Direct Discrimination of Edible Oil Type, Oxidation, and Adulteration by Liquid Interfacial Surface-Enhanced Raman Spectroscopy

Trends in authentication of edible oils using vibrational spectroscopic techniques

The authentication of edible oils has become increasingly important for ensuring product quality, safety, and compliance with regulatory standards. Some prevalent authenticity issues found in edible oils include blending expensive oils with cheaper substitutes or lower-grade oils, incorrect labeling regarding the oil's source or type, and falsely stating the oil's origin. Vibrational spectroscopy techniques, such as infrared (IR) and Raman spectroscopy, have emerged as effective tools for rapidly and non-destructively analyzing edible oils. This review paper offers a comprehensive overview of recent advancements in using vibrational spectroscopy for authenticating edible oils. The fundamental principles underlying vibrational spectroscopy are introduced and chemometric approaches that enhance the accuracy and reliability of edible oil authentication are summarized. Recent research trends highlighted in the review include authenticating newly introduced oils, identifying oils based on their specific origins, adopting handheld/portable spectrometers and hyperspectral imaging, and integrating modern data handling techniques into the use of vibrational spectroscopic techniques for edible oil authentication. Overall, this review provides insights into the current state-of-the-art techniques and prospects for utilizing vibrational spectroscopy in the authentication of edible oils, thereby facilitating quality control and consumer protection in the food industry.

A three-dimensional gold nanoparticles spherical liquid array for SERS sensitive detection of pesticide residues in apple

High-performance plasmonic substrates have recently attracted much research attention. Herein, a three-dimensional gold nanoparticles (AuNPs) spherical liquid array (SLA) with high "hot spots" and tunable nanometer gap by optimizing the proportion of AuNPs colloids over chloroform was synthesized based on a water-oil interfacial self-assembly strategy. The substrate demonstrated excellent surface-enhanced Raman scattering (SERS) performance using tetrathiafulvalene and rhodamine 6G (R6G) as probe molecules. With a simple extraction and soaking pretreatment process, the SLA exhibited high sensitivity for analysing triazophos on apple peels, with a limit of detection (LOD) of 0.005 µg/mL and recovery ranging from 96 to 110 %. Particularly, the chloroform produced an inherent characteristic peak at 665 cm-1, which was used as the internal standard to correct SERS signal fluctuation, leading to an improvement of the corresponding coefficient R2 from 0.97 to 0.99, thus improving the reproducibility. Therefore the SLA substrate possesses the potential for quantitative analysis of food contaminants.

Liquid Interfacial Coassembly of Plasmonic Arrays and Trace Hydrophobic Nanoplastics in Edible Oils for Robust Identification and Classification by Surface-Enhanced Raman Spectroscopy

The ubiquity of micro-/nanoplastics poses a visible threat to the environment, aquatic organisms, and human beings and has become a global concern. Here, we proposed a liquid interface-based strategy using surface-enhanced Raman spectroscopy to coassemble nanoplastics and gold nanoparticles into a dense and homogeneous plasmonic array, thereby enabling the rapid and sensitive detection of trace nanoplastics. In addition, due to the uniqueness of the oil-water immiscible two-phase interface, we achieved ideal results for the detection of nanoplastics in a complex matrix (e.g., aqueous environment and edible oil) with a detection limit of μg/mL. With the aid of the principal component analysis algorithm, the differentiation and identification of multiple nanoplastic components (e.g., polystyrene, polyethylene, and polyethylene terephthalate) in aqueous environments and common hazards (e.g., Bap and Phe) in edible oil were achieved. Therefore, our self-assembled plasmonic arrays are expected to be used for monitoring environmental pollution and food safety.

Lipidomic characteristics of three edible cold-pressed oils by LC/Q-TOF for simple quality and authenticity assurance

Distinguishing oil samples from each other is challenging but it is crucial for ensuring food quality, and for detecting and preventing the possible adulteration of these products. Lipidomic profiling is believed to provide sufficient information to get fit-to-purpose confidence of oil identification as well as to deliver oil-specific lipid features which could be used as targets for routine authenticity testing of camelina, flax, and hemp oil in food control laboratories. Conducted di- and triacylglycerol profiling by LC/Q-TOFMS yielded successful differentiation of the oils. A marker panel consisting of 27 lipids (both DAGs and TAGs) useful for quality verification and authenticity assurance of the oils was established. Moreover, sunflower, rapeseed, and soybean oils were analysed as potential adulterants. We identified 6 lipid markers (DAGs 34:6, 35:2, 40:1, 40:2, 42:2, and TAG 63:1) which can be used for revealing the adulteration of camelina, hemp, and flax seed oils with these oils.

Monitoring the lipid oxidation and fatty acid profile of oil using algorithm-assisted surface-enhanced Raman spectroscopy

Deep-fat frying of food develops lipid oxidation products that deteriorate oil and pose a health risk. This necessitates the development of a rapid and accurate oil quality and safety detection technique. Herein, surface-enhanced Raman spectroscopy (SERS) and sophisticated chemometric techniques were used for rapid and label-free determination of peroxide value (PV) and fatty acid composition of oil in-situ. In the study, plasmon-tuned and biocompatible Ag@Au core-shell nanoparticle-based SERS substrates were used to obtain optimum enhancement despite matrix interference to efficiently detect the oil components. The potent combination of SERS and the Artificial Neural Network (ANN) method could determine the fatty acid profile and PV with upto 99% accuracy. Moreover, the SERS-ANN method could quantify the low level of trans fats, i.e., < 2%, with 97% accuracy. Therefore, the developed algorithm-assisted SERS system enabled the sleek and rapid monitoring and on-site detection of oil oxidation.

Preparation of SERS substrate with 2D silver plate and nano silver sol for plasticizer detection in edible oil

As a widely used industrial additive of plastic products, phthalate ester (PAE) plasticizers can easily migrate into food, threatening human health. In this work, we proposed a rapid, precise, and reliable method to detect PAE plasticizers in edible oils by using surface-enhanced Raman spectroscopy (SERS) technology. A two-dimensional (2D) silver plate synergizing with a nanosilver sol was prepared as a substrate for SERS to detect potassium hydrogen phthalate (PHP), a hydrolysate of a PAE plasticizer. Detection conditions, such as pH values, drying times, and hydrolysate interference, were optimized. The working curve was well fitted with a linear parameter R² of 0.9994, and the minimum detection limit was evaluated as 10^-9 mol/L. Furthermore, the detection accuracy was supported by five edible oil samples. Therefore, using SERS technology to detect PHP is expected to provide an avenue for PAE plasticizer detection in oils and fats, and it features promising potential applications in food safety.

A facile heat-treatment solid phase microextraction method for SERS detection of isocarbophos in tea using a hand-held Raman spectrometer

A facile sensor system based on heat-treatment solid phase microextraction and Surface-Enhanced Raman Scattering (HT-SPME-SERS) was established for in-situ detection of isocarbophos in complex tea matrix. Starting from the action optimization of temperature control unit and air flow control unit, pesticide molecules volatilizing from solution are efficiently captured by substrate and generate real-time SERS signals by a hand-held Raman spectrometer, and the sensor system based on HT-SPME-SERS was finally established. A novel SERS substrate of Cu@rGO@Ag was developed as HT-SPME-SERS material, where reduced graphene oxide (rGO) enriched pesticide molecules by π-π stacking. A superior detection sensitivity brought by the ultra-high enhancement effect of Cu@rGO@Ag substrate was obtained. A good linear relationship between Raman intensity and isocarbophos concentration was obtained and the limit of detection (LOD) was as low as 0.00451 ppm. The detection results obtained from the sensor system have been verified by gas chromatography-mass spectrometer (GC-MS), showing its great application potential for the safety of agricultural products.

Determination of oxidative deterioration in edible oils by high-pressure photoionization time-of-flight mass spectrometry

Since lipid oxidation often causes serious food safety issues worldwide, determination of oil's oxidative deterioration becomes quite significant, which still calls for efficient analytical methods. In this work, high-pressure photoionization time-of-flight mass spectrometry (HPPI-TOFMS) was firstly introduced for rapid detection of oxidative deterioration in edible oils. Through non-targeted qualitative analysis, oxidized oils with various oxidation levels were successfully discriminated for the first time by coupling HPPI-TOFMS with the orthogonal partial least squares discriminant analysis (OPLS-DA). Furthermore, by targeted interpretation of the HPPI-TOFMS mass spectra and the subsequent regression analysis (signal intensities vs TOTOX values), good linear correlations were observed for several predominant VOCs. Those specific VOCs were promising oxidation indicators, which would play important roles as TOTOX to judge the oxidation states of tested samples. The proposed HPPI-TOFMS methodology can be used as an innovative tool for accurate and effective assessment of lipid oxidation in edible oils.

Colorimetric Sensing of the Peroxide Number of Milk Powder Using CsPbBr3 Perovskite Nanocrystals

In this study, a wavelength-shift-based colorimetric sensing approach for the peroxide number of milk powder using CsPbBr₃ perovskite nanocrystals (CsPbBr₃ NCs) has been developed. Through the fat extraction, REDOX reactions and halogen exchange, as well as the optimized experimental conditions, a colorimetric sensing method was established to determine the peroxide number of milk powder samples. The integrated process of milk powder fat extraction and the REDOX process greatly shortened the determination time. This colorimetric method has a good linear correlation in the range of the peroxide number from 0.02 to 1.96 mmol/kg, and the detection limit was found to be 3 μmol/kg. This study further deepens the application prospect of wavelength-shift-based colorimetric sensing using CsPbBr₃ NCs.

Multi-analyte High-Throughput Microplate-SERS Reader with Controllable Liquid Interfacial Arrays

High-throughput surface-enhanced Raman scattering (SERS) reader, especially for liquid sample testing, is of great significance and huge demand in biology, environment, and other analytical fields. Inspired by the principle of microplate reader, herein, we developed a microplate-SERS reader for semiautomatic and high-throughput assays by virtue of three-dimensional liquid interfacial arrays (LIAs). For the first time, the formation of LIA in oil-in-water state, water-in-oil state, and two-dimensional plane state is realized by operating the hydrophilicity (contact angle) of the container. Through the force analysis of LIA, the effect of organic (O) phase density on the relative position of LIA was quantified. In addition, the optimized reader offers fast and continuous semiautomatic detection of 12 samples below 10 min with great signal reproducibility (calibration with the characteristic peak of O phase as the internal standard). The isolated wells in the microplate prevent analyte cross talk, allowing accurate quantification of each sample. Multiplex analysis capability highlights that this reader has the ability of rapid identification and quantification of samples containing various analytes and concentrations. The results demonstrate high-resolution dual and triple analyte detection with fully preserved signal and Raman features of individual analytes in a mixture, which implies that it also has excellent anticounterfeiting applications. This microplate-SERS reader combines the superior advantages of the LIA, microplate, and SERS techniques to retrieve the molecular vibrational fingerprints of various chemicals in complex media.

DNAzyme signal amplification based on Au@Ag core-shell nanorods for highly sensitive SERS sensing miRNA-21

Here, we developed a surface-enhanced Raman scattering (SERS) sensor based on functionalized Au@Ag core-shell nanorods (Au@Ag NRs) and cascade DNAzyme amplifier (CSA) for sensitive and accurate determination of microRNA-21 (miRNA-21). The as-prepared SERS nanoprobes were composed of a thiol-modification hairpin probe (HP2)-functionalized Au@Ag NRs and hairpin DNAzyme (HP1-Dz). Compared with original gold nanorods, the silver shell caused an enhancement of plasmonic properties, resulting in a significant enhancement of Raman signals. In the presence of target miRNAs, the hairpin construction of HP1-Dz changed due to DNA/RNA hybridization; subsequently, the DNAzyme-catalyzed cleaving process changed, and the Raman signals of the SERS nanoprobes gradually "turned off" with time elapse because of the dissociation of the Raman reporter from the surface of Au@Ag NRs. Hence, based on this principle, the proposed SERS sensor exhibited good linearity in the range 0.5 fM to 10 nM for miRNA-21 detection with a detection limit (LOD) of 0.5 fM. The proposed SERS platform has potential application in quantitative and precise detection of miRNA-21 in human serum.

Analytical and Structural Tools of Lipid Hydroperoxides: Present State and Future Perspectives

Mono- and polyunsaturated lipids are particularly susceptible to peroxidation, which results in the formation of lipid hydroperoxides (LOOHs) as primary nonradical-reaction products. LOOHs may undergo degradation to various products that have been implicated in vital biological reactions, and thus in the pathogenesis of various diseases. The structure elucidation and qualitative and quantitative analysis of lipid hydroperoxides are therefore of great importance. The objectives of the present review are to provide a critical analysis of various methods that have been widely applied, and more specifically on volumetric methods, applications of UV-visible, infrared, Raman/surface-enhanced Raman, fluorescence and chemiluminescence spectroscopies, chromatographic methods, hyphenated MS techniques, NMR and chromatographic methods, NMR spectroscopy in mixture analysis, structural investigations based on quantum chemical calculations of NMR parameters, applications in living cells, and metabolomics. Emphasis will be given to analytical and structural methods that can contribute significantly to the molecular basis of the chemical process involved in the formation of lipid hydroperoxides without the need for the isolation of the individual components. Furthermore, future developments in the field will be discussed.

Advanced process analytical tools for identification of adulterants in edible oils - A review

This review summarizes the use of spectroscopic processes-based analytical tools coupled with chemometric techniques for the identification of adulterants in edible oil. Investigational approaches of process analytical tools such asspectroscopy techniques, nuclear magnetic resonance (NMR), hyperspectral imaging (HSI), e-tongue and e-nose combined with chemometrics were used to monitor quality of edible oils. Owing to the variety and intricacy of edible oil properties along with the alterations in attributes of the PAT tools, the reliability of the tool used and the operating factors are the crucial components which require attention to enhance the efficiency in identification of adulterants. The combination of process analytical tools with chemometrics offers a robust technique with immense chemotaxonomic potential. These involves identification of adulterants, quality control, geographical origin evaluation, process evaluation, and product categorization.

Mechanism, indexes, methods, challenges, and perspectives of edible oil oxidation analysis

Edible oils are indispensable food components, because they are used for cooking or frying. However, during processing, transport, storage, and consumption, edible oils are susceptible to oxidation, during which various primary and secondary oxidative products are generated. These products may reduce the nutritional value and safety of edible oils and even harm human health. Therefore, analyzing the oxidation of edible oil is essential to ensure the quality and safety of oil. Oxidation is a complex process with various oxidative products, and the content of these products can be evaluated by corresponding indexes. According to the structure and properties of the oxidative products, analytical methods have been employed to quantify these products to analyze the oxidation of oil. Combined with proper chemometric analytical methods, qualitative identification has been performed to discriminate oxidized and nonoxidized oils. Oxidative products are complex and diverse. Thus, proper indexes and analytical methods should be selected depending on specific research objectives. Expanding the mechanism of the correspondence between oxidative products and analytical methods is crucial. The underlying mechanism, conventional indexes, and applications of analytical methods are summarized in this review. The challenges and perspectives for future applications of several methods in determining oxidation are also discussed. This review may serve as a reference in the selection, establishment, and improvement of methods for analyzing the oxidation of edible oil. HighlightsThe mechanism of edible oil oxidation analysis was elaborated.Conventional oxidation indexes and their limited values were discussed.Analytical methods for the determination of oxidative products and qualitative identification of oxidized and non-oxidized oils were reviewed.

The application of machine-learning and Raman spectroscopy for the rapid detection of edible oils type and adulteration

Raman spectroscopy is an emerging technique for the rapid detection of oil qualities. But the spectral analysis is time-consuming and low-throughput, which has limited the broad adoption. To address this issue, nine supervised machine learning (ML) algorithms were integrated into a Raman spectroscopy protocol for achieving the rapid analysis. Raman spectra were obtained for ten commercial edible oils from a variety of brands and the resulting spectral dataset was analyzed with supervised ML algorithms and compared against a principal component analysis (PCA) model. A ML-derived model obtained an accuracy of 96.7% in detecting oil type and an adulteration prediction of 0.984 (R²). Several ML algorithms also were superior than PCA in classifying edible oils based on fatty acid compositions by gas chromatography, with a faster readout and 100% accuracy. This study provided an exemplar for combining conventional Raman spectroscopy or gas chromatography with ML for the rapid food analysis.

Magnetically Enhanced Liquid SERS for Ultrasensitive Analysis of Bacterial and SARS-CoV-2 Biomarkers

In this work, it is shown that surface-enhanced Raman scattering (SERS) measurements can be performed using liquid platforms to perform bioanalysis at sub-pM concentrations. Using magnetic enrichment with gold-coated magnetic nanoparticles, the high sensitivity was verified with nucleic acid and protein targets. The former was performed with a DNA fragment associated with the bacteria Staphylococcus aureus, and the latter using IgG antibody, a biomarker for COVID-19 screening. It is anticipated that this work will inspire studies on ultrasensitive SERS analyzers suitable for large-scale applications, which is particularly important for in vitro diagnostics and environmental studies.

Liquid-liquid interfacial self-assembled triangular Ag nanoplate-based high-density and ordered SERS-active arrays for the sensitive detection of dibutyl phthalate (DBP) in edible oils

DBP, one of the phthalic acid esters (PAEs), is known as an endocrine disruptor and is toxic to humans in abnormal concentrations. Here, a high-density and ordered SERS substrate based on the self-assembly of triangular Ag nanoplate (TAgNP) arrays is developed for DBP detection. Benefiting from the ordered arrangement and sharp corners of TAgNPS, the arrays can provide sufficient and uniform hotspots for reproducible and highly active SERS effects. Using Rhodamine 6G (R6G) as a reporter molecule, the SERS enhancement factor (EF) of the TAgNP arrays was found to be as high as 1.2 × 107 and the relative standard deviation was 6.56%. As a trial for practical applications, the TAgNP array substrates were used for the detection of dibutyl phthalate (DBP) in edible oils. In this assay, edible oil samples were added to hexane as an organic phase for the formation of the TAgNP arrays, which caused DBP to be loaded at hotspots. DBP in edible oils could be identified at concentrations as low as 10-7 M. This SERS substrate based on the TAgNP arrays has great potential applications in the high sensitivity and reproducible detection of contaminants in food.

Application of Raman spectroscopy in the rapid detection of waste cooking oil

Raman spectra were used to distinguish waste cooking oil from edible vegetable oils. Signals at 869, 969, 1302 and 1080 cm^-1 were found to be crucial to distinguish waste cooking oil from five edible oils using PCA. When waste cooking oil was added to soybean or olive oil, PCA could separate adulterated and pure oils, when the adulteration proportions reached 10% and 20%, respectively. Peaks at 969 (R² > 0.951), 1267 (R² = 0.987) and 1302 (R² > 0.984) cm^-1 responded linearly to adulteration. Heating assays and ¹H NMR analysis revealed that differences between the Raman spectra of waste cooking oil and edible oils at 969 and 1267 cm^-1 were directly related to heat treatment. This work highlights the potential for Raman spectroscopy to detect waste cooking oil.

Self-assembly of colloidal nanoparticles into 2D arrays at water-oil interfaces: rational construction of stable SERS substrates with accessible enhancing surfaces and tailored plasmonic response

Self-assembly at water-oil interfaces has been shown to be a cheap, convenient and efficient route to obtain densely packed layers of plasmonic nanoparticles which have small interparticle distances. This creates highly plasmonically active materials that can be used to give strong SERS enhancement and whose structure means that they are well suited to creating the highly stable, reproducible and uniform substrates that are needed to allow routine and accurate quantitative SERS measurements. A variety of methods have been developed to induce nanoparticle self-assembly at water-oil interfaces, fine tune the surface chemistry and adjust the position of the nanoparticles at the interface but only some of these are compatible with eventual use in SERS, where it is important that target molecules can access the active surface unimpeded. Similarly, it is useful to transform liquid plasmonic arrays into easy-to-handle free-standing solid films but these can only be used as solid SERS substrates if the process leaves the surface nanoparticles exposed. Here, we review the progress made in these research areas and discuss how these developments may lead towards achieving rational construction of tailored SERS substrates for sensitive and quantitative SERS analysis.

Quantitative determination of peroxide value of edible oil by algorithm-assisted liquid interfacial surface enhanced Raman spectroscopy

Edible oil is an indispensable food in daily life but early detection of its lipid oxidation is difficult. Developing new, rapid and accurate screening technique is urgently needed for oil quality control. Here we developed a surface-enhanced Raman spectroscopy analyzer based on plasmonic metal liquid-like platform (PML-SERS), which could directly analyze the oil sample in ca. 3 min. This analyzer has the ability and sensitivity to identify fingerprint peak changes. Moreover, the relative Raman intensity, I_1265/1436, has a good correlation with peroxide value (POV), which is used for quantitative detection. The fitting model combined with principal component analysis (PCA) realized rapid spectral recognition for determining POV in edible oil oxidation. The relative deviation between the POV measured by PML-SERS and the national standard method (NSM) was less than 10%. Our platform provided a practical solution for ultra-sensitive and fast analysis of POV in oil oxidation.

Surface-Enhanced Raman Spectroscopy for Rapid Screening of Cinnamon Essential Oils

Cinnamon essential oil is used in food flavoring, food preservation, and for complementary medicine. The most common types of cinnamon used in essential oils are true cinnamon (Cinnamomum verum) and cassia cinnamon (Cinnamomum cassia). True cinnamon is commonly adulterated with cassia cinnamon because it is cheaper. However, cassia cinnamon contains higher concentrations of coumarin which has been shown to have adverse health effects. There is a need to develop simple, nondestructive, rapid screening methods for quality control and food authentication and to identify adulteration of cinnamon essential oil. Currently, the most common methods to screen for coumarin in cinnamon include high-performance liquid chromatography (HPLC) and gas chromatography (GC). However, these methods require time-consuming sample preparation and detection. Vibrational spectroscopy methods are emerging as a promising alternative for rapid, nondestructive screening for food safety applications. In this study, a rapid screening method has been developed to examine cinnamon essential oils using surface-enhanced Raman spectroscopy (SERS). The experimental spectra were compared to theoretical calculations using the DFT method BP86/6-311++G(d,p) basis set. The limit of detection of coumarin was determined to be 1 × 10^-6 M or 1.46 mg/L using SERS with colloid paste substrates. Furthermore, 1:16 dilutions of cinnamaldehyde and 1:8 dilutions of eugenol were detected using SERS which can help determine if the cinnamon essential oil was made from bark or from leaves. Seven commercially available cinnamon essential oils were also analyzed and compared to reference solutions. SERS was able to discriminate between essential oils primarily composed of cinnamaldehyde and those composed of eugenol. Furthermore, the SERS method detected peaks that are attributed to coumarin in two of the commercially available samples. To date, this is the first time SERS has been used to rapidly screen cinnamon essential oils.

Enzyme-Assist-Interference-Free Strategy for Raman Selective Determination of Sialic Acid

Abnormal physiological levels of sialic acid (SA) could be used to diagnosis cancer progression stages. In this work, we describe an enzyme-assist-interference-free strategy for Raman selective determination of SA in serum. First, we assemble gold nanoparticles (Au NPs) onto the indium tin oxide glass (ITO) to construct an ITO/Au two-dimension substrate. Through modification of 4-mercaptoboric acid (4-MPBA) onto the surface of ITO/Au, the SA response plate is prepared due to the reversible esterification bond. In this strategy, a sandwich structure is rationally designed as ITO/Au/4-MPBA/SA/4-MPBA/Au to enhance the Raman scattering. The Raman detection linear concentration of SA ranged from 2.5 × 10^-7 to 1.5 × 10^-6 M, and a limit of detection about 1.2 × 10^-7 M could be achieved. Considering the presence of glucose (Glu) in physiological fluid, we introduce glucose oxidase to remove the interference from Glu and realize the accurate determination of SA. The proposed novel Raman rapid method provides an ultrasensitive and interference-free protocol for the early diagnosis of cancer.

Contactless and Simultaneous Measurement of Water and Acid Contaminations in Oil Using a Flexible Microstrip Sensor

The assessment of the petroleum product quality often involves multiple indicators, among which water content and acid value are two major parameters. The complexity of an oil sample and the narrow space in pipeline transport make it difficult to monitor the oil quality in real-time. Considering the practical requirements, a new type of flexible microstrip sensor is proposed in this work. The shape and line width of the microstrip sensor are studied and optimized by theory and experiments. The proposed square spiral-based microstrip sensor has good water content detection resolution at high frequencies with less acid interference, and it can determine the acid value in the low-frequency band. The sensor surface is further passivated, protecting it from direct contact with the oil sample to enhance the electrochemical robustness, and still achieves good detection linearity and high sensitivity. After encapsulation on a flexible substrate, the proposed microstrip sensor realized the non-contact determination of the water content and acid value of oil at the same time, which is only a few millimeters in size and can conform to various tubing wall shapes. Due to the fact that the manufacture of the sensor is CMOS-compatible, we expect it to be readily applied to many other miniaturized chemical-sensing applications.