Rapid and sensitive SERS detection of melamine in milk using Ag nanocube array substrate coupled with multivariate analysis

Rapid detection of tebuconazole based on hydrogel SERS chips

Tebuconazole is one of the most commonly used fungicides in agricultural production, that has the merits of highly effectiveness, broad spectrum and systemic function. Excessive tebuconazole may pose a great threat to human and animal health. Traditional detection techniques for tebuconazole usually have limitations such as expensive equipment, poor antibody stability, and time-consuming procedures. Herein, a sensitive sensor is developed for the rapid detection of tebuconazole based on hydrogel surface-enhanced Raman scattering (SERS) chips. Aggregated Ag nanoparticles (a-AgNPs) with tunable localized surface plasmon resonance (LSPR) wavelength are in-situ synthesized in polyvinyl alcohol (PVA) solution for preparing hydrogel SERS chips. Three hydrogel SERS chips are obtained to match the three commonly used laser wavelengths. On the basis, a match laser wavelength is selected according to the energy levels of tebuconazole and the Fermi level of a-AgNPs to gain a strong chemical enhancement. At the same time, the chip with a corresponding LSPR wavelength to the laser is applied to obtain a strong electromagnetic enhancement. Thus, highly sensitive SERS signal of tebuconazole is obtained. Furthermore, the obtained hydrogel SERS chips have good repeatability, outstanding reproducibility and strong anti-interference ability, and show outstanding reliability in practical applications. As a result, the SERS chips offer a reliable and convenient platform for the quick detection of tebuconazole in foods. The detection limit is as low as 1 ppb, and the recoveries is distributed in the range of 94.66-106.70 %. This work would promote greatly the application of SERS in small molecule detection.

Facile synthesis of Ag NPs@MgO nanosheets for quantitative SERS-based detection and removal of hazardous organic pollutants

Surface-enhanced Raman spectroscopy (SERS) is a highly precise and non-invasive analytical method known for its ability to detect vibrational signatures of minute analytes with exceptional sensitivity. However, the efficacy of SERS is subject to substrate properties, and current methodologies face challenges in attaining consistent, replicable, and stable substrates to regulate plasma hot spots across a wide spectral range. This study introduces a straightforward and economical approach that incorporates monodispersed silver nanoparticles onto 2-D porous magnesium oxide nanosheets (Ag@MgO-NSs) through an in-situ process. The resulting nanocomposite, Ag@MgO-NSs, demonstrates substantial SERS enhancement owing to its distinctive plasmonic resonance. The effectiveness of this nanocomposite is exemplified by depositing diverse environmental pollutants as analytes, such as antibiotic ciprofloxacin (CIP), organic dyes like rhodamine 6G (R6G) and methylene blue (MB), and nitrogen-rich pollutant like melamine (MLN), onto the proposed substrate. The proposed nanocomposite features a 2-D porous structure, resulting in a larger surface area and consequently providing numerous adsorption sites for analytes. Moreover, engineering the active sites of the nanocomposite results in a higher number of hotspots, leading to an enhanced performance. The nanocomposite outperforms, exhibiting superior detection capabilities for R6G, MB, and MLN at concentrations of 10-6 M and CIP at concentration of 10-5 M, with impressive uniformity, reproducibility, stability, and analytical enhancement factors (EF) of 6.3 x 104, 2 x 104, 2.73 x 104 and 1.8 x 104 respectively. This approach provides a direct and cost-effective method for the detection of a broad spectrum of environmental pollutants and food additives, presenting potential applications across diverse domains. The detected environmental pollutants and food additives are removed through both catalytic degradation (R6G and MB) and adsorption (CIP and MLN).

Quantitative detecting low concentration polystyrene nanoplastics in aquatic environments via an Ag/Nb2CTx (MXene) SERS substrate

In this study, the plasmonic Ag nanoparticles (Ag NPs) were uniformly anchored on the high conductivity Nb2CTx (MXene) nanosheets to construct an Ag/Nb2CTx substrate for surface-enhanced Raman spectroscopy (SERS) detection of polystyrene (PS) nanoplastics. The KI addition (0.15 mol/L), the volume ratio between substrate colloid and nanoplastic suspension (2:1), and the mass ratio of Nb2CTx in substrate (14%) on SERS performance were optimized. The EM hot spots of Ag/Nb2CTx are significantly enlarged and enhanced, elucidated by FDFD simulation. Then, the linear relationship between the PS nanoplastics concentration with three different sizes (50, 300, and 500 nm) and the SERS intensity was obtained (R2 > 0.976), wherein, the detection limit was as low as 10-4 mg/mL for PS nanoplastic. Owing to the fingerprint feature, the Ag/Nb2CTx-14% substrate successfully discerns the mixtures from two-component nanoplastics. Meanwhile, it exhibits excellent stability of PS nanoplastics on different detection sites. The recovery rates of PS nanoplastics with different sizes in lake water ranged from 94.74% to 107.29%, with the relative standard deviation (RSD) ranging from 2.88% to 8.30%. Based on this method, the expanded polystyrene (EPS) decomposition behavior was evaluated, and the PS concentrations in four water environments were analyzed. This work will pave the way for the accurate quantitative detection of low concentration of nanoplastics in aquatic environments.

Quantitative and rapid detection of nanoplastics labeled by luminescent metal phenolic networks using surface-enhanced Raman scattering

The escalating prevalence of nanoplastics contamination in environmental ecosystems has emerged as a significant health hazard. Conventional analytical methods are suboptimal, hindered by their inefficiency in analyzing nanoplastics at low concentrations and their time-intensive processes. In this context, we have developed an innovative approach that employs luminescent metal-phenolic networks (L-MPNs) coupled with surface-enhanced Raman spectroscopy (SERS) to separate and label nanoplastics, enabling rapid, sensitive and quantitative detection. Our strategy utilizes L-MPNs composed of zirconium ions, tannic acid, and rhodamine B to uniformly label nanoplastics across a spectrum of sizes (50-500 nm) and types (e.g., polystyrene, polymethyl methacrylate, polylactic acid). Rhodamine B (RhB) functions as a Raman reporter within these L-MPNs-based SERS tags, providing the requisite sensitivity for trace measurement of nanoplastics. Moreover, the labeling with L-MPNs aids in the efficient separation of nanoplastics from liquid media. Utilizing a portable Raman instrument, our methodology offers cost-effective, swift, and field-deployable detection capabilities, with excellent sensitivity in nanoplastic analysis and a detection threshold as low as 0.1 μg/mL. Overall, this study proposes a highly promising strategy for the robust and sensitive analysis of a broad spectrum of particle analytes, underscored by the effective labeling performance of L-MPNs when coupled with SERS techniques.

Realization of qualitative to semi-quantitative trace detection via SERS-ICA based on internal standard method

Surface-enhanced Raman spectroscopy (SERS) can quickly identify molecular fingerprints and has been widely used in the field of rapid detection. However, the non-uniformity inherent in SERS substrate signals, coupled with the finite nature of the detection object, significantly hampers the advancement of SERS. Nowadays, the existing mature immunochromatographic assay (ICA) method is usually combined with SERS technology to address the defects of SERS detection. Nevertheless, the porous structure of the strip will also affect the signal uniformity during detection. Obviously, a method using SERS-ICA is needed to effectively solve signal fluctuations, improve detection accuracy, and has certain versatility. This paper introduces an internal standard method combining deep learning to predict and process Raman data. Based on the signal fluctuation of single-antigen SERS-ICA test strip, the double-antigen SERS-ICA test strip was constructed. The full spectrum Raman data of double-antigen SERS-ICA test strip was normalized by the sum of two characteristic peaks of internal standard molecules, and then processed by deep learning algorithm. The Relative Standard Deviation (RSD) of Raman data of bisphenol A was compared before and after internal standard normalization of double-antigen SERS-ICA test strip. The RSD processed by this method was increased by 3.8 times. After normalization, the prediction accuracy of Root Mean Square Error (RMSE) is improved by 2.66 times, and the prediction accuracy of R-square (R2) is increased from 0.961 to 0.994. The results showed that RMSE and R2 were used to comprehensively predict the collected data of double-antigen SERS-ICA test strip, which could effectively improve the prediction accuracy. The internal standard algorithm can effectively solve the challenges of uneven hot spots and poor signal reproducibility on the test strip to a certain extent, so as to improve the semi-quantitative accuracy.

Trace level detection of melamine and cyanuric acid extracted from pet liquid food (milk) using a SERS Au nanogap substrate

This study reported an application of Au nanogap substrates for surface-enhanced Raman scattering (SERS) measurements to quantitatively analyze melamine and its derivative products at trace levels in pet liquid food (milk) combined with a waveband selection approach, namely variable importance in projection (VIP). Six different concentrations of melamine, cyanuric acid, and melamine combined with cyanuric acid were created, and SERS spectra were acquired from 550 to 1620cm-1. Detection was possible up to 200 pM for melamine-contaminated samples, and 400 pM concentration detection for other two groups. The VIP-PLSR models obtained correlation coefficient (R2) values of 0.997, 0.985, and 0.981, with root mean square error of prediction (RMSEP) values of 18.492 pM, 19.777 pM, and 15.124 pM for prediction datasets. Additionally, partial least square discriminant analysis (PLS-DA) was used to classify both pure and different concentrations of spiked samples. The results showed that the maximum classification accuracy for melamine was 100%, for cyanuric acid it was 96%, and for melamine coupled with cyanuric acid it was 95%. The results obtained clearly demonstrated that the Au nanogap substrate offers low-concentration, rapid, and efficient detection of hazardous additive chemicals in pet consuming liquid food.

Hydrogel SERS chip with strong localized surface plasmon resonance for sensitive and rapid detection of T-2 toxin

T-2 toxin is one of the naturally dangerous food contaminants, which is harmful to people and animals. Because of its strong toxicity and wide distribution, it is vital to develop a rapid and effective method for the detection of T-2 toxin. Herein, an excellent hydrogel surface-enhanced Raman scattering (SERS) chip is constructed for developing a novel SERS sensor to detect T-2 toxin using a portable Raman spectrometer. The SERS chip is prepared by in-situ Ca2+-mediated assembly of silver nanoparticles (AgNPs) in PVA solution, followed by a physical crosslinking possess. The assembled AgNPs produces a strong localized surface plasmon resonance (LSPR) at around 532 nm, which enables the high activity of SERS chip under the irradiation of 532 nm laser. Additionally, the unique structure of hydrogel makes the obtained chip show excellent reliability and anti-interference ability in detection. As a result, the developed SERS sensor shows many obvious advantageous including free of complex sample pretreatment (only a simple extraction), fast response (5 min), low limit of detection (0.41 ppb), wide detection range (1-10000 ppb), good recoveries (90.26-101.81 %) and relative standard deviations (2.8-6.7 %). Therefore, this SERS sensor provides a promising choice for rapid scanning and sensitive detection of trace T-2 toxin in complex matrices.

Biomass-assisted fabrication of rGO-AuNPs as surface-enhanced Raman scattering substrates for in-situ monitoring methylene blue degradation

Reduced graphene oxide-gold nanoparticles nanocomposites (rGO-AuNPs) with high surface-enhanced Raman scattering (SERS) activity was created by biomass-assisted green synthesis with Lilium casa blanca petals biomass for the first time, and its application for methylene blue (MB) degradation was explored through in-situ monitoring. Lilium casa blanca petals biomass was used as a reducing agent to reduce GO and chloroauric acid successively when carrying out rGO-AuNPs in-situ synthesis while it also acted as a capping agent. The produced rGO had oxygen-containing functional groups which had an outstanding performance in enhancing the SERS effect. Characterization results confirmed that the AuNPs were grafted onto the rGO sheet, and the mechanism study showed that total flavonoids in Lilium casa blanca petals biomass were the main biological compounds involved in the reduction. rGO-AuNPs had a high Raman enhancement factor (EF) which could reach 3.88 × 10⁷. The synthesized nanocomposite also had a good catalytic activity that could be employed as catalyst in MB degradation, and it could complete degradation within 15min. The reaction rate increased linearly with the amount of rGO-AuNPs, and the degradation could be in-situ monitored both by UV and SERS.

Raman spectroscopy: Principles and recent applications in food safety

Food contaminant is a significant issue because of the adverse effects on human health and economy. Traditional detection methods such as liquid chromatography-mass spectroscopy for detecting food contaminants are expensive and time-consuming, and require highly-trained personnel and complicated sample pretreatment. Raman spectroscopy is an advanced analytical technique in a manner of non-destructive, rapid, cost-effective, and ultrasensitive sensing various hazards in agri-foods. In this chapter, we summarized the principle of Raman spectroscopy and surface enhanced Raman spectroscopy, the methods to process Raman spectra, the recent applications of Raman/SERS (surface-enhanced Raman spectroscopy) in detecting chemical contaminants (e.g., pesticides, antibiotics, mycotoxins, heavy metals, and food adulterants) and microbiological hazards (e.g., Salmonella, Campylobacter, Shiga toxigenic E. coli, Listeria, and Staphylococcus aureus) in foods.

HPTLC+SRES screening of pesticide for point-of-care application as shown with thiram in juice

In this study, a HPTLC-platformed SERS detection was established for screening thiram in juice. After a simple extraction, the sample liquid was separated on HPTLC plates, which resulted in a specific zone for the analyte. Following infiltration with atomize water, the band of interest was easily scraped off and eluted. In parallel, a flexible and SERS-active substrate was fabricated by the in-situ synthesis of gold nanoparticles within cotton fabrics. Under optimized conditions, fingerprint-like signal at 1376 cm^-1 of the analyte were easily recorded by a hand-held Raman spectrometer with enough LOD (0.5 mg/L), LOQ (0.9 mg/L) and reproducibility (<11.7%). The optimized screening system was further validated with pear, apple and mango juice by determining the spike-and-recovery rates (75.6 to 112.8%). It was demonstrated that this method could be a facile point-of-care testing system tailored for pesticide screening.

CNN-assisted SERS enables ultra-sensitive and simultaneous detection of Scr and BUN for rapid kidney function assessment

Kidney disease is highly prevalent and may result in severe clinical outcomes. Serum creatinine (Scr) and blood urea nitrogen (BUN) are the most widely used biomarkers for kidney function assessment, yet when measured alone, the result can be affected by a variety of parameters such as age, gender, protein consumption, etc. Measuring Scr and BUN simultaneously can eliminate most of the external influences and greatly improve the assessment of kidney function. In this study, a real-time kidney function assessment system based on dual biomarker detection was proposed. Scr and BUN were determined using surface-enhanced Raman scattering (SERS) within the concentration range of 10^-1 to 10^-6 M and 0.28 to 100 mg dl^-1, respectively. A one-dimensional convolutional neural network (1D-CNN) model was employed to quantitatively analyze the concentration of biomarkers from the SERS spectral measurements. Moreover, we simulated a variety of kidney health conditions with 16 groups of mixed Scr and BUN in serum. The proposed CNN-assisted SERS method was used to quantify both biomarkers and provide diagnostic results. The Au core-Ag shell nanoprobes provided ultra-sensitive SERS detection and the CNN model achieved excellent regression results with an R² of 0.9871 in the testing dataset. The system demonstrated a rapid and robust evaluation for the assessment of kidney function, providing a promising idea for medical diagnosis with the help of spectroscopy and deep learning methods.

FT-IR combined with chemometrics in the quality evaluation of Nongxiangxing baijiu

Recently, there has been an increasing demand for developing a reliable method to assess the quality of liquor in the baijiu industry quickly and accurately. The present study sought to establish a strategy for rapid quantitative analysis of the primary flavor components in Nongxiangxing baijiu. Under the experimental conditions, 7 of the 10 major flavor components in Nongxiangxing baijiu could be quantified effectively, such as ethyl butyrate (R²p = 0.9942), ethyl lactate (R²p = 0.9438), n-butanol (R²p = 0.9048), isobutanol (R²p = 0.9696), acetic acid (R²p = 0.9600), butyric acid (R²p = 0.8448), caproic acid (R²p = 0.9971). This result indicates that FT-IR combined with quantitative chemometric modeling could be a potential approach for rapid quality assessment of Nongxiangxing baijiu. Overall, this study provides a theoretical basis for subsequent related studies on Nongxiangxing baijiu.

Arrays of Ag-nanoparticles decorated TiO2 nanotubes as reusable three-dimensional surface-enhanced Raman scattering substrates for molecule detection

Three-dimensional surface-enhanced Raman scattering (SERS) substrates usually provide more hot spots in the excitation light beam and higher sensitivity when compared with the two-dimensional counterpart. Here a simple approach is presented for the fabrication of arrays of Ag-nanoparticles decorated TiO2 nanotubes. Arrays of ZnO nanorods were fabricated in advance by a hydrothermal method. Then TiO2 nanotube arrays were achieved by immersing the arrays of ZnO nanorods in an aqueous solution of (NH4)2TiF6 for 1.5 h. Vertically aligned TiO2 nanotube arrays were modified with dense Ag nanoparticles by Ag mirror reaction. High density of Ag nanoparticles decorated on the fabricated TiO2 nanotubes provide plenty of hotspots for Raman enhancement. In addition, the fabricated array of Ag nanoparticles modified TiO2 nanotubes can serve as a reusable SERS substrate because of the photocatalytic activity of the TiO2 nanotubes. The SERS substrate adsorbed with analyte molecules can realize self-cleaning in deionized water after UV irradiation for 2.5 h. The sensitivity of the fabricated SERS substrate was investigated by the detection of organic dye molecules. The detectable concentration limits of rhodamine 6G (R6G), malachite green (MG) and methylene blue (MB) were found to be 10−12 M, 10−9 M and 10−8 M, respectively. The enhancement factor (EF) of the three-dimensional SERS substrate was estimated to be as high as ∼1.4×108. Therefore, the prepared Ag nanoparticles modified TiO2 nanotube arrays have promising potentials to be applied to rapid and trace SERS detection of organic chemicals.

Photonic crystal sensor for melamine based on magnetic molecularly imprinted nanoparticles self-assembled with an amphiphilic random copolymer

Magnetic molecularly imprinted nanoparticles (MMINPs) were obtained with a one-step process through miniemulsion self-assembly using an amphiphilic random copolymer as both an emulsifier and MMINP coating, oleic acid-modified magnetite nanoparticles as magnetic cores, and melamine (MEL) as the template molecule. MMINPs were assembled under an external magnetic field to construct photonic crystal (PC) sensor for naked-eye detection of MEL. The MMINPs were characterized by FT-IR, TEM, TGA, and VSM. The analytical performances of the magnetic molecularly imprinted PC sensor for MEL (MEL-MMIPCs) were investigated with respect to sensitivity, response time, selectivity, and stability. As the MEL concentration increases from 1.0 to 1.0 × 10⁶ μg/l, the reflection wavelength of MEL-MMIPCs shifted from 497 to 709 nm, and was linear with the logarithm of MEL concentration in this range. The detection limit was 0.21 μg/l (S/N = 3) and response time was within 30 s. The MEL-MMIPC sensor had an imprinting factor of 5.09, and selectivity factors for the analogs cyanuric acid and atrazine were 8.76 and 5.75, respectively, indicating the high sensitivity and selectivity. After 10 cycles of elution/response, MEL-MMIPCs still had a good ability to recognize MEL.

Dielectric Walls/Layers Modulated 3D Periodically Structured SERS Chips: Design, Batch Fabrication, and Applications

As an indispensable constituent of plasmonic materials/dielectrics for surface enhanced Raman scattering (SERS) effects, dielectrics play a key role in excitation and transmission of surface plasmons which however remain more elusive relative to plasmonic materials. Herein, different roles of vertical dielectric walls, and horizontal and vertical dielectric layers in SERS via 3D periodic plasmonic materials/dielectrics structures are studied. Surface plasmon polariton (SPP) interferences can be maximized within dielectric walls besieged by plasmonic layers at the wall thicknesses of integral multiple half-SPP_{plasmonic material-dielectric} -wavelength which effectively excites localized surface plasmon resonance to improve SERS effects by one order of magnitude compared to roughness and/or nanogaps only. The introduction of extra Au nanoparticles on thin dielectric layers can further enhance SERS effects only slightly. Thus, the designed Au/SiO₂ based SERS chips show an enhancement factor of 8.9 × 10¹⁰ , 265 times higher relative to the chips with far thinner SiO₂ walls. As many as 1200 chips are batch fabricated for a 4 in wafer using cost-effective nanoimprint lithography which can detect trace Hg ions as low as 1 ppt. This study demonstrates a complete generalized platform from design to low-cost batch-fabrication to applications for novel high performance SERS chips of any plasmonic materials/dielectrics.

Ferrocene-Doped Polystyrene Nanoenzyme and DNAzyme Cocatalytic SERS Quantitative Assay of Ultratrace Pb2+

A new, stable and high-catalytic activity ferrocene-doped polystyrene nanosphere (PN_Fer) sol was prepared by the hydrogel procedure and characterized by electron microscopy and molecular spectroscopy. Results show that the nanosol exhibits excellent catalysis of the new indicator nanoreaction between AgNO₃ and sodium formate to generate nanosilver with strong surface-enhanced Raman scattering (SERS), resonance Rayleigh scattering (RRS) and surface plasmon resonance absorption (Abs) trimode molecular spectral signals. This new nanocatalytic amplification trimode indicator reaction was coupled with the G-quadruplex DNAzyme catalytic amplification of Pb²⁺ aptamer to fabricate a new SERS quantitative/RRS/Abs assay platform for the determination of ultratrace amounts of Pb²⁺. The Pb²⁺ content in water samples was analyzed with satisfactory results.

Flexible SERS substrate of silver nanoparticles on cotton swabs for rapid in situ detection of melamine

It is important to be able to detect melamine via a sensitive and fast method in the field of food safety. Surface-enhanced Raman scattering (SERS) has attracted much attention due to its high sensitivity, rapid results, unique spectroscopic fingerprint, and nondestructive data acquisition. In this work, we describe the preparation of flexible CS-ATS-Ag cotton swabs for use in SERS by anchoring silver nanoparticles (AgNPs), as a highly-sensitive SERS material, on cotton swabs (CS) using N-[3-(trimethoxysilyl)propyl] diethylenetriamine (ATS) as the coupling agent. The flexible CS-ATS-Ag cotton swabs exhibited high SERS sensitivity, uniformity and reproducibility as a melamine molecule probe, and the limit of detection was calculated to be 0.2 ppm. A high SERS signal reproducibility was achieved, and the relative standard deviation (RSD) of the melamine peak at 699 cm^-1 was approximately 5.01%. Moreover, we successfully developed Chemical analysis App application software; a smartphone was used to convert data and record the results, then the data were geotagged using the GPS feature in the smartphone and uploaded to a central website. The goal of realizing instant transmission, timely processing, high sensitivity, portability and low cost was therefore achieved.

A novel aptamer RRS assay platform for ultratrace melamine based on COF-loaded Pd nanocluster catalytic amplification

Two COFs of BzBD and BzBD loaded Pd nanoclusters (BzBD_Pd) were prepared using 1,3,5-benzenetricarboxaldehyde (Bz), benzidine (BD) and CO reducing agent, and were characterized by transmission electron microscopy (TEM), X-ray powder diffraction (XRD), infrared spectroscopy (IR) and other techniques. BzBD_Pd can strongly catalyze the new and stable Au@NiP nanoreaction that exhibit a strong resonance Rayleigh scattering (RRS) peak at 538 nm and a surface plasmon resonance (SPR) absorption peak at 395 nm, and the sensitive and facile RRS technique was used to study the indicator reaction. Combining the nanocatalytic amplification reaction with specific aptamer (Apt) of some target molecules such as melamine (ML), urea (UR) and bisphenol A (BPA), a simple, sensitive and selective Apt RRS assay platform was established. The linear range of the RRS detection platform for melamine is 0.0025-0.04 nmol/L, and the detection limit (DL) is 1.96 × 10^-4 nmol/L. In addition, ML in real sample was analyzed, the stability of BzBD, BzBD_Pd, PdNPs and the catalytic mechanism of COF_Pd were also considered.