a DB-WAX column was used with CW/DVB. The results indicated that the chemical outputs of these plastics were different from each other. Most of the degradation products were formed for LDPE-MB and LDPE-PO. Furthermore, chemicals including benzoic acid and 5-oxohenanoic acid only showed up in LDPE-MB and LDPE-PO. Benzaldehyde, 3-methyl pentanal, and 2-propyl 5-oxohexanal were only identified in LDPE-MB, and the identification of esters was only possible in LDPE-
Starch and pure-LDPE.
Ou and Whang [68] studied organotin stabilizers in poly(vinyl chloride) (PVC) products using HS-SPME coupled with GC flame-photometric detection. The types of commercial products made of PVC used were a faucet package, tool box, cooling oil bottle, and water pipe. Before the SPME extraction, the PVC products were prepared by following procedures including cutting the plastics into small pieces, dissolving them tetrahydrofuran, and heating them. The samples were extracted with a PDMS fiber at 50
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ºC for 30 minutes. The results indicated that there were different amounts and different types or organotin compounds in each of the different commercial products made of
PVC.
A study by Pajaro et al. [69] demonstrated what kinds of VOCs come from plastic food packages and utensils by employing SPME-GC-MS. Plastics materials including plates, food containers, and soup containers from Cartagena city stores were cut into pieces and placed into 4 mL vials. The VOCs were extracted with a PDMS fiber while the vials were heated using different temperatures for 30 min. Over 30 compounds were found to be present in the different types of plastics. The results indicated that different compounds were able to be identified at 55ºC and 85ºC, and the chromatograms of different plastic materials could still be differentiated at the different temperatures.
2.4.5. Principle Component Analysis
PCA has been used for discriminating and classifying samples from data provided by MS [70]. In a study by Ziółkowska et. al. [70], PCA was done by using the data from the mass spectrum and using statistical software to group samples according to the relationship the components provided by MS. This method could be applied to the GC-
MS data for each condom brand. PCA would describe the variability of each sample with respect to each other. The results of the statistical analysis will group compounds in relation to each other, and each compound relation represents one of the condom brands.
Whether the brand can be differentiated from other brand will depend on how far apart the compound relation points of each brand are from each other. Applying principle component analyses delineated by Johnson and Wichern [71], let X’ represent condom brands represented by B’. Then X’ = {X1, X2, … Xn} => B’ = {B1, B2, … Bn} where
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B1, B2, … Bn represents n number of condom brands such as Durex, Crown, etc. If only nine samples are only being tested, then n = 9. Then, B’ = (B1, B2, … B9).
For each B, there is a set of data. In this application, this data are the relative abundances of each compound detected. Let the relative abundance for each compound be denoted as
C1, C2, … Cm, where m is the maximum number of compounds detected. Then for each Bi
where = 1, 2, . . . , 9 , Bi = (Ci1, Ci2, … Cim). The first step is to determine the ′ covariance⊆ 𝐵𝐵 matrix𝑖𝑖 . Let this covariance matrix be defined as Σ. Then,
( ) ( , ) ( , ) ( , ) ( , ) ( ) ( , ) ( , ) 𝑉𝑉𝑉𝑉𝑉𝑉 𝐵𝐵1 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵1 𝐵𝐵2 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵1 𝐵𝐵3 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵1 𝐵𝐵9 Σ = ⎡ ( , ) ( , ) ( ) ( , )⎤ . 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵2 𝐵𝐵1 𝑉𝑉𝑉𝑉𝑉𝑉 𝐵𝐵2 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵2 𝐵𝐵3 ⋯ 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵2 𝐵𝐵9 ⎢ 3 1 3 2 3 3 9 ⎥ ⎢𝐶𝐶𝐶𝐶𝐶𝐶(𝐵𝐵 , 𝐵𝐵 ) 𝐶𝐶𝐶𝐶𝐶𝐶(𝐵𝐵 , 𝐵𝐵 ) 𝑉𝑉𝑉𝑉𝑉𝑉( 𝐵𝐵, ) 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵( 𝐵𝐵) ⎥ ⎢ ⋮ ⋱ ⋮ ⎥ ⎣𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵9 𝐵𝐵1 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵9 𝐵𝐵2 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵9 𝐵𝐵3 ⋯ st 𝑉𝑉𝑉𝑉𝑉𝑉 𝐵𝐵9 ⎦ ( ) represents the variance of C1, C2, … Cm of the 1 tested brand denoted as .
1 1 𝑉𝑉𝑉𝑉𝑉𝑉(𝐵𝐵 , ) represents the covariance of C11, C12, … C1m and C21, C22, … C2m of 𝐵𝐵 and
1 2 1 𝐶𝐶𝐶𝐶𝐶𝐶. This𝐵𝐵 𝐵𝐵applies all the way to which is the final tested brand. 𝐵𝐵
2 9 Then𝐵𝐵 to find the principle components,𝐵𝐵 eigenvalues for this matrix are calculated. So,
( ) ( , ) ( , ) ( , ) 1 ( , ) ( ) ( , ) ( , ) 1 𝑉𝑉𝑉𝑉𝑉𝑉 𝐵𝐵1 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵1 𝐵𝐵2 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵1 𝐵𝐵3 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵1 𝐵𝐵9 Σ - λI = ⎡ ( , ) ( , ) ( ) ( , )⎤ – λ 1 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵2 𝐵𝐵1 𝑉𝑉𝑉𝑉𝑉𝑉 𝐵𝐵2 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵2 𝐵𝐵3 ⋯ 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵2 𝐵𝐵9 ⎡ ⋯ ⎤ ⎢ 3 1 3 2 3 3 9 ⎥ ⎢ ⎥ ⎢𝐶𝐶𝐶𝐶𝐶𝐶(𝐵𝐵 , 𝐵𝐵 ) 𝐶𝐶𝐶𝐶𝐶𝐶(𝐵𝐵 , 𝐵𝐵 ) 𝑉𝑉𝑉𝑉𝑉𝑉( 𝐵𝐵, ) 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵( 𝐵𝐵) ⎥ ⎢ 1 ⎥ ⎢ ⋮ ⋱ ⋮ ⎥ ⋮ ⋱ ⋮ 9 1 9 2 9 3 9 ⎢ ⎥ ⎣𝐶𝐶𝐶𝐶𝐶𝐶( 𝐵𝐵 )𝐵𝐵 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵( 𝐵𝐵, )𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵 𝐵𝐵( , ⋯) 𝑉𝑉𝑉𝑉𝑉𝑉 𝐵𝐵 ( ⎦ , ⎣) ⋯ ⎦ ( , ) ( ) ( , ) ( , ) 1 1 2 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵1 𝐵𝐵3 1 9 = 𝑉𝑉𝑉𝑉𝑉𝑉 𝐵𝐵( , − ) 𝐶𝐶𝐶𝐶𝐶𝐶(𝐵𝐵 , 𝐵𝐵 ) ( ) 𝐶𝐶𝐶𝐶𝐶𝐶(𝐵𝐵 , 𝐵𝐵 ) . ⎡ 2 1 λ 2 2 3 2 9 ⎤ ⎢ 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵 𝐵𝐵 𝑉𝑉𝑉𝑉𝑉𝑉 𝐵𝐵 − 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵 𝐵𝐵 ⋯ 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵 𝐵𝐵 ⎥ ⎢ 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵3 𝐵𝐵1 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵3 𝐵𝐵2 λ 𝑉𝑉𝑉𝑉𝑉𝑉 𝐵𝐵3 − 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵3 𝐵𝐵9 ⎥ ⎢ ( , ) ( , ) ( , ) λ ( ) ⎥ ⎢ ⋮ ⋱ ⋮ ⎥ 9 1 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵9 𝐵𝐵2 𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵9 𝐵𝐵3 9 Then the⎣ determinate𝐶𝐶𝐶𝐶𝐶𝐶 𝐵𝐵 𝐵𝐵 of this matrix is found by⋯ the𝑉𝑉𝑉𝑉𝑉𝑉 following:𝐵𝐵 − λ⎦
det(Σ − λI) = + + + … + , 𝑛𝑛 𝑛𝑛−1 𝑛𝑛−2 1 1 2 3 9 where , , . . . , are constants.𝑟𝑟 λSolving𝑟𝑟 λfor we𝑟𝑟 getλ values 𝑟𝑟 , λ , . . . , with their
1 2 9 1 2 9 corresponding𝑟𝑟 𝑟𝑟 eigenvectors,𝑟𝑟 (ei1, e i2, e i3, …, e λi9), which are foundλ byλ pluggingλ in each in Σ – λI = 0 and solving. Let equal the largest of , , . . . , . The eigenvectorλ
λ𝑚𝑚1 47 λ1 λ2 λ9
Texas Tech University, Amanda Patrick, December 2018
whose corresponding eigenvalue in which = max{ , , . . . , } is used in
𝑚𝑚1 1 2 9 determining the first principle component. Theλ eigenvectorλ withλ theλ second highest
eigenvalue is used in determining the 2nd principle component and so on. Each eigenvalue and their corresponding eigenvalue is denoted as the following:
, (e11, e 12, e 13, …, e 19) , (e21, e 22, e 23, …, e 29) λ𝑚𝑚1 𝑚𝑚2 . λ . .
, (e21, e 22, e 23, …, e 29).
λ𝑚𝑚9 The eigenvectors are multiplied by B’. Finally, the principle components are
Y1 = e11B1 + e12B2 + … + e19B9 Y2 = e21B1 + e22B2 + … + e29B9 . . .
Y9 = e91B1 + e92B2 + … + e99B9.
For a 2-dimensional plot, only the first two principle components, Y1 and Y2, are used.
The authors mention that if we take the variance for each eigenvector, we will result back
to their corresponding eigenvalue, .and if we find the covariance between two
𝑖𝑖 eigenvector the result will be 0 which λmeans they are uncorrelated.
Each principle component is used as a correspondence for representing the
brands. If each brand is replotted according to these principle components (Figure 2.4.3),
then we can say that brands that are plotted closer to each other have a higher correlation
and brands plotted further from each other have a lower correlation. If some of the tested
condoms are of the same brand and their respective values of each compound correlate,
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then these data points should be plotted in the same general area. In contrast, if brands are different, the corresponding values for each compound for both brands should differ so that they are not correlated. Then these plots would be in geometrically plotted in different areas.
Figure 2.4.3. Principle Component Analysis Results Interpretation
2.5. Hypotheses
2.5.1. Temperature Variation on Fingerprint Development
Fingerprint detection on condom substrates can be a means to determine suspect association in a time and cost-effective manner. Due to the chemical differences between each condom brand the chemical medium the fingerprint residue is in contact with will differ. With exposure to different environmental conditions such as temperature, the persistency and state of the residue may be affected. When a combination of these factors are present, it is hypothesized that the quality of fingerprint development on
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different brands that were exposed to different temperatures will have a significant difference.
2.5.2. Condom Brand Identification
To optimize evidence processing, investigation of efficient procedures for condom brand identification should be investigated. SPME is an instrument that provides means to sample in a least destructive and in a time efficient manner. SPME is able to sample the volatile space above a substrate. By sampling the headspace of a condom substrate, the condom is remaining closer to its native state, and can therefore be more likely analyzed by other methods if desired.
The extracts sampled with the SPME polymer are able to be analyzed by a variety of instruments including the GC-MS. Notably, the GC-MS is destructive, but the sampling procedure used is non-destructive, so this characteristic is not critical. That is, the destruction of the volatile sample emitting from the substrate will not cause destruction to the substrate itself. The desorbed compounds from the condoms would enter the column and be separated according to their affinity to the stationary phase relative to the inert gas phase which is measured by Rt values. Subsequently, these compounds would enter the MS phase where they would be broken down into ions are separated according to the mass to charge ratio. The mass to charge ratios for the ions of each initial compound as a spectrum. By comparing the types of compounds and differences in relative abundances of these compounds, the associations or differences of compounds detected between different brands. It is hypothesized that the compounds collected from the headspace of the different brands of condoms will produce different chromatogram and spectra data and using principle component analysis or
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another statistical analysis method such as hierarchical clustering, the variances of relative abundances of the compounds will be able to be used to statistically separate the different brands of condoms.
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3. Methods
There are minimal health risks with handling unused (i.e., right out of the package) condoms. Rubber gloves were worn, and metal twisters were used when handing the condoms. Procedures were performed in normal laboratory conditions.
Institutional review board (IRB) requirements were completed for using subjects for fingerprint population study, IRB#: IRB2016-113, Fingerprint Visualization on Used
Condoms.
3.1. Temperature Effect on Fingerprint Development
3.1.1. Materials
Condom products were purchased from Amazon. Condom brands, Durex Extra
Strength, LifeStyles Extra Strength, and Okamoto Crown chosen by a study by Radford
[72] were used for comparison purposes (Table 3.1.1). These brands are also among the most commonly encounter types of condoms in Lubbock TX [72]. Other materials included clear plastic Ziploc bags, a Magic Chef refrigerator, SafariLand Caron
DFO/ninhydrin Development Chamber, Omega-Print cyanoacrylate ester, a fuming chamber with a heating element, Dual Purpose atomic CRP Latent Print Powder
(Magnetic Silver/Black) magnetic powder, rhodamine 6G dye stain, Coherent Tracer
Laser, Nikon D7200 with 60mm lens camera, white light source, and a thin flexible wire.
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Table 3.1.1 Condoms brands tested
Condom brand
Durex Extra Strength
LifeStyles Extra Strength
Okamoto Crown
3.1.2. Experimental Procedures
Each type of condom from Table 3.1.1 was unpackaged and unrolled onto a flat surface. One male subject from the Texas Department of Public Safety volunteered to donate his prints. He was informed of the following described procedures and informed there would be no compensation for participation. In order to induce fingerprint residue, the subject’s hand was covered with a clear plastic bag for two minutes. The subject deposited five fingerprints from one hand onto 27 condoms. Of these 27 condoms, 9 were
Durex Extra Strength, 9 were LifeStyles Extra Strength, and 9 were Okamoto Crown
(Table 3.1.1). Each finger was placed one at a time onto the condom moving from tip of the condom down towards the base.
After fingerprint depositing, each brand of condom was stored in one of three different holding chambers, each varying in temperature. Magic Chef Refrigerator was used for the cooler temperature and the SafariLand Caron DFO/ninhydrin Development
Chamber was used for the warmer temperature. Evaluated temperatures were 15ºC, 24ºC, and 40ºC. This included a set range of temperatures indicative of normal or alternative
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environmental conditions. After exposure to the different temperatures for 8 hours, the condoms were developed with cyanoacrylate fuming and dusting with magnetic powder.
For cyanoacrylate fuming the following procedures adapted from Radford [72] were performed:
1. Each condom was placed into a superglue fuming chamber.
2. A quarter size amount of cyanoacrylate compound was poured into an aluminum
tray.
3. The chamber was closed, and heating element was turned on for 15 minutes.
4. After 15 minutes, the heating element was turned off, and the condoms were
allowed to sit for 24 hours before ventilation.
5. After first ventilation, steps 1 – 4 were repeated.
Figure 3.1.1. Condoms after superglue fuming being prepared for powdering
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After superglue fuming, each condom was laid out and powdered with magnetic powder.
The developed fingerprints on each condom were photographed and scored by a certified
fingerprint examiner according to Table 3.1.2. The scores for each condom brand were
compared between the different temperatures to see if there is a significant difference
among the scores associated with different temperatures and brands. The brand with the overall higher average and temperature with the overall higher average were used for a
population study in order to determine inter-person variability. For this study N = 20
males were instructed to deposit their prints using the same method as before each finger
from one hand from the base to the tip of the condom. Fingerprints were developed with superglue fuming and magnetic powder. Each fingerprint was scored by a certified fingerprint analysis using the scoring system described in Table 3.1.2.
After visualization, each print was photographed. For photographing, a thin
flexible metal wire shaped into a “U” was used fix the substrate to determined position. A
white transient light source was utilized for visualization purposes (Figure 3.1.2).
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Figure 3.1.2. White light source and thin flexible wire utilized for visualization and photographing developed fingerprints after development with superglue fuming and magnetic powder
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Table 3.1.2 Fingerprint Development Scoring with Description [73]
Score Description Example
1 No fingerprint development -
2 Poor fingerprint development (very few ridges visible, poor contrast).
3 Medium fingerprint development (either contrast or ridge detail was not good).
4 Good fingerprint development (either contrast or ridge detail was visible).
5 Excellent fingerprint development (contrast as well as ridge details are very clear).
3.1.3. Inter-person Variability
For determining inter-person variability, 20 male individuals were instructed to deposit all fingerprints from one hand onto a condom (same procedure used previously).
The brand of condom used was determined by the brand that performed the best in the temperature analysis. Similarly, the storage temperature used was the one that performed
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the best in the temperature analysis. After storage for 8 hours, each condom was
processed with cyanoacrylate fuming and magnetic powder the same way performed in
the temperature-brand analysis. Developed fingerprints from each condom were
photographed and scored by a fingerprint examiner using Table 3.1.2.
3.1.4. Dye Staining ─ Rhodamine 6G
Magnetic Powder has been previously shown to be the developmental method that resulted overall higher averages in development for this substrate [72]. For further comparison purposes, rhodamine 6G dye stain, made with a stock solution and methanol was used to stain all samples that were previously processed with superglue fuming and magnetic powder. After staining, each sample was placed under a laser with a lasing range of 570-660 nm while wearing polarizing goggles. Scoring was repeated for the temperature analysis and the population study.
3.2. Condom Brand Identification using HS-SPME
3.2.1. Materials and Standard Instrumental Procedures
The extraction method used was solid-phase microextraction (SPME). Fibers
tested were Supelco® brand and are varied in fiber coating and thickness (Table 3.2.1).
Before using the fibers, each was conditioned to allow any residual chemicals to desorb.
Per the instructions of Supelco®, the temperature and time for the conditioning varied by
the type of fiber (Table 3.2.2). Conditioning consisted of exposing each of the fibers to
determined temperature by injecting the fiber into the injection port of the GC for a set
time. An Agilent 6890N gas chromatograph with a 5973 mass selective detector was used
to analyze the samples.
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Table 3.2.1 Supelco® SPME fibers. Fiber Coating
Polydimethylsiloxane (PDMS)
Carboxen/Polydimethylsiloxane (CAR/PDMS)
Polydimethylsiloxane/Divinylbenzene (PDMS/DVB)
Divinylbenzene/Carboxen/Polydimethylsiloxane (DVB/CAR/PDMS)
Polyacrylate (PA)
Table 3.2.2 Conditioning parameters for each fiber
Fiber Coating Conditioning Temperature (ºC) Conditioning Time (minutes)
CAR/PDMS 250 30
PDMS 250 30
PDMS/DVB 300 30
DVB/CAR/PDMS 270 30
PA 280 30
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3.2.2. Experimental Procedures
3.2.2.1. SPME Method Optimization – Fiber Type & Sampling Time
To determine optimal conditions for condom profiling, preliminary tests were
conducted. Optimal sampling conditions were determined to be those that allowed
extraction of a sufficient number and abundance of compounds for discriminating
purposes. Variable conditions tested were the type of SPME fiber and the extraction time.
A combination of 5 different commercially available fibers and 5 different sampling
times were tested (Table 3.2.3).
Table 3.2.3 Combination of variables tested at room temperature for sampling optimization.
PDMS 1 hr. PA 1 hr. PDMS/DVB 1 hr. CAR/PDMS 1 hr. DVB/CAR/PDMS 1 hr.
PDMS 3 hr. PA 3 hr. PDMS/DVB 3 hr. CAR/PDMS 3 hr. DVB/CAR/PDMS 3 hr.
PDMS 6 hr. PA 6 hr. PDMS/DVB 6 hr. CAR/PDMS 6 hr. DVB/CAR/PDMS 6 hr.
PDMS 12 hr. PA 12 hr. PDMS/DVB 12 hr. CAR/PDMS 12 hr. DVB/CAR/PDMS 12 hr.
PDMS 24 hr. PA 24 hr. PDMS/DVB 24 hr. CAR/PDMS 24 hr. DVB/CAR/PDMS 24 hr.
These 25 different combinations were tested using the following procedures:
1. Condoms were cut along the rim to prevent the substrate from expanding to the top of the vial. 2. Each condom was deposited in the bottom of a 10 mL vial. 3. The vial was closed, and each condom was left undisturbed for 1 hour to allow volatiles to accumulate in the headspace. 4. Each SPME fiber (Table 3.2.1) was injected into one of the vials by piercing the plastic septum of the vial lid and injecting the fiber into the headspace of the vial. 5. The fibers were left to sample the headspace at one of combinations of sampling times indicated in Table 3.2.3 (Figure 3.2.1). 6. Each fiber was injected in the GC-MS port for 9 minutes with the parameters listed in Table 3.2.5. 7. The GC-MS data for each fiber were analyzed, and the optimal combination of fiber and sampling time selected based on highest number of detected compounds.
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Figure 3.2.1. Sampling headspace of condom substrates with various fibers: PA, PDMS, DVB/PDMS, CAR/PDMS, and DVB/CAR/PDMS
Table 3.2.4. Additional variables tested at varying temperatures
PDMS 35ºC PA 35ºC PDMS/DVB 35ºC CAR/PDMS 35ºC DVB/CAR/PDMS 35ºC 0.5 hr. 0.5 hr. 0.5 hr. 0.5 hr. 0.5 hr. PDMS 70ºC PA 70ºC PDMS/DVB 70ºC CAR/PDMS 70ºC DVB/CAR/PDMS 70ºC 0.5 hr. 0.5 hr. 0.5 hr. 0.5 hr. 0.5 hr.
These 10 more conditions were tested using the following procedures:
1. A heating block was preset to a set temperature according to Table 3.2.4. 2. Condoms were cut along the round edges to prevent the substrate from expanding to the top of the vial. 3. Each condom was deposited in the bottom of a 10 mL vial. 4. The vial was closed a placed on the heating element for 0.5 hrs. 5. Each SPME fiber (Table 3.2.1) was injected into one of the vials by piercing the plastic septum of the vial lid and injecting the fiber into the headspace of the vial. 6. The fibers were left to sample the headspace for 0.5 hrs. 7. After the half hour, each fiber was removed and injected in the GC-MS port for 9 minutes with the parameters listed in Table 3.2.5. 8. The GC-MS data for each fiber were analyzed, and the optimal combination of fiber and sampling time selected based on highest number of detected compounds.
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Table 3.2.5. Gas chromatogram-mass spectrometry parameters (Adapted from [6]) Carrier gas Helium (99.999%) at 1.0 mL/min with 7.1 PSI
Injection 250°C ; Manual Injection Mode ; 9 minutes
GC program 100°C (hold 2 min) to 300°C (hold 5 min)
Rate* 10°C / min
Split ratio Splitless
Scan mode Full scan
Scan mass range 40 - 500 amu
*This rate was a product of decreasing the rate by 0.5 to extend the time the compounds spent in the column
3.2.2.2. Condom Brand Profiling
To determine the chemical profile for each brand, each brand of condom was tested using the optimal conditions determined in the preliminary test.
The following procedures were performed for triplicate samples of each brand listed in
Table 3.1.1.
1. Each condom was placed into a vial. 2. The optimal fiber was injected into each vial by piercing the plastic septum of the vial lid and injecting it down. 3. Another vial with no condom present was injected for a negative control 4. Each fiber sampled the headspace of the condom at the optimal sampling time at room temperature. 5. Each fiber was retracted after sampling and injected into the GC/MS and desorbed for 9 minutes with the parameters listed in Table 3.2.5. 6. The GC-MS data for each brand was analyzed.
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3.3. Data Collection and Analyses
3.3.1. Condom Brand SPME Profiling
Once the optimal fiber sampling time was developed, 3 samples of each condom brand was evaluated with SPME-GC-MS. The chromatograms were used to determine which compounds were able to be detected for each condom brand. Using JMP Pro 12, data for each brand were analyzed using principle component analysis to determine if the different brands are able to be clustered away from each other.
3.3.2. Fingerprint Development ─ Temperature Effect
Irrespective of temperature treatment for each sample, all fingerprints from each selected temperature group was photographed and graded. The criteria used was a scoring system previously used by Jasuja et al. [73] (Table 3.1.2) by a certified fingerprint examiner. The results in the form of a grade was compared between all temperature groups and condom brands to determine temperature effect on ridge development. Using
SAS University Edition, standard N-way ANOVA testing using Tukey honestly significant difference (HSD) testing was implemented to evaluate temperature and brand effect on grading.
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4. Results
4.1. Temperature-Brand Effect on Fingerprint Development
4.1.1. Magnetic Powder
After each condom was developed with superglue fuming and magnetic powder, scores were taken for each developed fingerprint according to Table 3.1.2. There were
potentially 5 fingerprints on each of 27 condoms, making a total of 135 potential prints. If
no print was developed, the score for that fingerprint was automatically scored 1. Out of
the 135 deposits 47 or ~35% of the prints were able to be developed. Each of the 5
fingerprint scores from each condom was averaged into a five-print average. For all condoms, the five-print averages ranged from 1 to 3.2. Of these, there were 11 condoms in which no fingerprints developed. The variables associated with these condoms included all of the Durex placed in warm and Crown placed in warm. All the best fingerprint scores (i.e., the fingerprints that were scored 5) were developed on LifeStyles.
These were stored in either cool or warm temperatures.
All overall average scores when comparing each temperature were less than 2
(Figure 4.1.1). Condoms stored in cool temperatures had the overall greatest average,
1.62 (not significantly). The highest five-print average of these were 2.4 which was for
LifeStyles cool. Averages scored from deposits stored in 40ºC were scores ranging from
1 to 3.2. The overall average for these were 1.56 which was less than 0.84 less than the average for those stored in 15ºC. Averages scored from deposits stored in 24ºC ranged from 1 to 1.8. The overall average was 0.2 less than the average score for those stored in
15ºC. None of the overall scores between the temperatures were significant from each other.
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3.00
2.00 1.56 1.62 1.42 Average Socre
1.00 15ºC 24ºC 40ºC
Temperatue
Average 95 % Confidence Temperature Score Stdev. Interval 15ºC 1.62 0.55 1.35 1.90 24ºC 1.42 0.34 1.28 1.83 40ºC 1.56 0.86 1.15 1.70 Not significant
Figure 4.1.1. Overall averages per storage temperature after superglue fuming and magnetic powdering For each brand, the overall average for LifeStyles was the highest score, 2.04, (p
= 0.0015 and p = 0.0019 compared to Crown and Durex, respectively; Figure 4.1.2). This
was the only brand in which at least one developed print scored a 5. Of the 9 LifeStyles, 1
developed after 15ºC exposure and 2 developed after 40ºC exposure included an optimally scored print with the score 5. In addition, one of those LifeStyles had all five prints score above 1 (Figure 4.1.3). The lowest average was 1.27 which was from those developed from Crown. This was 0.77 lower than the overall score for LifeStyles.
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3.00
2.04
2.00
1.27 1.29 Average Score
1.00 Crown Durex LifeStyles Brand
Average 95 % Confidence Brand Score Stdev Interval Crown 1.27 0.32 0.99 1.54 Durex 1.29 0.41 1.01 1.56 LifeStyles 2.04* 0.65 1.77 2.32 *Significant from Durex and Crown with P < 0.005 for each
Figure 4.1.2. Overall averages per brand after development with superglue fuming and magnetic powder
LifeStyles 2 LifeStyles
5 3 3 3 2
Figure 4.1.3. Prints developed on Lifestyles stored in 40ºC after development with superglue fuming and magnetic powdering
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When averaging condoms of the same brand and storage temperature, LifeStyles
stored in warm (40ºC) had the highest overall average (Table 4.1.1). This was significant from each (p < 0.05) except LifeStyles stored in cool.
Table 4.1.1. Overall averages per temperature-brand combination
95 % Confidence Brand Temperature Average Score Stdev Interval LifeStyles Warm 2.67* 0.46 2.19 3.14 LifeStyles Cool 1.93 0.50 1.46 2.41 LifeStyles Room 1.53 0.46 1.06 2.01 Durex Cool 1.53 0.61 1.06 2.01 Crown Room 1.40 0.35 0.92 1.88 Crown Cool 1.40 0.35 0.92 1.88 Durex Room 1.33 0.31 0.86 1.81 Crown Warm 1.00 0.00 0.52 1.48 Durex Warm 1.00 0.00 0.52 1.48 *Significant between all (P < 0.05) except LifeStyles Cool
4.1.2. Inter-person Variability ─ Magnetic Powder
A sample size of 20 people deposited five fingerprints from each finger on one hand on the condom brand that had the overall highest average which was LifeStyles.
Together there were a total of 100 prints. Each were stored in cool temperature and developed with superglue fuming and magnetic powder. Scores between each fingerprint ranged between 1 and 4. Five-print averages ranged from 1 to 3 (Figure 4.1.4; Figure
4.1.6), and the overall average was 1.98. Compared to LifeStyles cool scores from the temperature analysis (Table 4.1.1) this was 0.05 higher. There was a high frequency of five-print scores that scored between 2 and 3 (Figure 4.1.1). Less than half of the five- print averages scored for the samples scored between 1 and 2 and between 3 and 4.
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Figure 4.1.4. Box and whisker plot of five-print averages from deposits of N = 20 males, stored in 15ºC, and developed with superglue fuming and magnetic powder
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Frequency
Five-print Average Figure 4.1.5. Distribution of five-print average sores among N = 20 sample after processing with superglue fuming and magnetic powder
Subject 20
4 4 3 2 2
Figure 4.1.6. Highest scored prints from a population study (N = 20 males) on LifeStyles which was stored in 15ºC and subsequently developed with superglue fuming and magnetic powder 4.1.3. Rhodamine 6G
After subsequent processing with rhodamine 6G, each print was scored again, and a five-print average was calculated for each condom. Five-print averages ranged from 1
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to 4.4. Those with the highest averages included Durex in 15ºC and Durex in 24ºC
(Figure 4.1.7). Those with the lowest were LifeStyles stored in 15ºC, LifeStyles stored in
24ºC, and Crown stored in 40ºC.
C ° 24
Durex 3 Durex
5 5 5 3 2
C ° 15
Durex 3 Durex
5 4 5 5 3 Figure 4.1.7. Fingerprint development with the highest five-print averages after development with superglue fuming, magnetic powder, and rhodamine 6G.
There were only 7 condoms that did not contain a print with a score of 5. These included all of Crown that were stored in 40ºC, 1 LifeStyles that was stored in 24ºC, and
1 of the samples of LifeStyles stored in 15ºC. Out of the total of 27 condoms, 18 contained fingerprints with a maximum score of 5. These included condoms from all combination of brand and storage temperature expect for Crown stored in 40ºC. Overall averages between each temperature varied between 2.62 and 2.91 with 15ºC having the highest average (not significant) (Figure 4.1.8).
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5.00
4.00 2.91 2.76 2.62 3.00
Average Score 2.00
1.00 15ºC 24ºC 40ºC Temperature
Temperature Average Score Stdev. 95 % Confidence Interval 15ºC 2.91 1.15 2.25 3.57 24ºC 2.76 1.05 2.10 3.41 40ºC 2.62 1.37 1.96 3.28 Not significant
Figure 4.1.8. Overall averages per storage temperature after subsequent rhodamine staining
Unlike the scores after magnetic powder, all five-prints averages from Durex were
at least 2. All Durex condom had at least 1 print that was scored a 5. Comparing overall averages for each brand, fingerprints deposited on Durex had better scores (p < 0.005;
Figure 4.1.9). Developed fingerprints on Durex had an overall average of 3.69 ± 0.77 which was 2.4 higher than Durex scored for magnetic powder and 1.65 higher than
LifeStyles which was best overall for magnetic powder.
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5.00
3.69 4.00
2.47 3.00 2.13
Average Score 2.00
1.00 Crown Durex LifeStyles
Brand
Brand Average Score Stdev. 95 % Confidence Interval Crown 2.13 1.01 1.47 2.79 Durex 3.69* 0.77 3.03 4.35 LifeStyles 2.47 1.10 1.81 3.13 *Significant from LifeStyles and Crown with P < 0.005 for each
Figure 4.1.9. Overall averages per brand after subsequent development with rhodamine 6G
For each temperature-brand combination, an overall average score was calculated.
All average scores were greater than 1 (Table 4.1.2). Durex stored in 40ºC had the highest average, 3.93 ± 0.12 (not significant). This was 0.8 higher than LifeStyles stored in 40ºC which had the overall highest score (p < 0.05; Figure 4.1.2) when developed with
magnetic powder. Previous condoms that had no development after magnetic powdering
did after rhodamine staining. These included one of the Crown brands stored in 40ºC.
Previously, none of these had any developed prints. After rhodamine staining and
visualization, one of these condoms contained a print that was scored a 4. Durex stored in
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40ºC also did not have any developed prints after magnetic powdering. After rhodamine
staining, all of these at least contained 3 prints with a score of 5.
Table 4.1.2. Averages for each temperature-brand combination after subsequent development with R6G
95 % Confidence Brand Temperature Average Score Stdev. Interval Durex Warm 3.93* 0.12 2.79 5.07 Durex Cool 3.60 0.92 2.46 4.74 Durex Room 3.53 1.17 2.39 4.67 LifeStyles Warm 3.13 1.22 1.99 4.27 Crown Cool 2.73 1.33 1.59 3.87 Crown Room 2.47 0.46 1.33 3.61 LifeStyles Cool 2.40 1.22 1.26 3.54 LifeStyles Room 1.87 0.81 0.73 3.01 Crown Warm 1.20 0.35 0.06 2.34 *Significant from Crown Warm P = 0.0448
4.1.4. Inter-person Variability-Rhodamine 6G
Five-print average scores calculated for N = 20 males ranged from 1 to 3.8
(Figure 4.1.10). Out of the 20, 9 condoms contained at least one print that scored a
maximum score of 5, and 2 condoms had an average score of 1. The overall average for
all condoms was 2.09 ± 0.73. Applying standard One - Way ANOVA, comparison between population scores after magnetic powder development and rhodamine 6G development - which were averages 1.98 ± 0.48 and 2.09 ± 0.73, respectively - was not significant (p = 0.58).
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Figure 4.1.10. Box and Whisker plot of deposits of N = 20 males, stored in 15ºC, and developed subsequently with Rhodamine 6G.
Frequency
Five-print Average Figure 4.1.11. Distribution of five-print average scores among N = 20 sample after subsequent processing with Rhodamine 6G.
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4.2. Condom Brand Identification via HS-SPME-GC-MS
4.2.1. Fiber and Sampling Time
PA and PDMS fibers yielded the least detected compounds ranging from 0 to 1
compound for all sampling times. This compound was N,N-dibutyl-formamide (Figure
4.2.1). N,N-diethyl-formamide and Decane was also found in CAR/PDMS and
DVB/PDMS in at least 3 of the different sampling times. It was found in
DVB/CAR/PDMS in all sampling times. 1-Methoxy-2-propyl acetate was another compound found in either DVB/PDMS or DVB/CAR/PDMS. This compound had a peak abundance when sampling with DVB/CAR/PDMS for 6 hrs. Decane, which was found when sampling with CAR/PDMS, DVB/PDMS, and DVB/CAR/PDMS, had peak abundance when sampling with DVB/CAR/PDMS at 12 hrs. The peak abundance for undecane and dodecane was with DVB/CAR/PDMS at 3 hrs. and 6 hrs., respectively.
Introducing temperature, N,N-dibutyl-formamide had a peak abundance higher than those at all sampling time under normal temperatures. These conditions were achieved by sampling with DVB/PDMS for 0.5 hrs. in 70ºC (Figure 4.2.1).
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Figure 4.2.1. Relative abundances of select compounds detected in LifeStyles for each fiber sampled at 1 hr., 3 hrs., 6 hrs., 12 hrs., and 24 hrs.
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Figure 4.2.2. Relative abundances of select compounds detected from LifeStyles for each fiber sampled for 0.5 hrs. at 35ºC and 70ºC
For DVB/PDMS, the number of unique compounds detected increased as sampling time was increased (Figure 4.2.3). Number of compounds detected after sampling with CAR/PDMS had a decline from 12 hrs. to 24 hrs. Sampling with
DVB/CAR/PDMS had a decline from 3 hrs. to 6 hrs. and 12 hrs. to 24 hrs. For 35ºC, the maximum number of different compounds detected was 8. This was from sampling with
DVB/PDMS. For 70ºC, the maximum number of different compounds detected was 13.
This resulted from sampling with DVB/PDMS and with DVB/CAR/PDMS. This result was higher than the number of different compounds detected for all fibers sampled for 1 hr. The highest number of different compounds detected was from using DVB/PDMS
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and DVB/CAR/PDMS. For DVB/PDMS this was achieved after sampling for 24 hrs. For
DVB/CAR/PDMS, this was achieved after sampling for 12 hrs.
25 20 2019 20
1415 14 15 13 13 13 12 10 8 6 7 6 Compounds 5 5 3 3 3 Number of Unique Unique of Number 2 0 1 0 0 0 1 0 1 1 1 1 0 1 0 0 0 0 PA PDMS CAR/PDMS DVB/PDMS DVB/CAR/PDMS
35°C 70°C 1 Hour 3 Hour 6 Hour 12 Hour 24 Hour
Figure 4.2.3. Number of compounds detected for each fiber after 1 hr., 3 hrs., 6 hrs., 12 hrs., and 24 hrs. sampling times
4.2.2. Brand identification
The relative abundances of each found compound for 3 LifeStyles, 3 Durex, and 3
Crown condoms were used in a principle component analysis. These data was used to
relate each condom according to principle component coordinates which result from
measuring combination of variances among the data. Results indicate that each brands relationship between the two principle components were more similar than the relationship of those of other brands. As a result, Durex 1, Durex 2, and Durex 3 are plotted in area closer to each other than the other brands. The same applies to the replicates of Crown and LifeStyles (Figure 4.2.4). Coordinates calculated for Crown 1 and Crown 3 (0.89, 0.35) and (0.91, 0.36), respectively are more similar than those for
Crown 2 (0.89, 0.34) resulting in these values being clustered closer together (Table
4.2.1). Taking into account the relative abundance of each compound among each brand
and performing PCA again, the compounds associated with the highest loadings, or the
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driving compounds, were N-butyl-1-Butanamine, 1-Methoxy-2-propyl acetate, and 1-
Tridecanol (Table 4.2.2).
Table 4.2.1. Coordinates indicating relationship between each principle component
Figure 4.2.4. Principle component analysis of condoms brands according to relative abundances of different compounds detected
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Table 4.2.2. Driving compounds
Hierarchical clustering was also performed on the data. The heat map indicates
the magnitude of the relative abundance for each compound (Figure 4.2.5). Each compound was ordered according to the similarity of the pattern of abundance for all condom brands. The white spaces indicate that no abundance of the respective compounds was detected. The darker coloring indicates a higher abundance was detected.
The dendrogram shows which categories are more correlated. Using the pattern of abundances of each compound, the dendrogram shows each replicate of each brand clustering together. LifeStyles 1, LifeStyles 2, and LifeStyles 3 are more correlated together than the other brands. Durex 1, Durex 2, and Durex 3 are more correlated than the other brands. And the same applies for the Crown samples. As was indicated by PCA, some of the samples within the same brand that clustered closer together relative to other in the same brand also did in the hierarchical clustering the same way.
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Figure 4.2.5. Heat map and dendrogram of compounds and condom brands
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5. Discussion
Condoms are challenging substrate because of their undetermined shape and the presence of lubricants. Also, the stretching mechanism of the condoms affect the topology of the surface. These characteristics add more variables in the already existing dynamic of changes of interest that can potentially affect a substrate.
5.1. Temperature analysis on Fingerprint Development
Development with magnetic powder did not always result optimally, as some fingerprints located pre-powdering did not develop after powdering. There are three general variables which may explain why a deposit may not develop. These are the quality of the deposit, the post-deposit manipulation of the substrate, and the way the developmental method was applied to the substrate. The experimental setup included consistent time in plastic bag in order to induce consistent eccrine residue, applying the same non-temperature related procedures to each substrate, and deposition instruction to each donor. These instructions were to place each finger on the substrate with normal pressure. Non-development after powdering was determined to result from the powder not sufficiently adhering to the polymerized ridges. Either the powder did not adhere sufficiently to the ridges or the powder adhered to the background resulting in lack of contrast. The lubricant present could be a factor in this. Another factor contributing to the lack of development is the deposition of the pinky finger at the tip of the condom. These generally score that high relative to the other finger and condom placement combinations.
This could have been a factor of either the pinky finger not leaving good deposits or that the tip of the condom is more wrinkled than the base of the condom resulting in poor deposition and, accordingly, poor development.
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Average scores of developed fingerprints on condoms by Radford [72] were 3.19
for Durex, 3.15 for LifeStyles, and 2.52 for Okamoto. Per Tukey HSD test, the scores for
Okamoto were significantly different. Out of all condoms, 2 out of Okamoto condoms
were deemed suitable for comparison, 17 for Durex and 21 for LifeStyles. These results
were consistent with results in this study where for magnetic powdering, LifeStyles had significantly higher average scores, and the brand with the lowest score average was
Okamoto Crown.
In Radford’s study, where superglue fuming and powdering was employed, 40 out
of 144 samples where stated to have been suitable. Of the 144, 36 were developed with magnetic powder. The author states that 13 out of 36 condoms that were developed with magnetic powder had a score ≥ 4. This yields 36% for all time since depositions tested.
One major difference in this study was that, instead of each print receiving a single score, each condom received a single score. It is unclear if, for example, a condom received a score of 5 because there contained a print that had a score of 5 or if all prints contained a score of 5. For this study, only 4 out of 27 condoms contained prints with a score ≥ 4 which is ~15% of the condoms tested. None of these included the ones stored in 24°C.
Differences in results could be attributed to the difference in the superglue fuming procedures. In this previous study, baking soda-saturated cotton balls were placed in the chamber while fuming which may have affected the chemical reaction that leads to polymerization of the residue. Comparing to R6G, 20 out of 27 or 74 % of the condoms contained prints with scores ≥ 4. Out of all that were stored in 24ºC, ~66 % scored ≥ 4. If comparing 5-print averages, only 30% were above 4.0 for all temperatures, and only 22% scored above 4.0.
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Possible reason why condoms stored in cool temperatures had higher averages
overall is that the cool temperature may help preserve the residue in its original state. The
lack of significance in the result may be attributed to the insignificant effect of the tested
variable or the sample size in conjunction with standard deviations resulting from natural
variations (e.g., the possibility of intra-brand variations like distribution of lubricant due
to how the package was stored or the natural variation of intra-donor residue secretions).
In a study by Gray [74], where room temperature was compared to refrigerator
temperature (40ºF or 4.44ºC), temperature was stated to have an effect on development
on several types of surfaces including plastic bottles, glass, and aluminum. Development
of fingerprints stored in the refrigerator was stated to be of higher quality compared to
ambient temperatures and room temperature. Fingerprint residue containing substrates under cooler temperatures may result in containing or achieving residue conditions optimal for superglue fuming. In this study, some of the residues on substrates stored in warmer temperatures had relatively better results, but these results were not significantly higher than all the residues on substrates under cooler temperatures. Even when comparing brand and temperature, LifeStyles warm was not significantly different from
LifeStyles cool (Table 4.1.1). Dominick, Nic Daéid and Bleay [75], after comparing
development of fingerprints on various substrates that had been exposed to elevated
temperatures over period of time found temperature and exposure time had a significant
affect and that superglue fuming in conjunction with BY40 stain was one of the optimal
methods used compared to vacuum metal deposition and iron oxide suspension.
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5.2. Identification of Condom Brands
In addition to detected compounds used for profiling, total ion chromatogram results included various siloxanes which were not included in the analysis since these were possible extraneous peaks. Extraneous peaks are not an uncommon occurrence in
SPME. Wercinski [61] points out that even when fibers are sampling a blank vial, the
GC-MS may still indicate that various types of siloxanes and nitrogen-containing compounds are present. These compounds are known to come from the vial septum and the glue used in the fiber assembly, respectively. To minimize interferences of siloxanes, the septa are usually baked overnight at 150°C [61]. Vials and septa were baked before sampling. However, there were some siloxanes present albeit most were not present significantly.
Using DESI-MS, Mirabelli et. al. [34], found compounds in condoms such as nonoxynol-9, polyethylene glycol, polydimethylsiloxane. Mirabelli et. al. [34] states that other compounds found which where methylmorpholine, N-octylamine, N,N-dibutyl formamide, and isonox, 132 are compounds used in lubrication. N,N-dibutyl formamide which was a common compound found for this study (Figure 4.2.1 and Figure 4.2.2) is known to be a catalyst and cosurfactant in condom production [34, 54].
Figure 5.2.1. Chemical structure of N,N- dibutyl-formamide [76]
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Compounds found by Jones [6] with SPME GC-MS included the following compounds: butylated hydroxytoluene, octadecanoic acid, n-hexadecanoic acid, heptasiloxane, n-hexadecanoic acid, octadecadienoic acid, octadecanoic acid, silane, undecanoic acid, and octadecyne, butenol. None of these compounds were identified in this study. This is likely a result of the different sampling conditions used. In Jones [6], the fiber was inserted into a diluted rinse of each condom. The compounds listed in addition to various siloxanes were the compounds stated to be present. The dilution and relatively short sampling time may have limited the number of compounds available to adsorb into the fiber. The state of the matrix (liquid as opposed to the headspace) may have affected the nature of the compounds that adsorbed which would explain why different compounds were detected in this study. Sampling time was only 30 minutes and fibers used were PDMS, DVB/PDMS, and PA. For this study, using DVB/PDMS and PA for 1 hr. no compounds were detected. Similar to what happened in this study, by using the diluted matrix, more compounds may be able to be detected by introducing heat or increasing sampling time. But sampling headspace may be desired to preserve the original state of the condom. Jones also stated that data for DVB/PDMS and PA were more similar to each other and were able to detect more compounds. In this study, PDMS and PA were more similar, and compared to the other fibers tested (DVB/PDMS,
CAR/PDMS, and DVB/CAR/PDMS), these fibers detected the least number of unique compounds. This may also be explained by the differences in sampling conditions used.
For PDMS, only 1 compound (N,N-dibutyl-Formamide) was able to be detected.
This was at sampling times, 1 hr., 3 hrs., and 12 hrs. and in temperatures, 35ºC and 70ºC.
In other sampling times tested, no compounds were detected. N,N-dibutyl-Formamide
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was detected in two different condom brands tested: LifeStyles and Crown (Figure 4.2.5) which indicates this compound may not be useful in differentiating between certain condom brands. In Jones [6], PDMS was stated to result in a chromatogram with equidistant peaks. With this fiber the retention times and mass spectra were stated to be
similar for different brands tested. The optimal fiber where 20 unique compounds were
detected (DVB/CAR/PDMS) is a combination of polymers including PDMS. If an
improved fiber was utilized, it may be a combination of fibers that did not include PDMS
since this may not be optimal complementary polymer for discrimination purposes.
The implications from this study may be inducted according to the applicable
conditions that were tested. Because samples were tested out of the package, variables
associated with other potential variables such as varying degrees of physical
manipulation, exposure to various materials (e.g., dirt, fibers, or body fluids), and sun
exposure cannot be inferred. Each of these potentially have multiple sub-variables that
may affect the persistence or transfer of lubrication which may affect the volatile
characteristics or fingerprint persistency. Variations of factors may either decrease,
increase, or do nothing to expected results. For factors limiting available results, further
analysis in method alterations may provide insight in how to mitigate the negative affect
of these factors. In which case, the accumulating possibilities fit into a magnitude of
analysis that warrants another study. Other limitations include subjects utilized were not
random since all were employees at DPS. This limits the reliability of generalizing this to
a larger male population. Additionally, fingerprint deposits for the temperature analysis
was completed in one day which incorporates confounds such as subject fatigue (i.e., the
subject over time could have changed the way he deposited his fingerprints from one
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condom to the next), and residue variation involved with repeated depositions within a day. In the population study, each subject was instructed to apply normal pressure.
However, the amount of pressure was likely not consistent between each subject due to the variation of what was comprehended as “normal pressure”. Rhodamine 6G was used as developmental method since it’s a stand routine procedure at DPS. This does not imply that other fluorescent techniques might not be as successful.
5.3. Conclusion
Condom substrates may be artifacts of interest in sexually related, unsexually related, or unknown circumstances. In either case, information deduced from the presence of these substrates may be available even when DNA is absent. These alternative methodologies may be desirable if the case is cost sensitive (i.e., there are only a limited amount of money able to be spent) and time sensitive in which case DNA analysis is not as convenient. Differences of temperatures on certain brands indicate that the substrate condition should be considered when applying a developmental method. As mentioned about the variations of different sub-types of substrates, different brands of condoms may need to be developed differently in order to optimize fingerprint development results. In conclusion to the temperature – brand variation on fingerprint development, the hypothesis that the quality of fingerprint development on different brands that were exposed to different temperatures will have a significant difference was supported for
Lifestyles in warm developing with superglue fuming and magnetic powder; and Durex in warm developing with superglue fuming and rhodamine 6G.
The differentiation of brands using headspace SPME – GC-MS is advantageous, because the brand of condom is able to be determined without the label wrapper and
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without extensively manipulating the condition of the condom substrate. This indicates that standard forensic protocol may include sampling the headspace of the condom before
storing the evidence to be further processing. If processing is going to be done with
rhodamine 6-G and the evidence is determined to be a Durex condom, then storage in
40ºC may help produce optimal results when implementing fingerprint development
techniques. In contrast, if the evidence is determined to a Crown brand, then storage in
more cooler temperatures may contributed to optimize fingerprint development when
processed. If magnetic powder is going to be implemented, then for the Durex condom,
storage in cooler temperatures may contribute in optimizing development results. In
conclusion to the brand differentiation results, the hypothesis that the variances of the
relative abundances of the compounds will be able to be used to statistically separate the
different brands of condoms was supported.
For cases involving sexual assault, many variables such as circumstances
involving the suspect and victim, types of evidence available, and perceptions of the jury
can affect the outcome of the case. Circumstantial evidence is a part of the case that
provides a subset of exclusional, inclusional, or other-variable dependent information that
has potential to guide investigators to more probative evidence or provide important
associations and means to disprove testimonial evidence. Condom substrates are one of
these types of evidence that may be relevant to these cases, and as more substrate
exposure variables and brands are tested, the more robust procedures (e.g., fingerprint
development, extraction and analyzation for brand identification) that can be established.
Establishing procedures that provide forensically relevant information adds potential
means to piecing together the truth and contribute to the sufficiency of the investigation.
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Taking into account of the major findings, general recommendations in processing condom evidence include to store condoms in cooler temperatures until processing with cyanoacrylate fuming and applying rhodamine 6G. Future studies should include determining which condom brands are common in which geographical locations.
Condom brand information may not only just be useful in providing information for using the optimal method for fingerprint development but also for determining where to condom was likely purchased.
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76. NIST, 2017 Formamide, n,n-dibutyl-. NIST Chemicstry WebBook 2017 [cited 2018] Available from: https://webbook.nist.gov/cgi/cbook.cgi?Name=N%2CN+dibutyl+Formamide&Un its=SI.
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Appendix I: Photographs and Scores of Developed Fingerprints
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Magnetic Power
15ºC
1
- moto Crown moto a Ok
3 2 2 2 1
- - - - - moto Crown 2 Crown moto a Ok
1 1 1 1 1
- - moto Crown 3 Crown moto a Ok
2 2 2 1 1
- - - - LifeStyles 1
3 1 1 1 1
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- LifeStyles 2
3 2 2 2 1
3
- - LifeStyles
5 3 2 1 1
- - - Durex 1 Durex
2 2 1 1 1
- - Durex 2 Durex
3 4 2 1 1
100
Texas Tech University, Amanda Patrick, December 2018
- - - - - Durex 3 Durex
1 1 1 1 1
24ºC
- - - Okomoto Crown 1 Crown Okomoto
3 2 1 1 1
2
- - - - - Okomoto Crown Okomoto
1 1 1 1 1
3
- - - - Okomoto Crown Okomoto
2 1 1 1 1
101
Texas Tech University, Amanda Patrick, December 2018
- LifeStyles 1
2 2 2 2 1
- - LifeStyles 2
3 2 2 1 1
- - - - - LifeStyles 3
1 1 1 1 1
- - - - - Durex 1 Durex
1 1 1 1 1
102
Texas Tech University, Amanda Patrick, December 2018
- - Durex 2 Durex
2 2 2 1 1
- - Durex 3 Durex
2 2 2 1 1
40ºC
- - - - - Okomoto Crown 1 Crown Okomoto
1 1 1 1 1
- - - - - Okomoto Crown 2 Crown Okomoto
1 1 1 1 1
103
Texas Tech University, Amanda Patrick, December 2018
- - - - - Okomoto Crown 3 Crown Okomoto
1 1 1 1 1
- - LifeStyles 1
5 3 2 1 1
LifeStyles 2
5 3 3 3 2
- LifeStyles 3
3 2 2 2 1
104
Texas Tech University, Amanda Patrick, December 2018
- - - - - Durex 1 Durex
1 1 1 1 1
- - - Durex 2 Durex
2 2 1 1 1
- - - - - Durex 3 Durex
1 1 1 1 1
105
Texas Tech University, Amanda Patrick, December 2018
Magnetic Powder ─ Population
LifeStyles stored in 15ºC
1
Subject
3 2 2 2 2
Subject 2
2 4 2 2 1
Subject 3
1 1 1 1 1
Subject 4
4 2 2 1 1
106
Texas Tech University, Amanda Patrick, December 2018
Subject 5
3 2 2 2 1
Subject 6
4 2 2 1 1
Subject 7
2 1 1 1 1
Subject 8
4 3 3 2 1
107
Texas Tech University, Amanda Patrick, December 2018
- - - - - Subject 9
1 1 1 1 1
Subject 10
2 2 1 1 1
Subject 11
2 2 2 1 1
Subject 12
3 2 2 1 1
108
Texas Tech University, Amanda Patrick, December 2018
Subject 13
2 2 2 1 1
Subject 14
4 4 2 1 1
Subject 15
2 2 2 2 2
Subject 16
2 4 2 2 2
109
Texas Tech University, Amanda Patrick, December 2018
Subject 17
2 2 2 3 1
Subject 18
3 2 3 1 1
Subject 19
2 2 2 1 1
Subject 20
4 4 3 2 2
110
Texas Tech University, Amanda Patrick, December 2018
Rhodamine 6G
15ºC
- - - Okomoto Crown 1 Crown Okomoto
3 2 1 1 1
2
- - - Okomoto Crown Crown Okomoto
5 3 1 1 2
3 Okomoto Crown Crown Okomoto
5 4 4 5 3
- LifeStyles 1
5 5 3 2 1
111
Texas Tech University, Amanda Patrick, December 2018
- - - - - LifeStyles 2
1 1 1 1 1
- LifeStyles 3
5 5 3 1 1
Durex 1 Durex
5 3 5 5 1
- - Durex 2 Durex
4 2 5 1 1
112
Texas Tech University, Amanda Patrick, December 2018
Durex 3 Durex
5 4 5 5 3
24ºC
- Okomoto Crown 1 Crown Okomoto
3 3 2 2 1
2
- Okomoto Crown Okomoto
5 3 4 2 1
3
- - Okomoto Crown Okomoto
4 3 2 1 1
113
Texas Tech University, Amanda Patrick, December 2018
- - - - - LifeStyles 1
1 1 1 1 1
- - LifeStyles 2
5 3 3 1 1
- LifeStyles 3
3 2 2 2 1
Durex 1 Durex
5 5 5 5 2
114
Texas Tech University, Amanda Patrick, December 2018
- - - Durex 2 Durex
5 3 1 1 1
Durex 3 Durex
5 5 5 3 2
40ºC
- - - - - Okomoto Crown 1 Crown Okomoto
1 1 1 1 1
- - - - - Okomoto Crown 2 Crown Okomoto
1 1 1 1 1
115
Texas Tech University, Amanda Patrick, December 2018
- - - - Okomoto Crown 3 Crown Okomoto
4 1 1 1 1
- - - - LifeStyles 1
5 1 1 1 1
- LifeStyles 2
5 5 5 5 1
- - LifeStyles 3
5 5 5 1 1
116
Texas Tech University, Amanda Patrick, December 2018
- Durex 1 Durex
5 5 5 4 1
- Durex 2 Durex
5 5 5 3 1
Durex 3 Durex
5 5 5 3 2
117
Texas Tech University, Amanda Patrick, December 2018
Rhodamine 6G ─ Population
Subject 1
2 2 3 1 1
2 - - - - - Subject
1 1 1 1 1
3 - - Subject
4 3 3 1 1
- - - Subject 4
2 2 1 1 1
118
Texas Tech University, Amanda Patrick, December 2018
- - Subject 5
2 2 5 1 1
- - - Subject 6
3 3 1 1 1
- - Subject 7
5 5 3 1 1
- - Subject 8
5 3 3 1 1
119
Texas Tech University, Amanda Patrick, December 2018
- Subject 9
3 2 2 2 1
- - - - Subject 10
5 1 1 1 1
- - Subject 11
5 5 1 1
- - - Subject 12
5 4 1 1 1
120
Texas Tech University, Amanda Patrick, December 2018
- - - Subject 13
3 5 1 1 1
- Subject 14
2 3 3 5 1
Subject 15
5 3 3 5 3
- - Subject 16
3 4 2 1 1
121
Texas Tech University, Amanda Patrick, December 2018
- - - - Subject 17
2 1 1 1 1
- - - - - Subject 18
1 1 1 1 1
- - Subject 19
3 2 2 1 1
- - - - - Subject 20
1 1 1 1 1
122
Texas Tech University, Amanda Patrick, December 2018
Appendix II: Compound Data and Chromatograms
123
Texas Tech University, Amanda Patrick, December 2018
Compound LifeStyles 1 LifeStyles 2 LifeStyles 3 Durex 1 Durex 2 Durex 3 Crown 1 Crown 2 Crown 3 Blank 1,3,5-Cycloheptatriene 0 0 10589546 0 0 0 0 0 0 0 Benzene, methyl- (CAS) 0 0 3029968 0 0 0 0 6386322 0 0 Hexanal 0 0 5141780 0 0 0 0 0 0 0 Butanoic acid, ethyl ester 0 0 21138612 0 0 0 0 0 0 0 Butanoic acid, 3-methyl-, ethyl 0 0 0 2664431 0 0 0 0 0 0 ester (CAS) p-Xylene 9982586 12287330 10518519 0 0 0 0 0 0 0 1-Methoxy-2-propyl acetate 23942746 27730362 94430445 0 0 0 0 0 0 0 (s)-3-Ethyl-4-methylpentanol 0 0 1706126 0 0 0 0 0 0 0 2-Pentene, 4,4-dimethyl- 0 0 0 0 0 0 0 5351036 0 0 Formamide, N,N-diethyl- 28934204 30091323 84375965 0 0 0 57792932 100740117 55957164 0 2-Propenenitrile, 3-phenyl-, (E)- 0 0 0 0 616916632 0 0 0 0 0 1-Butanamine, N-butylidene- 0 0 0 0 0 6874929 0 0 0 0 1-Butanamine, N-butyl- 9459564 0 24513311 0 0 0 0 0 0 0 Benzaldehyde 0 0 0 0 0 0 28320839 51590511 64339962 0 4-Nitro-4'- 0 0 0 0 0 0 287495387 0 0 0 chlorodiphenylsulphoxid Benzene, 1-ethyl-4-methyl- 0 0 14753909 0 0 0 0 0 0 0 Benzene, 1,2,3-trimethyl- 0 8125098 0 0 0 0 0 0 0 0 Benzene, 1,2,4-trimethyl- 9459564 0 0 0 0 0 0 0 0 0 1,5-Cyclooctadiene, 1,5- 0 0 0 0 64705850 69483291 0 0 0 0 dimethyl- Dodecane, 1-fluoro- 0 0 0 0 0 0 0 2694899 5537999 0 Dodecane, 2,2,11,11- 0 0 0 33687345 0 0 0 306117948 0 324774925 tetramethyl- Limonene 0 0 0 0 0 99493905 0 0 0 0 Decane, 2-methyl- 0 0 35309789 0 0 0 0 0 0 0 Dodecane 18499846 4790688 19950583 4289430 3769454 3385599 0 0 0 0 Benzyl Alcohol 0 0 0 212062862 0 183419915 0 0 0 0
124
Texas Tech University, Amanda Patrick, December 2018
Compound LifeStyles 1 LifeStyles 2 LifeStyles 3 Durex 1 Durex 2 Durex 3 Crown 1 Crown 2 Crown 3 Blank Phenol, 3-methyl- 0 0 0 0 229425530 0 0 0 0 0 Tridecane, 3-methyl- 0 0 18526426 0 0 0 0 0 0 0 Decane, 3-methyl- 7287533 0 21155358 11370945 0 0 0 0 0 0 Butane, 2-iodo-2-methyl- (CAS) 0 8229427 0 0 0 0 0 0 0 0 Decane, 3,8-dimethyl- 0 0 118236399 0 0 0 0 0 0 0 Undecane, 2,9-dimethyl- 0 0 0 15801845 0 0 0 0 0 0 Heptadecane, 2,6,10,14- 0 0 49034227 0 0 0 0 0 0 0 tetramethyl Octane, 3,4,5,6-tetramethyl- 0 14632884 39509188 0 0 0 0 0 0 0 Octane, 2-methyl- 0 0 0 0 3884170 5293558 0 0 0 0 Nonane, 3,7-dimethyl-(CAS) 0 0 0 0 0 5503012 0 0 0 0 Octane, 4-ethyl- 21736348 0 0 0 0 0 0 0 0 0 Undecane, 5-methyl- 0 40042826 117631053 0 0 18313529 0 0 0 0 Nonane, 2-methyl- 0 0 0 16025151 0 0 0 2961810 0 0 Octane, 3,5-dimethyl- 0 0 0 0 0 26018097 0 0 0 0 Hydroxylamine, O-decyl- 0 0 0 16087995 0 0 0 0 0 0 2-N-HEXYL-1-D1-AZIRIDINE 0 0 0 0 8267860 0 0 0 0 0 Decane 0 15998915 0 0 18276653 0 0 0 0 0 1-Octanol, 2-butyl- 0 15075075 0 22937893 0 13350617 0 25640210 0 0 6-Dodecene, (E)- 0 0 0 0 0 0 0 10420727 0 0 6-Dodecene, (Z)- 0 0 0 0 0 0 7931727 0 0 0 Undecane (CAS) 24062313 0 0 0 0 0 0 0 9150200 0 Tridecane, 4-methyl- 64172480 0 100291486 0 12803383 0 0 0 0 0 Dodecane, 2,6,10-trimethyl- 32962968 0 46186433 0 0 0 0 0 0 0 Dodecane, 2,6,11-trimethyl- 25344636 23035460 0 0 0 8124095 0 0 0 0 Dodecane, 2,7,10-trimethyl- 0 0 57400044 0 0 0 0 0 0 0 Decane, 3,7-dimethyl- 0 19832714 0 16942624 5435007 18038329 0 0 0 0 Linalool 0 0 0 0 407346555 513655604 0 0 0 0 Undecane 117590945 0 179907475 0 0 0 0 0 0 0
125
Texas Tech University, Amanda Patrick, December 2018
Compound LifeStyles 1 LifeStyles 2 LifeStyles 3 Durex 1 Durex 2 Durex 3 Crown 1 Crown 2 Crown 3 Blank 1-Pentene, 3-ethyl- 0 0 0 0 0 0 0 0 23540946 0 Nonadecane 0 30496090 0 0 0 0 0 0 0 0 1-Tridecanol (CAS) 0 0 23855513 0 0 0 0 0 0 0 Octane, 2,3-dimethyl- 0 0 0 0 5495745 5823716 0 0 0 0 Undecane, 4-methyl- 0 0 11850017 0 0 0 0 0 0 0 Heptadecane, 8-methyl- 0 0 6733921 0 0 0 0 0 0 0 Undecane, 2-methyl- 0 0 0 0 6218836 0 0 0 0 0 Undecane, 2,3-dimethyl- 0 0 18222038 0 0 0 0 0 0 0 Dodecane, 3-methyl- 0 0 0 0 0 11685059 0 0 0 0 Eicosane 4591898 0 0 0 8779859 11159915 0 0 0 0 4-Nonene, 2-methyl- 0 0 0 0 0 0 0 0 7619920 0 Tridecane, 7-propyl- 0 0 0 11463645 0 0 0 0 0 0 5-Undecene,3-methyl-, (E)- 0 0 0 0 0 0 0 0 4795735 0 (+)-.alpha.-Terpineol (p-menth- 0 0 0 0 0 0 0 8323327 0 0 1-en-8-ol) 2-Ethyl-1-dodecanol 0 0 0 0 0 0 0 5460961 0 0 3-Cyclohexene-1-methanol, 0 .alpha., .alpha.,4-trimethyl-, 0 0 0 0 0 0 0 0 10572348 (S)- Octane, 5-ethyl-2-methyl- 0 0 0 0 0 0 0 8036350 7321399 0 Benzene, 1-methoxy-4-(2- 0 0 0 0 17725337 13315987 0 0 0 0 propenyl)- Benzene, 1-methoxy-4-(1- 0 0 0 0 0 0 7623413 0 0 0 propenyl)- Benzothiazole 0 0 0 0 0 0 8430446 15554316 0 0 1,6-Octadien-3-ol, 3,7- 0 0 0 0 218519547 189917104 172451322 0 0 0 dimethyl-, acetate Dibutyl-cyanamime 0 0 0 0 0 1900340 0 0 0 0 4-Octene, 2,3,6-trimethyl- 0 0 0 3705668 0 0 0 0 0 0
126
Texas Tech University, Amanda Patrick, December 2018
Compound LifeStyles 1 LifeStyles 2 LifeStyles 3 Durex 1 Durex 2 Durex 3 Crown 1 Crown 2 Crown 3 Blank Formamide, N,N-dibutyl- 79878835 59817129 0 0 0 0 0 0 0 0 2,6-Octadien-1-ol, 3,7- 0 0 0 0 2148181 1965451 0 0 0 0 dimethyl-, acetate, (Z)- Copaene 1883921 0 2218167 0 0 0 0 0 0 0 Chloroxylenol 0 0 0 0 0 0 99614514 126994202 155373483 0
127
Texas Tech University, Amanda Patrick, December 2018
Blank
LifeStyles 1
LifeStyles 2
128
Texas Tech University, Amanda Patrick, December 2018
LifeStyles 3
Durex 1
Durex 2
129
Texas Tech University, Amanda Patrick, December 2018
Durex 3
Crown 1
Crown 2
130
Texas Tech University, Amanda Patrick, December 2018
Crown 3
131