Jinhyuk Park

We present an adherable temperature sensor on aramid fiber filament coated with reduced graphene oxide (rGO) and poly(diallyldimethylammonium chloride) (PDADMAC) complex. The PDADMAC dispersed in a graphene oxide aqueous solution was dried and reduced to an rGO-PDADMAC complex with laser irradiation. The rGO-PDADMAC sensor was characterized with a scanning electron microscope and Raman spectroscopy. The rGO-PDADMAC sensor showed a negative temperature coefficient resistance change at 40% relative humidity (RH). Furthermore, the sensor successfully detected 58% resistance variation from 25°C to 100°C as the pristine rGO sensor showed 61% resistance variation on a rigid surface. Also, the rGO-PDADMAC sensor demonstrated long-term reliability of 3% sensitivity for 7 days in normal room conditions at 25°C and 40% RH. Additionally, the adherable temperature sensor of the rGO-PDADMAC complex viscous to the porous structure of aramid fiber detected 55% sensitivity from 25°C to 100°C.

The spectroscopic method based on surface-enhanced Raman spectroscopy (SERS) technique combined with chemometric methods was developed for simple, cost-effective, and efficient analysis of chlorpyrifos (CPF) and aldicarb (ALD) pesticide residues in animal feed. Animal feeds free from the pesticides were spiked at different concentrations of CPF (0-20 mg/kg) and aldicarb (0-100 µg/kg). Gold nanoparticles were mixed with sample extract for SERS measurement. A significant spectral difference induced by the presence and different level of CPF and ALD concentration in animal feed was observed between the pesticide spiking groups. Different chemometric models applied on training datasets showed excellent classification rates (100 percent) while the models on external validation dataset exhibited lower correct classification rates (50.0-76.7 percent) with no false-negative error. The selected chemometric models for CPF and ALD quantification also showed a high predictive ability and performance. The developed models displayed no statistical significant difference between model predicted and reference values in the external validation dataset (p < 0.01). The study results indicate that the SERS spectroscopic method could be an effective and efficient analytical tool for pesticide analysis in highly complex animal feed matrices for screening at a point of sampling to improve food and feed safety. https://doi.org/10.21423/jrs-v08lee

Volatile organic compounds (VOCs) emitted from foods and plants are typically analyzed by gas chromatography/mass spectrometry (GC/MS) or electronic-nose (E-nose) analysis. GC/MS is highly sensitive but lacks portability, while E-nose equipment is portable but has a narrow range of analysis. In this study, a Raman-based VOC detection system was developed along with multivariate analysis for spectral differentiation of VOCs. A 5 μL droplet each of four representative VOCs (linalool, cis-3-hexenyl acetate, cis-3-hexen-1-ol, methyl salicylate) was pre-concentrated with Hayesep Q adsorbent in a sealed chamber. After a given collection time (20 and 60 min), Raman spectroscopy was used to measure the VOC eluates from each adsorbent. Two collection times were tested, and single VOCs versus VOC mixtures were compared. Finally, Raman spectral data were processed with baseline correction and normalization and analyzed with unsupervised and supervised learning techniques. After 20 minutes of collection, individual and mixed volatiles showed unique spectral features, and the multivariate techniques produced good discrimination among the VOCs. Raman spectroscopy was also used to measure mixtures containing three VOCs at five different concentrations, and when principle component regression was applied, a concentration–estimation curve with a high R² of 0.953 was generated. This system developed on VOC standards was tested on two types of tea (black and earl grey) to determine the differentiability of tea aromas, and several unique Raman spectra were observed from the tea samples. Therefore, the proposed Raman technique has proven to be effective at fast screening of multiple VOCs given off from foods and plants and is a good candidate for fast and portable applications.

We developed a novel substrate for the collection of volatile organic compounds (VOCs) emitted from either living or dried plant material to be analyzed by surface-enhanced Raman spectroscopy (SERS). We demonstrated that this substrate can be utilized to differentiate emissions from blends of three teas, and to differentiate emissions from healthy cotton plants versus caterpillar-infested cotton plants. The substrate we developed can adsorb VOCs in static headspace sampling environments, and VOCs naturally evaporated from three standards were successfully identified by our SERS substrate, showing its ability to differentiate three VOCs and to detect quantitative differences according to collection times. In addition, volatile profiles from plant materials that were either qualitatively different among three teas or quantitatively different in abundance between healthy and infested cotton plants were confirmed by collections on Super-Q resin for dynamic headspace and solid-phase microextraction for static headspace sampling, respectively, followed by gas chromatography to mass spectrometry. Our results indicate that both qualitative and quantitative differences can also be detected by our SERS substrate although we find that the detection of quantitative differences could be improved.

Surface-enhanced Raman spectroscopy (SERS) has been widely investigated in many applications. However, only little work has been done on using SERS for the detection of volatile organic compounds (VOCs), primarily due to the challenges associated with fabricating SERS substrates with sufficient hotspots for signal enhancement and with the surface interfacially compatible for the VOCs. This study investigated the phase transfer of Ag-nanospheres (AgNSs) from the aqueous phase to the non-aqueous phase by electrostatic interaction induced by cationic surfactants, and the feasibility of the transferred AgNSs as SERS substrates for the determination of methyl salicylate VOC. Results indicated that one of three cationic surfactants, tetraoctylammonium bromide (TOAB) dissolved in organic solvent showed successful phase transfer of the AgNSs confirmed by several characterization analyses. The complex formed by hydrophobic interaction between the transferred AgNSs and Tenax-TA adsorbent polymer was able to be utilized as a SERS substrate, and the volatile of methyl salicylate could be easily determined from SERS measurements at 4 h static volatile collection. Therefore, the proposed new techniques can be effectively employed to areas where many VOCs relevant to food and agriculture need to be analyzed.