Sensors for Detection of the Synthetic Dye Rhodamine in Environmental Monitoring Based on SERS

Rapid and sensitive detection of pharmaceutical pollutants in aquaculture by aluminum foil substrate based SERS method combined with deep learning algorithm

BACKGROUND

Pharmaceutical residual such as antibiotics and disinfectants in aquaculture wastewater have significant potential risks for environment and human health. Surface enhanced Raman spectroscopy (SERS) has been widely used for the detection of pharmaceuticals due to its high sensitivity, low cost, and rapidity. However, it is remain a challenge for high-sensitivity SERS detection and accurate identification of complex pollutants.

RESULTS

Hence, in this work, we developed an aluminum foil (AlF) based SERS detection substrate and established a multilayer perceptron (MLP) deep learning model for the rapid identification of antibiotic components in a mixture. The detection method demonstrated exceptional performance, achieving a high SERS enhancement factor of 4.2 × 105 and excellent sensitivity for trace amounts of fleroxacin (2.7 × 10-8 mol/L), levofloxacin (1.95 × 10-8 mol/L), and pefloxacin (6.9 × 10-8 mol/L),sulfadiazine, methylene blue, and malachite green at a concentration of 1 × 10-8 mol/L can all be detected, the concentrations of the six target compounds and their Raman intensities exhibit a good linear relationship. Moreover, the AlF SERS substrate can be prepared rapidly without adding organic reagents, and it exhibited good reproducibility, with RSD<9.6 %. Additionally, the algorithm model can accurately identify the contaminants mixture of sulfadiazine, methylene blue, and malachite green with a recognition accuracy of 97.8 %, an F1-score of 98.2 %, and a 5-fold cross validation score of 97.4 %, the interpretation analysis using Shapley Additive Explanations (SHAP) reveals that MLP model can specifically concentrate on the distribution of characteristic peaks.

SIGNIFICANCE

The experimental results indicated that the MLP model demonstrated strong performance and good robustness in complex matrices. This research provides a promising detection and identification method for the antibiotics and disinfectants in actual aquaculture wastewater treatment.

A novel surface cell imprinting-assisted SERS mapping strategy for ultrasensitive bacterial detection

Surface-enhanced Raman spectroscopy (SERS) is widely used for bacterial detection; however, insufficient specificity and quantitative capability are the primary limitations of this technology. In this study, we propose a novel multi-walled carbon nanotube-modified surface cell-imprinting SERS mapping platform that can specifically and quantitatively detect bacteria. This method utilizes a multi-walled carbon nanotube-modified surface cell-imprinting film as a substrate through which Salmonella typhimurium (S. typhimurium) is captured and labeled with SERS tags, generating an enhanced SERS signal indicating target capture. The specificity of this method is demonstrated by comparing its detection of five non-target bacteria. The SERS mapping platform exhibits strong quantification capability for S. typhimurium, with a broad linear range from 102 to 108 CFU/mL and a detection limit of approximately 1.49 CFU/mL. Notably, the SERS mapping platform can effectively detect S. typhimurium in chicken samples for early monitoring of contamination. By fabricating different multiwalled carbon nanotube-modified surface cell-imprinted films, the platform can be adapted to detect additional bacteria or other targets, offering a new approach for practical sample detection.

Detection of hyaluronidase in urine using hyaluronic acid-coated silver nanoparticles-based surface-enhanced Raman spectroscopy for the diagnosis of bladder cancer

Bladder cancer, a malignancy of the urinary tract, has shown a rising incidence rate in recent years. Current diagnostic methods often suffer from issues such as invasiveness, high costs, or insufficient sensitivity, creating an urgent need for a fast, simple, and non-invasive diagnostic approach. In this study, a novel diagnostic method for bladder cancer is proposed, using hyaluronic acid-coated silver nanoparticles (HA-AgNPs) as the substrate for surface-enhanced Raman scattering (SERS) to detect hyaluronidase (HAase), a biomarker for bladder cancer, in urine. This method is based on the hydrolysis of hyaluronic acid on HA-AgNPs by HAase, which generates oligomers and causes the breakdown of HA-AgNPs into smaller nanoparticles. The formation of oligomers enhances the surface shielding effect of the silver nanoparticles, promoting aggregation between particles and significantly weakening the SERS signal. By detecting changes in the SERS signal using Rhodamine (R6G), HAase was quantified. The experimental results show that there is a good linear relationship (R2 = 0.9991) between the SERS signal and the HAase concentration in the range of 3 × 10-4 U/mL to 3 × 101 U/mL. The method demonstrates high sensitivity and can effectively detect HAase concentration in urine. Combining principal component analysis (PCA) with linear discriminant analysis (LDA), effective classification of SERS spectra from 42 normal and 40 bladder cancer urine samples was achieved. Experimental results show that the sensitivity and specificity of this algorithm in distinguishing between the normal and bladder cancer groups reached 95.2 % and 95 %, respectively.

Recent Developments in SERS Microfluidic Chips: From Fundamentals to Biosensing Applications

This paper reviews the latest research progress of surface-enhanced Raman spectroscopy (SERS) microfluidic chips in the field of biosensing. Due to its single-molecule sensitivity, selectivity, minimal or no preprocessing, and immediacy, SERS is considered a promising biosensing technology. However, the nondirectional interactions between biological samples and the substrate, as well as fluctuations in the sample environment temperature during signal acquisition, can affect the stability and reproducibility of SERS signals. Integrating SERS spectroscopy with microfluidic chips not only leverages the continuous sample flow, high reaction efficiency, high throughput, and multifunctionality of microfluidic chips to address challenges in biosensing applications but also expands the scope of microfluidic technology by providing a novel on-chip optical detection method. The combination of SERS and microfluidic chips not only enables the complementary advantages of both technologies but also offers a highly promising "combined technology" for the field of biosensing. This paper starts by introducing the enhancement mechanisms of SERS and presents both labeled and label-free SERS strategies. Based on the differences in substrate properties, we broadly categorize SERS microfluidic chips into colloidal nanoparticle-based SERS microfluidic chips and fixed substrate-based SERS microfluidic chips. Finally, we review the latest research progress on SERS microfluidic chips for biosensing biological targets such as nucleic acids, proteins, small biomolecules, and live cells. In the conclusion and outlook section, we summarize the challenges faced by SERS microfluidic chips in biosensing and propose feasible solutions. To better leverage the role of SERS microfluidic chips in biosensing, we also present an outlook on the future development of this combined technology.

Label-free detection of kidney stones urine combined with SERS and multivariate statistical algorithm

Kidney stones are a common urological disease with an increasing incidence worldwide. Traditional diagnostic methods for kidney stones are relatively complex and time-consuming, thus necessitating the development of a quicker and simpler diagnostic approach. This study investigates the clinical screening of kidney stones using Surface-Enhanced Raman Scattering (SERS) technology combined with multivariate statistical algorithms, comparing the classification performance of three algorithms (PCA-LDA, PCA-LR, PCA-SVM). Urine samples from 32 kidney stone patients, 30 patients with other urinary stones, and 36 healthy individuals were analyzed. SERS spectra data were collected in the range of 450-1800 cm-1 and analyzed. The results showed that the PCA-SVM algorithm had the highest classification accuracy, with 92.9 % for distinguishing kidney stone patients from healthy individuals and 92 % for distinguishing kidney stone patients from those with other urinary stones. In comparison, the classification accuracy of PCA-LR and PCA-LDA was slightly lower. The findings indicate that SERS combined with PCA-SVM demonstrates excellent performance in the clinical screening of kidney stones and has potential for practical clinical application. Future research can further optimize SERS technology and algorithms to enhance their stability and accuracy, and expand the sample size to verify their applicability across different populations. Overall, this study provides a new method for the rapid diagnosis of kidney stones, which is expected to play an important role in clinical diagnostics.

Rhodamine and related substances in food: Recent updates on pretreatment and analysis methods

Rhodamine, a colorant prohibited in various consumer products due to its demonstrated carcinogenic, mutagenic, and toxic properties, necessitates the development of a straightforward, efficient, sensitive, environmentally friendly, and cost-effective analytical method. This review provides an overview of recent advancements in the pretreatment and determination techniques for rhodamine across diverse sample matrices since 2017. Sample preparation methods encompass both commonly used pretreatment techniques such as filtration, centrifugation, solvent extraction, and cloud point extraction, as well as innovative approaches including solid phase extraction, dispersive liquid-liquid microextraction, hollow fiber liquid phase microextraction, magnetic solid phase extraction, and matrix solid phase dispersion. The analytical techniques encompass high performance liquid chromatography, surface-enhanced Raman scattering, and sensor-based methods. Furthermore, a comprehensive examination is conducted to offer insights for future research on rhodamine regarding the advantages, disadvantages, and advancements in various pretreatment and determination methodologies.

Bioelectrochemical biosensors for water quality assessment and wastewater monitoring

Bioelectrochemical biosensors offer a promising approach for real-time monitoring of industrial bioprocesses. Many bioelectrochemical biosensors do not require additional labelling reagents for target molecules. This simplifies the monitoring process, reduces costs, and minimizes potential contamination risks. Advancements in materials science and microfabrication technologies are paving the way for smaller, more portable bioelectrochemical biosensors. This opens doors for integration into existing bioprocessing equipment and facilitates on-site, real-time monitoring capabilities. Biosensors can be designed to detect specific heavy metals such as lead, mercury, or chromium in wastewater. Early detection allows for the implementation of appropriate removal techniques before they reach the environment. Despite these challenges, bioelectrochemical biosensors offer a significant leap forward in wastewater monitoring. As research continues to improve their robustness, selectivity, and cost-effectiveness, they have the potential to become a cornerstone of efficient and sustainable wastewater treatment practices.

Fabrication and Application of Ag@SiO2/Au Core-Shell SERS Composite in Detecting Cu2+ in Water Environment

A sensitive and simple method for detecting Cu2+ in the water source was proposed by using surface-enhanced Raman scattering spectroscopy (SERS) based on the Ag@SiO2/Au core-shell composite. The Ag@SiO2 SERS tag was synthesized by a simple approach, in which Ag nanoparticles were first embedded with Raman reporter PATP and next coated with a SiO2 shell. The Ag@SiO2 nanoparticles had strong stability even in a high-concentration salty solution, and there were no changes to their properties and appearance within one month. The Ag@SiO2/Au composite was fabricated through a controllable self-assemble process. L-cysteine was decorated on the surface of a functionalized Ag@SiO2/Au composite, as the amino and carboxyl groups of it can form coordinate covalent bond with Cu2+, which shows that the Ag@SiO2/Au composite labelled with L-cysteine has excellent performance for the detection of Cu2+ in aqueous media. In this study, the SERS detection of Cu2+ was carried out using Ag@SiO2 nanoparticles, and the limit of detection (LOD) as low as 0.1 mg/L was achieved.

Enhanced Photoluminescence of R6G Dyes from Metal Decorated Silicon Nanowires Fabricated through Metal Assisted Chemical Etching

In this study, we developed active substrates consisting of Ag-decorated silicon nanowires on a Si substrate using a single-step Metal Assisted Chemical Etching (MACE) process, and evaluated their performance in the identification of low concentrations of Rhodamine 6G using surface-enhanced photoluminescence spectroscopy. Different structures with Ag-aggregates as well as Ag-dendrites were fabricated and studied depending on the etching parameters. Moreover, the addition of Au nanoparticles by simple drop-casting on the MACE-treated surfaces can enhance the photoluminescence significantly, and the structures have shown a Limit of Detection of Rhodamine 6G down to 10-12 M for the case of the Ag-dendrites enriched with Au nanoparticles.