Acetone Vapor-Sensing Properties of Chitosan-Polyethylene Glycol Using Surface Plasmon Resonance Technique

Article Acetone Vapor-Sensing Properties of Chitosan-Polyethylene Glycol Using Surface Plasmon Resonance Technique

Fahad Usman 1,* , John Ojur Dennis 1,*, E. M. Mkawi 2, Yas Al-Hadeethi 2, Fabrice Meriaudeau 3,*, Yap Wing Fen 4,5, Amir Reza Sadrolhosseini 5, Thomas L. Ferrell 6, Ahmed Alsadig 7 and Abdelmoneim Sulieman 8

1 Department of Fundamental and Applied Sciences, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak, Malaysia 2 Department of Physics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia; [email protected] (E.M.M.); [email protected] (Y.A.-H.) 3 ImViA EA 7535, Team IFTIM, Université de Bourgogne, 21000 Dijon, France 4 Department of Physics, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia; [email protected] 5 Institute of Advanced Technology, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia; [email protected] 6 Department of Physics and Astronomy, University of Tennessee, 401 Nielsen Physics Building and Joint Institute for Materials Research 1408 Circle Drive Room 219 2641 Osprey Way, Knoxville, TN 37996, USA; [email protected] 7 Department of Physics, Universita di Trieste, Piazzale Europa, 1, 34127 Trieste, Italy; [email protected] 8 Radiology and Medical Imaging Department, College of Applied Medical Sciences Prince Sattam bin Abdulaziz University, P.O. Box 422, Alkharj 11942, Saudi Arabia; [email protected] * Correspondence: [email protected] (F.U.); [email protected] (J.O.D.); [email protected] (F.M.)

Received: 16 October 2020; Accepted: 28 October 2020; Published: 4 November 2020

Abstract: To non-invasively monitor and screen for diabetes in patients, there is need to detect low concentration of acetone vapor in the range from 1.8 ppm to 5 ppm, which is the concentration range of acetone vapor in diabetic patients. This work presents an investigation for the utilization of chitosan-polyethylene glycol (PEG)-based surface plasmon resonance (SPR) sensor in the detection of trace concentration acetone vapor in the range of breath acetone in diabetic subjects. The structure, morphology, and elemental composition of the chitosan-PEG sensing layer were characterized using FTIR, UV-VIS, FESEM, EDX, AFM, and XPS methods. Response testing was conducted using low concentration of acetone vapor in the range of 0.5 ppm to 5 ppm using SPR technique. All the measurements were conducted at room temperature and 50 mL/min gas flow rate. The sensor showed good sensitivity, linearity, repeatability, reversibility, stability, and high affinity toward acetone vapor. The sensor also showed better selectivity to acetone compared to methanol, ethanol, and propanol vapors. More importantly, the lowest detection limit (LOD) of about 0.96 ppb confirmed the applicability of the sensor for the non-invasive monitoring and screening of diabetes.

Keywords: surface plasmon resonance sensor; acetone vapor detection; diabetes; chitosan- polyethylene glycol ﬁlm; non-invasive

Polymers 2020, 12, 2586; doi:10.3390/polym12112586 www.mdpi.com/journal/polymers Polymers 2020, 12, 2586 2 of 17

1. Introduction Diabetes has been ranked among the top deadliest diseases globally [1,2]. In 2019, the people suffering from diabetes were estimated to be 9.3% (463 million people) globally. Unfortunately, the number has been projected to rise to around 700 million by 2045 [2–4]. World Health Organization (WHO) has described diabetes as the major culprit for blindness, kidney failure, heart attacks, stroke, and lower limb amputation [3]. Currently, diabetes is being diagnosed through blood glucose monitoring. [2]. However, the requirement of drawing blood samples makes the method invasive, painful, inconvenient, and an avenue of infectious diseases as well as damaging tissues [5,6]. This paves a way to investigating more convenient ways. Fortunately, a high positive correlation has been reported between exhaled breath acetone and blood glucose [7]. This makes the relative level of exhaled acetone a suitable biomarker in detecting diabetes with a method of non-invasive monitoring [8]. Healthy subjects are reported to possess very low (0.1–0.8 ppm) acetone concentration while it might be elevated (1.8–5.0 ppm) in patients suffering from diabetes [7]. Numerous devices have been employed for the detection of acetone vapor at low concentrations. This includes conventional devices such as gas chromatography-mass spectrometry (GC-MS) and selective ion flow tube mass spectrometry (SIFT-MS). Despite the good sensitivity of these devices, the development and acceptance is hindered by their sophisticated instrumentation, nonreal-time measurement, expense, requirement of trained personnel, and scarcity [5]. On the other hand, metal oxide semiconductor (MOS)-based sensors have been reported to be the most investigated sensors in terms of low-concentration acetone vapor sensing [8]. However, these sensors are mostly operated at high temperature in addition to the selectivity and stability issues [8,9]. Optical sensors were reported to be more promising due to their greater sensitivity, electrical passiveness, freedom from electromagnetic interference, wide dynamic range, nonrequirement of reference electrode, freedom from electrical hazards, relatively high stability, the multiplexing capabilities, and the potential for higher-information content relative to that of electrical transducers [10]. In addition, another group of optical biosensors, surface plasmon resonance (SPR) sensors, has attracted many investigations due to their high sensitivity, real-time measurement, label-free measurement, and nonrequirement of electrodes [11–13]. These SPR sensors feature ultra-sensitive and selective detection when the surface is functionalized with certain materials depending on the analyte [11–15]. Studies have confirmed the promising applicability of chitosan-based materials in the detection of acetone vapor down to parts per million (ppm) levels [16]. Chitosan is an abundant material obtained from the de-acetylation of chitin. It is hydrophilic, biocompatible, moldable, biodegradable, renewable, nontoxic, cheap, and is a good absorbent material [17]. In addition, its amine and hydroxyl functional could play a vital role during interaction between an analyte and the surface of a chitosan-based material [18,19]. Moreover, addition of another polymer, polyethylene glycol (PEG) to chitosan, has been reported to increase the mechanical strength and biocompatibility of chitosan film [16,20]. This work was aimed at investigating acetone vapor-sensing properties of chitosan-PEG blend for possible non-invasive monitoring and screening of diabetes using the SPR technique. The performance measurements such as sensitivity, repeatability, binding affinity, and selectivity of the proposed sensor were explored and the results are reported here. Based on our literature survey, reports on the investigation of low concentrations of acetone vapor using SPR techniques are lacking.

2. Materials and Methods

2.1. Chemicals Chitosan, polyethylene glycol (PEG), acetic acid, acetone (99%), ethanol, methanol, and propanol were all supplied by Avantis chemicals supply, Ipoh-Perak, Malaysia from Merck (Darmstadt, Germany) and Sigma Aldrich (St. Louis, MO, USA). All the chemicals were analytical grade. Polymers 2020, 12, 2586 3 of 17

2.2. Fabrication of Au/Chitosan-PEG SPR Sensor Film Gold (Au) ﬁlm was deposited on cleaned microscopic glass slips, Menzel-Glaser, Braunscheig, Germany, using a sputter coater, SC7640. The sputter coater was set at 20 mA and 67 s in order to achieve the optimal gold thickness of about 50 nm [15]. The solution of chitosan-PEG blend was prepared by dissolving 500 mg of the chitosan powder in 9 mL of 2% acetic acid glacial. Then, 10 mg of PEG was dissolved in 1 mL deionized water. The two separate solutions were later mixed. In addition, the mixture was stirred for 24 h in order to obtain a homogeneous solution of the blend. The thin layer of the chitosan-PEG was deposited on top of the gold-coated substrate using POLOS™ spin coater at 6000 rpm and 30 s. The thin ﬁlm of the Au/chitosan-PEG was then kept in oven at 40 ◦C.

2.3. Characterization FTIR characterization was conducted using FTIR spectrometer (Bruker Instruments, 1 model Aquinox 55, Ettlingen, Germany) in the 4000–400 cm− range. The UV-VIS absorption and transmission spectra were obtained using Cary 100 UV-Vis Spectrophotometer from Agilent Technologies (Santa Clara, CA, USA). The surface morphology was studied using field emission scanning electron microscopy (FESEM) with images recorded by variable pressure field emission scanning electron microscope (VPFESEM), Zeiss Supra55 VP (Oberkochen, Germany). In addition, the energy-dispersive X-ray (EDX or EDS) was also conducted in order to determine the constituent elements for the blends. The thickness measurement was conducted using a surface roughness tester (SV-mutitoyo-3000, Mutitoyo, Aurora, IL, USA) and a surface profiler, AMBIOS, XP-200 based (AMBIOS, Santa Cruz, CA, USA) on a scratch following deposition of the film. An AFM study was conducted in order to investigate the surface roughness and coverage of the films. The functional groups of constituent materials present on the surface of the sensing layers were investigated by X-ray photoelectron spectroscopy (XPS, Thermo logical, K-alpha, Waltham, MA USA) in order to evaluate the interaction mechanism between the sensing layer and the acetone vapor.

2.4. SPR Measurement The experimental characterization was conducted using the setup illustrated in Figure1. The details of the setup are contained in the picture illustrated in Figure S1. The setup is based on Kretschmann configuration. Typically, an Au/chitosan-PEG sensor film was attached onto the base of the SF11 prism using a Norland index matching liquid. The prism with attached sensor film was then placed on an optical stage for control and in order to allow the light to reach the gold film from interior through one face of the prism. At a specific angle of incidence, the SPR angle, the intensity of the light wave reflected from the other face was reasonably reduced. This is the SPR response, which was recorded by a silicon photodiode detector. The signal was then processed by a lock-in amplifier (SR530) and it was displayed as a sharp dip on a PC. The SPR angle is sensitive to 1 milliradian changes. In addition, the gas was conveyed to a stainless-steel gas measuring cell attached to the sensing layer by a plastic tube. This conveyance was optimally controlled by the mass flow meters and valves, as shown in Figure1 and Figure S1. The temperature and the relative humidity were monitored by humidity/temperature meter, HT-601C. All the experiments were conducted at room temperature. The optimum flow rate was explored in the range of 50–250 mL/min. Polymers 2020, 12, x 4 of 17 Polymers 2020, 12, 2586 4 of 17 Polymers 2020, 12, x 4 of 17

Figure 1. Sketch diagram of the entire surface plasmon resonance (SPR) response testing setup.

Figure 1. Sketch diagram of the entire surface plasmon resonance (SPR) response testing setup. 3. ResultsFigure 1. Sketch diagram of the entire surface plasmon resonance (SPR) response testing setup. 3. Results 3.3.1. Results Structural, Morphological, and Chemical Compositional Characterization of the Sensing Layer 3.1. Structural, Morphological, and Chemical Compositional Characterization of the Sensing Layer 3.1. Structural,Figure 2 depictsMorphological, the FTIR and spectrum Chemical ofCo thempositional chitosan-PEG Characterization blend. The of broadthe Sensing peak Layer at 3274 cm−1 is 1 due Figureto the2 N–Hdepicts stretching the FTIR and spectrum O–H ofstretching the chitosan-PEG vibrations blend. of the The chitosan broad peakand atPEG 3274 [21]. cm −Theis Figure 2 depicts the FTIR spectrum of the chitosan-PEG blend. The broad peak at 3274 cm−1 is duebroadness to the N–His further stretching confirming and O–H the stretchingassociation vibrations of the two of polymeric the chitosan materials. and PEG Moreover, [21]. The broadnessthe peaks due to the N–H stretching and O–H stretching vibrations of the chitosan and PEG [21]. The isat further2920 and conﬁrming 2856 cm− the1 are association attributed ofto thethetwo asymmetric polymeric and materials. symmetric Moreover, C–H stretching, the peaks respectively at 2920 and broadness1 is further confirming the association of the two polymeric materials. Moreover, the peaks 2856[22,23]. cm −Theare peak attributed at 1080 to cm the−1 asymmetriccould be attributed and symmetric to the C–O C–H stretching stretching, of respectively ether group [22 for,23 PEG]. The while peak at 2920 and 12856 cm−1 are attributed to the asymmetric and symmetric C–H stretching, respectively atthe 1080 peaks cm −898could and be 820 attributed cm−1 could to the also C–O be stretching attributed ofether to the group similar forPEG PEG while characteristics’ the peaks 898 peaks and [22,23]. The1 peak at 1080 cm−1 could be attributed to the C–O stretching of ether group for PEG while 820observed cm− couldpreviously also be [21,22]. attributed to the similar PEG characteristics’ peaks observed previously [21,22]. the peaks 898 and 820 cm−1 could also be attributed to the similar PEG characteristics’ peaks observed previously [21,22]. (e)

(e) 898

898 820 686 2856 820 686 2920 3274 1648 2856 2920 1580 3274 % Transmittance % 1648 1580 % Transmittance % 1080

1080 1000 1500 2000 2500 3000 3500 4000 -1 Wavenumber (cm ) 1000 1500 2000 2500 3000 3500 4000 Figure 2. FTIR spectra ofWavenumber chitosan-Polyethylene (cm-1) glycol blend. Figure 2. FTIR spectra of chitosan-Polyethylene glycol blend. Figure3 shows the absorption and transmittance spectra of the chitosan-PEG. It is reported that Figure 2. FTIR spectra of chitosan-Polyethylene glycol blend. chitosanFigure featured 3 shows no absorptionthe absorption peak and within transmittance 300–900 nm sp [24ectra]. However, of the chitosan-PEG. the minor peak It observed is reported around that chitosan featured no absorption peak within 300–900 nm [24]. However, the minor peak observed Figure 3 shows the absorption and transmittance spectra of the chitosan-PEG. It is reported that chitosan featured no absorption peak within 300–900 nm [24]. However, the minor peak observed

Polymers 2020, 12, x 5 of 17

around 350–400 nm could be attributed to the presence of PEG [25,26]. On the other hand, the transmittance value of the material indicates its promising application in the visible range [27]. Polymers 2020, 12, 2586 5 of 17

0.7 0.9 350–400 nm could be attributed(e) to the presence Absorbance of PEG [ 25,26 Transmittance]. On the other hand, the transmittance 0.8 value of the material0.6 indicates its promising application in the visible range [27]. PolymersThe 2020 surface, 12, x morphology and EDX spectrum of the chitosan-PEG are shown0.7 in Figure54 ofa,b, 17 respectively. Figure40.5a shows no obvious feature for the chitosan-PEG surface. This could be due to aroundthe flatness 350–400 nature nm of could chitosan be filmsattributed and itto is the consistent presence with of thePEG previous [25,26]. workOn0.6 the [28 other,29]. In hand, addition, the 0.4 transmittanceit confirms the value absence of the of bubblesmaterial in indicates the chitosan-PEG its promising blend application [29]. in the visible range [27]. 0.5 0.3

0.7 0.40.9 Transmittance Absorbance (a.u.) Absorbance (e) Absorbance Transmittance 0.2 0.3 0.6 0.8

0.1 0.20.7 0.5 300 400 500 600 700 800 Wavelength (nm) 0.6 0.4 Figure 3. UV-VIS absorption and transmittance spectra of chitosan-PEG blend.0.5 0.3

The surface morphology and EDX spectrum of the chitosan-PEG are shown0.4 in Transmittance Figure 4a,b, Absorbance (a.u.) Absorbance respectively. Figure 4a shows no obvious feature for the chitosan-PEG surface. This could be due to 0.2 the flatness nature of chitosan films and it is consistent with the previous work [28,29].0.3 In addition, it confirms the absence of bubbles in the chitosan-PEG blend [29]. 0.1 0.2 As shown in 300Figure 4b, 400the higher 500 oxygen 600(%) contents 700 in the 800chitosan-PEG confirm the abundance in OH functional group, which has the potential to increase the analyte-sensing layer Wavelength (nm) interaction [30]. In addition, EDX could penetrate down to about 2000 nm [31]. As such, Si and Au could be observed, which originated from the substrates and the gold film, respectively. FigureFigure 3. 3. UV-VISUV-VIS absorption absorption and and transmittanc transmittancee spectra spectra of of chitosan-PEG chitosan-PEG blend.

The surface morphology and EDX spectrum of the chitosan-PEG are shown in Figure 4a,b, respectively. Figure 4a shows no obvious feature for the chitosan-PEG surface. This could be due to the flatness nature of chitosan films and it is consistent with the previous work [28,29]. In addition, it confirms the absence of bubbles in the chitosan-PEG blend [29]. As shown in Figure 4b, the higher oxygen (%) contents in the chitosan-PEG confirm the abundance in OH functional group, which has the potential to increase the analyte-sensing layer interaction [30]. In addition, EDX could penetrate down to about 2000 nm [31]. As such, Si and Au could be observed, which originated from the substrates and the gold film, respectively.

FigureFigure 4. (4.a) FESEM(a) FESEM image image of chitosan-PEG, of chitosan-PEG, (b) energy-dispersive (b) energy-dispersive X-ray (EDX)X-ray spectrum(EDX) spectrum and elemental and compositionelemental composition of chitosan-PEG. of chitosan-PEG.

AsThe shown surface in Figure roughness4b, the of higher the glass oxygen substrate, (%) contents gold inlayer, the chitosan-PEGand the chitosan-PEG-coated confirm the abundance gold inlayer OH functional were derived group, from which the has AFM the potential surface tomorp increasehological the analyte-sensingimages shown layerin Figure interaction S2a–c, [30 ]. Inrespectively. addition, EDX The could surface penetrate features down are in to consistenc about 2000e with nm the [31 ].respective As such, FESEM Si and Auimage. could Based be observed, on the whichroughness originated data fromin Table the 1, substrates both the roughness and the gold aver film,age (Ra) respectively. and Root Mean Square (RMS) roughness valuesThe for surface the glass roughness substrate of and the gold glass layer substrate, could lead gold to a layer, good andSPR sensor the chitosan-PEG-coated [32]. The Ra roughness gold value for the chitosan-PEG films is 5.87 nm while its RMS value is 9.29 nm. This higher roughness layer were derived from the AFM surface morphological images shown in Figure S2a–c, respectively. The surface features are in consistence with the respective FESEM image. Based on the roughness data Figure in Table 4. 1(,a both) FESEM the roughnessimage of chitosan-PEG, average (Ra) (b and) energy-dispersive Root Mean Square X-ray (RMS)(EDX) roughnessspectrum and values for theelemental glass substrate composition and of goldchitosan-PEG. layer could lead to a good SPR sensor [32]. The Ra roughness value for the chitosan-PEG films is 5.87 nm while its RMS value is 9.29 nm. This higher roughness value couldThe improve surface the roughness response of of the sensorglass substrate, due to the gold potentially layer, and increased the chitosan-PEG-coated adsorption capability gold of layerrough were surfaces derived [33]. from the AFM surface morphological images shown in Figure S2a–c, respectively. The surface features are in consistence with the respective FESEM image. Based on the roughness data in Table 1, both the roughness average (Ra) and Root Mean Square (RMS) roughness values for the glass substrate and gold layer could lead to a good SPR sensor [32]. The Ra roughness value for the chitosan-PEG films is 5.87 nm while its RMS value is 9.29 nm. This higher roughness

PolymersPolymers2020 2020, 12, 12, 2586, x 6 of6 17 of 17

value could improve the response of the sensor due to the potentially increased adsorption capability Tableof rough 1. Roughness surfaces [33]. parameters for the glass, gold, and the chitosan-PEG ﬁlm surfaces. The optimum gold thickness for the SPR generation is around 50 nm [15]. As shown in Figure Material Ra (nm) RMS (nm) S3a–b, similar values, 47.458 nm and about 50 nm, were obtained for the surface profiler- and surface roughness tester-based measurements,Glass respectively. 0.16 0.22 Gold 2.13 4.05 Chitosan-PEG 5.87 9.29 Table 1. Roughness parameters for the glass, gold, and the chitosan-PEG film surfaces.

Material Ra (nm) RMS (nm) The optimum gold thickness for the SPR generation is around 50 nm [15]. As shown in Figure Glass 0.16 0.22 S3a,b, similar values, 47.458 nm and about 50 nm, were obtained for the surface profiler- and surface Gold 2.13 4.05 roughness tester-based measurements, respectively. Chitosan-PEG 5.87 9.29 3.2. Acetone Detection Measurement 3.2. Acetone Detection Measurement 3.2.1. Optimization of Experimental Conditions 3.2.1. Optimization of Experimental Conditions Prior to the response testing, the temperature and the relative humidity of the optimal flow rate were monitoredPrior to the using response a humidity testing, /thetemperature temperature meter, and HT-601C.the relative Subsequently, humidity of the these optimal conditions flow rate were maintainedwere monitored with the using aid ofa humidity/temperature a protective fabric, illustrated meter, HT-601C. in Figure S1.Subsequently, these conditions wereFigure maintained5 shows with measured the aid SPRof a protec angletive at various fabric, illustrated flow rates in in Figure the range S1. of 50–250 mL /min for the Figure 5 shows measured SPR angle at various flow rates in the range of 50–250 mL/min for the synthetic air, water vapor, and 5 ppm acetone vapor. It was observed that the highest SPR angle was synthetic air, water vapor, and 5 ppm acetone vapor. It was observed that the highest SPR angle was recorded at the flow rate of 50 mL/min for all the analytes at the recorded chamber temperature of recorded at the flow rate of 50 mL/min for all the analytes at the recorded chamber temperature of about 29.0 C. The measured relative humidity (RH) % values in the chamber for the synthetic air about 29.0◦ °C. The measured relative humidity (RH) % values in the chamber for the synthetic air (carrier gas), water vapor, and 5 ppm acetone vapor were about 20.09% RH, 92.81% RH, and 87.50% (carrier gas), water vapor, and 5 ppm acetone vapor were about 20.09% RH, 92.81% RH, and 87.50% RH, respectively. As such, all the subsequent chitosan-PEG-based SPR measurements were conducted RH, respectively. As such, all the subsequent chitosan-PEG-based SPR measurements were underconducted these under conditions. these conditions.

46 Synthetic air Water vapour Acetone vapour (5ppm) 45

SPR angle (degree) 42

50 100 150 200 250 Flow rate (ml/min) FigureFigure 5. 5.SPR SPR angle angle vs.vs. ﬂowflow raterate on the response of of ch chitosan-PEG-baseditosan-PEG-based SPR SPR sensor sensor in insynthetic synthetic airair (carrier(carrier gas), gas), water water vapor, vapor, and and 55 ppmppm acetoneacetone vapor.

3.2.2.3.2.2. SPR SPR Response Response onon thethe Chitosan-PEG-BasedChitosan-PEG-Based Se Sensornsor to to Different Different Acetone Acetone Vapor Vapor Concentrations Concentrations inin Air Air PriorPrior to to the the investigation investigation of the of chitosan-PEG-based the chitosan-PEG-based sensor responsesensor toresponse the various to the concentrations various ofconcentrations acetone vapor, of theacetone steady vapor, condition the steady for the cond SPRition measurement for the SPR measurem and the restorationent and the of restoration the sensing layerof the were sensing achieved layer bywere allowing achieved 5-min by allowing exposure 5- tomin the exposure analytes to and the synthetic analytes air,and respectively synthetic air, [15 ]. Therespectively SPR response [15]. The of chitosan-PEGSPR response of sensing chitosan-PEG layer to sensing dry air layer (synthetic to dry air (synthetic at 20.09% air RH) at 20.09% different, waterRH) different, vapor (humidified water vapor air (humidified at 92.81% air RH), at 92.81% and to RH), acetone andvapor to acetone concentrations vapor concentrations from 0.5 ppmfrom to 50.5 ppm ppm in humidifiedto 5 ppm in airhumidified (at 87.50% air RH) (at was87.50% measured, RH) was as measured, shown in as Figure shown6a. in A Figure positive 6a. SPR A positive shift was observed with the increase in the concentration of the acetone vapor. The SPR shift was due to changes Polymers 2020, 12, x 7 of 17

SPR shift was observed with the increase in the concentration of the acetone vapor. The SPR shift was due to changes in the surface plasmon properties of the gold film plus absorbate relative to the gold film alone, as caused by the optical properties of the absorbed analyte as well as the change of the refractive index of the sensing layer [15]. Figure 6b,c shows the graph of the SPR angle against time and calibration curve, respectively. The excellent repeatability and linearity infer the suitability of the device for acetone vapor sensing in the exhaled breath for diabetes monitoring and screening within the range of 1.8 ppm to 5 ppm in diabetic subjects [7]. The repeatability of the chitosan-PEG-based SPR sensor was assessed by the Polymers 2020, 12, 2586 7 of 17 values of standard deviation and the coefficient of variation (COV) [15,34]. Based on the results presented in Table S1, the average standard deviation for the three replicas was about 0.054. In inaddition, the surface the plasmonrelative standard properties deviation of the ( goldRSD) film or the plus coefficient absorbate of variat relativeion to (COV) the gold value film was alone, found as causedto be 0.123%. by the optical These propertiesindicate the of repeatability the absorbed of analyte the measurement as well as the [35,36] change. This of the behavior refractive is further index of theillustrated sensing layerin Figure [15]. 6b. FigureIn order6b,c to shows compute the the graph calibration of the SPR curve angle of the against acetone time detection and calibration of the chitosan curve,- respectively.PEG-based TheSPR excellent sensor, the repeatability effect of water and linearityvapor was infer eliminated the suitability, as shown of the in devicethe last forcolumn acetone of Table vapor S1. sensing The calibration curve is illustrated in Figure 6b, which shows a good linear response of the sensor. The in the exhaled breath for diabetes monitoring and screening within the range of 1.8 ppm to 5 ppm linear regression analysis is governed by the Equation (1), in diabetic subjects [7]. The repeatability of the chitosan-PEG-based SPR sensor was assessed by the values of standard deviation and the coeΔffiθcient = kC of + I variation (COV) [15,34]. Based on the results(1) presented in Table S1, the average standard deviation for the three replicas was about 0.054. In addition, where Δθ is the average SPR angle shift, k is the slope, which is the sensitivity in degree/ppm, C is thethe relative acetone standard concentration deviation in ppm (RSD), and or I theis the coe intercept.fficient of Figure variation 6b indicates (COV) valuethat the was average found SPR to be 0.123%.shift is Theselinearly indicate correlated the repeatability to the acetone of v theapor measurement concentration [35 in,36 air]. This with behavior a high correlation is further illustratedfactor of in0.974 Figure and6b. with a corresponding sensitivity value of 0.348 degree/ppm.

1.2 (b) (a) Air H2O vapour 0.5 ppm 1 ppm 45 0.5 ppm 2 ppm 3 ppm 4 ppm 5 ppm 1 ppm 2 ppm 1.0 87.50% RH 44 3 ppm 4 ppm 5 ppm

0.8 43

Reflectance

SPR angle (degree) 42 0.6 Synthetic air 20.09% RH 41 38 40 42 44 46 48 50 0 5 10 15 20 25 30 Incidence angle (degree) Time (mins)

(b)(c) 3

y=0.348x+1.270 Adjusted R2=0.974

Average SPR shift (degree) 1 1 2 3 4 5 Acetone concentration (ppm) Figure 6. (a) Reﬂectance versus incident angle for the chitosan-PEG-based SPR response in dry air, Figure 6. (a) Reflectance versus incident angle for the chitosan-PEG-based SPR response in dry air, water vapor, and the various concentrations of the acetone vapor from 0.5 ppm to 5 ppm, (b) SPR angle water vapor, and the various concentrations of the acetone vapor from 0.5 ppm to 5 ppm, (b) SPR versus time of the single layer chitosan-PEG-based SPR sensor at diﬀerent acetone vapor concentrations angle versus time of the single layer chitosan-PEG-based SPR sensor at different acetone vapor from 0.5 ppm to 5 ppm as compared to synthetic air levels, and (c) SPR angle shift versus acetone concentration from 0.5 ppm to 5 ppm.

In order to compute the calibration curve of the acetone detection of the chitosan-PEG-based SPR sensor, the eﬀect of water vapor was eliminated, as shown in the last column of Table S1. The calibration curve is illustrated in Figure6b, which shows a good linear response of the sensor. The linear regression analysis is governed by the Equation (1),

∆θ = kC + I (1) where ∆θ is the average SPR angle shift, k is the slope, which is the sensitivity in degree/ppm, C is the acetone concentration in ppm, and I is the intercept. Figure6b indicates that the average SPR shift is Polymers 2020, 12, x 8 of 17

concentrations from 0.5 ppm to 5 ppm as compared to synthetic air levels, and (c) SPR angle shift versus acetone concentration from 0.5 ppm to 5 ppm.

3.2.3. Thickness Variation of Layers and Lowest Detection Limit (LOD) of the Chitosan-PEG Films The result presented in Figure 6 is from a single layer of chitosan-PEG deposited at 6000 rpm for Polymers 2020, 12, 2586 8 of 17 30 s. In order to investigate the effect of layer thickness on the sensitivity of the chitosan-PEG-based SPR sensor, four different chitosan-PEG sensing layers with 2, 3, 4, and 5 layers deposited on top of thelinearly first layer correlated to increase to the acetonethickness vapor were concentration also prepared in and air with tested. a high Figure correlation S4a,b shows factor the of 0.974effect and of thewith number a corresponding of layers on sensitivity the SPR curves value ofand 0.348 the degreesensitivity,/ppm. respectively. The results are summarized in Figure 7 and Table 2. It could be observed from Table 2 that the full width at half maximum (FWHM)3.2.3. Thickness increases Variation with number of Layers of layers, and Lowest which Detection is attributed Limit to (LOD)the increase of the in Chitosan-PEG the thickness Films of the chitosan-PEGThe result sensing presented layer. in FigureFrom 6Figure is from 7 ait single can be layer observed of chitosan-PEG that the sensitivity deposited decreases at 6000 rpm with for number30 s. In orderof chitosan-PEG to investigate layers, the e ffwhichect of layeris in accordan thicknessce on with the sensitivitya result on of the the SPR chitosan-PEG-based detection of ethanol SPR andsensor, isopropanol four different [37]. chitosan-PEG This could be sensing due to layers the withdecrease 2, 3, 4,of andthe 5penetration layers deposited depth on of top the of surface the first plasmonlayer to increasewave [12,14]. thickness Based were on alsothe result prepared presented and tested. in Figure Figure 7 S4a,band Table shows 2, the it could effect be of theconcluded number thatof layers single-layer on the SPR chitosan-PEG-based curves and the sensitivity, SPR sensor respectively. is the best The in results terms are of summarized sensitivity, inFWHM, Figure7 andand figureTable2 of. It merit could (FOM). be observed from Table2 that the full width at half maximum (FWHM) increases with numberThe oflowest layers, detection which is attributedlimit (LOD) to theof the increase chitosan-PEG-based in the thickness ofSPR the acetone chitosan-PEG vapor sensingsensor layer.was estimatedFrom Figure using7 it the can ratio be observed 3𝜎/𝑠𝑒𝑛𝑠𝑖𝑡𝑖𝑣𝑖𝑡𝑦 that the [38], sensitivity where decreasesσ stands for with the numberstandard of deviation chitosan-PEG of the layers,blank sample.which is The in accordance SPR curves with of the a result blank on sample the SPR and detection its values of ethanolfor one-layer and isopropanol chitosan-PEG-based [37]. This couldSPR acetonebe due vapor to the decreasesensor are of shown the penetration in Figure S5 depth and ofTable the surfaceS2, respectively. plasmon The wave standard [12,14]. deviation Based on ( theσ) ofresult 10 replicas presented was in evaluated Figure7 and to be Table about2, it 0.0001. could be This concluded gives the that LOD single-layer value of chitosan-PEG-basedabout 0.96 parts per billionSPR sensor (ppb). is the best in terms of sensitivity, FWHM, and figure of merit (FOM).

0.4 Experimental data Linear Fit

y=-0.551x+0.3931

0.3 Adj. R2=0.98

0.2 Sensitivity (degree/ppm)

0.1 0123456 Number of Layers Figure 7. Sensitivity versus number of chitosan-PEG layers. Figure 7. Sensitivity versus number of chitosan-PEG layers. Table 2. Performance characteristics of chitosan-PEG SPR acetone vapor sensor based on 1, 2, 3, 4, Tableand 5 2. deposited Performance layers characteristics of chitosan-PEG of chitosan-PEG ﬁlms. SPR acetone vapor sensor based on 1, 2, 3, 4, and 5 deposited layers of chitosan-PEG films. Number of Layers FWHM (Degree) Sensitivity (Degree/ppm) FOM (per ppm) Number1 of layers FWHM 4.86 (degree) Sensitivity 0.348(degree/ppm) FOM (per 0.07 ppm) 21 5.124.86 0.348 0.280 0.07 0.05 22 7.815.12 0.280 0.216 0.05 0.03 42 8.857.81 0.216 0.165 0.03 0.02 5 indeﬁnite 0.130 0 4 8.85 0.165 0.02 5 indefinite 0.130 0 The lowest detection limit (LOD) of the chitosan-PEG-based SPR acetone vapor sensor was estimated using the ratio 3σ/sensitivity [38], where σ stands for the standard deviation of the blank sample. The SPR curves of the blank sample and its values for one-layer chitosan-PEG-based SPR acetone vapor sensor are shown in Figure S5 and Table S2, respectively. The standard deviation (σ) of 10 replicas was evaluated to be about 0.0001. This gives the LOD value of about 0.96 parts per billion (ppb). PolymersPolymers 20202020, 12, 12, x, 2586 9 of9 17of 17

3.2.4. SPR Angle Versus Time Graph of Single-Layer Chitosan-PEG-Based SPR Sensor for the 3.2.4. SPR Angle Versus Time Graph of Single-Layer Chitosan-PEG-Based SPR Sensor for the Detection Detectionof Acetone of Acetone Vapor Vapor TheThe SPR SPR angle angle of of the the single-layer single-layer chitosan-PEG chitosan-PEG-based-based SPRSPR sensorsensor was was evaluated evaluated in in order order to to investigateinvestigate the the recovery, recovery, response,response, stability, stability, and and reversibility reversibility of the of measurements the measurements [39–41]. [39–41]. The graph The graphis shown is shown in Figure in Figure8 as a plot 8 as of a SPR plot angle of SPR as a angle function as ofa function time [ 15 ,42of ].time Unfortunately, [15,42]. Unfortunately, our SPR system our SPRsetup system could setup not provide could not SPR provide angle measurement SPR angle measur data fasterement than data 3.5 min faster after than each 3.5 run min due after to the each need run dueto to control the need and adjustto control some and of itsadjust components some of manually. its components Therefore, manually. accurate Therefore, response and accurate recovery response time andvalues recovery could time not bevalues determined. could not However, be determined. it could However, be observed it fromcould Figure be observed8 that both from the Figure response 8 that bothand the recovery response times and would recovery be less times than would 1 min each be less after than exclusion 1 min of each the 3.5after min. exclusion Excellent of reversibility the 3.5 min. Excellentand recovery reversibility of the sensor and recovery was observed of the when sens theor supplywas observed of the 5 ppmwhen acetone the supply vapor of was the ceased 5 ppm acetoneand replaced vapor was by the ceased introduction and replaced of the by synthetic the introd air.uction Other concentrationsof the synthetic of air. the Other acetone concentrations vapor also of showedthe acetone similar vapor characteristics also showed (Figure similar6b). characteristics (Figure 6b).

46 5 ppm acetone vapour 45 87.50% RH

Synthetic air SPR angle (degree) 42 20.09% RH

41 0 102030405060 Time (mins) FigureFigure 8. 8.SPRSPR angle angle versus versus time time of of the the single-layer single-layer chitosan-PEG-basedchitosan-PEG-based SPR SPR sensor sensor at at 5 ppm5 ppm acetone acetone vaporvapor concentration concentration as as compar compareded to to synthetic synthetic air levels.levels.

3.2.5. Binding Affinity of Acetone toward SPR Sensor with Single Layer of Chitosan-PEG 3.2.5. Binding Affinity of Acetone toward SPR Sensor with Single Layer of Chitosan-PEG The investigation of the binding strength between the single-layer chitosan-PEG SPR sensor and The investigation of the binding strength between the single-layer chitosan-PEG SPR sensor acetone vapor was deduced from the plotting graph of the average SPR angle shifts as a function of the and acetone vapor was deduced from the plotting graph of the average SPR angle shifts as a function average acetone concentrations, shown in Figure6c. This graph was fitted to the nonlinear and linear of formatsthe average of the acetone Langmuir concentrations, and the Freundlich shown isothermin Figure models,6c. This asgraph shown was in fitted Equation to the (S1), nonlinear (S2), (S3), and linearand formats (S4), respectively of the Langmuir [15,43]. The and fits the with Freundlich low error isotherm value and models, higher correlation as shown factorin Equation were regarded (S1), (S2), (S3),as theand best (S4), [44 respectively]. Figure9a–d [15,43]. shows The the graphsfits with for low the error nonlinear value Langmuir and higher fittings, correlation linear Langmuir factor were regardedfittings, as nonlinear the best Freundlich [44]. Figure fittings, 9a–d shows and linear the Freundlichgraphs for fittings,the nonlinear respectively. Langmuir These fittings, results linear are Langmuirpresented fittings, in Table nonlinear3. As shown Freu inndlich Figure fittings,9 and Table and3 ,linear the parameter Freundlich∆ θfittings,is the SPR respectively. shift, ∆θmax Theseis resultsthe maximum are presented SPR shift in Table at saturation, 3. As shownC is thein Figure concentration 9 and Table of the 3, analyte, the parameter and KD isΔθ the is equilibriumthe SPR shift, Δθdissociationmax is the maximum constant. ASPRffinity shift constant at saturation, (KA) is the C reciprocal is the concentration of KD. In addition, of the 1 /analyte,n is the heterogeneity and KD is the equilibriumfactor [43,45 dissociation]. A variation cons in thetant. slope Affinity (1/n) betweenconstant 0 ( andKA) is 1 isthe associated reciprocal with of aK chemisorptionD. In addition, process.1/n is the heterogeneityWhen a slope factor above [43,45]. 1 is observed, A variation then a in physical the slope absorption (1/n) between process is0 expectedand 1 is [ 46associated,47]. KF can with be a chemisorptionrelated to the strengthprocess. ofWhen the adsorptive a slope above bond or 1 adsorptionis observed, capacity. then Furthermore,a physical absorption∆θmax is measured process is 1 expectedin degree, [46,47].KA is measuredKF can be inrelated ppm− to, and theK strengthD and KF ofare the measured adsorptive in ppm bond [15 ,48or]. adsorption capacity. Furthermore,The correlation Δθmax is factormeasured values infor degree, the nonlinear KA is measured Langmuir, in linearppm−1 Langmuir,, and KD and nonlinear KF are Freundlich,measured in ppmand [15,48]. linear Freundlich fittings are 0.84, 0.92, 0.95, and 0.96, respectively. This shows that the Freundlich The correlation factor values for the nonlinear Langmuir, linear Langmuir, nonlinear Freundlich, and linear Freundlich fittings are 0.84, 0.92, 0.95, and 0.96, respectively. This shows that the Freundlich model also fit better for the chitosan-PEG SPR sensing layer. Freundlich model also showed smaller values of standard error, reduced chi-square, and residual sum of squares.

Polymers 2020, 12, 2586 10 of 17 model also ﬁt better for the chitosan-PEG SPR sensing layer. Freundlich model also showed smaller values of standard error, reduced chi-square, and residual sum of squares. However, the error and variability values observed in the Langmuir are not reasonably high. As such, both the Langmuir and the Freundlich models could be used to describe the adsorption process on the surface of the chitosan-PEG sensing layer. In addition, the ∆θmax value obtained was closer to the maximum shift of 3.057 ppm, depicted in Table S1 and Figure6. In this regard, the linear Langmuir model showed the closest value (2.994 ppm) due to the lower standard error of its intercept (0.306) compared to nonlinear model (0.328). Furthermore, the K value, 1.12 ppm 1 (2.704 107 M 1 or 1.120 103 g/mg), for the A − × − × nonlinear Langmuir model is more reliable for its low standard error compared to the linear model. Additionally, the higher KA value compared to KD value of 0.893 ppm indicates the greater aﬃnity of the acetone toward the chitosan-PEG sensing layer [15].

Table 3. Binding parameters of acetone vapor toward single-layer chitosan-PEG-based SPR sensor extracted from nonlinear Langmuir, linear Langmuir, nonlinear Freundlich, and linear Freundlich ﬁttings.

Model Format Parameter Value Standard Error ∆θmax 3.227 0.328

1/KA 0.893 0.320 Adj. R2 0.840 - Langmuir Non-linear Reduced chi-square 0.060 -

KA 1.120 -

KD 0.893 - Residual sum of squares 0.160 - Adj. R2 0.917 - Intercept 0.334 0.306 Langmuir Linear Slope 4.458 0.595 ∆θmax 2.994 -

KA 0.075 -

KD 13.333 -

KF 1.647 0.082 n 2.874 0.337 Freundlich Non-linear Adj. R2 0.947 - Reduced chi-square 0.020 - Residual sum of squares 0.014 - Adj. R2 0.961 - Intercept 0.516 0.031 Freundlich Linear Slope 0.328 0.030

KF 1.430 - n 3.049 -

For the Freundlich ﬁttings, the linear format showed the best correlation, less variability, and lower error values, as shown in Table3. As such, its result was considered against the nonlinear format, where it was observed that KF and n values were 1.430 ppm and 3.049, respectively. The KF value was equivalent to 5.921 10 8 M[48,49]. In addition, chemical adsorption process was expected to be × − dominant on the surface of the chitosan-PEG, since the slope (1/n) < 1 [46]. Polymers 2020, 12, 2586 11 of 17

Polymers 2020, 12, x 11 of 17

Experimental data (a) Experimental data (b) 3.0 2.0 Non-Linear Langmuir fit Linear Langmuir fit Adj. R-Square=0.840 Adj. R-Square=0.917 2.5 1.5

(degree) 2.0 1.0 (per degree)

Δθ Δθ

1.5 Δθ 0.5 1/

1.0 0.0 12345 0.2 0.3 0.4 0.5 0.6 0.7 0.8 1/Acetone concentration (per ppm) Acetone concentration (ppm)

1.2 Experimental data (c) (d) 3.0 Experimental data Non-Linear Freundlich fit Linear Freundlich fit 1.0 Adj. R-Square=0.947 Adj. R-Square=0.961

) 2.5 0.8 (degree)

2.0 ) degree

( 0.6

Δθ θ ( Δ n l 1.5 0.4

1.0 0.2 0123456 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 Acetone concentration (ppm) ln(C) (ppm)

Figure 9. Binding affinity between the single-layer chitosan-PEG-based SPR sensor and various acetone concentrationsFigure 9. Binding fitted affinity to (a) nonlinear between Langmuir,the single-layer (b) linear chitosan-PEG-based Langmuir, (c) nonlinear SPR sensor Freundlich, and various and (d) linearacetone Freundlich concentrations isotherms fitted models. to (a) nonlinear Langmuir, (b) linear Langmuir, (c) nonlinear Freundlich, and (d) linear Freundlich isotherms models. 3.2.6. Detection Mechanism and Selectivity Test of the Single-Layer Chitosan-PEG-Based SPR Acetone Vapor3.2.6. Detection Sensor Mechanism and Selectivity Test of the Single-Layer Chitosan-PEG-Based SPR AcetoneThe Vapor knowledge Sensor of functional groups on the surface of the chitosan-PEG sensing layer is required for theThe prediction knowledge of the of dominantfunctional interaction groups on mechanism the surface and of the the reason chitosan-PEG for a selective sensing detection layer ofis therequired acetone for vapor the prediction [50], and this of the is also dominant accomplished interaction by XPS mechanism characterization. and the Its reason spectra for are a shownselective in Figuredetection 10 .of The the assignment acetone vapor of various[50], and peaks this is is also summarized accomplished in Table by XPS S3. Thecharacterization. presence of the Its carbon,spectra nitrogen,are shown and in Figure oxygen 10. in The XPS assignment scan spectrum of various confirms peaks the is existencesummarized of the in Table chitosan-PEG S3. The presence blend [51 of]. Furthermore,the carbon, nitrogen, the C 1s and scan oxygen of the chitosan-PEGin XPS scan spectr blendum was confirms resolved the to existence the binding of the energies chitosan-PEG (BEs) of 286.69blend [51]. eV (C–OH), Furthermore, 284.90 eVthe (C–NH,C 1s scan C–NH of 2theor chitosan-PEG C=C), 288.35 eVblend (C= O),was 285.31eV resolved (Contamination, to the binding C–Cenergies or C–H), (BEs) andof 286.69 about eV 289 (C–OH), eV (O–C 284.90=O) [eV52]. (C–NH, Furthermore, C–NH2 theor C=C), O1s peak 288.35 was eV resolved (C=O), 285.31eV to three peaks,(Contamination, which include C–C theor C–H), BEs of and 533.13 about (C= O),289 531.49eV (O–C=O) (C–OH), [52]. and Furthermore, 533.53 (C–O) the[52 ].O1s The peakpresence was ofresolved hydroxyl to three (OH) peaks, and C–NH which further include confirms the BEs the of presence533.13 (C=O), of chitosan 531.49 (C–OH), [51,53]. The and N1s 533.53 peak (C–O) was resolved[52]. The topresence two diff erentof hydroxyl peak Bes’ (OH) positions and C–NH at 400.05 further eV andconfirms 402.21 the eV, presence which could of chitosan be attributed [51,53]. to Pyrollic–NThe N1s peak (–NH–) was andresolved Pyridinic–N to two (different=N–), respectively peak Bes’ [51positions]. These at abundant 400.05 eV functional and 402.21 groups eV, wouldwhich playcould a be vital attributed role in the to selectivePyrollic–N acetone (–NH–) vapor and detection.Pyridinic–N (=N–), respectively [51]. These abundant functionalBased groups on the resultwould of play the surfacea vital role characterization, in the selective the acetone interaction vapor between detection. the chitosan-PEG layer and the acetone vapor could be due to multiple mechanisms. But the dominant interaction mechanism was predicted using the adsorption study to be based on chemisorption process. The chemisorption process is described by a two-step process. First, the exposure of the chitosan-PEG sensing layer to air led to the chemisorption of oxygen. This chemisorbed oxygen captured electron from the conduction band of the chitosan-PEG, which consequently produced ionic oxygen species, as shown in Equations (2)–(5). In the second step, when the chitosan-PEG sensing layer was exposed to acetone vapor, it reacted

Polymers 2020, 12, 2586 12 of 17

with the ionic oxygen species, which consequently led to increase in conductivity due to the release of the captured electron back to the conduction band, which in turn altered the refractive index value. This process is described in a simplified form by Equation (6) [54,55]. Conductivity describes how fast an electric charge can pass through a material or medium. A physical field that surrounds the electric charges is called electric field. On the other hand, the ability to allow the passage of an electric field through a material can be described by the parameter of real part dielectric constant [56,57]. The complex refractive index (n) of a medium can be related to its complex dielectric constant (εr) using the solution of Maxwell’s equation, shown in Equation (7) [58]. This indicates that n value increases with increase in εr value. Based on this, it can be concluded that the movement of the captured electron back to the conduction band will increase the dielectric constant value, which will in turn increase the refractive index value. O (gas) O (adsorbed) (2) 2 ↔ 2 O (adsorbed) + e− O −(adsorbed) (3) 2 ↔ 2 O −(adsorbed) + e− 2O−(adsorbed) (4) 2 ↔ 2 O−(adsorbed) + e− O −(adsorbed) (5) ↔ 2 CH COCH (gas) + O − CO (gas) + H O (gas) + 2e− (6) 3 3 → 2 2 n = √εr (7) In addition, the hydrogen bond formation between the hydrogen of the NH group in chitosan-PEG and the oxygen from the CO group of the acetone could act as an electrical bridge for the electron transfer [29]. This would enhance the response of the SPR sensor by producing greater change in Polymersrefractive 2020, 12 index, x value. 12 of 17

Figure 10. XPS spectra of the (a) survey scan, (b) C1s, (c) N1s, and (d) O1s, peaks for the single-layer Figurechitosan-PEG 10. XPS spectra blend thin of the ﬁlm (a) survey scan, (b) C1s, (c) N1s, and (d) O1s, peaks for the single-layer chitosan-PEG blend thin film

Based on the result of the surface characterization, the interaction between the chitosan-PEG layer and the acetone vapor could be due to multiple mechanisms. But the dominant interaction mechanism was predicted using the adsorption study to be based on chemisorption process. The chemisorption process is described by a two-step process. First, the exposure of the chitosan-PEG sensing layer to air led to the chemisorption of oxygen. This chemisorbed oxygen captured electron from the conduction band of the chitosan-PEG, which consequently produced ionic oxygen species, as shown in Equations (2)–(5). In the second step, when the chitosan-PEG sensing layer was exposed to acetone vapor, it reacted with the ionic oxygen species, which consequently led to increase in conductivity due to the release of the captured electron back to the conduction band, which in turn altered the refractive index value. This process is described in a simplified form by Equation (6) [54,55]. Conductivity describes how fast an electric charge can pass through a material or medium. A physical field that surrounds the electric charges is called electric field. On the other hand, the ability to allow the passage of an electric field through a material can be described by the parameter of real part dielectric constant [56,57]. The complex refractive index (n) of a medium can be related to its complex dielectric constant (εr) using the solution of Maxwell’s equation, shown in Equation (7) [58]. This indicates that n value increases with increase in εr value. Based on this, it can be concluded that the movement of the captured electron back to the conduction band will increase the dielectric constant value, which will in turn increase the refractive index value.

O2(gas) ↔ O2(adsorbed) (2)

O2(adsorbed) + e− ↔ O2−(adsorbed) (3)

O2−(adsorbed) + e− ↔ 2O−(adsorbed) (4)

O−(adsorbed) + e− ↔ O2−(adsorbed) (5)

CH3COCH3 (gas) + O2− → CO2 (gas) + H2O (gas) +2e− (6)

Polymers 2020, 12, x 13 of 17

= ε n r (7)

In addition, the hydrogen bond formation between the hydrogen of the NH group in chitosan-PEG and the oxygen from the CO group of the acetone could act as an electrical bridge for the electron transfer [29]. This would enhance the response of the SPR sensor by producing greater

Polymerschange2020 in refractive, 12, 2586 index value. 13 of 17

3.2.7. Selectivity of Chitosan-PEG-Based SPR Sensor to Acetone Vapor 3.2.7. Selectivity of Chitosan-PEG-Based SPR Sensor to Acetone Vapor The cross-sensitivity (selectivity) of the single-layer chitosan-PEG SPR sensor to acetone was confirmedThe cross-sensitivity by investigating (selectivity) and comparing of the single-layerthe response chitosan-PEG of the sensor SPR to sensor water to vapor, acetone 5ppm was conﬁrmedpropanol, by5 ppm investigating methanol, and and comparing 5 ppm ethanol the response with that of the of sensor5 ppm to acetone water vapor, vapor. 5 ppmThe selectivity propanol, 5graph ppm is methanol, shown in andFigure 5 ppm 11. It ethanolwas observed with that that of the 5 maximum ppm acetone SPR vapor. angle Thein air, selectivity vapor (about graph 93% is shownRH), acetone in Figure vapor, 11. Itpropanol was observed vapor, thatmethanol the maximum vapor, and SPR ethanol angle vapor in air, were vapor 41.41, (about 41.95, 93% 44.95, RH), acetone43.95, 42.94, vapor, and propanol 43.22 degrees, vapor, respectively. methanol vapor, The ex andclusion ethanol of the vapor humidity were 41.41,effect made 41.95, the 44.95, response 43.95, 42.94,of 5 ppm and acetone 43.22 degrees, to be about respectively. 33%, 66%, The and exclusion 57% higher of the than humidity that eofﬀ ect5 ppm made propanol, the response 5 ppm of 5methanol, ppm acetone and to5 ppm be about ethanol, 33%, respectively. 66%, and 57% The higher higher than response that of of 5 ppmthe chitosan-PEG propanol, 5 ppm SPR methanol, sensor to andacetone 5 ppm could ethanol, be attributed respectively. to Thethe higherhigher responsenumber ofof the carbon chitosan-PEG atoms and SPR the sensor rateto of acetone evaporation could be[42,59]. attributed The number to the higher of carbon number atoms of carbonand the atoms rate of and evaporation the rate of for evaporation all the analytes [42,59 ].are The presented number ofin carbonTable 4 atoms[42]. It andcould the be rate observed of evaporation that both forthe all acetone the analytes and the are propanol presented shared in Table the same4[ 42 number]. It could of becarbons, observed butthat acetone both showed the acetone higher and response the propanol due sharedto its higher the same rate number of evaporation. of carbons, Furthermore, but acetone showedcomparison higher among response the alcohols due to its (propanol, higher rate ethanol, of evaporation. and methanol) Furthermore, indicates comparison the domination among of thethe alcoholsnumber (propanol,of carbon atoms. ethanol, and methanol) indicates the domination of the number of carbon atoms.

Figure 11. Selectivity of the chitosan-PEG sensing layer to 5 ppm acetone vapor compared to humidity, Figure 11. Selectivity of the chitosan-PEG sensing layer to 5 ppm acetone vapor compared to 5 ppm propanol, 5 ppm methanol, and 5 ppm ethanol vapors. humidity, 5 ppm propanol, 5 ppm methanol, and 5 ppm ethanol vapors. Table 4. Properties of the analytes extracted from a previous work [42]. Table 4. Properties of the analytes extracted from a previous work [42]. Evaporation Rate Hydrocarbon Chemical Formula Carbon Number nEvaporation-butyl acetate Rate= 1.0 Hydrocarbon Chemical formula Carbon number Acetone C3H6O 3n-butyl 14.4acetate=1.0 AcetoneEthanol C 32HH6OO 23 14.4 1.7 Propanol C3H8O 3 1.3 Ethanol C2H6O 2 1.7 Methanol CH4O 1 4.1 Propanol C3H8O 3 1.3 Methanol CH4O 1 4.1 4. Conclusions

The detection of acetone vapor at low concentration using chitosan-PEG-based SPR sensor was investigated. The intention was to explore the possibility of using the SPR sensor in the non-invasive monitoring and screening of diabetes. The surface characterization confirmed the presence of important functional groups such as OH and amine that could lead to a highly sensitive and selective detection of acetone. Furthermore, the results indicated that the sensor could detect the acetone vapor down to 0.96 ppb with sensitivity value of about 0.35 degree/ppm. The achieved LOD is far less than the diabetes threshold (1.8–5 ppm). This confirms the potentiality of the sensor. In addition, the adsorption studies based on the Langmuir and Freundlich isotherm models indicated good affinity of the sensing Polymers 2020, 12, 2586 14 of 17 layer to acetone. Also, the heterogeneity factor (1/n) of <1 predicted the chemisorption process to be the dominant interaction mechanism. These are in addition to the good selectivity against the interfering analytes, linearity, repeatability, and stability. As such, the chitosan-PEG-based SPR sensor could realize a non-invasive sensor for monitoring and screening of diabetes using the acetone vapor from exhaled breath.

Supplementary Materials: The following are available online at http://www.mdpi.com/2073-4360/12/11/2586/s1. Figure S1: Picture of the experimental SPR setup. Table S1: Data for the chitosan-PEG-based SPR sensor. Figure S2: AFM images of glass, gold, and chitosan-PEG surfaces. Figure S3: Thickness of gold thin film deposited at 20 mA, 67s estimated using a (a) surface profiler and (b) surface roughness tester. Figure S4: (a) SPR curves of different layers of the chitosan-PEG-based SPR sensor, (b) SPR angle shift versus the acetone concentration. Figure S5: Blank SPR response. Table S2: Blank sample response, Langmuir and Freundlich adsorption equations (Equations (S1)–(S4)). Table S3: Assignment of the C1s, O1s, N1s, and S2p peaks for the chitosan-PEG thin layer. Author Contributions: Conceptualization, F.U. and J.O.D.; methodology, F.U., A.S., and F.M.; software, F.U. and A.R.S.; validation, J.O.D., F.M., Y.W.F., and Y.A.-H.; formal analysis, F.U., A.A., and T.L.F. investigation, F.U. and Y.A.-H.; resources, J.O.D., A.R.S., and Y.W.F.; data curation, F.U.; writing—original draft preparation, F.U.; writing—review and editing, J.O.D., F.M., T.L.F., Y.W.F., A.S., and A.R.S.; visualization, F.M., A.A., T.L.F., and E.M.M.; supervision, J.O.D., Y.W.F., A.R.S., and F.M.; project administration, J.O.D., E.M.M., and F.M.; funding acquisition, J.O.D., Y.A.-H., and E.M.M. All authors have read and agreed to the published version of the manuscript. Funding: The Deanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah, Saudi Arabia, funded this project, under grant no. (FP-141-42). Acknowledgments: The authors would like to thank the Deanship of Scientific Research (DSR) at King Abdulaziz University, Saudi Arabia, for funding this project; and the Institute of Advanced Technology (ITMA), Universiti Putra Malaysia; Optics lab, University Putra Malaysia; and the Universiti Teknologi PETRONAS, Malaysia, for the provision of the research environment and all the required technical support. Conflicts of Interest: The authors declare no conflict of interest.

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