Raman Spectroscopy Research Articles

Magnetically-assembled multifunctional Fe3O4@SiO2@Au particles for SERS detection of low-concentration dye molecules

Abstract Surface-enhanced Raman scattering (SERS) is a sensitive spectroscopic method to detect low concentration-low volume analytes. Owing to this, there has been a rising interest in developing improved as well as novel nanostructured substrates for SERS applications. For SERS applications, it is desirable to have large-scale assemblies of such nanostructures that can sustain multiple electromagnetic ‘hotspots’ for improved sensitivity. In this work, we use magnetic-field aided large-scale assembly of multifunctional magnetic-plasmonic particles to generate a large area SERS substrate. The particles, composed of a Fe3O4 core with a thin silica coating followed by Au nanoparticles (Fe3O4@SiO2@Au), were synthesized by simple chemical methods. The multifunctional particles were characterized using powder x-ray diffraction, transmission electron microscopy, Raman spectroscopy, and SQUID magnetometer. Magnetic assembly of the composite particles, carried out using a bi-electromagnet setup, was used for SERS detection of organic dyes such as rhodamine B and methylene blue. Using this scheme, it was possible to detect ultra-low concentrations (up to 1fM) of the dye molecules. This method is promising for applications such as chemical sensors, biomolecular detection, cancer detection, and hyperthermia treatment, forensic investigations, and drug delivery.

Construction of chalcopyrite surface with multiple copper sites by using additional copper ions

It is found that copper ions can significantly multiply the copper sites on chalcopyrite surface, which is because of the modification of copper ions on chalcopyrite surfaces. In this study, the mechanism underlying the modification of copper ions on chalcopyrite surfaces was thoroughly investigated by using Energy dispersive Spectrometer, X-ray photoelectron spectroscopy, Cyclic voltammetry, Raman spectroscopy, Density functional theory calculation and Molecular dynamics simulation. The findings indicate that copper ions facilitate the dissolution of iron, leading to the appearance of numerous S species on chalcopyrite surface. Cu(II) added into the system can be reduced to Cu(I) by Fe(II) on chalcopyrite surface, and the resultant Cu(I) ions form stable Cu-S complexes with the S species. The Cu(I)-S complexes on chalcopyrite surface can provide more copper sites for other reagent adsorption during flotation. The pre-modification of chalcopyrite with copper ions significantly enhances the efficiency of reagent adsorption, thereby reducing the dosage of reagent required for chalcopyrite depression.

Electrifying energy storage by investigating the electrochemical behavior of CoCr2O4/graphene-oxide nanocomposite as supercapacitor high performance electrode material

This study reports novel three-step electrochemical fabrication of CoCr2O4/graphene-oxide nanocomposite on glassy carbon electrode including sequential synthesis of graphene-oxide using modified Hummer's method, CoCr2O4 nanoparticles using sol-gel method and the cost-effective co-precipitation technique for nanocomposite formation. The resulting nanocomposite was subjected to comprehensive analytical and morphological analysis. X-ray diffractometry (XRD) confirms nanocomposite formation with reduced average crystallite size value of 26.9 nm whereas SEM indicates spherical grains existence within nanocomposite. Energy-dispersive X-ray spectrometry (EDS) confirms no impurity peak existence whereas Raman spectroscopy clearly indicated D and G band existence at 1345 and 1587 cm−1 respectively. Photoluminescent spectra reveals decreasing trend in band gap value about 3.49 eV. The electrochemical properties of CoCr2O4/graphene-oxide nanocomposite electrode explored, showcasing remarkable capacitance with a surface area of merely 0.068 cm2, 574.8 F/g specific capacitance in alkaline 1M KOH and 488.6 F/g specific capacitance in acidic 0.1M H2SO4 electrolyte. Moreover, synthesized nanocomposite demonstrates remarkable electrochemical stability resulting capacitance retention about 95 % after 100 cycles in 1M KOH electrolyte. GCD analysis reveals impressive power and energy density values of 2489 W/kg and 14.88 Wh/kg respectively. These outstanding properties make the nanocomposite an attractive material for next-generation supercapacitors and energy storage solutions.

Vibrational Markers of a Model Circulating Metastatic Cells LLC-R9

Metastasis in oncological diseases remains one of the main reasons for negative prognosis regarding treatment. Any new data on the biophysical and biochemical characteristics of circulating metastatic cells will help to develop a concept for antimetastatic therapy. In this study, we found a number of differences in the spectroscopic and morphological features of circulating metastatic cells. FT-IR and Raman spectra cultivated by adhesive and de-adhesive methods (with the latter used as a model for metastatic cells) have shown spectroscopic features, namely in FT-IR spectra in the region of CH stretching vibrations, which are associated with structural rearrangements in the cell membrane, as well as changes in the intensity and position of the PO2− group vibration bands correlated with proliferative activity. The spectral features in the regions of OH stretching and Amide I vibrations as well as other spectral markers of the metastatic cells grown under different cultivation conditions were derived. Raman spectra showed a redistribution of the amino acid Tyr/Trp (tryptophan to tyrosine) ratio and in Tyr doublet intensity in the region of 500–900 cm−1, as well as varying glycogen levels in different cells. The spectroscopic markers are in accordance with biochemical data. CARS and confocal optical microscopy were applied to determine the state of the cells and the F-actin expression level, which turned out to be higher for adhesive cells in comparison with de-adhesive cells. The shape and the morphological properties of the cells differ drastically. The correlation of vibrational markers with biochemical data and the cytofluorometric method was discussed.

Insights into the interactions between cellulose and hemicellulose during pyrolysis for optimizing the properties of biochar as a potential energy vector

Cellulose and hemicellulose, the main components of biomass, undergo noticeable interactions during biomass pyrolysis. In this study, biochar was produced by the co-pyrolysis of cellulose and hemicellulose. Three co-pyrolysis parameters, namely, pyrolysis temperature (400–800 °C), residence time (5–30 min), and percentage of cellulose (0–100 %), were investigated to optimize the properties of biochar, including the application of response surface methodology in the experimental study. The analysis revealed that co-pyrolysis interactions could improve the biochar yield by up to 41.37 % (567.74 °C, 19.52 min, 50 % cellulose percentage). The co-pyrolysis interactions specifically enhanced the fixed carbon content, elemental carbon content, and higher heating value of the biochar, with the most significant enhancements being 0.87 %, 3.60 %, and 3.85 %, respectively, while simultaneously decreasing the volatile content, [H]/[C] ratio, and [O]/[C] ratio of the biochar, with the most significant reductions of −9.30 %, −10.81 %, and −26.71 %. Based on the observed decrease in the intensity ratio of the D-band and G-band of biochar in the Raman spectra, greater co-pyrolysis interactions increased the graphitization degree of the biochar. The analysis of X-ray photoelectron spectroscopy (XPS) investigations revealed that the interactions enhanced the contents of the C-C, C-O/C-O-C, aromatic, and OH functionalities while reducing the number of COO-, COOH, and CO functional groups. The results of this work indicate that the co-pyrolysis interaction between cellulose and hemicellulose contributes to optimizing the properties of biochar as a potential energy vector.

SERS-AI Based Detection and Bioanalysis of Malodorous Components in Kitchen Waste.

The prevention and control of odor gas generated from kitchen waste are significant missions in research on environmental pollution. Because of the high complexity and variability of kitchen waste, the development of a suitable technique with high sensitivity for the accurate detection of odor gas is an urgent and core task in this frontier field. Here, a technique combining surface-enhanced Raman spectroscopy (SERS) and artificial intelligence (AI) is explored for detecting malodorous components in the leachate of kitchen waste. Initially, 1706 SERS spectra were collected from synthetic kitchen waste under various fermentation parameters. Several AI algorithms were used to classify three levels of odor intensity based on SERS spectra, among which the Random Forest Classifier algorithm model showed a high prediction accuracy of 86.5%. Then, by integrating Raman data, the AI algorithm model identified hydrogen sulfide (H2S) and ammonia (NH3) as the dominant malodorous components in the odor gas. Finally, the structural characteristics of the microbial communities are investigated. With the help of Raman's intensities of malodorous components, many more insights into microorganisms in the fermentation process are revealed, which has important research value in the prevention and controlling of odor gas generated from kitchen waste. Furthermore, the microbial metabolic pathways of sulfur and nitrogen are discussed here. This SERS-AI-based novel technique not only has a broad potential for odor pollution but also could be applied to another complicated biochemical system with functional bacteria.

Platform for Aldehyde and Ketone Quantitation Using Surface-Enhanced Raman Spectroscopy.

Colorimetric methods for aldehyde and ketone analyses are plagued by interferences. Each aldehyde or ketone generates a blue color, but with a different reaction coefficient. It is, therefore, not possible to differentiate these compounds from a single test. By using surface-enhanced Raman spectroscopy, we demonstrate unique fingerprints for each reaction product, enabling aldehyde and ketone speciation. With the further addition of an isotopologue internal standard, we demonstrate aldehyde and ketone quantification at levels lower than those possible with colorimetric techniques. This method paves the way for a powerful and practical tool for analyzing these crucial chemical building blocks.

Study of morphology, phase composition, optical properties, and thermal stability of hydrothermal zirconium dioxide synthesized at low temperatures.

Oxide nanoparticles exhibit unique features such as high surface area, enhanced catalytic activity, and tunable optical and electrical properties, making them valuable to various industry applications as well as for the development of new research projects. Nowadays, ZrO2 nanoparticles are widely used as catalysts and precursors in ceramic technology. Hydrothermal synthesis with metal salts is one of the most common methods for producing stable tetragonal-phase zirconium dioxide nanoparticles. However, hydrothermal synthesis requires relatively high process temperatures (160-200°C) and the use of advanced heat-resistant autoclaves capable of maintaining high pressure. This paper investigates how different precursors (ZrOCl₂·8H₂O and ZrO(NO₃)₂·2H₂O) and synthesis temperatures (110-160°C) affect the phase composition, optical properties, size, and shape of ZrO₂ nanoparticles produced by hydrothermal synthesis without calcination. In addition, the effect of temperature exposure in the range of 100-1000°C on the phase stability of the synthesized nanoparticles was studied. X-ray diffraction and Raman spectroscopy techniques were used to determine the structure and phase composition, while the optical properties were examined through the analysis of transmission and absorption spectra in the visible and UV ranges. It was found that the obtained particles at synthesis temperatures of 110-130°C have predominantly cubic c-ZrO2 phase, which changes to monoclinic phase when heated above 500°C. Analysis of visible and UV spectroscopy data reveals that the experimental samples have pronounced absorption in the middle UV range (200-260nm) and have an energy band gap Eg varying from 4.8 to 5.1eV. The hydrothermal powders synthesized in this study can be used as absorbers in the mid-UV range and as reinforcing additives in the preparation of technical ceramics.

Cooperative Active Sites on Ag2Pt3TiS6 for Enhanced Low-Temperature Ammonia Fuel Cell Electrocatalysis.

Ammonia has attracted considerable interest as a hydrogen carrier that can help decarbonize global energy networks. Key to realizing this is the development of low temperature ammonia fuel cells for the on-demand generation of electricity. However, the efficiency of such systems is significantly impaired by the sluggish ammonia oxidation reaction (AOR) and oxygen reduction reaction (ORR). Here, we report the design of a bifunctional Ag2Pt3TiS6 electrocatalyst that facilitates both reactions at mass activities exceeding that of commercial Pt/C. Through comprehensive density functional theory calculations, we identify that active site motifs composed of Pt and Ti atoms work cooperatively to catalyze ORR and AOR. Notably, in situ shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS) experiments indicate a decreased propensity for *NOx formation and hence an increased resistance toward catalyst poisoning for AOR. Employing Ag2Pt3TiS6 as both the cathode and anode, we constructed a low temperature ammonia fuel cell with a high peak power density of 8.71 mW cm-2 and low Pt loading of 0.45 mg cm-2. Our findings demonstrate a pathway towards the rational design of effective electrocatalysts with multi-element active sites that work cooperatively.

Unmixing inducing polymerization of a sodium-molybdenum borosilicate network

Glass network polymerization critically influences rheological behavior and with it the kinetics and dynamics of nuclear waste immobilization. Molybdenum-bearing borosilicate melts may undergo unmixing and rheological changes, which is dominantly controlled by the associated chemical modifications of the melt network. Here, we obtain in-situ (500–940 °C) Raman spectra to probe structural changes of a sodium-molybdenum borosilicate melt undergoing unmixing. The extraction of alkali and molybdenum to form droplets induces polymerization of the residual borosilicate network. Conversely, the opposite phenomenon is observed during droplet re-dissolution. This work provides new insights into the polymerization of a molybdenum-bearing borosilicate composed of two composition sets due to a miscibility gap and has direct contributions for the immobilization of nuclear wastes.

Efficient generation of multi-order Raman radiation in aqueous solutions derived from -CH2 and -NH2 vibrations via cascaded four-wave mixing and Stokes processes.

Multiple coherent radiations are achieved in a water-3-aminopropanol (3AP) mixed solution through cascaded four-wave mixing (C-FWM) and cascaded Stokes (C-Stokes) processes, both driven by stimulated Raman scattering (SRS) in this work. The O-H vibration peak from water is replaced by the emergence of the -NH2 symmetric stretching Raman peaks from 3AP, with intensity approaching that of the -CH2 symmetric stretching peak. The dual-wavelength SRS signals for the -NH2 and -CH2 stretching vibrations have a relatively small frequency interval of about 400 cm-1 (16 nm). By varying the 3AP concentration and pump energy, these two peaks from 3AP act as new pump sources, enabling the successful generation of up to 16th-order Stokes and 5th-order anti-Stokes radiation through C-FWM and C-Stokes processes. The resulting spectrum spans a broad wavenumber range from -3318 to 6629 cm-1 (452 to 822 nm), offering a new approach for broadband coherent light sources and multi-order Raman spectra in liquid media.

Multimodal separation and cross fusion network based on Raman spectroscopy and FTIR spectroscopy for diagnosis of thyroid malignant tumor metastasis

The diagnosis of cervical lymph node metastasis from thyroid cancer is an essential stage in the progression of thyroid cancer. The metastasis of cervical lymph nodes directly affects the prognosis and survival rate of patients. Therefore, timely and early diagnosis is crucial for effective treatment and can significantly improve patients’ survival rate and quality of life. Traditional diagnostic methods, such as ultrasonography and radionuclide scanning, have limitations, such as complex operations and high missed diagnosis rates. Raman spectroscopy and FTIR spectroscopy can well reflect the molecular information of samples, have characteristics such as sensitivity and specificity, and are simple to operate. They have been widely used in clinical research in recent years. With the development of intelligent medical diagnosis technology, medical data shows a multi-modal trend. Compared with single-modal data, multi-modal data fusion can achieve complementary information, provide more comprehensive and valuable diagnostic information, significantly enhance the richness of data features, and improve the modeling effect of the model, helping to achieve better results. Accurate disease diagnosis. Existing research mostly uses cascade processing, ignoring the important correlations between multi-modal data, and at the same time not making full use of the intra-modal relationships that are also beneficial to prediction. We developed a new multi-modal separation cross-fusion network (MSCNet) based on deep learning technology. This network fully captures the complementary information between and within modalities through the feature separation module and feature cross-fusion module and effectively integrates Raman spectrum and FTIR spectrum data to diagnose thyroid cancer cervical lymph node metastasis accurately. The test results on the serum vibrational spectrum data set of 99 cases of cervical lymph node metastasis showed that the accuracy and AUC of a single Raman spectrum reached 63.63% and 63.78% respectively, and the accuracy and AUC of a single FTIR spectrum reached 95.84% respectively and 96%. The accuracy and AUC of Raman spectroscopy combined with FTIR spectroscopy reached 97.95% and 98% respectively, which is better than existing diagnostic technology. The omics correlation verification obtained correlation pairs of 5 Raman frequency shifts and 84 infrared spectral bands. This study provides new ideas and methods for the early diagnosis of cervical lymph node metastasis of thyroid cancer.

Synthesis and Characterization of New Organoammonium, Thiazolium, and Pyridinium Triiodide Salts: Crystal Structures, Polymorphism, and Thermal Stability

Triiodide salts are of interest for a variety of applications, including but not limited to electrochemical and photochemical devices, as antimicrobials and disinfectants, in supramolecular chemistry and crystal engineering, and in ionic liquids and deep eutectic solvents. Our work has focused on the design of salt–solvate cocrystals and deep eutectic solvents in which the triiodide anion interacts as a halogen bond acceptor with organoiodine molecules. To understand structure–property relationships in these hybrid materials, it is essential to have benchmark structural and physical data for the parent triiodide salt component. Herein, we report the structure and thermal properties of eight new triiodide salts, three of which exhibit polymorphism: tetrapentylammonium triiodide (1a and 1b), tetrahexylammonium triiodide (2), trimethylphenylammonium triiodide (3), trimethylbenzylammonium triiodide (4), triethylbenzylammonium triiodide (5), tri-n-butylbenzylammonium triiodide (6), 3-methylbenzothizolium triiodide (7a and 7b), and 2-chloro-1-methylpyridinium triiodide (8a and 8b). The structural features of the triiodide anion, Raman spectroscopic analysis, and melting and thermal decomposition behavior of the salts, as well as a computational analysis of the polymorphs, are discussed. The polymorphic pairs here are distinguished by symmetric versus asymmetric triiodide anions, as well as different packing patterns. Computational analyses revealed more subtle differences in their isosurface plots. Importantly, this study provides reference data for these new triiodide salts for comparison to hybrid cocrystals and deep eutectic solvents formed from their combination with various organoiodines.

Comparative Study of Surface Modification Techniques for Enhancing Biocompatibility of Ti-6Al-4V Alloy in Dental Implants

Comparative Study of Surface Modification Techniques for Enhancing Biocompatibility of Ti-6Al-4V Alloy in Dental Implants

Benchmarking the integration of hexagonal boron nitride crystals and thin films into graphene-based van der Waals heterostructures

Abstract We present a benchmarking protocol that combines the characterization of boron nitride (BN) crystals and films with the evaluation of the electronic properties of graphene on these substrates. Our study includes hBN crystals grown under different conditions (atmospheric pressure high temperature, high pressure high temperature, pressure controlled furnace) and scalable BN films deposited by either chemical or physical vapor deposition (CVD or PVD). We explore the complete process from boron nitride growth, over its optical characterization by time-resolved cathodoluminescence (TRCL), to the optical and electronic characterization of graphene by Raman spectroscopy after encapsulation and Hall bar processing. Within our benchmarking protocol we achieve a homogeneous electronic performance within each Hall bar device through a fast and reproducible processing routine. We find that a free exciton lifetime of 1 ns measured on as-grown hBN crystals by TRCL is sufficient to achieve high graphene room temperature charge carrier mobilities of 80,000 cm2/(Vs) at a carrier density of |n| = 1×1012 cm−2, while respective exciton lifetimes around 100 ps yield mobilities up to 30,000 cm2/(Vs). For scalable PVD-grown BN films, we measure carrier mobilities exceeding 10,000 cm2/(Vs) which correlates with a graphene Raman 2D peak linewidth of 22 cm−1. Our work highlights the importance of the Raman 2D linewidth of graphene as a critical metric that effectively assesses the interface quality (i.e. surface roughness) to the BN substrate, which directly affects the charge carrier mobility of graphene. Graphene 2D linewidth analysis is suitable for all BN substrates and is particularly advantageous when TRCL or BN Raman spectroscopy cannot be applied to specific BN materials such as amorphous or thin films. This underlines the superior role of spatially-resolved spectroscopy in the evaluation of BN crystals and films for the use of high-mobility graphene devices.

Optimization of CuAl2O4 Nanoparticles for Enhanced Photocatalytic Degradation of Organic Dyes Under UV and Visible Light.

Organic dyes, due to their persistence and toxicity, represent a significant environmental challenge. This study focuses on the photocatalytic degradation of organic dyes using CuAl2O4 nanoparticles, synthesized through the co-precipitation method, under visible light irradiation. The synthesized nanoparticles were thoroughly characterized using Fourier Transform Infrared (FT-IR) spectroscopy, Raman spectroscopy, and X-ray Diffraction (XRD) to determine their chemical, structural, and crystalline properties. The optical properties of the nanoparticles, particularly their ability to absorb light, were also investigated, highlighting their importance in enhancing photocatalytic performance. Methyl Violet dye was selected as a model pollutant to assess the photocatalytic efficiency of these nanoparticles. The results showed that the CuAl2O4 nanoparticles degraded about 72.49% of Methyl Violet in 120min under UV and visible light, with the high efficiency attributed to the generation of electron-hole pairs and reactive oxygen species, including superoxide anions and hydroxyl radicals. These active agents are critical in the degradation process. The findings demonstrate the potential of CuAl2O4 nanoparticles as nontoxic and highly effective photocatalysts for environmental remediation, offering a promising solution for treating wastewater contaminated with hazardous organic dyes. This study enhances the understanding of the photocatalytic behavior of CuAl2O4 nanoparticles and emphasizes their potential in reducing environmental pollution through efficient degradation of harmful compounds.

CO Oxidation over Cu/Ce Binary Oxide Prepared via the Solvothermal Method: Effects of Cerium Precursors on Properties and Catalytic Behavior

Cu/Ce binary oxides were prepared via the one-pot solvothermal method, and the effects of different cerium precursors (cerium nitrate and cerium ammonium nitrate) on the catalytic activity and resistance to water vapor or CO2 of the prepared samples for low-temperature CO oxidation reaction were investigated. The physicochemical characteristics of the catalysts were characterized via thermal analyses (TG-DSC), X-ray diffraction (XRD), Raman spectroscopy, N2 adsorption/desorption, inductively coupled plasma-atomic emission spectrometry (ICP-AES), X-ray photoelectron spectroscopy (XPS), in situ diffuse reflectance infrared Fourier transform spectroscopy (in situ DRIFTs), and temperature-programmed reduction with H2 (H2-TPR). The results indicated that the CuO/CeO2 catalyst (CC-N) prepared with cerium nitrate showed higher activity for low-temperature CO oxidation, which can be ascribed to its larger specific surface area and pore volume, higher amounts of highly dispersed CuO species with strong interaction with CeO2, Cu+ species, and more active surface oxygen species, compared with the counterpart prepared with cerium ammonium nitrate (CC-NH). Furthermore, the CC-N catalyst also exhibited better resistance to CO2 poisoning than CC-NH.

High-Efficiency Self-Powered Photodetector for UV-Visible-NIR Spectrum Using Solution-Processed TiO2/Cu2ZnSnS4 Heterojunction in Superstrate Configuration

This study introduces a sustainable and efficient approach for self-powered photodetection using a solution-processed TiO2/CZTS heterojunction to detect the broad electromagnetic spectrum. CZTS thin films with a pure kesterite phase are synthesized via a cost-effective sol-gel spin coating technique, eliminating the need for high-temperature post-deposition sulfurization. The formation of the kesterite phase in CZTS films is confirmed through microstructural studies, Raman spectroscopy, and optical analyses. A high-quality heterojunction is fabricated by depositing the CZTS layer on chemically synthesized TiO2 thin film on FTO-coated glass substrates, and its photoresponse characteristics are studied under 365nm, 405nm, 532nm, 650nm, and 980nm light in a superstrate configuration. The heterojunction exhibits optimal photoresponsivity (~1.28mA/W), detectivity (~4.77 ×10¹⁰ Jones), and rise/decay times (~54 ms/27 ms) at zero external bias. It also demonstrates efficient performance under 1 sun AM1.5G solar spectrum. The photodetection mechanism through carrier dynamics under illumination for the heterostructure is further investigated using impedance spectroscopy, incident light-dependent capacitance-voltage characteristics, and photo-capacitance measurements. This approach provides a cost-effective and scalable solution for self-powered photodetection, offering significant potential for integration into various optoelectronic devices for renewable energy harvesting and sensing applications.

Subtype-Specific Detection in Stage Ia Breast Cancer: Integrating Raman Spectroscopy, Machine Learning, andLiquid Biopsy for Personalised Diagnostics.

This study explores the integration of Raman spectroscopy (RS) with machine learning for the early detection and subtyping of breast cancer using blood plasma samples. We performed detailed spectral analyses, identifying significant spectral patterns associated with cancer biomarkers. Our findings demonstrate the potential for classifying the four major subtypes of breast cancer at stage Ia with an average sensitivity and specificity of 90% and 95%, respectively, and a cross-validated macro-averaged area under the curve (AUC) of 0.98. This research highlights efforts to integrate vibrational spectroscopy with machine learning, enhancing cancer diagnostics through a non-invasive, personalised approach for early detection and monitoring disease progression. This study is the first of its kind to utilise RS and machine learning to classify the four major breast cancer subtypes at stage Ia.

Highly responsive gas sensors based on grain boundary–rich polycrystalline few-layer MoS2 films for NO2 detection

Abstract This study addresses the issues of insufficient sensitivity and poor reversibility for NO2 detection by successfully fabricating a sensor based on uniform and high-quality few-layer MoS2 polycrystalline material using chemical vapor deposition. This approach aims to improve the response of the sensor by exploiting the abundance of grain boundary (GB) defects in polycrystalline MoS2 membranes. Comprehensive surface morphology analysis of the few-layer MoS2 polycrystalline films was conducted using microscopy, Raman spectroscopy, and X-ray photoelectron spectroscopy to characterize their chemical composition and properties. Subsequently, evaluation of 1–100-ppm NO2 was conducted at room temperature (25 °C). The results show excellent performance of the sensor, with a response range of 11–82.24. Notably, under ultraviolet excitation at room temperature, this sensor exhibits a response time of only 41 s to 50 ppm of NO2 with complete recovery and improved sensitivity, maintaining reliable stability over eight weeks. Furthermore, the findings reveal that the sensor demonstrates high selectivity toward NO2 gas with limit of detection and limit of qualification values of 10 and 34 ppb, respectively. Owing to the abundant adsorption sites provided by GB defects in polycrystalline thin films, the response performance of the sensor is effectively enhanced. This study provides valuable insights into the future design and development of high-performance NO2 gas sensors.