Surface Enhanced Raman Spectroscopy Substrates Research Articles

Exploring the role of graphene-metal hybrid nanomaterials as Raman signal enhancers in early stage cancer detection

Molecular diagnosis plays a significant role in detection of biomolecules linked to early stage cancer since it offers greater sensitivity and reliability for identification of biomarker level changes as the disease progresses. The application of vibrational spectroscopy in biomarker detection is defined by the fingerprint spectrum of a molecule originating from single-molecule vibrations. This characteristic makes surface enhanced Raman spectroscopy (SERS) a promising tool for identification of biomarkers. The performance of the SERS technique largely depends on the material being used as the SERS substrate. Graphene, with its large surface area and abundance of aromatic regions, is considered advantageous as SERS substrate. Combining graphene with metal nanomaterials considerably increases SERS signal intensity, thereby enhancing detection sensitivity. Therefore, this review emphasizes the significance of selecting graphene-metal nanohybrids as suitable SERS substrates for signal amplification. The detail understanding of the mechanism of graphene-metal hybrid in SERS based detection of early stage cancer is also presented. Furthermore, several examples demonstrated the application of graphene-metal hybrid nanomaterials in detecting biomarkers and cancer cell differentiation using SERS imaging.

Phase Transformation on Two-Dimensional MoTe2 Films for Surface-Enhanced Raman Spectroscopy.

Two-dimensional (2D) transition metal dichalcogenides (TMDs) have recently become attractive candidate substrates for surface-enhanced Raman spectroscopy (SERS) owing to their atomically flat surfaces and adjustable electronic properties. Herein, large-scale 2D 1T'- and 2H-MoTe2 films were prepared using a chemical vapor deposition method. We found that phase structure plays an important role in the enhancement of the SERS performances of MoTe2 films. 1T'-MoTe2 films showed a strong SERS effect with a detection limit of 1 × 10-9 M for the R6G molecule, which is one order of magnitude lower than that of 2H-MoTe2 films. We demonstrated that the SERS sensitivity of MoTe2 films is derived from the efficient photoinduced charge transfer process between MoTe2 and adsorbed molecules. Moreover, a prohibited fish drug could be detected by using 1T'-MoTe2 films as SERS substrates. Our study paves the way to the development and application of high-performance SERS substrates based on TMD phase engineering.

DLC based substrate enabling single molecule detection by Surface Enhanced Raman Spectroscopy (SERS)

This work shows a new and surprising application of Diamond-Like Carbon as Surface Enhanced Raman Spectroscopy (SERS) substrate. It was investigated with the well-known Rhodamine 6G (R6G) as SERS test molecule and extended the detection limit to the astonishing attomolar level, which means single molecule detection. The SERS substrate started by depositing excellent quality Diamond-Like Carbon (DLC) on aluminum, followed by laser modification of the DLC in a delimited area that defines the SERS substrate. The laser action gives electrical conductivity between the scratched surface and the aluminum. Silver was electrodeposited on this delimited area. The high Enhancement Factor was around 5 × 1012 at an R6G concentration of 7 × 10−18 M, observed only at few (and difficult to hit upon) points since the surface density was smaller than 2 R6G molecules/mm2. At each of the larger concentrations tested (7 × 10−15, 7 × 10−12, 7 × 10−9 and 7 × 10−6 M), the Raman intensities were in the same order of magnitude along the whole substrate, indicating a pretty homogeneous sensitivity. The repeatability among 5 samples tested at 7 × 10−12 M showed a standard deviation of only 18 %. The nano porous structure of the silver deposits, shown by Field Emission Gun Scanning Electron Microscopy (FEG-SEM) appears to be like many other studies with electroplated silver. However, the Raman spectra backgrounds show that amorphous carbon is interacting with the silver nanoparticles. A probable explanation for the superior EF is the synergistic contributions of plasmon enhancement from silver and chemical enhancement from amorphous carbon nanostructure.

Enhanced SERS signal in the hybrid substrate through electronic modulation of CVD grown single-layer graphene

The ever-growing demand for sensitive and reliable detection of hazardous material in the food chain and trace detection of chemical entities in a variety field attracted advanced Surface Enhanced Raman Spectroscopy (SERS) active material such as graphene-based hybrid SERS. The graphene‑silver nanostructures (AgNS) based hybrid SERS substrates are explored to understand the critical role of pristine graphene grown by chemical vapor deposition (CVD) on SERS signal and its possible mechanism. A lithography-free fabrication process has been developed for growth of uniform array of AgNS with varying both particle sizes and inter-particle gaps. The optimal AgNS with feature size ~40 nm and inter-particle spacing of ~13 nm demonstrated the maximum SERS enhancement with Rhodamine 6G (R6G). The single-layer graphene (SLG) grown by CVD with the aid of controlling the reaction geometry with growth under a free molecular regime leads to the highest quality graphene with I2D/IG ratio of ~3.58 and ID/IG ratio of 0.1539. The flow regime-controlled CVD-grown SLG integrated with AgNS and its SERS enhancement mechanism is explored for trace detection of R6G. The graphene with its ability to modulate the electronic structure and tune it relative to the highest occupied molecular orbital-lowest occupied molecular orbital (HOMO-LUMO) levels of R6G molecules resulted in improved SERS signal by about an order for graphene-AgNS hybrid structure as compared to bare AgNS. The obtained findings paved the way for the futuristic and reliable hybrid SERS substrate for trace-level detection of a wide range of chemical entities.

Surface-enhanced Raman spectroscopy substrates for monitoring antibiotics in dairy products: Mechanisms, advances, and prospects.

Antibiotic residues in dairy products have become an undeniable threat to human health. Surface-enhanced Raman spectroscopy (SERS) has been widely used in efficiently detecting antibiotics because of its characteristics including fast response, high resolution, and strong resistance to moisture interference. However, as a core part of SERS technology, the design principle and detection performance of enhanced substrates used in monitoring antibiotics in dairy products have not yet received enough attention. Thus, it is necessary to give a critical review of the recent developments of SERS substrates for monitoring antibiotics in dairy products, which can be expected to provide inspiration for the efficient utilization of SERS technology. In this work, advances in various SERS substrates applied in sensing antibiotics in dairy products were comprehensively reviewed. First, the enhancement mechanisms were introduced in detail. Significantly, the types of enhanced materials (plasmonic metal particles [PMPs], PMPs/semiconductor composite materials) and biometric design strategies including immunoassay, aptamer, and molecularly imprinted polymers-based SERS biosensors applied in dairy products were systematically summarized for the first time. Meanwhile, the performance of SERS substrates used for the detection of antibiotics in dairy products was addressed from the aspects of dynamic linear range and detection restriction strategy. Finally, the conclusions, challenges, and future prospects of SERS substrates for antibiotic monitoring in dairy products were deeply discussed, which also provide new opinions and key points for constructing SERS substrates applied in complex food matrix in the future.

Three-Dimensional (3D) Surface-Enhanced Raman Spectroscopy (SERS) Substrates for Sensing Low-Concentration Molecules in Solution.

The use of surface-enhanced Raman spectroscopy (SERS) in liquid solutions has always been challenging due to signal fluctuations, inconsistent data, and difficulties in obtaining reliable results, especially at very low analyte concentrations. In our study, we introduce a new method using a three-dimensional (3D) SERS substrate made of silica microparticles (SMPs) with attached plasmonic nanoparticles (NPs). These SMPs were placed in low-concentration analyte solutions for SERS analysis. In the first approach to perform SERS in a 3D environment, glycerin was used to immobilize the particles, which enabled high-resolution SERS imaging. Additionally, we conducted time-dependent SERS measurements in an aqueous solution, where freely suspended SMPs passed through the laser focus. In both scenarios, EFs larger than 200 were achieved, which enabled the detection of low-abundance analytes. Our study demonstrates a reliable and reproducible method for performing SERS in liquid environments, offering significant advantages for the real-time analysis of dynamic processes, sensitive detection of low-concentration molecules, and potential applications in biomolecular interaction studies, environmental monitoring, and biomedical diagnostics.

Perfluorodecanethiol-Functionalized Silver Nanoparticles on Polyester Films as High-Performance Surface-Enhanced Raman Spectroscopy Substrates.

The insufficient capabilities of current surface-enhanced Raman scattering (SERS) substrates in enriching dilute analytes from complex media severely restrict detection sensitivity, hampering practical applications. To meet this demand, in this study, a novel super hydrophobic membrane that can be directly prepared on a large scale based on the silver nanoparticles (AgNPs) functioning with perfluorodecanethiol (PFDT) is fabricated and evaluated as an SERS substrate. Firstly, polyester (PET) films modified with sodium chloride were proven to be capable of loading AgNPs, and the sizes of AgNPs were investigated. In addition, the PFDT concentration and reaction time for functionalizing the surface of AgNPs have been optimized. The relationship between the hydrophobic properties of the film and its SERS performance was then studied. The PET@Ag-PFDT film demonstrates two orders of magnitude superior SERS performance than the unmodified PET@Ag substrate, with a detection limit of folic acid approaching 5 × 10-10 M.

Polyelectrolyte modified Ag-nanosphere: A Practical Approach for Sensitive and Selective SERS-based Detection of Organic Dye Pollutants

This study presents a cost-effective method for fabricating surface-enhanced Raman spectroscopy (SERS) substrates using Ag-nanospheres (AgNS) capped with Poly(diallyldimethylammonium chloride) (PDADMAC) and poly(styrene sulfonate) (PSS). AgNS synthesis involves immersing Ag-nanocrystals in a nonaqueous solution, mixed with PEs in an aqueous solution via ultrasonic disturbance. Resulting aggregates form stable spherical assemblies with diameters ranging from 150 nm to 450 nm, and various characterization techniques, including scanning electron microscopy with energy-dispersive X-ray, UV-visible spectrophotometry, dynamic light scattering, and zeta potential analysis, were employed to analyze their fundamental chemical and physical properties. These qualified AgNSs serve as SERS substrates for sensitive and selective identification of charged organic dye contaminants, such as rhodamine 6G (R6G) and rose bengal (RB). Sensitivity assessments with the optimized quantities of either PDADMAC or PSS-capped AgNSs demonstrate successful detection down to concentrations of 10-14 M for RB and 4 x 10-13 M for R6G. The same SERS substrates also enable electrostatically driven selective detection even in analyte mixtures, and an additional variation of the SERS substrate comprising a complex of PDADMAC-capped and PSS-capped AgNSs exhibited distinct SERS spectra influenced by both positively and negatively charged analytes. Finally, successful detection of two oppositely charged pesticides was achieved through electrostatic attraction, so theses polyelectrolytes capped AgNS-based SERS substrate presents a promising avenue for efficiently and selectively detecting charged organic contaminants.

2D MoS2 plasmonic nanocavity based SERS platform for bilirubin detection

Although various methods can be used to detect bilirubin at the micromolar level, achieving reliable detection in the sub-nanomolar range remains challenging. Sensitivity at these ultralow levels is vital, as new evidence strongly associates bilirubin with chronic heart, lung, and neurological disorders. This accuracy is also essential for creating diagnostic protocols that can efficiently track bilirubin levels, assisting in managing related conditions. Such advancements will lead to enhanced diagnostic tools and methods, enabling more precise bilirubin monitoring in clinical environments. Here, the aforesaid blind-spot is addressed by utilizing surface enhanced Raman spectroscopy (SERS) as fingerprint technique to detect bilirubin concentrations as low as 0.1 nM. A plasmonically active 2D MoS2 based SERS substrate is formulated and optimized for single step SERS sensing of bilirubin. Plasmonic cavity based approach is utilized to circumvent the problem related to fluorescent background overwhelming the SERS signal. The 2D MoS2 based SERS platform shows threefold enhancement of scattering in comparison to the traditional gold nanoparticle on Si/SiO2 approach. The Raman signature of bilirubin is calibrated by taking citrate as a stable reference analyte and is shown to vary linearly with logarithmic concentration across the picomolar to micromolar range.

Functionalized MXene (Ti3C2TX) Loaded with Ag Nanoparticles as a Raman Scattering Substrate for Rapid Furfural Detection in Baijiu.

Furfural is an essential compound that contributes to the distinctive flavor of sauce-flavored Baijiu. However, traditional detection methods are hindered by lengthy and complex sample preparation procedures, as well as the need for expensive equipment. Therefore, there is an urgent need for a new approach that allows rapid detection. In this study, we developed a novel surface-enhanced Raman spectroscopy (SERS) substrate by constructing MXene (Ti3C2TX) @Ag nanoparticles (Ag NPs) through an electrostatic attraction method. The MXene (Ti3C2TX) @Ag NPs were successfully fabricated, with adsorbed NaCl-treated Ag NPs uniformly absorbed on the surface of MXene (Ti3C2TX), creating high-density distributed SERS "hot spots". The prepared substrate demonstrated excellent sensitivity, uniformity, repeatability, and long-term stability, with a low detectable concentration of 10-9 M for R6G (Rhodamine 6G) and an enhancement factor of up to 7.08 × 105. When applied for the in situ SERS detection of furfural in Baijiu, the detection limit was as low as 0.5 mg/L. Overall, the proposed method offers rapid, low-cost, and sensitive quantitative analysis, which is significant not only for detecting furfural in Baijiu but also for identifying hazardous substances and distinguishing between authentic and counterfeit Baijiu products.

Black Silicon Surface-Enhanced Raman Spectroscopy Biosensors: Current Advances and Prospects.

Black silicon was discovered by accident and considered an undesirable by-product of the silicon industry. A highly modified surface, consisting of pyramids, needles, holes, pillars, etc., provides high light absorption from the UV to the NIR range and gives black silicon its color-matte black. Although black silicon has already attracted some interest as a promising material for sensitive sensors, the potential of this material has not yet been fully exploited. Over the past three decades, black silicon has been actively introduced as a substrate for surface-enhanced Raman spectroscopy (SERS)-a molecule-specific vibrational spectroscopy technique-and successful proof-of-concept experiments have been conducted. This review focuses on the current progress in black silicon SERS biosensor fabrication, the recent advances in the design of the surface morphology and an analysis of the relation of surface micro-structuring and SERS efficiency and sensitivity. Much attention is paid to problems of non-invasiveness of the technique and biocompatibility of black silicon, its advantages over other SERS biosensors, cost-effectiveness and reproducibility, as well as the expansion of black silicon applications. The question of existing limitations and ways to overcome them is also addressed.

Femtosecond laser-induced black silicon: a dual application in photodetection and surface-enhanced Raman scattering

A multifunctional structured silicon with enhanced optical and photoelectric properties has been processed by femtosecond (fs) laser in ambient air. The structured surface decorated with Au nanoparticles (NPs) exhibits excellent infrared absorption properties related to localized surface plasmon resonance (LSPR) coupled to microstructures. Over 75% absorption is achieved at 1550 nm, which is three orders of magnitude higher than that of unprocessed Si. The absorption enhancement results in increased photocurrent response in n + -n junction diodes, exhibiting a responsivity of 125 mA/W and an external quantum efficiency (EQE) of 10% at 1550 nm, for a bias voltage of 10 V. Moreover, the structured Si is also tested as a surface-enhanced Raman spectroscopy (SERS) substrate showing a strong signal under 638 nm excitation with Raman enhancement factors (EFs) as high as 108. In particular, the capability of detecting Raman analyte down to 10−11 M for RhB and 10−10 M for 4-MBA is demonstrated, simultaneously assessing the enhanced near-field due to the LSPR originating from the processed surface roughness leading to the valuable performances achieved by the n + -n junction diodes. These results offer a new path toward the elaboration of high-efficiency applications of Si structured surfaces in the fields of photoelectric sensing and detection.

The Fabrication of Gold Nanostructures as SERS Substrates for the Detection of Contaminants in Water.

Gold nanostructures (AuNSs) were used to fabricate surface-enhanced Raman spectroscopy (SERS) substrates. These AuNSs were produced using the solid-state dewetting method from thin films. The fragmentation process was studied at 300 °C, with durations of thermal treatment of 1, 3, 6, and 12 h. These SERS substrates were then employed to detect Rhodamine B (RhB) as the model analyte, simulating a contaminant in the water at a concentration of 5 ppm. The morphology of the AuNSs was examined using SEM, which revealed a spheroidal shape that began to coalesce at 12 h. The size of the AuNSs was estimated to range from 22 ± 7 to 24 ± 6 nm, depending on the annealing time. The localized surface plasmon resonance of the AuNSs was determined using absorption spectroscopy, showing a shift as the annealing time increased. The SERS signals of RhB adsorbed on the AuNS substrates were validated by performing a 10 × 10 point map scan over each sample surface (1, 3, 6, and 12 h), and a comparative analysis showed no significant differences in the positions of the bands; however, variations in intensity enhancement ranged from 5 to 123 times at 6 and 1 h, respectively.

Comparative SERS Activity of Homometallic and Bimetallic Core-Satellite Assemblies.

The fabrication of core-satellite (CS) assemblies offers a versatile strategy for tailoring the optical properties of plasmonic nanomaterials. In addition to key factors like size, shape, and spatial arrangement of individual components, the combination of plasmonic units with different compositions (e.g., gold and silver) has been demonstrated to produce materials with enhanced properties and functionalities applicable across a range of fields. Notably, several CS assembly variants have emerged as promising substrates for surface-enhanced Raman spectroscopy (SERS). In this study, we address a gap in the knowledge by conducting a systematic cross-comparison of the optical and SERS properties of highly bright homo- and bimetallic CS assemblies. We evaluated the SERS efficiencies of these different superstructures across various excitation wavelengths and supported our findings with numerical simulations. The insights gained from this study offer a valuable foundation for researchers seeking to select and optimize the most suitable CS assemblies for their given SERS application.

“Partner” cellulose gel with “dialysis” function: Achieve the integration of filtration-enrichment-SERS detection

Hydrogel and aerogel materials have garnered significant attention in constructing effective surface-enhanced Raman spectroscopy (SERS) substrates due to their excellent adsorption capabilities, high specific surface area, and abundant chemical groups. However, in liquids with complex compositions, non-specific adsorption of macromolecules can lead to surface scaling and pore clogging of the substrate material, limiting the selective enrichment and SERS detection of target molecules. To address this, an innovative aerogel-chimeric hydrogel material (CH@S-CNF/SA/Ag NPs) was developed. The aerogel component, with its high specific surface area and electronegative properties, functions as a SERS “chip” for adsorption and detection of target molecules. Simultaneously, the mesoporous structure of the hydrogel “shell” effectively filters macromolecules from the solution. These CH@S-CNF/SA/Ag NPs were utilized as SERS substrate materials for detecting urine from healthy individuals and patients with chronic kidney disease stage 5 (CKD5). When combined with machine learning algorithms, the detection accuracy reached 99.50%. This work represents a significant advancement in the specific adsorption and SERS detection of small molecules in complex biological samples such as urine and blood.

Raman enhancement via double optical resonances in all-dielectric photonic crystal slabs

All-dielectric photonic structures are an important class of substrates in surface-enhanced Raman spectroscopy (SERS), utilizing optical resonant modes to significantly enhance the electromagnetic field and amplify the Raman signals. In this study, we demonstrate the double-resonance approach to realize significant Raman enhancement using all-dielectric photonic crystal (PhC) slab. The double-resonance condition is satisfied by designing optical resonant modes in photonic bands to match frequencies of both excitation laser and Raman signals. By the fabricated PhC slab, the significant enhancement for the Raman signal of silicon is demonstrated. The enhanced Raman signals exhibit a uniform distribution on the PhC slab. The method of Raman enhancement via double optical resonances can advance the field of all-dielectric SERS and holds potential for future SERS applications.

Ultrasensitive detection of contaminants in milk using a novel NMS-Ag modified water-resistant paper substrate

Rapid and precise detection of harmful substances in food products is essential for ensuring public health and safety. This study introduces a novel surface-enhanced Raman spectroscopy (SERS) substrate, composed of a molybdenum disulfide‑silver nanocomposite, applied to flexible, water-resistant filter paper for detecting melamine and bisphenol A (BPA) in milk. Optimized molybdenum disulfide (NMS) nanoflowers (NFs) were synthesized through hydrothermal methods and high-temperature annealing, then modified with silver (Ag) nanoparticles to form the NMS-Ag nanocomposite (NMSA6). This substrate greatly enhances the Raman signal, achieving an enhancement factor of approximately 1.49 × 107 and a detection limit as low as 10−11 M for simultaneous multi-component analysis. Finite-difference time-domain (FDTD) simulations confirm the enhancement mechanism. The NMSA6 substrate demonstrates remarkably low detection limits for BPA and melamine, facilitating the analysis of various hazardous substances. These findings highlight the substrate's potential for highly sensitive, label-free detection, presenting a viable tool for food safety monitoring.

Impact of Graphene Oxide on SERS Enhancement of Arylated Gold Nanospheres: Mechanistic Insight.

The performance of gold nanospheres as substrates for surface-enhanced Raman spectroscopy (SERS) investigation has been compromised by their low adsorption efficiency, high colloidal dispersibility, and diminishing hot spots. However, gold nanosphere substrates modified using aryldiazonium gold(III) chemistry via durable gold-carbon bonds are promising for SERS enhancement due to their controlled organic layer density. In this study, arylated gold nanospheres AuNSs-COOH have shown SERS enhancement when incorporated into graphene oxide (GO) to form nanocomposites (NCs) labeled AuNSs-COOH/GO (AuNCs). Our investigation using X-ray photoelectron spectroscopy (XPS) surface analysis showed that the gold-aryl nanospheres reached their maximum SERS enhancement with an optimal coating. The evaluation included the Au 4f chemical environment and compact graphitic layers for the SERS substrate optimization. The fabricated AuNC substrates demonstrated superior efficiency and reproducibility. A broad linear range of 10-3-10-7 M 4-nitrophenol detection was obtained with exceptional repeatability, as evidenced by the relative standard deviation (RSD) of 9.32%. A detailed investigation of the energy profiles, particularly the valence band maximum (VBM) and band gap values of the substrate and analyte, depicted the electromagnetic (EM) and charge-transfer-induced enhancement and the role of GO inclusion in substrate efficiency in SERS enhancement mechanisms. The finite-difference time domain (FDTD) simulation results revealed that AuNCs incorporated with graphitic nanostructures exhibited the most substantial SERS effect through an EM field enhancement mechanism. This study demonstrated significant SERS enhancement using gold-aryl nanospheres when modified with GO, in contrast to the typical reliance on anisotropic nanostructures.

Ag-deposited nanostructured Boehmite substrates for the detection of explosives with surface enhanced Raman spectroscopy

We propose aluminum oxide (Boehmite) sputter-deposited with Ag substrates for Surface-Enhanced Raman Spectroscopy (SERS). These substrates are cost-effective and easily fabricated by heating aluminum in an aqueous environment to create Boehmite, followed by Ag sputtering. The metal deposition is optimized, resulting in random arrays of Ag nanostructures with a diameter of ∼100 nm and a spacing of <100 nm leading to significant enhancement of the Raman signal. The performance and sensitivity of the substrates are initially tested with the use of Crystal Violet analyte which results in limits of detection close to 10−10M. These substrates are used for the rapid detection of four different explosive compounds: Nitroglycerin (NG), Picric Acid (PA), Cyclotrimethylene trinitramine (RDX) and 2,4,6-Trinitrophenylmethylnitramine (Tetryl). A series of Raman spectra are collected for these four selected explosives on the fabricated substrates and principal component analysis (PCA) was used for proper evaluation and identification of the corresponding measured spectra.

TinyML-Raman: A novel IoT based field-deployable spectra analysis for accurate identification of pharmaceuticals and trace dye-pesticide mixtures from facile SERS method

BackgroundUpcoming inexpensive, compact Internet of Things (IoT) microcontrollers i.e., tiny-machine learning (TinyML) takes the ML driven Raman spectroscopy one step ahead for realization of more affordable and highly compact field deployable instruments. Further, lack of large spectral datasets and need for numerous specialized SERS substrates impede the development of various ML-based surface enhanced Raman spectroscopy (SERS) applications. The aim is to introduce TinyML analysis on wide range of spectra classes using customized dataset obtained with low-cost SERS. In this regard, it is vital to establish an optimum ML model and efficient data handling methodology for low memory TinyML units. ResultsWe introduce a novel TinyML methodology for accurate classification of large spectra classes with smartphone assistance for data communication and results visualization. To generate large customized spectral dataset, we present a facile, micro-drop SERS using Au colloids and reusable grooved Al substrates. The results demonstrated that memory efficient 8-bit data quantization based convolutional neural network is effective for accurate identification of 22 different spectra classes of trace dye-pesticide mixtures and pharmaceuticals. In this novel quantized data analysis on significantly varied intensity and complex variation spectra classes i.e., many individual, binary-mixtures and some with varied compositions, data normalization is shown to be powerful for improving ML classification accuracy from about 55 % to >99.5 %. Its robustness is demonstrated using inter-instrument driven data variations such as spectral shifts, high noise, and abscissa-flip, with five-fold cross validation of model performance. In addition, on-site quantification of analyte through spectral intensity is also demonstrated. SignificanceThis study opens up a new approach of ML analysis towards realization of next generation field deployable analytical instruments maintaining data privacy. It presents a detailed procedure of quantized spectral data analysis and its implementation in TinyML, attractive for various users and instrument manufacturers. The presented innovative computer-free ML analysis can be employed in all types of spectrometers, meeting the common goal of Raman spectroscopy i.e., accurate identification of complex spectra classes.