Colloidal gold clusters formation and chemometrics for direct SERS determination of bioanalytes in complex media

New insights into the surface Enhanced Raman Scattering (SERS) response of adenine using chemometrics

The SERS response of adenine is one of the most studied, due to its outstanding exaltation. However, the spectra obtained strongly differ according to the experimental conditions and still remain not well understood. To be able to search for the presence of this molecule in complex environments, it is essential to better understand the SERS response of adenine alone. After a brief presentation of the literature on the subject, we present results suggesting that the experimental spectra would result from the overlap of different spectroscopic signatures, that may probably be due to different non-covalent interactions or different electromagnetic fields experienced by adenine molecules. An independent component analysis is reported. Our results underline the difficulty to precisely analyze the experimental data, the need to continue this research and to constitute data banks that would allow comparing the spectra obtained in different laboratories according to the experimental conditions.

Layer-by-Layer Biopolymer Assembly for the In Situ Fabrication of AuNP Plasmonic Paper-A SERS Substrate for Food Adulteration Detection

Here, we introduce an environmentally friendly approach to fabricate a simple and cost-effective plasmonic paper for detecting food additives using surface-enhanced Raman spectroscopy (SERS). The plasmonic paper is fabricated by in situ growth of gold nanoparticles (AuNPs) on filter paper (FP). To facilitate this green fabrication process, we applied a double-layered coating of biopolymers, chitosan (CS) and alginate (ALG), onto the FP using a layer-by-layer (LbL) assembly through electrostatic interactions. Compared to single-layer biopolymer coatings, double-layered biopolymer-coated paper, ALG/CS/FP, significantly improves the reduction properties. Consequently, effective in situ growth of AuNPs can be achieved as seen in high density of AuNP formation on the substrate. The resulting plasmonic paper provides high SERS performance with an enhancement factor (EF) of 5.7 × 1010 and a low limit of detection (LOD) as low as 1.37 × 10-12 M 4-mercaptobenzoic acid (4-MBA). Furthermore, it exhibits spot-to-spot reproducibility with a relative standard deviation (RSD) of 8.2% for SERS analysis and long-term stability over 50 days. This paper-based SERS substrate is applied for melamine (MEL) detection with a low detection limit of 0.2 ppb, which is sufficient for monitoring MEL contamination in milk based on food regulations. Additionally, we demonstrate a simultaneous detection of β-agonists, including ractopamine (RAC) and salbutamol (SAL), exhibiting the multiplexing capability and versatility of the plasmonic paper in food contaminant analysis. The development of this simple plasmonic paper through the LbL biopolymer assembly not only paves the way for novel SERS substrate fabrication but also broadens the application of SERS technology in food contaminant monitoring.

Self-Assembly of Silver Nanowire Films for Surface-Enhanced Raman Scattering Applications

The development of SERS detection technology is challenged by the difficulty in obtaining SERS active substrates that are easily prepared, highly sensitive, and reliable. Many high-quality hotspot structures exist in aligned Ag nanowires (NWs) arrays. This study used a simple self-assembly method with a liquid surface to prepare a highly aligned AgNW array film to form a sensitive and reliable SERS substrate. To estimate the signal reproducibility of the AgNW substrate, the RSD of SERS intensity of 1.0 × 10^-10 M Rhodamine 6G (R6G) in an aqueous solution at 1364 cm^-1 was calculated to be as low as 4.7%. The detection ability of the AgNW substrate was close to the single molecule level, and even the R6G signal of 1.0 × 10^-16 M R6G could be detected with a resonance enhancement factor (EF) as high as 6.12 × 10¹¹ under 532 nm laser excitation. The EF without the resonance effect was 2.35 × 10⁶ using 633 nm laser excitation. FDTD simulations have confirmed that the uniform distribution of hot spots inside the aligned AgNW substrate amplifies the SERS signal.

Unraveling surface-enhanced Raman spectroscopy results through chemometrics and machine learning: principles, progress, and trends

Surface-enhanced Raman spectroscopy (SERS) has gained increasing attention because it provides rich chemical information and high sensitivity, being applicable in many scientific fields including medical diagnosis, forensic analysis, food control, and microbiology. Although SERS is often limited by the lack of selectivity in the analysis of samples with complex matrices, the use of multivariate statistics and mathematical tools has been demonstrated to be an efficient strategy to circumvent this issue. Importantly, since the rapid development of artificial intelligence has been promoting the implementation of a wide variety of advanced multivariate methods in SERS, a discussion about the extent of their synergy and possible standardization becomes necessary. This critical review comprises the principles, advantages, and limitations of coupling SERS with chemometrics and machine learning for both qualitative and quantitative analytical applications. Recent advances and trends in combining SERS with uncommonly used but powerful data analysis tools are also discussed. Finally, a section on benchmarking and tips for selecting the suitable chemometric/machine learning method is included. We believe this will help to move SERS from an alternative detection strategy to a general analytical technique for real-life applications.

Nanotechnology-Enabled Biosensors: A Review of Fundamentals, Design Principles, Materials, and Applications

Biosensors are modern engineering tools that can be widely used for various technological applications. In the recent past, biosensors have been widely used in a broad application spectrum including industrial process control, the military, environmental monitoring, health care, microbiology, and food quality control. Biosensors are also used specifically for monitoring environmental pollution, detecting toxic elements' presence, the presence of bio-hazardous viruses or bacteria in organic matter, and biomolecule detection in clinical diagnostics. Moreover, deep medical applications such as well-being monitoring, chronic disease treatment, and in vitro medical examination studies such as the screening of infectious diseases for early detection. The scope for expanding the use of biosensors is very high owing to their inherent advantages such as ease of use, scalability, and simple manufacturing process. Biosensor technology is more prevalent as a large-scale, low cost, and enhanced technology in the modern medical field. Integration of nanotechnology with biosensors has shown the development path for the novel sensing mechanisms and biosensors as they enhance the performance and sensing ability of the currently used biosensors. Nanoscale dimensional integration promotes the formulation of biosensors with simple and rapid detection of molecules along with the detection of single biomolecules where they can also be evaluated and analyzed critically. Nanomaterials are used for the manufacturing of nano-biosensors and the nanomaterials commonly used include nanoparticles, nanowires, carbon nanotubes (CNTs), nanorods, and quantum dots (QDs). Nanomaterials possess various advantages such as color tunability, high detection sensitivity, a large surface area, high carrier capacity, high stability, and high thermal and electrical conductivity. The current review focuses on nanotechnology-enabled biosensors, their fundamentals, and architectural design. The review also expands the view on the materials used for fabricating biosensors and the probable applications of nanotechnology-enabled biosensors.

MCR-ALS with sample insertion constraint to enhance the sensitivity of surface-enhanced Raman scattering detection

The multivariate curve resolution-alternative least squares (MCR-ALS) algorithm was modified with sample insertion constraint to deconvolute the overlapping peaks in SERS spectra. The developed method was evaluated by the spectral data simulated using a Gaussian distribution function to generate two independent peaks corresponding to a capping agent and an analyte. The spectra were generated with different overlapping levels and various intensity ratios of the analyte to the capping agent. By using MCR-ALS with the sample insertion constraint, the peak of the capping agent was completely excluded to obtain a calibration model of the analyte with R² > 0.95 under all conditions. Furthermore, our developed method was later applied to a real SERS measurement to quantify carbofuran (analyte) using the azo-coupling reaction with p-ATP (capping agent) on silver nanoparticles as a SERS substrate. A calibration model of derivative carbofuran phenol was generated with R² = 0.99 and LOD = 28.19 ppm. To assess the performance of the calibration model, the model was used to estimate the concentration of carbofuran in an external validation set. It was found that the RMSE of prediction was only 2.109 with a promising R² = 0.97.

Advancing Biosensors with Machine Learning

Chemometrics play a critical role in biosensors-based detection, analysis, and diagnosis. Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved impressive advances. However, novel advanced ML methods, especially deep learning, which is famous for image analysis, facial recognition, and speech recognition, has remained relatively elusive to the biosensor community. Herein, how ML can be beneficial to biosensors is systematically discussed. The advantages and drawbacks of most popular ML algorithms are summarized on the basis of sensing data analysis. Specially, deep learning methods such as convolutional neural network (CNN) and recurrent neural network (RNN) are emphasized. Diverse ML-assisted electrochemical biosensors, wearable electronics, SERS and other spectra-based biosensors, fluorescence biosensors and colorimetric biosensors are comprehensively discussed. Furthermore, biosensor networks and multibiosensor data fusion are introduced. This review will nicely bridge ML with biosensors, and greatly expand chemometrics for detection, analysis, and diagnosis.

Silver-Based SERS Pico-Molar Adenine Sensor

Adenine is an important molecule for biomedical and agricultural research and applications. The detection of low concentration adenine molecules is thus desirable. Surface-enhanced Raman scattering (SERS) is a promising label-free detection and fingerprinting technique for molecules of significance. A novel SERS sensor made of clusters of silver nanostructures deposited on copper bumps in valleys of an etched silicon substrate was previously reported to exhibit a low and reproducible detection limit for a 10⁻¹¹ M neutral adenine aqueous solution. Reflection of laser illumination from the silicon surface surrounding a valley provides additional directions of laser excitation to adenine molecules adsorbing on a silver surface for the generation of enhanced SERS signal strength leading to a low detection limit. This paper further reports a concentration dependent shift of the ring-breathing mode SERS adenine peak towards 760 cm⁻¹ with decreasing concentration and its pH-dependent SERS signal strength. For applications, where the pH value can vary, reproducible detection of 10⁻¹² M adenine in a pH 9 aqueous solution is feasible, making the novel SERS structure a desirable pico-molar adenine sensor.

Silver SERS Adenine Sensors with a Very Low Detection Limit

The detection of adenine molecules at very low concentrations is important for biological and medical research and applications. This paper reports a silver-based surface-enhanced Raman scattering (SERS) sensor with a very low detection limit for adenine molecules. Clusters of closely packed silver nanoparticles on surfaces of discrete ball-like copper bumps partially covered with graphene are deposited by immersion in silver nitrate. These clusters of silver nanoparticles exhibit abundant nanogaps between nanoparticles, where plasmonic coupling induces very high local electromagnetic fields. Silver nanoparticles growing perpendicularly on ball-like copper bumps exhibit surfaces of large curvature, where electromagnetic field enhancement is high. Between discrete ball-like copper bumps, the local electromagnetic field is low. Silver is not deposited on the low-field surface area. Adenine molecules interact with silver by both electrostatic and functional groups and exhibit low surface diffusivity on silver surface. Adenine molecules are less likely to adsorb on low-field sensor surface without silver. Therefore, adenine molecules have a high probability of adsorbing on silver surface of high local electric fields and contribute to the measured Raman scattering signal strength. We demonstrated SERS sensors made of clusters of silver nanoparticles deposited on discrete ball-like copper bumps with very a low detection limit for detecting adenine water solution of a concentration as low as 10⁻¹¹ M.

Development and application of fluorescence sensor and test strip based on molecularly imprinted quantum dots for the selective and sensitive detection of propanil in fish and seawater samples

Molecularly imprinted quantum dots (MIP-QDs) were successfully synthesized via reversed-phase microemulsion and used as the specific recognition element and signal probe of a fluorescence sensor or test strip to achieve the highly sensitive detection of propanil. The physical-chemical characteristics and excellent selectivity of MIP-QDs were elucidated. Under optimized parameters, the MIP-QDs had good linearity at the propanil concentration range of 1.0 μg/L to 20.0 × 10³ μg/L by fluorescence quenching. The developed MIP-QD-based fluorescence sensor showed good recoveries ranging from 87.2 % to 112.2 %, and the relative standard deviation was below 6.0 % for the fish and seawater samples. In addition, the limits of detection (LODs) for fish and seawater were 0.42 μg/kg and 0.38 μg/L, respectively. The fluorescence test strip developed on the basis of the MIP-QDs also displayed satisfactory recoveries of 90.1 %-111.1 %, and the LOD for propanil in the seawater sample was 0.6 μg/L. The proposed fluorescence sensor and test strip were successfully used in propanil determination in environment and aquatic products.