Copper-Based Point-Of-Care Sensor for Heavy Metal Determination in Public Health Applications

COPPER-BASED POINT-OF-CARE SENSOR FOR HEAVY METAL DETERMINATION IN PUBLIC HEALTH APPLICATIONS

A dissertation submitted to the Graduate School of the University of Cincinnati in partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY

in the Department of Electrical Engineering and Computing Systems of the College of Engineering and Applied Science

2015

by Xing Pei

B.S., Peking University, China, 2009

Committee Chair: Ian Papautsky, Ph.D. ABSTRACT

This work describes development of the first copper (Cu)-based sensor for determination of heavy metals, such as zinc (Zn), lead (Pb) and cadmium (Cd). Heavy metals require careful monitoring, yet current methods are too complex for a point-of-care (POC) system.

Electrochemistry offers a simple approach to metal determination, but traditional electrodes are difficult or expensive to microfabricate, preventing wide-spread use. The sensor described in this work features a new low-cost electrode material which offers simple fabrication, while maintaining competitive electrochemical performance. The sensors of this work were fabricated by photolithography and electroplating to form the three electrodes used for anodic stripping voltammetry (ASV): a Cu working electrode, a Cu auxiliary electrode, and a Cu/CuCl2 reference electrode. They were demonstrated to be sufficiently stable for at least one electrochemical measurement through the careful examination of each electrode. For the metals of interest, the

Cu-based sensors exhibited limit of detection (LOD) of 140 nM (9.0 ppb) for Zn, 21 nM (4.4 ppb) for Pb and 118 nM (13 ppb) for Cd. The sensor was also used to demonstrate measurements in biological (blood, serum) and environmental (surface water) sample matrices.

These results demonstrate the advantageous qualities of this POC electrochemical sensor for public health applications, which include a small sample volume (µL-scale), reduced cost, short response time and high accuracy at low concentrations of analyte.

ACKNOWLEDGMENTS

First, I would like to thank my advisor Dr. Ian Papautsky for his guidance during this work. His attitude, patience, awareness of details in experiments and records, and perspective of the project, set an excellent example as a productive researcher and professor. He showed me constant support and encouragement during my path towards an independent researcher. This invaluable experience will provide energy for the rest of my life.

I would like to thank other members of my committee, Dr. William R. Heineman, Dr.

Adam Bange, Dr. Chong Ahn and Dr. Fred Beyette. A special thank you to Dr. Heineman for his insights in electrochemistry and suggestions for methodology. His kindness infects all surrounding people. I would like to thank Dr. Bange for his help to validate our results and his ideas to solve problems during research. Dr. Ahn for wonderful courses in microfabrication, his enthusiasm, and insightful questions during the progress of this work. Dr. Beyette for cooperation with this work, and the opportunities to work with people from another area.

I would like to thank Ron Flenniken and Jeff Simkins for the cleanroom access and facilities and their hard work and valuable time for device fabrication. And thank you to Dr.

Necati Kaval for easy access and professional help of facilities in Department of Chemistry.

I would also like to thank all my lab mates from BioMicroSystems Laboratory. Special thanks to Dr. Preetha Jothimuthu, for her mentorship and valuable experience, and Wenjing

Kang, for her company and high standard of cleanliness. Thanks to Dr. Woohyuck Choi, Taher

Kagalwala, Dr. Li Shen, Michael Ratterman, Josi Herren, Dr. Jian Zhou, Dr. Ananda Banerjee, Nivedita, Xiao Wang, Yuguang Liu, Prithvi Raj Mukherjee and Richard Murdock, for the simple and friendly environment for study and research, and warmness as a group. I would like to thank collaborators from other labs, Dr. Robert Wilson, Dr. Wei Yue, Ram Kumar, Geethanga De

Silva and Benjamin Zerhusen from Dr. Heineman and Dr. Beyette’s groups for their efforts in this work.

Finally, I would like to thank my friends and family. My host family, John and Cynthia

Featherstone, for their help for me to settle down in a foreign country. Thanks to my dojo sister,

Zhizhen Wu, for her enterprising and easygoing attitude in work and life. More importantly, my parents and sister on the other side of this planet, whom magically make me feel safe and supportive without too many words. Peace.

TABLE OF CONTENTS

LIST OF FIGURES ...... iii

LIST OF TABLES ...... vi

LIST OF ABBREVIATIONS ...... vii

CHAPTER 1 INTRODUCTION ...... 1

State of the art in metal determination ...... 3 Scope of work ...... 10 Chapter summaries...... 12

CHAPTER 2 COPPER-BASED ELECTROCHEMICAL SENSOR ...... 13

Experimental methods ...... 15 Cu auxiliary electrode ...... 16 Cu/CuCl2 reference electrode ...... 19 Cu working electrode ...... 23 Summary ...... 26

CHAPTER 3 DETERMINATION OF METALS IN BUFFER ...... 27

Determination of Zn ...... 27 Determination of Pb ...... 34 Determination of Cd ...... 41 Summary ...... 46

CHAPTER 4 DETERMINATION OF MULTIPLE METALS ...... 47

Zn determination in presence of Pb ...... 48 Pb determination in presence of Zn ...... 51 Pb determination in presence of Cd ...... 52 Cd determination in presence of Pb ...... 54 Summary ...... 56

CHAPTER 5 DETERMINATION OF METALS IN REAL WORLD SAMPLES ...... 57

Zn in serum ...... 58 Pb in blood ...... 63 Pb and Cd in surface water ...... 69

i Summary ...... 75

CHAPTER 6 CONCLUSIONS ...... 77

APPENDIX ...... 80

REFERENCES ...... 109

ii LIST OF FIGURES

Figure Page 1. Illustration of ASV of Pb, Cd and Zn on a solid Cu working electrode (WE)...... 4 2. (a) Schematic of the electrochemical cell, working electrode (WE), auxiliary electrode (AE), and reference electrode (RE). (b) Photograph of the sensor with a mini-USB potentiostat connection...... 14

3. Fabrication process diagram for Cu-based sensor with Cu/CuCl2 RE. (a) Metal evaporated onto glass slides. (b) Electrode patterned by photolithography and wet etching. (c) Polymer well bonded by plasma discharge. (d) RE formatted by electrodeposition...... 15 4. Stability of Cu as an AE. (a) Images of un-oxidized Cu AE, and Cu AEs that have undergone 20 min and 60 min of oxidation. (b) Chronopotentiometry of Pt and Cu AEs under current of 10 µA. The curve for 200 nm Cu AE is an average of four measurements (n = 4), with the inset illustrating the point of failure of the actual four curves...... 18

5. (a) Cyclic voltammetry (CV) performed with Cu/CuCl2 (solid) or Ag/AgCl (dashed) as RE, in acetate buffer (0.2 M, pH 6) with 10 mM Zn. Scan rate = 100 mV/s. (b) ASV performed with Cu/CuCl2 (solid) or Ag/AgCl (dashed) as RE, in acetate buffer (0.2 M, pH 6) and 30 µM Zn...... 19

6. Potential of Cu/CuCl2 electrode in saturated KCl (buffered, pH 7.0) vs. commercial Ag/AgCl (double junction)...... 21

7. Potential of integrated Cu/CuCl2 and Ag/AgCl electrodes in acetate buffer (0.2 M, pH 6) vs. commercial Ag/AgCl (double junction)...... 22 8. (a) Anodic stripping voltammetry (ASV) of 10 μM Zn in acetate buffer (0.2 M, pH 6) with increasing duration of preconcentration. (b) Potential of Zn anodic stripping peak shifting over preconcentration duration...... 23 9. (a) CV of different WE materials in acetate buffer (0.2 M, pH 4.65) with commercial Ag/AgCl (double junction) RE, and Pt AE. Scan rate = 100 mV. (b) Threshold potentials (i = 10 µA) of different WE materials...... 24 10. (a) CV of Cu-based sensor in acetate buffer (0.2 M) with different pHs. Scan rate = 100 mV/s. (b) The threshold potential (i = 4 µA) at different pHs...... 25 11. CV in acetate buffer (0.2 M, pH 6) with 10 mM Zn. Scan rate = 100 mV/s...... 28 12. Optimization of experimental parameters: (a) pH of acetate buffer, (b) preconcentration potential, (c) preconcentration duration, (d) square wave period,

iii (e) square wave amplitude, (f) square wave increment. ASV performed in 10 µM Zn acetate buffer (0.2 M)...... 30 13. ASV of Zn samples in (a) 100 nM - 40 µM range and (b) 100 nM - 5 µM range. Experiments performed in acetate buffer (0.2 M, pH 6). Preconcentration potential -1 V, duration 300 s, amplitude 50 mV, period 60 ms, increment 6 mV...... 32 14. Calibration curves for Zn using (a) peak height and (b) peak area of stripping voltammograms...... 33 15. CV in acetate buffer (0.2 M, pH 5.5) with 100 µM and 1 mM Pb. Scan rate = 100 mV/s...... 35 16. Optimization of experimental parameters: (a) pH of acetate buffer, preconcentration (b) potential and (c) duration, square wave (d) period, (e) amplitude and (f) increment. ASV performed in 10 µM Pb acetate buffer (0.2 M)...... 36 17. ASV of acetate buffer (0.2 M, pH 5.5) before (grey) and after (black) deoxygenating, compared with 0.5 and 1 µM Pb...... 39 18. ASV of Pb in (a) 25 nM - 10 µM range and (b) 25 nM - 1 µM range. Analyses performed in acetate buffer (0.2 M, pH 5.5). Preconcentration potential -0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV. (c) Calibration curve for Pb in buffer...... 40 19. CV in acetate buffer (0.2 M, pH 6) with 200 µM or 500 µM Cd. Scan rate = 100 mV/s...... 42 20. (a) ASV of Cd in 20-200 µM range. Analyses performed in acetate buffer (0.2 M, pH 6). Preconcentration potential -0.9 V, duration 180 s. (b) Response currents at different concentrations of Cd in buffer...... 43 21. ASV of 5 and 10 µM Cd. Analyses performed in acetate buffer (0.2 M, pH 6). Preconcentration potential -0.9 V, duration 300 s...... 44 22. CV in 1 mM nitric acid with 200 µM or 1 mM Cd. Scan rate = 100 mV/s...... 44 23. (a) ASV of Cd in 0.5-10 µM range. Analyses performed in 1 mM nitric acid. Preconcentration potential -0.9 V, duration 180 s. (b) Calibration of Cd in nitric acid...... 45 24. ASV of 30 µm Zn (purple dot), spiked with 5 µm Pb (red dash), and 5 µm Cd (blue solid). Preconcentration potential -1.3 V, duration 300 s, amplitude 25 mV, period 70 ms, increment 4 mV ...... 47 25. (a) ASV of Zn and Pb. Analyses performed in acetate buffer (0.2 M, pH 6). Preconcentration potential -1 V, duration 300 s, amplitude 50 mV, period 60 ms, increment 6 mV. (b) Pb peak currents with different concentrations of Pb and Zn. (c) Zn peak currents with different concentrations of Zn and Pb...... 49 26. (a) Zn peak currents with different concentrations of Zn and Pb. (b) Pb peak currents with different concentrations of Pb and Zn. First step: preconcentration potential -0.8 V, duration 120 s, second step: preconcentration potential -1 V, duration 300 s, amplitude 50 mV, period 60 ms, increment 6 mV...... 50

iv 27. Zn peak currents with different concentrations of Zn and Pb. Preconcentration potential -0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV...... 52 28. (a) ASV of Pb and Cd. Analyses performed in acetate buffer (0.2 M, pH 5.5). Preconcentration potential -0.9 V, duration 300 s, amplitude 25 mV, period 70 ms, increment 4 mV. (b) Pb peak currents with different concentrations of Pb and Cd. Preconcentration potential -0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV...... 53 29. (a) ASV of Cd ranging at 0.5-5 µM. Analyses performed in acetate buffer (0.2 M, pH 5.5). First step: preconcentration potential -0.8 V, duration 120 s, second step: preconcentration potential -0.9 V, duration 300 s, amplitude 25 mV, period 70 ms, increment 4 mV. (b) Calibration of Cd in acetate buffer with present of 1 µM Pb...... 55 30. (a) ASV of Zn extract from bovine serum with additional 1 and 5 µM Zn, sample volume 200 µL. Preconcentration potential -1 V, duration 300 s, amplitude 50 mV, period 60 ms, increment 6 mV. (b) Standard addition curve for measurement of Zn concentration...... 61 31. ASV of serum sample a) mixed with Metexchange® or b) extracted, and with additional 100 - 500 ppb Pb. Preconcentration potential -0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV...... 64 32. ASV of digested blood and with additional 0.5 – 2 ppm Pb. Preconcentration potential -0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV...... 66 33. (a) ASV of digested blood with additional 20 – 500 ppb Pb. Preconcentration potential: first step: -0.4 V duration, duration 60 s, second step: -0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV. (b) Standard addition of Pb in digested blood...... 68 34. (a) ASV of pond water diluted by acetate buffer (0.2 M, pH 5.5), and additional 10 - 50 ppb Pb. Preconcentration potential -0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV. (b) ASV after background subtraction. (c) Standard addition curve for Pb in pond water...... 71 35. (a) ASV of pond water spiked with 50 ppb Pb, then diluted by acetate buffer (0.2 M, pH 5.5), and additional 10 - 50 ppb Pb. Preconcentration potential -0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV. (b) ASV after background subtraction. (c) Standard addition curve for Pb in pond water...... 72 36. (a) ASV of river water sample and additional 25 - 500 ppb Pb. Preconcentration potential -0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV. (b) Standard addition curve for Pb in river water sample...... 73 37. (a) ASV of pond water diluted by acetate buffer (0.2 M, pH 5.5), and additional 0.5-5 µM Cd. First step: preconcentration potential -0.8 V, duration 120 s, second step: preconcentration potential -0.9 V, duration 300 s, amplitude 25 mV, period 70 ms, increment 4 mV. (b) Standard addition curve for Cd in pond water...... 75

v LIST OF TABLES

Table Page 1. Summary of LOD and lowest detectable concentration of Cd using different Cu- based sensors...... 55

vi LIST OF ABBREVIATIONS

AAS = atomic absorption spectroscopy

AE = auxiliary electrode

AdSV = adsorptive stripping voltammetry

ASV = anodic stripping voltammetry

BIA = batch injection analysis

CDC = centers for disease control and prevention

CE = capillary electrophoresis

CNT = carbon nanotube

CPE = carbon paste electrode

CV = cyclic voltammetry

DPASV = differential pulse anodic stripping voltammetry

EA = electrothermal atomization

FWHM = full width at half maximum

GCE = glassy carbon electrode

HMDE = hanging mercury drop electrode

ICP-AES = inductively coupled plasma atomic emission spectrometry

ICP-MS = inductively coupled plasma mass spectrometry

ICP-OES = inductively coupled plasma optical emission spectrometry

IIP = ion imprinted polymer

vii LOD = limit of detection

MEMS = micro electro mechanical system

MWCNT = multi-walled carbon nanotube

NP = nanoparticle

ITO = indium tin oxide

PAD = paper-based analytical device

PANI = polyaniline

PCB = printed circuit board

PDMS = polydimethylsiloxane

POC = point-of-care

PSA IR = potential stripping analysis with inverse current

RE = reference electrode

SIA = sequential injection analysis

SPA-MLR = multivariate linear regression aided by successive projection algorithm

SPME = solid phase microextraction

SPE = screen printed electrode

SWASV = square wave anodic stripping voltammetry

WE = working electrode

viii CHAPTER 1

INTRODUCTION

Determination of trace heavy metals is important due to adverse impacts on the environment and human health. The three heavy metals discussed in this work include Pb [1-4],

Cd [3-7] and Zn [4]. Pb and Cd are both carcinogens [8-11]. Pb is highly poisonous, as it affects almost every organ and system, such as kidney, nervous system and immune system, and could permanently reduce the cognitive capacity of children [12, 13]. The inhalation of Cd can result in fever, chemical pneumonitis, pulmonary edema and death [14, 15]. Itai-itai disease is an example of mass poisoning caused by Cd contaminated water and crops. For Zn, on the one hand, excess Zn intake can lead to Cu deficiency and neurologic disease such as myelopathy or

Alzheimer’s [16, 17]. On the other hand, Zn is an essential trace metal that plays a key role in metabolism [18, 19]. Critically ill patients with abnormally low Zn levels [20-22] need supplementation [23-25] to restore homeostasis, thus careful monitoring of Zn levels in blood becomes critically important.

Conventional methods for metal determination are based on atomic absorption spectroscopy (AAS) [26] or inductively coupled plasma mass spectrometry (ICP-MS) [27].

While both of these methods provide accurate measurements in any matrices even complex as serum or blood, they require expensive instrumentation and highly-trained operators. Another challenge is that the amount of sample necessary to perform these analyses is often significant,

1 and can be difficult to obtain in pediatric or severely ill patients. Furthermore, significant time delays are associated with these approaches due to shipping of samples to centralized labs, making them less desirable or even unsuitable.

Electrochemical techniques offer sufficiently low limit of detection (LOD) for trace metal determination and simpler structure for miniaturization. The commercially available point-of- care (POC) devices and those demonstrated in research settings typically rely on the electrochemical approach of anodic stripping voltammetry (ASV) [28, 29]. However, there are challenges to determination of heavy metals. Metals with negative stripping potential, such as

Zn and Mn, demand sufficiently large potential window. Metals in biological samples, such as

Pb and Zn, are not readily detectable as they bind to cells and proteins, requiring complex sample pretreatments. LeadCare® II which is the only commercial POC system for blood Pb measurement has a reportable range of 33-650 ppb [30], but is less applicable nowadays when most children have blood Pb levels below 10 ppb [31]. Some metals, such as Cd, have physiological levels below 1 ppb, which is challenging to achieve for electrochemical sensors.

Recently, our group reported the first microscale sensor for determination of Pb, Cd and

Zn using a bismuth (Bi) working electrode (WE), silver/silver chloride (Ag/AgCl) reference electrode (RE) and gold (Au) auxiliary electrode (AE) [32, 33]. The sensor performed reliably in acetate buffer with LODs of 6 µM , 0.34 µM and 1.65 µM , for Zn, Pb and Cd, respectively. Zn is the only metal of the three of which LOD satisfied the requirement of its level. However, detection of Zn in serum exhibited large variability, making determination challenging [34].

Evaporated Bi WEs could determine Zn in serum with minimum variability, yet the fabrication procedure for these electrodes was complex and costly [35]. Moreover, use of Au is not

2 conducive to low-cost disposable sensors needed in POC applications. The goal of this dissertation is to develop a new POC sensor to address these issues.

State of the art in metal determination

AAS and ICP-MS are the gold standards for heavy metal determination. These techniques are heavily relied on to determine heavy metals in wide range of sample matrixes

[36]. They offer excellent LODs, which is crucial in trace metal analysis, and can measure multiple metals simultaneously [37]. Other techniques often require confirmation with spectrometric techniques, or integrate them for a better analysis method [38]. While mechanical

(surface acoustic wave) sensors have been studied for heavy metal determination, optical sensors are the most common alternative approach.

Optical sensors for determination of heavy metals have several themes based on the intrinsic optical properties of analytes, chromogenic and fluorogenic reagents, quenchable fluorophors, ionophore or biomolucles in biosensors [39]. Spectrophometric methods allow low

LOD (in nM range) for metals in biological samples [40]. Fluorescent chemodosimeters can be used to detect analytes through a highly selective and irreversible chemical reaction between the dosimeter molecule and the target analyte and provided signal changes in absorption wavelength and color [41]. Fluorescent small molecules that respond to metal ions in the cell offer the ability to probe physiological consequences of the cell biology of metals with spatial and temporal fidelity and visualize metal accumulation and function in living systems [42]. Whole cells that emit a bioluminescent or fluorescent signal in presence of heavy metal and metal- binding protein of which the capacitance changes based on direct interaction with metal ions were used for the determination of bioavailable heavy metals in environmental samples [43].

Fluorescent and colorimetric sensors for Ag, Au, Pt ions were reviewed due to their wide range

3 of applications and biological significance according to structural classifications or mechanisms

[44].

Electrochemistry for heavy metal determination

Electrochemistry is a commonly used sensing approach for heavy metal determination.

Here, the electrical signals are generated due to chemical reactions at the electrodes. These techniques can be based on potentiometric [45], voltammetric [46] or conductometric

(capacitance or impedance) [47] measurements, and in some cases, electrodes can be interdigitated [48] or integrated into an FET [49]. Stripping voltammertry [50] is one of the voltammetric techniques which provides low LOD for heavy metals at trace levels, and offers ability for simultaneous determination [51]. Anodic stripping voltammetry (ASV) (Fig. 1) involves a preconcentration step to accumulate the target metal ions onto the electrode surface by reducing them to atoms, followed by a positively-scanned stripping step to re-oxidize the metal back to its ionic form. ASV is rapid, cost-effective, and can yield provides LODs in the sub-nM range. There are many interesting developments of electrochemical sensors [52-57]; the following section offers a brief review.

Preconcentration Stripping I Pb2+ , Cd2+ , Zn2+ Pb2+ , Cd2+ , Zn2+ Pb0, Cd0, Zn0 Pb0, Cd0, Zn0

Cu Cu glass glass V +-

Fig. 1 Illustration of ASV of Pb, Cd and Zn on a solid Cu working electrode (WE).

4 Electrochemical sensors for heavy metal determination

Advancements in materials have direct impact on developments in analytical chemistry

[58], especially on working electrodes used in electrochemical sensors. Carbon [59] (reticulated vitreous carbon [60], carbon paste [61], CNT-epoxy composite [62], graphene [63]), wide bandgap semiconductor [64], sol-gel silica [65, 66], organic conjugated polymer (conducting polymers) [67] were used for electrodes or modifiers for high surface area ratio, enhanced sensitivity, excellent mechanical and electrical properties, biomolecule compatibility or easy fabrication. Nanomaterials, such as CNT [68] and metal nanoparticles [69] (Pt, Au [70, 71], Cu) offer a powerful method for enhancing electrochemical determinations [72, 73], although environmental impact of these advanced materials is a concern due to toxicity [74, 75].

Nontoxic solid amalgam [76, 77] or Bi [29, 78-80] on different electrode substrate (pencil lead

[81], carbon paste [82], carbon fiber [83]) have been reported to replace the widely used mercury electrodes in stripping analysis.

To move analysis out of large laboratories to the field [84], the whole system needs to be portable [85] and easy to use [86, 87]. The so-called micro total analytical system or lab-on-a- chip trend benefits significantly from MEMS techniques from the fabrication perspective. This thin-film technique is capable of providing precisely controlled small features. For example, using MEMS techniques, an integrated electrode system [88] with sensor arrays [89] can be fabricated on Si wafer, which could be used with an automated flow system for in situ measurements of trace metals [90].

Miniaturized sensors/sensor arrays can also be fabricated using carbon-based materials

[91] by thick film technique like screen printing. Screen printing provides a cheaper choice other than thin film fabrication thus disposable [92-94] electrodes from both material and cost

5 perspective. Inkjet printing [95] was an important tool in industrial mass fabrication for sensors and microfluidic paper-based analytical devices (PADs) [96] with increasing material choices.

Whitesides’ group reported a microfluidic PAD consisting of paper-based microfluidic channels patterned by photolithography or wax printing and screen-printed electrodes for quantifying Pb in aqueous solution [97].

System integration must also be considered, although this is only gaining attention now.

Wireless data transmission was realized with power source provided by microbial fuel cell with low-power, high-efficiency electronic circuitry [98]. Wearable electrochemical sensors on textile materials or directly on the epidermis were developed for non-invasive multi-analyte analysis in the healthcare, fitness domain [99].

Determination of Pb, Cd and Zn using stripping voltammetry

As discussed earlier, there is great interest in determinations of Pb, Cd and Zn using stripping voltammetry. A summary of the most recent publications with respect to electrode materials and themes, stripping techniques, experimental setups, and sample matrices is presented in a table in the appendix. A brief discussion follows.

The electrode materials used in stripping analysis are diverse. Though mercury toxicity is well known, a modified hanging mercury drop electrode (HMDE) is still very common due to superior performance [100-114]. The mercury-free alternatives include carbon and other metals.

Glassy carbon electrode [115-207] and carbon paste electrode [208-247] are the most studied carbon-based electrodes. Almost all carbon-based electrodes were chemically modified to enhance their electrochemical performance. The most common modifiers include metals such as

Bi, Sn and Sb, organics such as polyaniline (PANI), nano structures such as CNT, or complex mixtures of all. Other carbon-based electrodes include graphite [248-258], boron-doped-

6 diamond [259-264], carbon microfiber [265] and CNT [266-270]. Graphene has also been grown on Si wafer for use in electrochemical sensors [271-273]. Screen-printing is an attractive alternative to fabricate carbon-based electrodes, which are printed on polyester sheets using ink thus making sensors low cost and disposable [274-304]. Another interesting fabrication procedure includes using double-sided conductive carbon tape on ITO glass [305]. Screen printing could be used to form metallic electrodes too, e.g., Au, Sb, Sn and Bi [306-309]. An ex situ Bi film electrode on Cu substrate was prepared using toner transfer method and polyester paper with Cu plate [310].

Different metals have also been considered to replace Hg as electrodes. Alloy galinstan

[311] and metals Au [312-317],Pt [318], Ag [319], Ti [320, 321], Al [322] and Cu [323] can be prepared as disk electrode in a similar way as GCE. Au and Ag were fabricated as microwires

[324-327] that were vibrated during preconcentration to increase sensitivity. MEMS fabrication techniques also played a role to realize Bi, Ag, Pt, Sb, Sn, Au electrodes on Si [328-333], ITO

[334], glass [335], polymer [336] or PCB [337].

Electrode arrays were realized in different materials. Graphite-epoxy composite electrodes were modified by three peptides and the three sensors were used at multiple pHs for simultaneous determination of Pb, Cd and Zn [251]. A series of Boron-doped diamond microelectrode arrays on Si wafer were fabricated to quantify Cd in river water and spiked human urine sample [261]. Bi microdisk arrays on Si wafer conferred improved performance to analyze Pb and Cd [330]. The same group fabricated three-electrode cell with integrated metal film electrodes on Si wafer consisting of Bi microdisk, Ag and Pt [328]. A hybrid Au microelectrode array and light addressable potentiometric sensors were fabricated on Si wafer to quantify Pb and Zn [333].

7 In most experimental setups, for each experiment electrodes are immersed into solution containing metal ions and experiments are initiated manually; however automated setups using the lab-on-a-chip concept are gaining popularity. A two-step, sequential determination employing two WEs was defined to determine five metals in food matrices (electrode: Au,

HMDE) [313]. A thin layer electrochemical flow cell with capillary electrophoresis (CE) was involved in an automated system for preconcentration, cleanup, separation and determination for five trace metal ion analysis in a single run (electrode:GCE) [168]. A robotic device with a three-electrode assembly controlled by computer micropositioning was adapted for measurements in a 24-well microtiter plate and each microtitier plate run included a sequence of electrode pretreatment, water rinsing and measurements of Pb and Cd (electrode: Bi/pencil lead)

[254]. A thermostated electrochemical flow cell for the flow-batch analysis based on solenoid micropumps and three-way valves was developed to carry out a fully automated procedure with temperature control for on line determination of Pb and Cd with a low consumption of 700 µL of reagents (electrode: Bi film/SPE) [290]. Sequential injection lab-on-valve were applied to stripping voltammetry for determination of Pb (electrode: MWCNT/MOF/GCE) [169]. A sequential injection analysis system consisting of an 8-port selection valve, a syringe pump and a holding coil was used to deliver samples and reagents for determination of Pb and Cd (electrode:

Bi/crown ether/Nafion/SPE) [289]. Another sequential injection analysis system consisting of a syringe pump, an 8-port selection valve, and a 6-port switching valve with mini-column for solid phase extraction was employed for on line preconcentration and determination of Pb and Cd with consumption of 720 µL (electrode: Bi/CNT/SPE) [291]. In one automatic system using flow- injection technique, a minimum injection of 0.5 mL, was required for a 90s deposition. For bigger volumes, deposition has to be linearly increased [292].

8 The automation systems stated above offer favorable features related to batch systems, e.g., higher sample throughput, low reagent and sample consumption, lower risk of contamination, and simple automated operation. However, the three-electrode system involved is discrete, which prevents further miniaturization. There are a few examples of integrated three- electrode systems though they were used in a traditional way as immersed into solutions. Au microelectrode array on Si wafer served as both WE and AE with an external Ag/AgCl RE

[333]. Modified Au electrode on glass with Pt counter electrode was also used with an external

Ag/AgCl RE [335]. Three-electrode cells (Bi microdisks, Ag and Pt) were fabricated by a multi- step microfabrication approach combining sputtering and photolithography on Si wafer [328].

The same group reported a different cell with Sb film WE [331]. Following are the only publications reporting integrated three-electrode systems used in the way with potential of further microfluics integration for lab-on-a-chip. A paper-based analytical device consumed only 15 µL of solution which was dropped on filter paper put above the surface of electrodes, though not all three electrodes were formed in similar manner but an Ag/AgCl wire and Pt wire integrated with the carbon tape on ITO [305]. A reusable polymer lab-on-a-chip sensor was reported with Ag WE and AE and Ag/AgCl RE in microfluidic channels for continuous and on- site heavy metal monitoring of Pb with only 13.5 µL of sample volume [336]. A rotary disc voltammetric sensor using similar integrated Ag sensors on PCB with 24-sensing holes was fabricated for semi-continuous measurements of Pb [337].

Of three metals of interset, Zn is the least determined metal due to its negative stripping potential. Several electrode materials provide potential windows sufficiently wide to determine

Zn in addition to mercury [100, 102, 106-109, 111-113, 198, 313], including 1) glassy carbon or carbon paste electrode modified by Hg nanodroplets [202, 234], Sn [116], Ga [242], Bi [126,

9 156, 178, 191], Hg-Bi/SWCNT [120], Bi/mesoporous carbon [180], Bi/montomorillonite [210],

Bi oxide plates [250], Fe3O4 nanocrystal [175, 194], Zn IIP [176], Sb [128, 138], glutathione

[251], 2) boron-doped diamond [260], 3) carbon fiber [265], metal catalyst free CNT [267], CNT thread [269], 4) screen printed carbon electrode modified by Pb film [274], Bi/Nafion/MWCNT

[276, 279], Nafion/Bi [302, 303], 5) Au electrode modified by nafion/metal catalyst free CNT

[312], DPA/AuDP [314], Bi [317], 6) Ag modified by Hg [319], 7) Sn [332], 8) Au [333, 335].

The most common matrices are environmental samples (water from tap, river, spring, sea, pool, lake, drinking, reservoir, and soil), food samples (rice, beverage, milk, vegetable, sauce, and fish) and industrial sample (bioethanol fuel, wastewater, mineral water, eyewash). A few biological matrices were test mainly for Pb and Cd, including eagle blood [304], human hair [124, 221,

225, 228], teeth [224], finger nail [233], urine [261, 266], blood serum [253] and blood [164].

There were a few publications that reported Zn in biological sample. Zn level in mice liver was determined using mercury electrode [111]. A wearable tattoo-based SPE sensor was demonstrated for real-time monitoring of Zn in sweat [303]. We [312] and others [302] reported

Zn determination in serum.

From these publications, it is clear that lab-on-a-chip sensors for heavy metal determination are still under development, let-alone miniaturized integrated system with complex sample preparation. Determination of trace metals in biological samples is also a bottle-neck for most electrochemical sensors.

Scope of work

In this dissertation, a new Cu-based sensor was developed for heavy metal determination by ASV. We investigated Cu as a new material for disposable POC electrochemical sensors, with the goal of low-cost and simple fabrication while retaining the electrochemical

10 performance. Cu is a commonly used material in electronics, but not in conventional electrochemical systems, since it is easily oxidized. Nevertheless, it offers a number of advantages, including significantly lower cost and compatibility with microfabrication methods.

The Cu-based sensors consisted of a Cu WE and AE with a new Cu/CuCl2 RE. The sensors were fabricated by evaporation, photolithograpy, etching, electroplating and bonding. This dissertation demonstrated the Cu-based sensors were sufficiently stable for at least one electrochemical measurement, which is more than sufficient when disposable POC applications are considered. More importantly, the sensors exhibited good performance for determination of heavy metals.

The toxicity and wide occurrence of heavy metal requires reliable and accessible detection techniques. There is significant contamination of freshwater resources and an accelerating accumulation of toxic metals in the human food chain [338]. Ground water carries contaminants from agricultural [339], industrial, and domestic activities, while winds and currents transport pollutants from atmospheric [340] and oceanic sources to different ecosystems

[341]. People around the world pay great attention to assess heavy metals in varieties of cases, especially for food [342] like crops [343], vegetables [344-347], fish [36, 344], and also other segments on upper stream of contamination like air/water/soil [346, 348, 349]/sediments [350], or biomarkers [351] in exposed population. Toxicity of heavy metals has been reviewed [352] by international bodies like WHO. In this dissertation, the three heavy metals, Pb, Zn and Cd were measured individually in water from several sources, as a representative environmental sample, and serum, as a representative biological sample.

11 Chapter summaries

Following this introduction, Chapter 2 will provide details of the development of the Cu- based sensors, from motivation, fabrication and experimental setup, to examination of each electrode. Chapter 3 will describe sensor optimization and determination of each metal in buffer.

Chapter 4 will discuss the characteristics of the Cu-based sensor when more than one metal is present in solution. Chapter 5 will then describe use of the sensor in determination of target metals in biological (blood, serum) and environmental (surface water) samples. Chapter 6 will summarize and conclude this work.

12 CHAPTER 2

COPPER-BASED ELECTROCHEMICAL SENSOR

Our group previously demonstrated a miniature electrochemical cell with Bi WE for determination of metals such as Mn and Zn that exhibit very negative stripping potentials [33-

35]. The sensor size was approximately 15 mm × 19 mm, required only microliters of sample, and performed an analysis in less than 15 min. While both electrodeposited and thermally- evaporated Bi films were investigated, it is the evaporated Bi WEs that proved to exhibit more stable (coefficient of variation < 2%) measurements of Zn in acetate buffer [35]. Although the evaporated Bi WEs performed well for Zn (LOD = 60 nM), the fabrication procedure for these electrodes was complex and costly, requiring multiple photolithography, e-beam evaporation, and lift-off process steps. For a disposable sensor, cost is the most critical challenge after performance. Thus, we investigated new materials for disposable POC electrochemical sensors, with the goal of low-cost and simple fabrication while retaining the electrochemical performance.

To overcome the aforementioned shortcomings of the Bi-based sensors, we developed a sensor based on a Cu thin film. Using Cu as sensor material has the potential to address all of the challenges of a disposable POC sensor, from the fabrication prospective. Our sensor consisted of a Cu WE, a Cu/CuCl2 RE, and a Cu AE, as illustrated in Fig. 2a. The layout of the electrode patterns was generally similar to our earlier work, with a user-friendly interface that

13 integrated an edge board connector and a mini-USB port to provide simplified connection and accessibility (Fig. 2b). Fabrication of such a sensor involves a single photolithography step on a

PDMS

Cu AE

Cu/CuCl2 RE Cu WE

Glass

(a)

(b) Fig. 2 (a) Schematic of the electrochemical cell, working electrode (WE), auxiliary electrode (AE), and reference electrode (RE). (b) Photograph of the sensor with a mini-USB potentiostat connection.

thermally-evaporated Cu film. This is a significant improvement, eliminating the alignment necessary for the second photolithography step in evaporated Bi WE fabrication. Migrating to a

Cu/CuCl2 RE can also eliminate the additional step of electroplating Ag in the fabrication of a

Ag/AgCl RE. These advantages of Cu from the cost and fabrication points of view make the Cu- based sensor concept highly appealing if the electrochemical performance is acceptable. Thus, experiments were performed to examine suitability of Cu for all three electrodes for ASV measurements in a disposable sensor intended for single use applications.

14 Experimental methods

The sensor was fabricated using a combination of lithographic and deposition techniques.

The process is illustrated in Fig. 3. Metal layers of 20 nm titanium (Ti) /200 nm Cu were evaporated (Temescal FC-1800 E-Beam Evaporator) onto glass slides cleaned in Piranha solution (Fig. 3a). An etching mask of 2 µm approximately was formed using photolithography with Shipley 1818 photoresist and developer 351. The three electrode patterns with contact pads were formed by wet etching in Cu etchant for 10 s followed by Ti etchant for 3 s, with 1 min of rinsing in DI water after each etching step (Fig. 3b). An integrated Ag/AgCl RE was fabricated by electroplating 300 nm approximately Ag (Techni-Silver Cyless II RTU, Technic Inc.) on Cu for 60 s with cathodic current of 3 mA/cm2 and then chloridizing the Ag in 1M KCl with anodic current of the same current density for 30 s to convert part of the Ag film to AgCl. The new RE,

2 Cu/CuCl2, was fabricated by chloridizing Cu in 1 M KCl with 3 mA/cm anodic current for 30 s.

During the electrodeposition, the integrated Cu AE was used to sustain the current (Fig. 3d). Cu Lithography PDMS Cu/CuCl2

(a) (b) (c) (d)

Fig. 3 Fabrication process diagram for Cu-based sensor with Cu/CuCl2 RE. (a) Metal evaporated onto glass slides. (b) Electrode patterned by photolithography and wet etching. (c) Polymer well bonded by plasma discharge. (d) RE formatted by electrodeposition.

A polymer well with 9 mm diameter and 3 mm thickness approximately was fabricated in polydimethylsiloxane (PDMS) using the standard soft lithography process [353]. It was bonded to a clean glass substrate containing the electrode patterns using plasma discharge (BD-20AC,

Electo-Technic Products Inc.) after 20 s of treatment on the PDMS surface only. An interface

15 consisting of an edge-board connector (Sullins, EBC05DRAS) and a mini-USB port were soldered on a PCB to simplify and improve connection between the sensor and the potentiostat.

A miniature USB WaveNow Potentiostat/Galvanostat (AFTP1, Pine Instrument) with

AfterMath Data Organizer software was used in all electrochemical experiments. A sensor was inserted into the interface and connected to the potentiostat using a mini-USB cable (Fig. 2b).

Chronopotentiometry under 10 µA current was performed to evaluate the quality of the Cu AE, while a Bruker ContourGT-K1 Optical Microscope was used to scan its surface roughness. Both cyclic voltammetry (CV) and ASV were performed to compare potential windows and chronopotentiometry to compare stability of sensors with two types of REs. The sweep rate for

CV was 100 mV/s. ASV was also used to calibrate the Cu WE for metals, and to measure metal levels in unknown samples. For all the experiments performed, we used 100 µL as the sample volume; the only exception is that it was increased to 200 µL for the measurements in serum.

After a series of optimizations of preconcentration conditions and stripping waveform parameters, we selected preconcentration potential and duration, waveform period, increment and amplitude, to achieve higher sharpness and resolution of the stripping peaks. For the calculation of LOD, we repeated our lowest measurable data point of metal – for 7× and obtained the standard deviation. We also obtained the slope of the correlation equation and calculated the

LOD as 3σ/slope.

Cu auxiliary electrode

It was critical to first demonstrate that a Cu AE can provide stable current during both preconcentration and stripping steps, since a Cu AE is easily oxidized when functioning as an anode in ASV. In conventional electrochemical cells, AEs are fabricated from inert materials, such as Pt or graphite. Thus, we assessed the stability of our Cu AE by comparing it with a Pt

16 electrode using chronopotentiometry under 10 µA current, which is the typical upper limit of current we see in stripping experiments. During this experiment, we used a graphite electrode as the cathode, with Cu or Pt as the anode.

As expected, the Pt electrode maintained a stable potential at about 1.3 V for the oxidation of water during the entire 60 min experiment (Fig. 4), indicating that it is an excellent, perfectly polarizable AE. The Cu electrode, on the other hand, is a non-polarizable electrode undergoing oxidation during the entire process. To evaluate stability of multiple devices, we repeated the experiment four times with a fresh sensor each time and obtained the average curve.

The Cu AE exhibited a stable behavior for the first 10 min by providing relatively constant potential at about only 0.1 V for the oxidation of Cu. The oxidation and stripping of Cu happened at a low rate, which had little effect on the surface of the electrode during this time

(Fig. 4a-0 min). The roughness of a fresh Cu surface was 0.3 ± 0.03 nm. The observed signal variability was quite low (coefficient of variation = 5%), although the Pt electrode was clearly superior (coefficient of variation = 0.2%). In the next 10 min, however, the potential began drifting positively, which coincides with an observable degree of degradation of the AE: reduced

Cu thickness, and increased surface roughness to 6.1 ± 2.3 nm (Fig. 4a-20 min). After 20 min the potential shifted abruptly to a significantly more positive value where the AE continued to function, but with erratic behavior of the potential. At this stage the electrode process is probably a combination of Cu and water oxidation because the Cu surface area is below the level needed to sustain the 10 µA current by Cu oxidation alone. By 60 min, the Cu layer of the electrode is largely removed (Fig. 4a-60 min). This introduced a substantial increase in resistance for a given current (Fig. 4b).

17 These results demonstrate that a Cu anode is able to sustain current, and thus could be used as an AE if the experiment time is kept short. For most stripping analyses, 10 min is sufficient and the current during preconcentration is generally below 10 µA. Thus, a 200 nm thick Cu AE is acceptable for our disposable sensors. For preconcentration duration longer than

10 min with larger current, the Cu AE film may be oxidized completely. In this case the sensor

RE WE AE 0 min 20 min 60 min (a) 1.5

1.2 Pt

0.9 Cu 200 nm 0.3 0.6

Cu 230 nm Potential (V) Potential 0.3 0 12 22

0 Cu >1 µm 0 10 20 30 40 50 60 Time (min) (b) Fig. 4 Stability of Cu as an AE. (a) Images of un-oxidized Cu AE, and Cu AEs that have undergone 20 min and 60 min of oxidation. (b) Chronopotentiometry of Pt and Cu AEs under current of 10 µA. The curve for 200 nm Cu AE is an average of four measurements (n = 4), with the inset illustrating the point of failure of the actual four curves. will no longer function as a three-electrode system. If more robust electrodes are needed, e.g. for applications with more acidic electrolyte or longer preconcentration duration for lower LOD, the electrode could be formed from a thicker layer of Cu or a larger AE. With more sacrificial Cu for oxidation, the stable region can be extended depending on film thickness (Fig. 4b).

Alternatively, it could be coated by a more-polarizable metal such as palladium (Pd) while this would introduce a more complex fabrication procedure. Having established that the Cu AE is

18 capable of supporting current for the duration sufficient for rapid analysis, we next examined the electrochemical performance of the Cu/CuCl2 RE.

Cu/CuCl2 reference electrode

We used CV and ASV to evaluate the Cu/CuCl2 RE of our Cu-based sensor and compare it with the commonly-used Ag/AgCl RE. CVs were performed in acetate buffer (0.2 M, pH 6) spiked with 10 mM Zn to indicate the position of the stripping peak. We used two sensors for these experiments – one with an integrated Ag/AgCl RE and one with the new Cu/CuCl2 RE. As results in Fig. 5a illustrate, the Zn stripping peak on a Cu WE occurs at -970 mV vs. Ag/AgCl,

250 Acetate buffer vs. 200 Cu/CuCl2 10 mM Zn vs. 150 Cu/CuCl2 Acetate buffer vs. 100 Ag/AgCl 50 10 mM Zn vs. Ag/AgCl

Current (µA) Current 0 -50 -100 -1.7 -1.5 -1.3 -1.1 -0.9 -0.7 -0.5 -0.3 -0.1 Potential (V) (a) 8 Acetate buffer vs. Cu/CuCl2 30uM Zn vs. 6 Cu/CuCl2 Acetate buffer vs. Ag/AgCl 4 30uM Zn vs. Ag/AgCl

Current (µA) Current 2

0 -1.4 -1.2 -1 -0.8 -0.6 -0.4 -0.2 Potential (V) (b) Fig. 5 (a) Cyclic voltammetry (CV) performed with Cu/CuCl2 (solid) or Ag/AgCl (dashed) as RE, in acetate buffer (0.2 M, pH 6) with 10 mM Zn. Scan rate = 100 mV/s. (b) ASV performed with Cu/CuCl2 (solid) or Ag/AgCl (dashed) as RE, in acetate buffer (0.2 M, pH 6) and 30 µM Zn.

19 but shifts more positively to -910 mV for sensors using Cu/CuCl2 RE. The 60 mV difference in peak potential due to differences in RE half-cell potentials is not significant. Overall, the performance of Cu/CuCl2 RE in CV analysis appears to be comparable to sensors with Ag/AgCl

RE.

To further demonstrate the function of the sensor with Cu/CuCl2 RE and compare it with

Ag/AgCl, ASV was performed in acetate buffer (0.2 M, pH 6) and 30µM Zn. ASV was carried out at preconcentration potential -1.3 V for duration 300 s. The square wave parameters were set default as following: amplitude 25 mV, period 70 ms, and increment 4 mV. As results in Fig. 5b illustrate, the Zn stripping peaks in ASV are -0.8 V for both sensors. The peak on ASV using sensors with Ag/AgCl RE is distorted and have lower signal with larger full width at half maximum compared to that with Cu/CuCl2 RE. In the next set of experiments, we examined stability of the Cu/CuCl2 RE.

To access stability of the Cu/CuCl2 RE, we examined the open circuit potential against a commercially-available double-junction Ag/AgCl RE (MI-401F, Microelectrodes Inc.) in saturated KCl solution (4.6 M at 20 °C) to accelerate electrode aging [354]. As results in Fig. 6 show, the electrode potential drifted rapidly for the first few minutes, but “stabilized” at -338 mV after 10 min with a slower drift rate of 0.37 mV/min. The drift of the Cu/CuCl2 RE is quite large compared to other microscale Ag/AgCl RE electrodes reported in literature [355, 356], which exhibit an extremely low drift rate of 0.034 mV/h, or <1 mV for longer than 100 h. Yet, the difference in such an aging experiment is expected since RE in that work was protected by multiple layers of membrane, while our RE is naked and directly exposed to the solution, which is simpler to fabricate and is an advantage from the device fabrication and reproducibility points of view. Other REs made of Ag/AgCl without protective layers also exhibited small potential

20 drift of 2 mV approximately for at least 1000 min [357], but the fabrication procedures, materials and electrode structure differ from ours in very significant aspects. Thus, additional comparison of the Cu/CuCl2 and Ag/AgCl REs in our sensor is needed before a conclusion can be reached.

-250

-280

-310

-340

Potential (mV) Potential -370

-400 0 10 20 30 40 50 60 Time (min)

Fig. 6 Potential of Cu/CuCl2 electrode in saturated KCl (buffered, pH 7.0) vs. commercial Ag/AgCl (double junction).

Next, and more importantly, we tested performance of the integrated Cu/CuCl2 and

Ag/AgCl REs in practical samples by examining their open circuit potentials against the commercial Ag/AgCl RE in acetate buffer (0.2 M, pH 6) (Fig. 7). To simulate the working environment of our integrated REs in the buffer, no additional Cl- was introduced (except for the minute amount of impurity in NaOH used to adjust pH and any Cl- resulting from the dissolution of CuCl2 and AgCl from the surfaces of the reference electrodes), so both the REs were unpoised and examined directly. The potential difference between the integrated Cu/CuCl2 and the commercial Ag/AgCl REs was -59 ± 3 mV, while the difference between the integrated and commercial Ag/AgCl RE was -36 ± 6 mV. The Cu/CuCl2 RE exhibited a short 28 s response time in stabilizing the potential difference, which was faster than the 46 s observed for the

Ag/AgCl RE. This difference in the response time may be due to differences in solubility of

CuCl2 and AgCl, which suggests that measurements in the Cu-based electrochemical cell can be

21 performed soon after introducing sample and does not require a 46 s wait period for stabilization as is the case with the Ag/AgCl RE. The more convenient fabrication process combined with its acceptable stability in buffer makes the integrated Cu/CuCl2 RE and attractive option to this sensor compared to the conventional Ag/AgCl RE.

40 Cu/CuCl2 20 Ag/AgCl 0

-20

-40 Potential (mV) Potential -60

-80 0 10 20 30 40 50 60 Time (min)

Fig. 7 Potential of integrated Cu/CuCl2 and Ag/AgCl electrodes in acetate buffer (0.2 M, pH 6) vs. commercial Ag/AgCl (double junction).

To assess stability of the Cu/CuCl2 RE in stripping analysis, we performed ASV on samples containing 10 µM Zn in acetate buffer (0.2 M, pH 6) with preconcentration durations ranging from 1 to 10 min. The potential of the resulting Zn peaks (Fig. 8a) shifted from -792 mV to -821 mV with increasing preconcentration duration. The average potential of the Zn peaks was -809 ± 8.5 mV, while the peaks slowly drifted at a rate of -2.9 mV/min (Fig. 8b).

While these results suggest that the Cu/CuCl2 RE is not perfectly stable, this shift does not actually affect our application since we are measuring the amplitude of Zn peak current, and the

Zn peak potentials do not exhibit direct correlations to the peak amplitudes. Having established that Cu-based AE and RE are possible, we focused on determining if Cu can be used as a WE for

ASV.

22 Cu working electrode

Cu has never to our knowledge been used as a pure, solid metal WE to perform stripping voltammetry, though some previous research has explored using Cu amalgam drop or solid electrode for the determination of trace metals [358-360], and thus its potential window is not known. As the first step in evaluating the Cu WE, we compared it with a commonly-used Au

15 10 min

9 29 mV 6

Current (µA) Current 1 min 3

0 -1.1 -1 -0.9 -0.8 -0.7 -0.6 -0.5 -0.4 Potential (V) (a) -0.7

-0.75

-0.8

-0.85(V) Potential

-0.9 0 1 2 3 4 5 6 7 8 9 10 11 Time (min)

(b) Fig. 8 (a) Anodic stripping voltammetry (ASV) of 10 μM Zn in acetate buffer (0.2 M, pH 6) with increasing duration of preconcentration. (b) Potential of Zn anodic stripping peak shifting over preconcentration duration. WE and electroplated Bi WE we used in the past [33-35], using a standard three-electrode system (external Ag/AgCl RE and external Pt AE). Fig. 9a shows the results for CV in acetate buffer (0.2 M, pH 4.65), illustrating the negative potential working range of the three electrodes.

The positive end of the working range of the Cu electrode extends to its oxidation potential of -

23 0.01 V, which is more positive than the stripping potential of Bi (-0.085 V). The significant increase in current at negative potentials indicates reduction of water, which leads to degradation of the electrode and gas evolution at the AE. The negative end of the working range of the Cu

WE extends to -0.95 V approximately, which is between that of Au and Bi WEs. The actual potential for the Zn peak still depends on the choice of REs.

200

100

-100 Bi

-200 Au

Current (µA) Current -300 Cu

-400 -1.4 -1.2 -1 -0.8 -0.6 -0.4 -0.2 0 0.2 Potential (V) (a) -1.2

-1.1

-1

-0.9 Potential (V) Potential -0.8

-0.7 Au Cu Bi WE (b) Fig. 9 (a) CV of different WE materials in acetate buffer (0.2 M, pH 4.65) with commercial Ag/AgCl (double junction) RE, and Pt AE. Scan rate = 100 mV. (b) Threshold potentials (i = 10 µA) of different WE materials. The negative potential limits of the three electrodes are compared at 10 µA threshold current (Fig. 9b), which is typical of ASV analysis. With the Zn stripping peak at -0.8 V, the potential limit of the Cu film is sufficiently negative to make it a suitable electrode material. The potential limit of Bi is -1.2 V. While the Zn stripping peak on the evaporated Bi WE shifts to -

1.1 V approximately, Bi is also suitable. Au, with the least negative potential limit of -0.8V,

24 does not have the range for Zn determination, as substantial increase in current due to reduction of water will drown the Zn stripping signal. As our analysis of the potential window shows, the

Cu WE offers a sufficiently negative range for determination of Zn (and other trace metals with less negative stripping potentials, such as Pb and Cd) without exhibiting too much H+ reduction.

To further explore the electrochemical characteristics of the Cu-based sensor, we investigated the effect of buffer pH on the potential window of the Cu electrode. CV analysis was performed in 0.2 M acetate buffers with pHs in the 4.65-6.5 range. As results in Fig. 10a

50 Zn Cd Pb 0

-50 pH 4.65 pH 5 -100 Potential Window pH 5.5 pH 6

Current (µA) Current -150 pH 6.5

-200 -1.4 -1.2 -1 -0.8 -0.6 -0.4 -0.2 0 0.2 Potential (V)

(a) -0.8

-0.9

-1

-1.1

-1.2 Potential (V) Potential -1.3

-1.4 4 4.5 5 5.5 6 6.5 7 pH

(b) Fig. 10 (a) CV of Cu-based sensor in acetate buffer (0.2 M) with different pHs. Scan rate = 100 mV/s. (b) The threshold potential (i = 4 µA) at different pHs. show, the potential window of the sensor expands negatively as pH approaches neutral values, due to decrease in water reduction current with decreased concentration of H+ in the solution as expected. Dependence of the potential window of the Cu WE can be seen in Fig. 10b, which

25 plots the negative potential limits for each pH at a threshold current of 4 µA, which is the maximum current at pH 6.5. For acetate buffer with pH < 4.65, water electrolysis begins at a more positive potential than the Zn stripping peak. For buffer with pH > 6.5, Zn2+ forms hydroxides [361], which affects the actual free ion concentration in the solution, and mass transport to the electrode surface to deposit Zn atoms, leading to large variability. Thus for

ASV, buffer with a more acidic pH is preferably selected to prevent precipitation of metal hydroxides, especially for Pb or Cd which tend to form less soluble hydroxides than Zn. For buffer with pH 6, despite the water reduction starting at -1.1 V, the potential window of Cu is still sufficiently wide for determination of Zn, offering a 130-190 mV window for Zn pre- deposition. Compared with the Bi WE, the potential window of the Cu-based sensor is smaller, but is sufficiently negative to permit determination of trace metals such as Zn, Cd or Pb.

Summary

In this chapter, details of the development of the Cu-based sensors were discussed. The

Cu-based sensor was fabricated on glass substrate with Cu layer, and patterned in a single photolithography step to form all three electrodes used for ASV: a Cu WE, a Cu AE, and a RE formed by chloridization (Cu/CuCl2 RE) after bonding with PDMS well. A miniature USB

WaveNow Potentiostat with AfterMath software was used in all electrochemical experiments. A sensor was inserted into the interface and connected to the potentiostat using a mini-USB cable.

The Cu-based sensors were demonstrated to be sufficiently stable for at least one electrochemical measurement by examining each electrode (AE, RE, WE). The demonstrated Cu-based sensors will be optimized and calibrated for each metal in buffer as discussed in the next chapter.

26 CHAPTER 3

DETERMINATION OF METALS IN BUFFER

This chapter focuses on determination of three heavy metals (Zn, Pb and Cd) by the Cu- based sensors in buffer individually. Subsequent chapters will deal with multi-metal determination and determination in real-world samples. The three metals were selected due to their compelling significance, as discussed briefly in the introduction and in more detail below.

Determination of Zn

Zn is an essential trace metal that plays a key role in metabolism as a component of many enzymes, hormones, and nucleic acid transcription-related factors [18, 19]. Pediatric and adult studies have consistently demonstrated abnormally low Zn levels in critically ill patients [20-22].

While Zn homeostasis can be easily restored through Zn supplementation [23-25], excess Zn intake can lead to Cu deficiency and neurologic disease such as myelopathy or Alzheimer’s [16,

17]. For such patients, careful monitoring of Zn levels in blood becomes critically important for the supplementation strategy to work. Traditionally, such measurements are performed in blood serum, with total Zn concentrations in the 65-95 µg/dL (10-15 µM) range [362].

CV in acetate buffer

CVs were performed in acetate buffer (0.2 M, pH 6) spiked with 10 mM Zn to indicate

27 the position of the stripping peak. As results in Fig. 11 illustrate, the Zn stripping peak on a Cu

WE occurs at -910 mV vs. Cu/CuCl2 RE. Comparing to the negative potential limit of the Cu

WE, -1.1V (at 10 µA threshold current), the stripping peak indicates working window sufficiently wide for Zn preconcentration. After obtaining the potential window and positions of

250 Zn stripping 200 150 10 mM Zn 100 50 Acetate buffer

Current (µA) Current 0 -50 Zn deposition -100 -1.7 -1.5 -1.3 -1.1 -0.9 -0.7 -0.5 -0.3 -0.1 Potential (V)

Fig. 11 CV in acetate buffer (0.2 M, pH 6) with 10 mM Zn. Scan rate = 100 mV/s. the deposition and stripping Zn peaks, we determined and optimized ASV parameters for determination of Zn using the Cu-based sensors.

Optimization of ASV parameters

Experimental parameters (buffer pH, preconcentration potential and duration,) and stripping waveform parameters were optimized for maximum stripping peak current and peak sharpness in acetate buffer (0.2 M) containing 10 µM of Zn. For each parameter, experiments were performed in triplicate. For pH optimization, ASV was performed in acetate buffer with pH in the 4.65-6.5 range (Fig. 12a). For pH < 6, reduction of water started at -0.9 V, which was close to the Zn peak at -0.8 V. Acetate buffer with pH 6.5 provided the widest potential window in CV, while in ASV multiple peaks were observed as Zn hydroxides began to form at a nearly- neutral pH. Voltammograms at pH 6 showed the most stable peaks, with coefficient of variation

28 of 12%, compared with 21%-75% for other pH values. Thus, pH 6 was identified as best.

Preconcentration potential is a critical parameter for ASV, thus different potentials from -

0.9 to -1.3 V were tested to select the most suitable value (Fig. 12b). When the potential was too negative, the formation of hydrogen from water reduction reduced efficiency of deposition and affected repeatability of experiments. ASV with preconcentration potential of -1 V provided both the largest peak current and the smallest variation, and was thus selected as the optimal deposition potential.

Preconcentration duration is another critical parameter for ASV as it directly influences the sensor LOD and the overall duration of analysis. Preconcentration durations in the 1-10 min range were investigated (Fig. 12c). For relatively short depositions, the Zn peak amplitude steadily increased with longer preconcentration duration, saturating at 5 min. Additionally, the coefficient of variation for the 5 min preconcentration was 6%, but increased to 24% for the 10 min preconcentration, due to the partial degradation of the AE of Cu-based sensor. Thus, 5 min preconcentration duration was selected for the following ASV experiments.

The waveform parameters of ASV using Osteryoung square wave voltammetry for the stripping step were also optimized as shown in Fig. 12d-f. By decreasing the period and increasing amplitude and increment of the square wave, the peak current kept increasing.

However, the purpose of optimization was not only to increase peak current which represents high sensitivity, but also to accomplish sharp peaks for the accurate measurement of different metals in mixtures, and to reduce the device-to-device variation to obtain low LOD. Therefore, another characteristic - full width at half maximum (FWHM) - was also considered as a secondary factor to distinguish peak sharpness straightforwardly and select the proper parameters. The larger FWHM indicates the peak begins to lose its resolution even though its

6 16 0.14

5 12 0.13

FWHM FWHM

4 A) μ

3 8 0.12

(V)

2 Current ( Current Current (µA) Current 4 0.11 1

0 0 0.1 4.5 5 5.5 6 6.5 7 0 20 40 60 80 pH Period (ms) (a) (d) 4 10 0.14

8 3 0.13

FWHM FWHM (V)

A) μ μ 6 2 0.12

4 Current ( Current Current ( Current 1 0.11 2

0 0 0.1 0.8 0.9 1 1.1 1.2 1.3 1.4 0 30 60 90 120 Potential (V) Amptitude (mV) (b) (e) 16 12 0.14

12 9

FWHM FWHM (V) A)

A) 0.13

μ μ 8 6

0.12 Current ( Current Current ( Current 4 3

0 0 0.11 0 2 4 6 8 10 12 0 3 6 9 12 15 Time (min) Increment (mV) (c) (f) Fig. 12 Optimization of experimental parameters: (a) pH of acetate buffer, (b) preconcentration potential, (c) preconcentration duration, (d) square wave period, (e) square wave amplitude, (f) square wave increment. ASV performed in 10 µM Zn acetate buffer (0.2 M).

30 peak current is increasing, which increases the LOD, and makes it challenging to quantify certain metals if their peaks overlap. Therefore, instead of using extreme parameters for the square wave just to increase the peak amplitude, we carefully optimized the values to achieve higher sharpness and resolution of the peaks. We selected 50 ms, 60 mV and 6 mV for period, amplitude and increment values, respectively, and the resulting signal current was amplified from 3 µA when using default parameters of 70 ms, 25 mV and 4 mV, respectively, to 8 µA.

ASV in acetate buffer

Following optimization of experimental and stripping waveform parameters optimization, a calibration curve was constructed by performing ASV in acetate buffer (0.2 M, pH 6) with 100 nM - 40 µM of Zn spiked, as shown in Fig. 13. This range brackets the physiological range of

Zn in blood (10-15 µM), while illustrating that the LOD of the sensor allows for multi-fold dilution, if necessary. We used the optimized square wave ASV (SWASV) parameters, as discussed above. For most concentrations, we repeated experiments three times (n = 3) using a new disposable device each time to obtain standard deviation. Representative stripping voltammograms over the entire 100 nM - 40 µM concentration range are shown in Fig. 13a, while close ups of the lower 100 nM - 5 µM range are shown in Fig. 13b.

The resulting calibration curves appeared to be bimodal (Fig. 14a), with each segment exhibiting strong linearity. The correlation equation is I(µA)=1.11 ×[Zn(µM)]+0.608 (R2 =

0.994 for n = 5) for the concentrations below 5 µM, and I(µA)=0.394 ×[Zn(µM)]+4.55 (R2 =

0.968 for n = 6) for the concentrations above 5 µM. The calibration plot in lower range (<5 µM) exhibited higher sensitivity (1.11 µA/µM). For 100 nM, which was the lowest Zn concentration sample, an n = 7 was used to calculate the LOD = 140 nM (9 ppb) based on 3σ/slope. Compared with the Bi sensor we reported previously [34, 35], the calculated LOD of the Cu-based sensor

31 for Zn determination is close but we were able to experimentally measure much lower Zn concentration (100 nM vs. 1 µM). Kefala [363] and Demetriades [81] also reported much lower

LODs for Zn using Bi-coated glassy carbon electrodes or pencil-lead graphite (6 nM or 0.4 ppb), but the inability to microfabricate these electrodes has prevented their use in POC applications.

The lower linear range (<5 µM) is below the physiological range of 10-15 µM. This is important since dilution is unavoidable during serum extraction, and the performance of sensors with extracted samples is not as good as that in buffer, as we discuss below. For the Cu-based sensor, the linear range brackets the physiological range of 10-15 µM Zn in serum with a dilution factor of 3-100×.

25 40 µM 20

Current (µA) Current 5 µM 5

0 -1.05 -0.95 -0.85 -0.75 -0.65 -0.55 -0.45 Potential (V) (a) 10 5 µM 8

Current (µA) Current 100 nM 2

0 -1.05 -0.95 -0.85 -0.75 -0.65 -0.55 -0.45 Potential (V) (b) Fig. 13 ASV of Zn samples in (a) 100 nM - 40 µM range and (b) 100 nM - 5 µM range. Experiments performed in acetate buffer (0.2 M, pH 6). Preconcentration potential -1 V, duration 300 s, amplitude 50 mV, period 60 ms, increment 6 mV.

32 We also investigated higher concentrations of Zn from 5-40 µM for complete characterization. Double peaks appeared when concentration exceeded 20 µM, which is a common phenomenon on solid electrodes [364]. We attribute this to the difference in stripping potential for Zn that has been deposited on a thin layer of Zn instead of on Cu WE at high concentrations, since the surface of the Cu WE becomes covered with a monolayer of Zn atoms before the deposition is complete. Thus, Zn will be stripped from different surfaces at different potentials, resulting in broadened or doubled stripping peaks. Specifically for voltammograms in the 20-40 µM range, we considered the left shoulder to be related to Zn stripped from Zn surface, and the peak on the positive side to be attributed to Zn oxidized from Cu surface. Therefore, we

25 y = 0.394x + 4.55

20 R² = 0.968 A)

μ 15

10 Current ( Current 5 y = 1.112x + 0.608 R² = 0.994 0 0 5 10 15 20 25 30 35 40 45 Concentration (μM)

(a) 5

y = 0.097x + 0.162 4 R² = 0.990

W) 3 μ

2 Area ( Area

1 y = 0.140x + 0.0743 R² = 0.992 0 0 5 10 15 20 25 30 35 40 45 Concentration (μM) (b) Fig. 14 Calibration curves for Zn using (a) peak height and (b) peak area of stripping voltammograms.

33 measured the peak height of positive peaks for the 20-40 µM range to plot the calibration curve

(red in Fig. 14a). As clearly seen from the result, the broad double peaks lead to almost 3× loss of sensitivity (0.394 µA/µM). Considering the area under each peak (Fig. 14b) instead of the peak height leads to improved linearity, but the calibration curve remains bimodal. Nevertheless, peak height is a much simpler measurement and is a good representation of the lower range for our sensor, which is of more importance in our application.

Determination of Pb

Pb is highly poisonous that affects almost every human organ, such as kidney, nervous system and immune system. It can cause kidney cancer, gliomas, and lung cancer in rodents, and acts synergistically with other carcinogens [9]. Blood Pb levels of 10-15 μg/dL (100-150 ppb or

0.48-0.72 μM) [8] in newborn and very young infants result in cognitive and behavioral deficits

[12, 13]. The sources of Pb exposure include mining, smelting, Pb-containing gasoline and Pb paint [1]. It can enter the body through hand-to-mouth contact or through contaminated food or water. The high toxicity and common occurrence require carefully monitoring of Pb. The guideline value for the safe level of Pb in drinking water is 10 ppb (48 nM) [365].

CV in acetate buffer

To confirm the position of the Pb stripping peak on a Cu WE, CV was performed in acetate buffer (0.2 M, pH 5.5) spiked with 100 µM and 1 mM Pb (Fig. 15). With the Pb stripping peak appearing at -0.3 V vs. Cu/CuCl2, the negative potential limit of the Cu WE, -

1.1V (at 10 µA threshold current), indicates a wide working window for Pb preconcentration.

The second stripping peak at -0.5 V is a separate Pb peak due to high concentration, at which the

Pb has been deposit on a thin layer of Pb instead of the Cu WE. The similar phenomenon is also

34 80 Acetate buffer 60 100 µM Pb 1 mM Pb 40 Pb stripping 20 0 -20

Current (µA) Current -40 Pb deposition -60 -1.4 -1.2 -1 -0.8 -0.6 -0.4 -0.2 0 0.2 Potential (V)

Fig. 15 CV in acetate buffer (0.2 M, pH 5.5) with 100 µM and 1 mM Pb. Scan rate = 100 mV/s. observed in ASV analysis. After obtaining the potential window and positions of the deposition and stripping Pb peaks, we determined and optimized ASV parameter for determination of Pb using the Cu-based sensors.

Optimization of ASV parameters

Before we constructed a calibration curve and determined the LOD of Cu-based sensors for Pb determination, experimental parameters (buffer pH, preconcentration potential, and preconcentration duration) were optimized for good repeatability, maximum stripping peak current and peak sharpness. For this, 100 µL samples containing 10 µM of Pb in acetate buffer

(0.2 M) were used. For each parameter, experiments were performed in triplicate.

For pH optimization, ASV was performed in acetate buffer with pH in the 4.65-6.5 range, the same as in CV when we investigated potential windows for Cu WE. As results in Fig. 16a show, for buffer with acidic pH, signal variability was significant, exhibiting coefficients of variation of 22% and 34% for pH 5 and 4.65, respectively. Acetate buffer with neutral pH provided more stable response, yet the peak currents were relatively small, exhibiting peak currents of 7.5 and 8.2 µA for pH 6 and 6.5, respectively. Voltammograms at pH 5.5 showed the

14 25 12 20

A) μ μ 8 15

6 10 Current ( Current Current ( Current 4 5 2 0 0 4.5 5 5.5 6 6.5 7 20 30 40 50 60 70 80 pH Period (ms) (a) (d) 16 10 0.14

8 12 0.13

FWHM FWHM (V)

A) μ

A) 6 μ 8 0.12 4

Current ( Current 0.11 Current ( Current 4 2

0 0 0.1 -1.2 -1 -0.8 -0.6 -0.4 -0.2 0 30 60 90 120 Potential (V) Amptitude (mV) (b) (e) 150 12 0.14

120 9

FWHM FWHM (V) A)

A) 0.13 μ 90 μ 6 60

0.12 Current ( Current Current ( Current 3 30

0 0 0.11 0 2 4 6 8 10 12 14 16 0 3 6 9 12 15 Time (min) Increment (mV) (c) (f) Fig. 16 Optimization of experimental parameters: (a) pH of acetate buffer, preconcentration (b) potential and (c) duration, square wave (d) period, (e) amplitude and (f) increment. ASV performed in 10 µM Pb acetate buffer (0.2 M).

36 second largest peak current of 8.9 µA with acceptable coefficient of variation of 15%. Thus, pH

5.5 was selected for the following experiments.

Preconcentration potentials from -0.5 to -1.1 V were tested to select the most suitable value (Fig. 16b). When more negative potentials were used, from -0.5 V to -0.7 V, the peak currents increased from approximately 80% to 90% of the average peak current (10.4 µA) with potential from -0.8 V to -1.1 V. With potential more negative than -0.8 V, the peak current saturated at 10.4 ± 0.7 V. When the potential was as negative as -1.1 V, the formation of hydrogen from water reduction reduced efficiency of deposition and affected repeatability of experiments, which brought a large variation of peak currents with coefficient was 42%. ASV with preconcentration potential of -0.8 V provided the second largest peak current (10.7 µA) and the smallest variation (5.8%), and was thus selected as the optimal deposition potential.

Preconcentration durations in the 1-15 min range were investigated (Fig. 16c). In this range, we did not see a distinct saturation curve or a large variation with longer preconcentration duration, while the Cu-based sensor was obviously degraded with 15 min preconcentration duration and resulted in a large variation of peak currents with coefficient of 15%. One possible reason is sample volume which will be discussed in the calibration section below. Instead of a real optimized value, we kept 5 min as a compromising default preconcentration duration for the following ASV experiments. For real-world applications, there are trade-offs between shorter preconcentration duration (faster process) and lower LOD, or fabrication cost and complexity.

The threshold preconcentration duration for the current Cu-based sensor is about 10 min for most

ASV (current below 10 μA) which is limited by deterioration of the Cu AE. If more robust electrodes are needed for applications with longer preconcentration duration for lower LOD or in more acidic electrolyte, we can deposit a thicker layer of Cu for the AE, design a larger AE or

37 deposit another layer of noble metal on top of the AE. We reserve the flexibility of adjusting preconcentration duration accordingly when we determine Pb in real-world samples using the

Cu-based sensor.

The waveform parameters of ASV using Osteryoung square wave voltammetry for the stripping step were also optimized as shown in Fig. 16d-f. The optimization process is the same as that for Zn discussed before. For Pb, we selected 50 ms, 50 mV and 8 mV for period, amplitude and increment values, respectively, and the resulting signal current was amplified from 8 µA when using default parameters of 70 ms, 25 mV and 4 mV, respectively, to 35 µA.

Effect of oxygenation

Following the ASV optimization, we performed analyses using 0.5-10 µM Pb in acetate buffer (0.2 M, pH 5.5) to constructed a calibration curve and calculate the LOD. However, with

Pb concentrations below 0.5 µM, we observed a constant 1.6 µA peak at -0.36 V (Fig. 17). We examined experimental factors related to the sensor and stripping waveform (including AE and

RE, buffer ionic strength, preconcentration parameters, square wave waveform parameters), and were able to rule them all out as they showed little influence on the peak. Thus, we concluded that the peak was mainly from WE or electrolyte composition.

One parameter that did have an effect on the peak was buffer pH. In borate buffer with basic pH, we observed a huge 25 µA peak at -0.2 V, while in acetate buffer with more acidic pH or nitric acid, the peak shrunk or disappeared. Additional cleaning steps of the WE surface by hydrochloride acid prior to experiments did not help. However, we found that deoxygenating buffer before experiments and sealing the PDMS well during experiments, caused the peak to disappear. Based on these observations, we believe the peak is most likely an oxide stripping peak, which can be dissolved by acid or formed in basic environment if sensors are exposed to

38 oxygen. To eliminate the effect of this peak but not affect the sensor’s performance, we chose to deoxygenate the buffer to get a measurable Pb peak with lower concentration. Fig. 17 demonstrates the necessity and effect of this procedure. The peak of buffer (grey) is similar to

5 1 µM Pb

4 A)

μ 3 buffer 0.5 µM Pb

2 Current ( Current 1 deoxygenated buffer 0 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 Potential (V) Fig. 17 ASV of acetate buffer (0.2 M, pH 5.5) before (grey) and after (black) deoxygenating, compared with 0.5 and 1 µM Pb. that of 0.5 µM Pb, and after deoxygenating, the background (black) is plainer. Thus, for the following experiments with Pb below 0.5 µM, we deoxygenated the sample solution by bubbling nitrogen for 5min.

ASV in acetate buffer

A calibration curve was constructed by performing ASV in 0.025-10 µM Pb in acetate buffer (0.2 M, pH 5.5), as shown in Fig. 18a, with close up of the lower 25 nM - 1 µM range shown in Fig. 18b. For most concentrations, we repeated experiments three times (n = 3) using a new disposable device each time to obtain standard deviation. It is possible to choose a smaller volume while obtaining the same signal (minimum 35 µL with preconcentration duration for 5 min), due to the mass-transport limitation of our system [35], however, since it is not critical to use minimum sample volume in water analysis, we chose 100 µL for convenience. The range of

Pb we tested, 0.025-10 µM, or 5 ppb to 2 ppm, brackets from the safety level of Pb in drinking

39 water 10 ppb, the concern blood Pb level (50, 250, and 300 ppb, for children, adults, and Pb exposed workers, respectively), to the majority of blood Pb levels in poisoning victims.

As our results in Fig. 18a-b show, when the Pb concentration is below 10 µM, ASV shows a single stripping peak. While when the Pb concentration is as high as 10 µM, a small

40 10 µM

A) μ 20

Current ( Current 10 1 µM

0 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 Potential (V)

(a) 5

4 1 µM A)

μ 3

2 25 nM Current ( Current 1

0 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 Potential (V)

(b) 100

A) 10 μ

y = 3.432x - 0.066 0.1 2

Current (log (log Current R = 0.999

0.01 0.01 0.1 1 10 Concentration (log µM) (c) Fig. 18 ASV of Pb in (a) 25 nM - 10 µM range and (b) 25 nM - 1 µM range. Analyses performed in acetate buffer (0.2 M, pH 5.5). Preconcentration potential -0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV. (c) Calibration curve for Pb in buffer.

40 shoulder starts to appear at -0.5 V. The possible reason is that Pb starts to be deposit on top of

Pb instead of Cu, which requires lower potential to strip off. With Pb concentration below 0.5

µM , the Pb stripping peak shifts from -0.31V to -0.34V. The 30mV shifting results from the buffer de-oxygenation, as the voltammograms shift as a whole indicated by the earlier Cu stripping. This shift did not affect the measurements of peak or the calibration curve.

The calibration curve, shown in Fig. 18c, indicates the sensitivity of the Cu-based sensor for Pb in acetate buffer is 3.43 µA/µM, with good linearity (R2 = 0.999). The correlation equation is I(µA)=3.43 ×[Pb(µM)]-0.066 (R2 = 0.999 for n = 9). Seven measurements of 25 nM

Pb were performed for calculating the LOD, which was 21 nM or 4.4 ppb (3σ/slope method, n =

7). For most carbon-based sensors, LOD for Pb is usually in the range of 0.03-2 ppb even with shorter preconcentration duration (Table 1) due to larger sample volume and better agitation.

Several microsensors using materials like carbon [276] and bismuth [110] have been reported for

Pb determination and the LOD can be as low as 0.5 ppb with silver electrode [336].

Nevertheless, the LOD for Pb using Cu-based sensor is low enough to determine whether the Pb in environmental samples exceeds the safe level in drinking water.

Determination of Cd

Cd is a carcinogen inorganic toxicant of great environmental and occupational concern

[10, 11]. Inhalation of Cd can result in fever, chemical pneumonitis, pulmonary edema and death [14, 15]. The most dangerous exposures to Cd are inhalation of fine dust and fumes which come from fossil fuel combustion, phosphate fertilizers, production of iron, steel, cement and nonferrous metals and smoking. Itai-itai disease is an example of mass poisoning caused by Cd contaminated water and crops [34]. More importantly, the levels of Cd in organs such as liver and kidney increase with age because of the lack of an active biochemical process for its

41 elimination coupled with renal reabsorption [35]. Cd concentrations in healthy persons without excessive exposure are generally <1 μg/L (9 nM) in either blood or urine.

CV in acetate buffer

CV was performed in acetate buffer (0.2 M, pH 6) spiked with 200 µM and 500 µM Cd to confirm position of the Cd stripping peak on a Cu WE (Fig. 19). At lower concentration of

Cd, 200 µM, a broad stripping peak appeared at -0.4 V, spanning from -0.6 to -0.2 V. At higher concentration, 500 µM, a sharp peak appears at -0.6 V. This double peak phenomenon is similar to Pb on Cu surface. The corresponding deposition potentials for these two peaks are -0.5 V and

-0.7 V approximately. Nevertheless, with the negative potential limit of the Cu WE, -1.1V, the

Cu-based sensor exhibits a wide working window for Cd preconcentration.

15 Acetate buffer 10 200 µM Cd 500 µM Cd 5 Cd stripping 0

-5

Current (µA) Current Cd deposition -10

-15 -1.4 -1.2 -1 -0.8 -0.6 -0.4 -0.2 0 0.2 Potential (V)

Fig. 19 CV in acetate buffer (0.2 M, pH 6) with 200 µM or 500 µM Cd. Scan rate = 100 mV/s.

ASV in acetate buffer

ASV was performed in 20-200 µM Cd in acetate buffer (0.2 M, pH 6), as shown in Fig.

20a. Sharp Cd stripping peaks appeared at -0.65 V approximately in this concentration range and decreased with lower concentration. However, the variability of the sensors was not good.

Fig. 20b showed big error bars, coefficients of variation ranging from 19% to 77%, indicating

42 unacceptable reliability of sensors even in this high concentration range. The linearity of the curve is also less than desirable (R2 = 0.811).

140 120 200 µM 100 80 60

Current (µA) Current 40 20 20 µM 0 -1 -0.8 -0.6 -0.4 -0.2 Potential (V)

(a) 140 120 y = 0.345x - 10.3 100 R² = 0.811 80 60 40

Current (µA) Current 20 0 -20 0 40 80 120 160 200 Concentration (µM)

(b) Fig. 20 (a) ASV of Cd in 20-200 µM range. Analyses performed in acetate buffer (0.2 M, pH 6). Preconcentration potential -0.9 V, duration 180 s. (b) Response currents at different concentrations of Cd in buffer. Performance of the Cu-based sensor for determination of Cd at lower concentrations did not improve. Fig. 21 shows the ASV of 5 and 10 µM of Cd in acetate buffer. With a preconcentration duration of 300 s, the voltammgram of 5 µM was the same as acetate buffer alone, and the 10 µM concentration exhibited a peak at -0.65 V smaller than 1 µA. Considering that the range of Cd in real world samples is particularly low, in the single or even sub ppb level, it is unlikely to obtain a comparable LOD when solutions with concentration 1000x higher could not generate a clear peak. Thus, another supporting electrolyte, nitric acid, was investigated.

43 4 Aacetate buffer 5 µM Cd 3 10 µM Cd

Current (µA) Current 1

0 -1 -0.8 -0.6 -0.4 -0.2 0 Potential (V)

Fig. 21 ASV of 5 and 10 µM Cd. Analyses performed in acetate buffer (0.2 M, pH 6). Preconcentration potential -0.9 V, duration 300 s.

CV in nitric acid

CV was performed in 1 mM nitric acid with 200 µM and 1 mM Cd (Fig. 22). Nitric acid

(1 mM) was chosen as supporting electrolyte since ASV of Cd was performed by others [138,

336], including Cu on GCE[164]. Also, the peak at -0.4 V disappeared in background of ASV.

0.2 0 -0.2 -0.4 1mM HNO3 -0.6 200 µM Cd -0.8 1 mM Cd

Current (mA) Current -1 -1.2 -1.4 -1.2 -1 -0.8 -0.6 -0.4 -0.2 0 0.2 Potential (V)

Fig. 22 CV in 1 mM nitric acid with 200 µM or 1 mM Cd. Scan rate = 100 mV/s.

As nitric acid attacks Cu especially when biased, we reduced the ionic strength to 1 mM.

In the CV of 1 mM nitric acid (Fig. 22), the current range was within 20 µA, since the ionic strength of the solution was relatively low and no chemical reaction occurred at the surface of the

WE. For solutions spiked with Cd, the current increased dramatically to 1 mA, which caused

44 difficulty in observing Cd deposition and stripping. One reason for the huge current besides the deposition of Cd is that the Cd stock solution is Cd in 0.5 N nitric acid, thus 1 mM Cd will provide extra nitric acid 5 mM approximately. Note that with Cd concentration below 10 µM in

ASV, the extra nitric acid is less than 0.05 mM, which can be neglected. Though no clear Cd peak appeared in the CV, the moderate current in CV of 1 mM nitric acid indicates the Cu-based sensor has a potential window in the range as negative as -1 V, and ASV can be performed in this electrolyte.

ASV in nitric acid

ASV was performed in 0.5-10 µM Cd in 1 mM nitric acid as shown in Fig. 23a. The Cd

12 1 mM nitric acid 10 0.5 µM 1 µM 3 µM A) 8

μ 5 µM 6 10 µM

4 Current ( Current 2

0 -1 -0.8 -0.6 -0.4 -0.2 0 Potential (V) (a) 4

A) μ 2 y = 0.265x + 0.7175 R² = 0.935

Current ( Current 1

0 0 2 4 6 8 10 12 Concentration (µM) (b) Fig. 23 (a) ASV of Cd in 0.5-10 µM range. Analyses performed in 1 mM nitric acid. Preconcentration potential -0.9 V, duration 180 s. (b) Calibration of Cd in nitric acid.

45 peaks were broad and their positions were not consistent, ranging from -0.45 to -0.5 V. Another issue is that the baselines of ASV with different concentrations did not overlap with the background curve, which suggests Cu WEs were undergoing an unpredictable reaction during stripping, likely being etched by nitric acid. The calibration curve, shown in Fig. 23b, indicates the sensitivity of Cu-based sensor for Cd in nitric acid is 0.265 µA/µM, with linearity R2 =

0.935. The correlation equation is I(µA)= 0.265 ×[Cd(µM)]+0.718 (R2 = 0.999 for n = 5).

Three measurements of 0.5 µM Cd were performed for calculating the LOD, which was 1 µM or

112 ppb (3σ/slope method, n=3). Note that the calculated LOD is higher than the actual detectable lowest concentration, most likely due to the variability of sensors (coefficient of variation = 20%). Though the detectable concentration in nitric acid is 100x below that in acetate buffer, it is still too high compared to the target level of Cd in real world samples.

Summary

In this chapter, the Cu-based sensors were optimized for determination of Zn, Pb and Cd in buffer. CV of each metal was performed to show the stripping peak in buffer. Experimental parameters, including buffer pH, preconcentration potential and duration, square wave parameters, were optimized for each metal in buffer. The LOD for each metal was calculated after constructing calibration curves using ASV. The Cu-based sensors exhibited LODs with

140 nM/9.0 ppb, 21 nM/4.4ppb and 1 µM/112 ppb for Zn and Pb in acetate buffer, and Cd in nitric acid, respectively. As the Cu-based sensor with bare Cu WE did not show LOD sufficiently low for Cd determination in either supporting electrolytes commonly used in electrochemistry, Cd determination will be revisited in Chapter 5 where other metals are also present in solution act as a metal modifier for the Cu WE.

46 CHAPTER 4

DETERMINATION OF MULTIPLE METALS

This chapter will discuss performance of the Cu-based sensor when more than one metal is present in the solution. One advantage of the ASV technique is the possibility of simultaneous determination of multiple metals. For the three metals investigated in this work, three stripping peaks are clearly visible. The Cu-based sensors are able to show all three peaks in a proper concentration range (Fig. 24 blue solid). However, it is possible for the metal ions to interfere with each other so that the peaks are depressed, leading to inaccurate determination and poor

LOD. In this chapter, we will explore how presence of one metal influences another metal’s stripping peak when using the Cu-based sensors. More specifically, we examined interaction of

10 Pb 8

Zn 6

Current (µA) Current Cd 2

0 -1.4 -1.2 -1 -0.8 -0.6 -0.4 -0.2 Potential (V)

Fig. 24 ASV of 30 µm Zn (purple dot), spiked with 5 µm Pb (red dash), and 5 µm Cd (blue solid). Preconcentration potential -1.3 V, duration 300 s, amplitude 25 mV, period 70 ms, increment 4 mV

47 Zn and Pb, since both are present in blood. We also examined interaction of Cd and Pb, since both are environmental contaminants and can be present in the same water sample.

Zn determination in presence of Pb

Zn and Pb are both present in blood and other biofluids, such as sweat. Preconcentration of Pb is unavoidable for Zn determination since the potential for Zn preconcentration is so negative that the majority of metals would be deposited onto the surface of WEs. Therefore, it is important to investigate if Pb will interfere with Zn determination.

ASV was performed in solutions containing 0, 0.25, 0.5, 1 µM Pb and 0, 0.5, 1, 3 µM Zn using parameters for Zn determination in acetate buffer. Sharp and distinct Zn and Pb peaks appeared at their stripping potentials (Fig. 25a). With low Zn concentration (< 3 µM/196 ppb),

Pb peaks (Fig. 25b) with 0 to 3 µM Zn are overlapped with each other, indicating that Zn has no obvious effect on Pb peaks. Comparing to the individual Pb ASV, Pb peaks with 0 – 3 µM Zn exhibit even smaller coefficients of variation, which are 6%, 6%, 3% to 9%, 11%, 13% for 0.25,

0.5, 1 µM Pb, respectively.

Zn peaks, however, showed a relationship in the presence of Pb (Fig. 25c). For 0.5, 1 µM

Zn with 0.25 – 1 µM Pb, Zn peaks are only 85% and 74% of Zn peaks without Pb, while having no clear correlation with Pb concentration. The coefficients of variation for these two concentrations are also smaller than individual Zn ASV, which are both 3% comparing to 12% and 20 % for 0.5, 1 µM Zn, respectively. For 3µM Zn, Zn peaks exhibit decreasing trend with increasing Pb concentration. However, Zn peaks with 0.25 – 1 µM Pb are 94% of individual Zn peaks, and the coefficient of variation is comparable to that of individual Zn, which are 9% and

8%, respectively. Thus, when Zn and Pb concentrations are in this range, the Pb effects on Zn peaks can be neglected. With Pb concentration > 1 µM, Zn peaks are below the lowest range of

Zn 6

Pb 4

Current (µA) Current 2

0 -1 -0.8 -0.6 -0.4 -0.2 0 Potential (V)

(a) 3

2.5

1.5 No Zn 1

Current (µA) Current 0.5 µM Zn 0.5 1 µM Zn 3 µM Zn 0 0 0.2 0.4 0.6 0.8 1 1.2 Concentration of Pb (µM) (b) 5

2 No Pb

Current (µA) Current 0.25 µM Pb 1 0.5 µM Pb 1 µM Pb 0 0 0.5 1 1.5 2 2.5 3 3.5 Concentration of Zn (µM) (c) Fig. 25 (a) ASV of Zn and Pb. Analyses performed in acetate buffer (0.2 M, pH 6). Preconcentration potential -1 V, duration 300 s, amplitude 50 mV, period 60 ms, increment 6 mV. (b) Pb peak currents with different concentrations of Pb and Zn. (c) Zn peak currents with different concentrations of Zn and Pb.

49 Zn peaks without Pb. Though it is rare to have such high concentration of Pb in real world samples, a two-step preconcentration strategy was investigated to explore if it will help reduce the effect of Pb on Zn determination.

ASV was performed in the same solutions as before. The two-step preconcentration strategy is to apply a voltage of -0.8 V for 120 s then using the same parameters as before. In theory, Pb and Zn will be deposited onto the surface of WE sequentially, thus reducing the interference commonly observed in voltammograms using solid WEs. For 0.5, 1 µM Zn, this

3 No Pb 2 Current (µA) Current 0.25µM Pb 1 0.5µM Pb 1µM Pb 0 0 0.5 1 1.5 2 2.5 3 3.5 Concentration of Zn (µM) (a) 4.5 4 3.5 3 2.5 2 No Zn 1.5

Current (µA) Current 0.5µM Zn 1 1µM Zn 0.5 3µM Zn 0 0 0.2 0.4 0.6 0.8 1 1.2 Concentration of Pb (µM) (b) Fig. 26 (a) Zn peak currents with different concentrations of Zn and Pb. (b) Pb peak currents with different concentrations of Pb and Zn. First step: preconcentration potential -0.8 V, duration 120 s, second step: preconcentration potential -1 V, duration 300 s, amplitude 50 mV, period 60 ms, increment 6 mV. two-step deposition helps to bring Zn peaks closer to the normal range of Zn peaks without Pb

(Fig. 26a), which are 94% and 90% of average peak with smaller coefficients of variation of 8%

50 and 11%. For 3 µM Zn, Zn peaks still have the decreasing trend with increasing present Pb. The average of Zn peaks with 0.25 – 1 µM Pb increases to 106% of individual Zn peaks, with a larger coefficient of variation of 17%. And with 1 µM Pb, Zn peaks are still below the lowest range of

Zn peaks without Pb. Thus, the two-step strategy did not solve the issue. One possible reason is that the first step of preconcentration cannot deplete the Pb in the solution due to mass transport limit of the system, t, so in the second step, the two metals are still co-deposited on the Cu WE instead of expected sequential deposit and stripping.

Pb peaks, on the other hand, exhibit larger variations than previously (Fig. 26b), most likely due to the longer preconcentration duration. Moreover, 0.25 µM Pb peaks are distorted when there is no or 0.5 µM Zn, the cause of which is unclear. In conclusion, the two-step preconcentration helps for Zn peaks closer to the normal range while causes large variation especially for Pb peaks. Considering the little improvement and undesirable issue, the two-step preconcentration strategy was not explored for other compositions.

Pb determination in presence of Zn

Zn is a ubiquitous metal. Even though the optimized preconcentration potential for Zn is

0.2 V more negative than Pb, it is highly possible that a fraction of Zn would deposit with Pb at its preconcentration potential. The following experiments investigate how presence of Zn affects the ASV of Pb.

ASV was performed in solutions containing 0.5, 1 µM Pb and 0-10 µM Zn using parameters for Pb determination. Only Pb peaks appeared since the stripping step started at -0.8

V which is the same potential of Zn peaks. Contrary to the negligible effects of Zn on Pb peaks during Zn determination, Pb peaks are more sensitive to the presence of Zn using opitimized parameters for Pb determination. For 1 µM Pb, peaks (Fig. 27) decreased rapidly to 57% with

51 4 1 µM Pb

0.5 µM Pb 3

2 Current (µA) Current

1 0 2 4 6 8 10 12 Concentration (µM)

Fig. 27 Zn peak currents with different concentrations of Zn and Pb. Preconcentration potential - 0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV.

Zn concentration of 0.5 and 1 µM, and become more consistent around 50% when Zn is higher than 3 µM. Comparing to the individual Pb ASV, coefficients of variation are comparable for most concentrations, from 2-9%, to the 13% for 1 µM Pb, while being as large as 23% with Zn concentration of 3 µM. For 0.5 µM Pb, the effects are smaller, where peaks only decreased to

85% and stabilized, with comparable coefficients of variation from 4-8%. Thus, the presence of

Zn does affect Pb ASV in the form of broad and shrinking Pb, thus affectsing the sensitivity and

LOD for Pb determination. Note that this effect can be reduced by adjusting parameters, for example, preconcentration potential, but the adjustment itself will also sacrifice the LOD of the sensors. However, if coefficients of variation are the only concern (for example, execution of standard addition approach when LOD is well below the targeted range of the application), the

Zn effects on Pb can still be neglected expect for some rare composition (1 µM Pb with 3 µM Zn in the compositions we tested).

Pb determination in presence of Cd

The Cd stripping peak occurs at approximately 200 – 300 mV more negative than Pb, and has been reported to interfere with Pb [366]. The preconcentration potential of -0.8 V for Pb

52 determination is not negative enough for quantifying Cd using the Cu-based sensor. To purposely obtain the peaks for both metals using parameters for Pb determination, the Cd level has to be higher than 2 µM (225 ppb), which rarely exists in practical samples. However, similarly to the Pb determination with Zn, Cd with low concentrations of 0.1-1 µM does have impact on Pb determination, as shown in Fig. 28a.

Pb 1 µM 4

with Cd 0 A)

μ 3

2 1 µM Current ( Current 1

0 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 Potential (V)

(a) 4 1 µM Pb

3 0.5 µM Pb

Curretn (µA) Curretn 1

0 0 0.5 1 1.5 Concentration (µM)

(b) Fig. 28 (a) ASV of Pb and Cd. Analyses performed in acetate buffer (0.2 M, pH 5.5). Preconcentration potential -0.9 V, duration 300 s, amplitude 25 mV, period 70 ms, increment 4 mV. (b) Pb peak currents with different concentrations of Pb and Cd. Preconcentration potential -0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV. ASV was performed in solutions containing 0.5, 1 µM Pb and 0-1 µM Cd using parameters for Pb determination. Only Pb peaks appeared since the LOD of Cu-based sensors for Cd was not low enough for Cd below 1 µM . For 1 µM Pb, peaks (Fig. 28b) did shrink by

40% with 1 µM Cd compared to the individual Pb ASV, yet with decreasing Cd levels to 0.1

53 µM, the ratio reduced to 25%. More importantly, with lower Pb concentrations, for example 0.5

µM (104 ppb), which is still a relatively high level in real world samples, the Pb peaks without or with 0.1-1 µM Cd are overlapped with each other, which means Cd levels showed no correlation with Pb peaks. Regarding to the coefficients of variation, the Pb peaks with 0.1-1 µM Cd exhibit comparable values ranging from 5-17% and 3-15%, for 1 and 0.5 µM Pb, respectively.

Therefore, for real world samples, Cd interference will not be an issue for Pb determination using Cu-based sensors.

Cd determination in presence of Pb

In Chapter 3, we discussed that the Cu-based sensor with bare Cu WE does not have the

LOD sufficiently low for Cd determination in tested supporting electrolytes. The Cd peaks in acetate buffer were too small. While the Cd peaks in nitric acid were larger, they were broad with varied stripping potentials and their baselines did not overlap with the background curve.

However, as results in the previous section suggest, the Cu-based sensors modified by Pb might offer better performance for Cd determination in acetate buffer.

ASV was performed in 0.3-5 µM Cd with 1 µM Pb as shown in Fig. 29a. Concentrations of Pb from 0.25-1 µM and first step preconcentration potentials from -0.3- -0.9 V were investigated and 1 µM Pb and -0.8 V were chosen for the following calibration curve. The Cd peaks were distinct with overlapping baselines while their stripping potentials were shifting from

-0.48 to -0.52 V with increasing concentrations. The calibration curve, shown in Fig. 29b, indicates the sensitivity of the Pb-modified Cu-based sensor for Cd is 0.516 µA/µM, with linearity R2 = 0.977. The sensitivity is about 2× that of the Cu-based sensor for Cd in nitric acid.

Three measurements of 0.3 µM Cd were performed for calculating the LOD. The value is 41.6 nM or 4.7 ppb (3σ/slope method, n = 3), which is 10× smaller than that in nitric acid. Table 1 is

54 6

Cd 4 5 µM Pb 1 µM

2 0.3 µM Current (µA) Current

0 -0.9 -0.8 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 Potential (V) (a) 3.5 3 2.5 2 y = 0.516x + 0.267 1.5 R² = 0.977

Current (µA) Current 1 0.5 0 0 1 2 3 4 5 6 Concentration (µM) (b) Fig. 29 (a) ASV of Cd ranging at 0.5-5 µM. Analyses performed in acetate buffer (0.2 M, pH 5.5). First step: preconcentration potential -0.8 V, duration 120 s, second step: preconcentration potential -0.9 V, duration 300 s, amplitude 25 mV, period 70 ms, increment 4 mV. (b) Calibration of Cd in acetate buffer with present of 1 µM Pb.

Table 1: Summary of LOD and lowest detectable concentration of Cd using different Cu-based sensors.

LOD Lowest conc. Working electrode Supporting electrolyte (ppb) tested (ppb) Cu Acetate buffer (0.2 M, pH 5.5) 1073 2240 Cu Nitric acid (1 mM) 112 56 In situ plated Bi (200 ppb) on Cu Acetate buffer (0.2 M, pH 5.5) 18 50 In situ plated Pb (207 ppb) on Cu Acetate buffer (0.2 M, pH 5.5) 4.7 34

55 a summary showing improved determinations of Cd in buffer (including nitric acid as supporting electrolyte) using different modified Cu-based sensors. Though the LOD is still one level higher than the typical Cd level in real world samples, it shows the possibility for Cd determination using Cu-based sensors with simple modification.

Summary

This chapter discussed how the presence of one metal influenced another metal’s stripping peak using Cu-based sensors. Generally, though the target metals showed smaller currents when other metals of higher concentration were co-deposit, the influence could be neglected when the concentrations are in the typical range of real world samples. Moreover, the

Cd determination using Cu-based sensors was improved when Pb was also present in the solution. The LOD of Cu-based sensor for Cd is 118 nM/13 ppb when 1 µM Pb is co-deposited with Cd in acetate buffer. After this critical characterization step, the next chapter will discuss the use of the sensor to determine metals in blood or serum and water samples.

56 CHAPTER 5

DETERMINATION OF METALS IN REAL WORLD SAMPLES

This chapter discusses electrochemical performance of the Cu-based sensor in real world samples. Sample matrices include blood serum, as an important biological sample, and different water samples, as environmental examples.

Blood is used in numerous diagnostic tests and blood typing. Though blood or serum has an important disadvantage of being an invasive matrix, new analytical techniques that allow the use of other matrices that are less or non-invasive, such as saliva, urine, meconium, nails, hair, and semen or breast milk, are still under development [367]. And the correlation of analytes between blood and other biological matrices is unclear. So blood or serum is still the ideal matrix for most chemicals due to its contact with the whole organism and its equilibrium with organs and tissues where chemicals are stored. The concentration ranges of interests are 65-95

µg/dL (10-15 µM) for Zn and < 50 ppb for Pb.

The use of fresh water for activities like irrigation and industrial applications can have adverse impacts on downstream ecosystems. Drinking water is safe to be used with low risk of immediate or long term harm. Drinking water contaminated with heavy metals leads to widespread illnesses and is a major cause of death and misery in many countries. Reduction of waterborne diseases is a major public health goal in developing countries. Monitoring water quality is an important perspective for that goal, driving people to develop reliable and simple

57 methods for wide applications. The concentration ranges of interest are < 10 ppb for Pb and < 1 ppb for Cd. Different sample pretreatments will be discussed in different applications followed by using Cu-based sensors to determine Zn, Pb and Cd in different samples.

Zn in serum

Monitoring of Zn levels in serum is in great demand in clinical settings. Zn is an essential trace metal and component of many biological species. Either deficiency or excess of

Zn will result in illness as discussed before. Total Zn concentrations in serum is in the 65-95

µg/dL (10-15 µM) range [362]. The determination of Zn in serum is a critical challenge for ASV sensors since the technique only measures free metal ions, while as much as 60% of Zn in serum may be bound by protein [368].

Direct measurement of Zn in serum or diluted serum without any sample preparation is impossible when the LOD of the sensor is on the same order of magnitude as metal concentration. This was the case with our first generation Bi WE sensor [33]. With a substantially improved LOD, 130 nM, nearly 100× below the typical range of Zn in serum, our second generation Bi WE sensor [34] may be possible to directly measure free Zn in serum.

Motivated by the hypothesis that free Zn may exhibit better correlation with medical conditions, and simplicity of sample preparation by dilution with buffer over digestion or extraction, we attempted to determine free Zn ions in diluted serum directly. However, no Zn peak could be measured in diluted serum without spiking additional Zn. Further, we performed tests in serum spiked with 20-60 µM of Zn and diluted in the range of 5-100×. As the dilution factor increased, the stripping peak current increased as well, although it remained at much lower current levels than the corresponding concentrations in buffer. Sensitivity of the sensor vs. dilution factor revealed a saturation behavior while these saturation values were well below the sensitivity

58 exhibited in the buffer. These experiments suggested that pretreatment of serum is necessary for this application.

There are a number of options for pretreatment of serum for electrochemical trace metal determination. Digestion of serum is the easiest approach, and will break up proteins and release

Zn sequestered within their structure. However, we found that the commercial product

Metexchange® [369] originally developed for ASV determination of Pb, did not work for Zn most likely due to higher binding affinity between Zn and protein [370]. While the commonly- used method of acidification by HCl to digest serum worked, the results were not impressive as only spiked samples could be measured and it was impossible to calculate concentration of Zn in the original sample [33]. Thus, a more complex approach that is able to extract metal ions from proteins and remove proteins by phase separation is needed. We used the extraction procedure reported by our lab which achieves 97% recovery of Zn [312] in serum by stripping voltammetry.

The extraction procedure with dithizone and trifluoroacetic acid used to extract Zn from bovine serum is as follows. Dithizone in weight of 12.8 mg was first dissolved in 10 mL chloroform and deprotonated by mixing with 10 mL (pH 9) 1 M ammonia/0.5 M ammonium buffer solution to form the extracting solution. Then the extracting solution was mixed with the solution containing 1 mL bovine serum and 0.5 mL of 0.05 M potassium thiocyanate ethanolic solution. The mixture was sonicated for 5 min and then transferred into a 50 mL plastic tube and centrifuged for 10 min at 4,000 rpm. The organic phase was collected and sonicated with 10 mL

2 M trifluoroacetic acid for another 5 min. The clear aqueous phase was collected and mixed with acetate buffer (0.2 M). The pH was adjusted to 6 with NaOH for the following ASV experiments.

59 ASV of Zn in serum

To demonstrate Zn determination in extracted serum, we used the standard addition approach. ASV was performed in the extracted serum diluted 2× with acetate buffer (0.2 M, pH

6), and samples spiked with additional 1 µM and 5 µM of Zn (Fig. 30a). We used the same stripping parameters as in buffer, except for double volume of 200 µL and preconcentration duration of 600 s. Single and sharp peaks were observed in ASV voltammograms of three identical experiments for each sample, validating the stability and capability of Cu-based sensors for detecting Zn in extracted serum. The background currents for water reduction of the three concentrations overlapped and the potentials of Zn stripping peaks were -831 mV, -844 mV, and

-765 mV for the original and +1 µM, +5 µM samples, respectively. Based on our previous results using Bi WE and Ag/AgCl RE, the several orders of magnitude differences in the chloride concentration between acetate buffer with no chloride added and serum extract would lead to a positive shift of the Zn peak of several hundred mV [35]. However, the Zn peaks are at approximately the same position as in buffer while deviating more from each other. The most likely reason for this is the stability of the Cu/CuCl2 RE. The absence of large positive shift is due to the longer preconcentration duration that will result in a negative shift of the Zn peaks as discussed earlier during evaluation of the Cu/CuCl2 RE. Meanwhile, the peak deviation shown

5 in Fig. 30a is related to the fact that CuCl2 is much more soluble than AgCl, with an 10 difference approximately in their solubility.

We calculated the Zn concentration in the original serum extract using the standard addition curve (Fig. 30b). The correlation equation I(µA)=0.411×[Zn(µM)]+0.485 (R2 =0.993 for n = 3) indicates that sensitivity of the Cu-based sensor for Zn in extracted serum is nearly 3× below in buffer. Considering the larger deviation of potentials and smaller peak amplitudes of

60 Zn stripping peaks, the performance of the Cu WE in extracted serum is not as good as that in buffer, which is attributed to significantly higher complexity of serum as the sample matrix.

Nevertheless, we successfully determined the concentration of Zn in blood serum to be 14.8 ±

1.8 µM using the Cu-based sensor.

+ 5 µM 4

+ 1 µM

Current (µA) Current 2 serum

1 -1.05 -0.95 -0.85 -0.75 -0.65 -0.55 -0.45 Potential (V)

(a) 4

y = 0.411x + 0.485 3 R² = 0.993

Current (µA) Current 1

0 0 2 4 6 Concentration (µM)

(b) Fig. 30 (a) ASV of Zn extract from bovine serum with additional 1 and 5 µM Zn, sample volume 200 µL. Preconcentration potential -1 V, duration 300 s, amplitude 50 mV, period 60 ms, increment 6 mV. (b) Standard addition curve for measurement of Zn concentration.

The same samples were tested in separate ASV experiments using the Bi WE sensor, leading to a comparable value of 12.8 ± 2.2 µM Zn. Our Cu-based sensor exhibited the ability to measure Zn at much lower concentrations than the approximately 20 µM result reported previously using boron-doped diamond [371] or HMDE for measurements in the 49-63 µM range [372]. ICP-MS techniques have been reported to detect Zn with a LOD = 61 nM (4 ppb)

61 in whole blood or serum [373]. Although our miniaturized Cu-based voltammetric sensors are unable to match the precision and LODs of modern spectroscopic and mass spectrometry techniques, the measurements that they are able to do are in the physiologically relevant range, and using low-cost materials with simple fabrication, which is more favorable for disposable sensors.

Regarding possible interferences with Zn deposition and stripping, for our target sample matrix, blood serum, trace metals that exhibit stripping peaks in the potential range of interest are

Mn2+, Cd2+ and Cr3+. Fe ions have high level in blood while its high binding affinity with hemoglobin prevent being freed for electrochemical determination by the pretreatment we employed. The Mn peaks are expected to occur at approximately 200 mV more negative than Zn thus Mn is not expected to be deposited using the parameters of Zn determination. The Cd and

Cr peaks are expected to occur at approximately 350 mV more positive than Zn, while they are both present in trace levels in blood, less than 1 ppb or at approximately 77-500 nM (4-27 ppb)

[374], respectively. Metals with even more positive stripping potentials are not expected to affect Zn determination in the manner of difficulties in quantifying adjacent stripping peaks but would lead to depressed Zn peaks due to co-deposit with Zn. For example, Pb2+, which are 500 mV more positive than Zn, has to be below 207 ppb for negligible interference according to the discussion in Chapter 4, though the tolerance level is relatively high when its typical level in blood is 10 ppb [31]. In summary, these stripping peaks are all absent from the voltammograms and any presence of these trace metals in the sample would lead to minute peaks that would not severely affect Zn stripping.

62 Pb in blood

Blood Pb level is used to screen people at risk for Pb poisoning especially for industrial workers and children who live in urban areas. Pb is a highly poisonous metal, as it affects almost every human organ, such as kidney, nervous system and immune system. It can permanently reduce the cognitive capacity of children. Blood Pb level of 50 ppb is the level of concern stated by the CDC, while Pb in blood at even lower levels than that were found to be inversely associated with children's IQ scores [12]. LeadCare® II is a commercial POC system for testing blood Pb. It employs ASV to detect Pb in whole blood using carbon-based electrodes. The reportable range of the LeadCare® II system is 33-650 ppb [30] and reaches below the stated level of concern, however is less applicable for a diagnostic instrument as most children today exhibit Pb levels below 10 ppb [31].

Pb level is reported as total concentration in whole blood, thus ASV tests require sample pretreatment since most of the Pb binds to blood cells. Metexchange® is a reagent used in

LeadCare® II to lyse red blood cells so that the Pb becomes available for detection. The first generation of reagent contains chromium chloride 1.07 wt%, calcium acetate 1.43 %, mercuric ion 0.0028 wt%, confidential acids and buffer for pH control and a surfactant to suppress foaming. The second generation of Mextexchange contains hydrochloric acid 1.01 wt%. The pretreatment procedure was to mix the blood sample (in our case, bovine serum) and reagent in

1:29 v:v ratio and then incubate at room temperature for at least 60 min. Then the pH was adjusted to 5.5 with NaOH and diluted 2× with acetate buffer (0.2 M, pH 5.5), and samples were spiked with additional 0.6-1.2 ppm of Pb. The same extraction procedure developed for Zn described in the previous section was employed for ASV of Pb in serum. An alternative

63 digestion procedure involving nitric acid and surfactant (Triton X-114) was also employed here for ASV of Pb in whole blood.

ASV of Pb in serum

ASV was performed in serum pretreated by Metexchange® of generation one and spiked samples (Fig. 31a) with the same stripping parameters as in buffer. Pb peaks appeared in ASV in

4 serum with metexchange 600 ppb 3 800 ppb 1 ppm 2 1.2 ppm

1 Current (µA) Current 0

-1 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 Potential (V) (a) 12 extracted serum 100 ppb 9 200 ppb 500 ppb 6

Current (µA) Current 3

0 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 Potential (V) (b) Fig. 31 ASV of serum sample a) mixed with Metexchange® or b) extracted, and with additional 100 - 500 ppb Pb. Preconcentration potential -0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV. sample with spiked Pb of at least 600 ppb. The potentials of Pb peaks are -0.34 V, -0.37 V, -0.34

V and -0.33V for samples spiked with from 600 ppb to 1.2 ppm, respectively, which are comparable to -0.34V, the potential of Pb peaks with concentration below 0.5 µM in buffer. The voltammgrams are not stable with two background peaks at -0.2 and -0.15 V which have no

64 correlation with concentrations of Pb. The instability indicated that the reagent may strongly interfere with the Cu-based sensors which leads to a LOD too large for Pb determination.

The same extraction procedure developed for Zn was used to extract all metals including potential Pb in serum. The pH of the extracted sample was adjusted to 5.5 with NaOH and diluted 2× with acetate buffer (0.2 M, pH 5.5), and samples were spiked with additional 100-500 ppb of Pb. ASV was performed in the extracted serum and spiked samples (Fig. 31b) with same stripping parameters as above. Small Pb peaks appeared in ASV for the sample with spiked Pb of at least 100 ppb. The potentials of Pb peaks are -0.32 V, -0.34 V and -0.33 V for samples spiked with from 100 to 500 ppb. These potentials are not as stable as those of Pb in buffer while they are greatly improved compared to that of samples pretreated by Metexchange®. The currents of Pb peaks are also greatly improved. Specifically, the current for extracted sample spiked with 500 ppb is 7 µA compared to currents of 0.5-1 µA in Metexchange® treated samples spiked with 600-1200 ppb of Pb. However, compared to currents in buffer, the background currents are not as plain but elevate in the reported range and the current in extracted sample still gets depressed especially for lower concentrations. The currents for Pb of 100, 200, 500 ppb can be calculated to be 1.6, 3.2 and 8.2 µA, respectively, using calibration equation of Pb in buffer, while the currents in extracted samples spiked with that amount of Pb are 0.2, 1.2 and 7 µA.

Considering that the target level of Pb in blood is below 50 ppb and dilution factors larger than

10, these results are far from satisfactory.

The technique could be improved by optimizing experimental parameters. Longer preconcentration duration may provide 2x smaller LOD, while improvement of 2 magnitude demands more efficient mass transport, larger effective electrode surface area, etc. A preferable

LOD could be as low as, 4 ppb for example, to compensate for the dilution factors and for more

65 accurate determination. Considering the target matrix is whole blood rather than serum, we proceed without further improvement for Pb in serum but focus on pretreatments and ASV in whole blood.

ASV of Pb in whole blood

Whole blood pretreated by Metexchange® of generation two also caused problems for the Cu-based sensors. The preconcentration potential could not be held for the preconcentration duration of 5 min since their AEs were stripped off rapidly and the electrochemical cell broke down. With reduced preconcentration duration of 3 min, the resulting voltammograms were still too noisy to quantify.

Digestion procedures involving nitric acid and surfactant (Triton X-114) were employed as an alternative of Metexchange® for ASV of Pb in whole blood. The pH of the extracted sample was adjusted to 5.5 with NaOH and diluted 2× with acetate buffer (0.2 M, pH 5.5), and samples were spiked with additional 0.5-2 ppm of Pb. ASV was performed in the digested blood and spiked samples (Fig. 32) with the same stripping parameters as in buffer. Similar to the

40 blood 500 ppb 30 1 ppm 2 ppm

Current (µA) Current 10

0 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 Potential (V)

Fig. 32 ASV of digested blood and with additional 0.5 – 2 ppm Pb. Preconcentration potential - 0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV. extracted serum, the background currents appeared elevated and the currents depressed rapidly at lower concentrations. For samples spiked with 2 ppm, the potential of Pb peaks was -0.28 V

66 which is slightly more positive than -0.31V as potential of 10 µM (2.07 ppm) in buffer, while their average currents are comparable as 29.8 and 34.7 µA, respectively. For samples spiked with 1 ppm though, the current is rapidly reduced to 3 µA, compared to 16 µA of 5 µM (1.04 ppm). With spiked concentrations below 500 ppb, the Pb peaks are not quantifiable.

For demonstration purpose only, an in situ electroplated Hg on Cu-based sensors were used to determine Pb in digested blood. Whole blood was pretreated using digestion procedures involving nitric acid only, followed by the same buffer dilution and spiking procedure as before.

Fig. 33 shows the capability of quantifying Pb in digested blood using the Hg modified Cu-based sensors. The Pb stripping peaks (Fig. 33a) were -0.43 V, -0.43V, -0.48V and -0.38 V for the original and +20 ppb, +100 ppb, +500 ppb samples, respectively. The approximate 100 mV shift of Pb peaks could be caused by several factors, including the different overpotentials of the two different WEs, chloride concentration and stability of Cu/CuCl2 RE in different matrices. Pb concentration in the digested blood was calculated to be 63.3 nM (13.1 ppb) using the correlation equation I(µA)=6.35×[Pb(µM)]+0.402 (R2 = 0.999 for n = 3). Multiplied by the dilution factor of buffer dilution and digestion procedure, the Pb concentration in blood is determined to be 110 ppb using Hg modified Cu-based sensors.

Contrary to the rapidly reduced current with lower Pb concentrations using unmodified

Cu-based sensors in digested blood or extracted serum, the Hg modified sensors exhibited similar performance in buffer and digested blood. It implies that the Hg thin film deposit on the surface of WE was functioning as a protective layer from complex components in the matrices which were affecting the electrochemical performance of unmodified Cu-based sensors.

However, since Hg is prohibited in the procedure because of its toxicity and alternatives with similar performance in blood are difficult to find, determination of Pb in whole blood is still

67 challenging especially when targeting at low LOD. Improvements from sample preparation and sensing techniques are both important for future development.

18 + 500 ppb 15

Current (µA) Current + 20 ppb 3 sample 0 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 Potential (V)

(a) 20

y = 6.351x + 0.402 Current (µA) Current 5 R² = 0.9996

0 0 1 2 3 Concentration (µM)

(b) Fig. 33 (a) ASV of digested blood with additional 20 – 500 ppb Pb. Preconcentration potential: first step: -0.4 V duration, duration 60 s, second step: -0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV. (b) Standard addition of Pb in digested blood. Regarding possible interferences with determination of Pb in blood, trace metals that exhibit stripping peaks in the potential range of interest are Cd2+, Cr3+ and Sn2+. Zn is not is not expected to be deposited using the parameters of Pb determination, while according to the discussion in Chapter 4, the interference is negligible only when Pb level is below 207 ppb. The

Cd and Cr peaks occur at approximately 150 mV more negative than Pb, while they are both present in trace levels in blood as discussed in interferences with Zn. These stripping peaks are all absent from the voltammograms and any presence of these trace metals in the sample would

68 not severely affect Pb stripping. Sn though, whose stripping potential is only 50 – 100 mV more negative than Pb with level in blood at approximately 7.4 – 11.2 ppb [375], is possible to interfere with determination of Pb in blood, which needs confirmation from other techniques.

Pb and Cd in surface water

Pb in surface water

Determination of Pb in different water samples is a common environmental application for electrochemical sensors. The high toxicity and common occurrence requires carefully monitoring of Pb not only in blood but also in water for public health. Pb affects almost every human organ, such as kidney, nervous system and immune system. It could cause kidney cancer, gliomas, and lung cancer in rodents, and acts synergistically with other carcinogen [9]. The sources of Pb exposure include mining, smelting, Pb-containing gasoline and Pb paint [1]. It can enter the body through hand-to-mouth contact or through contaminated food or water. The guideline value for the safe level of Pb in drinking water is 10 ppb (48 nM) [365].

In the following applications, we performed a simple dilution as sample pretreatment.

This proved to be sufficient, although there are other more complex sample pretreatment methods for environmental matrices such as microwave-assisted digestion [376]. The more common sample pretreatment is extraction. It has been widely applied for trace heavy metal assessment in analysis of soil [377], sediment [378, 379] and sludge [380]. Sequential extraction techniques are considered to be necessary to determine heavy metals and their speciation which is a more accurate estimation than total elements determination [378-380]. Solid phase extraction using MWCNT [381] and magnetic particles [382] receives considerable attention benefiting from the characteristics of the materials. Nevertheless, sample pretreatments are

69 determined by the complexity of the sample matrices and simpler sample pretreatments are desirable for POC applications.

ASV of Pb in pond water

Water from a local pond (Burnet Woods, Cincinnati, OH) was collected and measured for

Pb using Cu-based sensors. The sample was diluted 2× with acetate buffer (0.2 M, pH 5.5) and spiked with additional Pb. ASV (Fig. 34a) was performed in the original sample and with additional Pb from 10 to 50 ppb with the same parameters as in buffer. In this range of Pb concentration, the small slope of the low background current may affect the determination of the baselines thus the quantification of the Pb peaks. Therefore, baseline subtraction is applied to all voltamgrams by subtracting the background current value of the background current at corresponding potentials. The ASV after baseline subtraction is shown in Fig. 34b. The potential of the Pb peak is -0.34 V, which is comparable to those in buffer. The calibration curve

(Fig. 34c) indicates the sensitivity is 3.05 µA/µM and linearity (R2 = 0.949). The sensitivity is slightly smaller than but comparable to that in buffer which is 3.43 µA/µM. The concentration of Pb in the pond water is determined to be 34.5 ppb, which is higher than 10 ppb, the safety level of Pb in drinking water, thus the local pond is still polluted by Pb and needs water process before human use. To further validate the reliability of this method, 50 ppb Pb was spiked to the original sample and processed though the same procedure.

ASV (Fig. 35a) was performed in the spiked sample and with the same additional Pb from 10 to 50 ppb. The ASV after baseline subtraction is shown in Fig. 35b. The calibration curve (Fig. 35c) indicates the sensitivity is 2.05 µA/µM and linearity (R2 = 0.972). The sensitivity and the currents at the same concentrations are smaller than that in previous samples, without obvious reasons. Nevertheless, we determined the concentration of Pb in the spiked

3 + 50 ppb 2.5

A) 2 μ 1.5 + 10 ppb sample

1 buffer Current ( Current 0.5

0 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 Potential (V) (a) 2 + 50 ppb 1.5

A) 1 μ 0.5 + 10 ppb sample

0 Current ( Current -0.5

-1 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 Potential (V) (b) 1.2

0.8

0.6

0.4 y = 3.048x + 0.254

Current (µA) Current R² = 0.949 0.2

0 0 0.1 0.2 0.3 Concentration (µM) (c) Fig. 34 (a) ASV of pond water diluted by acetate buffer (0.2 M, pH 5.5), and additional 10 - 50 ppb Pb. Preconcentration potential -0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV. (b) ASV after background subtraction. (c) Standard addition curve for Pb in pond water.

71 3 + 50 ppb 2.5

A) 2 μ + 10 ppb 1.5 sample+50ppb buffer

1 Current ( Current

0.5

0 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 Potential (V) (a) 2 + 50 ppb 1.5

A) 1 μ + 10 ppb 0.5 sample+50 ppb

0 Current ( Current -0.5

-1 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0 Potential (V) (b) 1.2

0.8

0.6

0.4 y = 2.048x + 0.410 R² = 0.972

Peak current (µA) current Peak 0.2

0 0 0.1 0.2 0.3 Concentration (µM) (c) Fig. 35 (a) ASV of pond water spiked with 50 ppb Pb, then diluted by acetate buffer (0.2 M, pH 5.5), and additional 10 - 50 ppb Pb. Preconcentration potential -0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV. (b) ASV after background subtraction. (c) Standard addition curve for Pb in pond water.

72 sample to be 82.8 ppb, 48.3 ppb higher than the calculated concentration in the original sample, thus the recovery is 96.6%.

ASV of Pb in river water

We collected water from Ohio River (Newport, KY) and measured Pb using the Cu-based sensors. Sample pH was adjusted to 5.5 using acetic acid and diluted 2× by acetate buffer (0.2

M, pH 5.5). Fig. 36a shows the ASV of the original sample and spiked with additional 25-500 ppb Pb, using the same parameters as in buffer. Pb peaks appear at the same position, -0.3 V, as in buffer.

18 + 500 ppb (2.4 µM) 15

Current (µA) Current + 25 ppb (0.12 µM) 3 sample 0 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 Potential (V)

(a) 20

Current (µA) Current 5 y = 6.206x - 0.184 R² = 0.998

0 0 1 2 3 Concentration (µM)

(b) Fig. 36 (a) ASV of river water sample and additional 25 - 500 ppb Pb. Preconcentration potential -0.8 V, duration 300 s, amplitude 50 mV, period 50 ms, increment 8 mV. (b) Standard addition curve for Pb in river water sample.

73 Standard addition curve (Fig. 36b) shows the linear response for additions of Pb. The correlation equation is I(µA)=6.21 ×[Pb(µM)]-0.184 (R2 = 0.998 for n = 5). The sensitivity,

6.21 µA/µM, is two times of that in acetate buffer. One possible reason is larger ionic strength of the sample due to its complex composition. Since there is no Pb peak in the ASV of the original sample, the Pb level in the sample from the Ohio River (Cincinnati, OH) is less than 2

(dilution factor) × LOD, 8.8ppb, which is below the safe level in drinking water. The same sample was also delivered to Dr. Bange’s lab and tested by AAS. The AAS result confirmed that there was no Pb contamination in the sample.

ASV of Cd in pond water

Water from a local pond (Burnet Woods, Cincinnati, OH) was collected (Oct. 15, 2014) and measured for Cd using Cu-based sensors. The sample was diluted 2× with acetate buffer

(0.2 M, pH 5.5) and spiked with additional Pb of 1 µM and Cd from 0.5 to 5 µM. ASV (Fig.

37a) was performed using the same parameters as in buffer. The potentials of Cd peaks, similar as in buffer, were shifting from -0.43- -0.45 V with concentration below 2 µM, to -0.55 V with concentration of 5 µM. The calibration curve (Fig. 37c) indicates the sensitivity is 0.245 µA/µM with linearity of R2 = 0.981. The sensitivity is half of that in buffer which is 0.516 µA/µM, which is probably due to the lower ionic strength of the water sample. Using the lowest peaks for calculating the LOD, the value is 113 nM (13 ppb), the same as in buffer. Since there is no

Cd peak in diluted sample, we can conclude that the concentration of Cd in the pond water is less than 26 ppb. Even though the value is not yet in the practical range due to the limit of electrochemical performance of Cu-based sensors for Cd determination, this experiment demonstrate that the sample itself would not bring extra issue for Cd determination.

74 3 Cd Pb + 5 µM (560 ppb) 1 µM

+ 0.5 µM (56 ppb)

1 Current (µA) Current

sample 0 -0.9 -0.8 -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 Potential (V) (a) 1.6

1.2

0.8

y = 0.245x + 0.228 Current (µA) Current 0.4 R² = 0.982

0 0 1 2 3 4 5 6 Concentration (µM)

(b) Fig. 37 (a) ASV of pond water diluted by acetate buffer (0.2 M, pH 5.5), and additional 0.5-5 µM Cd. First step: preconcentration potential -0.8 V, duration 120 s, second step: preconcentration potential -0.9 V, duration 300 s, amplitude 25 mV, period 70 ms, increment 4 mV. (b) Standard addition curve for Cd in pond water.

Summary

In this chapter, the Cu-based sensors were used to determine heavy metals in real world samples. We measured Zn in serum, Pb in blood and several types of surface water. Different sample pretreatments were discussed in different applications. For metals in surface water, samples were simply diluted by buffers and directly measured. For Pb determination in serum, both conventional digestion using special reagents and extraction procedure were employed for samples and compared regarding to ASV using Cu-based sensors. Extraction was used for Zn determination in serum. After sample pretreatment, original sample and samples spiked with

75 metals in proper range were measured by ASV using Cu-based sensors. Metal levels were then calculated based on the fitting equations of the standard addition curves.

76 CHAPTER 6

CONCLUSIONS

In this dissertation, a Cu-based sensor for ASV determination of Zn, Pb and Cd, was demonstrated. The Cu-based sensor was fabricated on glass substrate with Cu layer, and patterned by photolithography to form the three electrodes used in ASV: a Cu WE, a Cu AE, and a Cu/CuCl2 RE. These sensors were demonstrated to be sufficiently stable for at least one electrochemical measurement by examining each electrode. The LOD for each metal was calculated based on the calibration curves after optimization of experimental parameters. The

Cu-based sensors exhibited LODs of 140 nM (9.0 ppb) for Zn, 21 nM (4.4 ppb) for Pb, and 43 nM (4.7 ppb) for Cd (co-deposit with 1 µM Pb) in acetate buffer, respectively. The Cu-based sensors were then used to determine heavy metals in real world samples. We measured Zn in bovine serum, and Pb in blood and several types of surface water. Different sample pretreatments, dilution, conventional digestion using special reagents and extraction procedure were employed in different applications. Metal levels were successfully determined based on the standard addition curves. We also investigated how the presence of one metal influenced another metal’s stripping peak using Cu-based sensors and demonstrated that the influence could be neglected when the concentrations are in the typical range of real world samples.

Several features make this sensor ideally suited for POC applications. Firstly, Cu is a low-cost electrode material compared to Au or Pt. Though Cu is not a commonly used material

77 for electrochemical systems since it can easily oxidize, preconcentration in ASV helps to maintain the Cu WE in its original metallic state by applying a negative potential. We also demonstrated that the Cu-based sensor with a Cu/CuCl2 RE was sufficiently stable for ASV with a preconcentration duration as long as 600 s. Thus, the Cu-based sensors are qualified to be the low-cost disposable sensors for POC instruments. Second, the microfabrication procedure of the

Cu-based sensor is quite simple. Microfabrication offers the potential for mass production, which can further reduce the cost of the sensor. Simple fabrication also helps to reduce the variations among individual sensors, which is crucial for disposable applications. Third, the Cu- based sensors offer competitive performance in electrochemical detection. By optimizing experimental parameters, the Cu-based sensor exhibits low LOD for Zn and Pb, and the possibility to achieve the low Cd level. In experiments with environmental samples, ASV can be performed in sample simply pretreated by dilution. In experiments with extracted serum and digested blood samples, good quality peaks were observed that can be used to quantify the concentration of Zn or Pb using the standard addition approach.

On the other hand, there are also limitations for this sensor. Since the potential window is limited by the oxidation of Cu, the Cu-based sensors could only detect those metals that reduce at more negative potentials such as Pb, Cd and Zn discussed in this work, excluding metals which reduce at more positive potentials, such as As and Ag. A potential solution for this limitation is to electroplate another electrode material on top of Cu in order to extend the potential window without the high costs introduced by metal evaporation. The second limitation is that, compared to Bi coated carbon-based electrodes, the LOD of the Cu-based sensor is still high although this could be explained by the largely reduced sample volume and smaller WE area. Third, the behavior of sensors in serum extraction samples is still not favorable. The Cu-

78 based sensor is not as robust as carbon-based electrodes in that its behavior is highly dependent on the chemicals used in the extraction procedure. Cu can react with some commonly used acids like sulfuric acid so the chemicals involved have to be well controlled. These limitations suggest that there is more work to improve the Cu-based sensors to better accomplish the goal for public health.

79 APPENDIX

This Appendix contains a table summarizing recent publications in stripping analysis for

Pb, Cd and Zn (search engine: scopus, key word: stripping and (lead or cadmium or zinc) in title/keywords/abstract, year: 2011-present, exclude: citation < 8 for year 2011 and 2012).

In the table, the following chemicals are abbreviated as:

ABSA: p-aminobenzene sulfonic acid MES: mercaptoethanesulfonate APTE: 1,2-bis-[o-aminophenyl thio] ethane MOF: metal organic framework BDC: 1,4-benzenedicarboxylate MOPS 3-(N-morpholino)-propanesulfonic acid [Bmim]BF4: 1-butyl-3-methylimidazolium MPTMS: (3-mercaptopropyl) trimethoxysilane tetrafluoroborate MTTZ: 5-mercapto-1-methyltetrazole BTC: benzene-1,3,5-tricarboxylate N-BDMP: nitro benzoyl BTPP: bis(3-(2-thenylidenimino)propyl)piperazine diphenylmethylenphosphorane CB: 4-carboxybenzo NTA: nitrilotriacetic acid COC: cyclic olefin copolymer OPFP: octylpyridinium hexafluorophosphate CTS: crosslined chitosan PDA: polydopamine DAN: diaminonaphthalene PMO: periodic mesoporous organosilica DMcT: dimercapto-1,3,4-thiadiazole PmPD: poly(m-phenylenediamine)/ DPA: dipicolinic acid POPSO: piperazizne-N, N’-bis(2- DTCPA: 7,9-dithiophene-2yl-8H- hydroxypropanesulfonic acid) cyclopenta[a]acenaphthalene-8-one P-ABSA: poly(p-aminobenzene sulfonic acid) EDTA: ethylene diaminetetraacetate SAS: sodium salicylaldehyde-5-sulfonate EMIM TCB: 1-ethyl-3-methylimidazolium SDS: sodium dodecyl sulfate tetracyanoborate TBA: tetrabutylammonium GA: gallic acid TBrTP: meso-tetrakistetrabromothienyl porphyrin GO: graphene oxide TCFC: 3,8-bis(9,9-bis(6-(9H-carbazol-9-yl)hexyl)- HP-β-CD-RGO: hydroxypropyl-β-cyclodextrin- 9H-fluoren-2-yl)-1,10-phenanthroline reduced graphene oxide TH: thionine HQ: hydroxyquinoline Z-BHPBP: (Z)-2-((3-(4-(3-(5-bromo-2- IDA-PPy: Polypyrrole functionalized with hydroxybenzylideneamino) iminodiacetic acid propyl)piperazin-1-yl)propylimino) methyl)- L: 4-((1H-1,2,4-triazol-3-ylimino)methyl)phenol 4-bromophenol

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