Plasmonic surface-enhanced Raman scattering nano-substrates for detection of anionic environmental contaminants: Current progress and future perspectives

Exploring the applications for Abscissic acid (ABA) detection using perovskite derived opto-electronic sensors

The hormone abscisic acid (ABA) is crucial in the regulation of many physiological processes in plants, particularly in stress response and developmental control. Recent developments in detection methods utilizing opto-electronic sensors have enabled a more profound comprehension of the processes linked to plant hormones, namely ABA. The present work investigates the potential uses of opto-electronic sensors produced from tailored perovskite materials for the targeted detection of ABA. Modified perovskite substrates, which are characterized by their large surface area, intense Raman scattering, and great sensitivity, provide a distinct advantage in differentiating ABA from other interfering substances present in intricate plant media. Notwithstanding the advancements in these sophisticated detection methods, there is still a significant lack of knowledge on how the distinct opto-electronic characteristics of high-purity perovskite crystals impact their ability to detect ABA. This work aims to close this gap by a thorough investigation of the production, modification, and use of sensors based on perovskite materials. This study also intends to give a thorough analysis comparing the performance of perovskite substrates with traditional substrates, with a specific focus on important characteristics including efficiency, specificity, and sensitivity. Furthermore, the objective of this study is to evaluate the capacity of perovskite substrates to surpass the constraints of conventional detection techniques, namely in terms of sensitivity and interference from competing matrix components. The objective of this work is to make novel contributions to the design and optimization of opto-electronic sensors based on perovskite materials, with the goal of achieving more accurate and dependable detection of ABA. Consequently, this could facilitate the advancement of specialized diagnostic instruments for monitoring plant hormones, so enabling the use of enhanced agricultural techniques and effective stress management in plants.

SERS-Based Local Field Enhancement in Biosensing Applications

Surface-enhanced Raman scattering (SERS) stands out as a highly effective molecular identification technique, renowned for its exceptional sensitivity, specificity, and non-destructive nature. It has become a main technology in various sectors, including biological detection and imaging, environmental monitoring, and food safety. With the development of material science and the expansion of application fields, SERS substrate materials have also undergone significant changes: from precious metals to semiconductors, from single crystals to composite particles, from rigid to flexible substrates, and from two-dimensional to three-dimensional structures. This report delves into the advancements of the three latest types of SERS substrates: colloidal, chip-based, and tip-enhanced Raman spectroscopy. It explores the design principles, distinctive functionalities, and factors that influence SERS signal enhancement within various SERS-active nanomaterials. Furthermore, it provides an outlook on the future challenges and trends in the field. The insights presented are expected to aid researchers in the development and fabrication of SERS substrates that are not only more efficient but also more cost-effective. This progress is crucial for the multifunctionalization of SERS substrates and for their successful implementation in real-world applications.

Machine Learning-Assisted Surface-Enhanced Raman Spectroscopy Detection for Environmental Applications: A Review

Surface-enhanced Raman spectroscopy (SERS) has gained significant attention for its ability to detect environmental contaminants with high sensitivity and specificity. The cost-effectiveness and potential portability of the technique further enhance its appeal for widespread application. However, challenges such as the management of voluminous quantities of high-dimensional data, its capacity to detect low-concentration targets in the presence of environmental interferents, and the navigation of the complex relationships arising from overlapping spectral peaks have emerged. In response, there is a growing trend toward the use of machine learning (ML) approaches that encompass multivariate tools for effective SERS data analysis. This comprehensive review delves into the detailed steps needed to be considered when applying ML techniques for SERS analysis. Additionally, we explored a range of environmental applications where different ML tools were integrated with SERS for the detection of pathogens and (in)organic pollutants in environmental samples. We sought to comprehend the intricate considerations and benefits associated with ML in these contexts. Additionally, the review explores the future potential of synergizing SERS with ML for real-world applications.

Recent advances of MOF-based SERS substrates in quantitative analysis of food contaminants: a review

Advancements in food-contaminant detection technologies can significantly improve food safety and human health. Surface-enhanced Raman spectroscopy (SERS) has become the preferred analytical method for food-safety detection owing to its numerous advantages, which include unique 'molecular fingerprinting' features, high sensitivity, rapid responses, and non-invasive characteristics. Raman-signal enhancements rely heavily on high-performance SERS substrates. In recent years, metal-organic framework (MOF)-based SERS substrates have gained attention as promising candidates for developing SERS technologies owing to their distinctive structures and functions. This review comprehensively examines recent advances in MOF-based SERS substrates, focusing on the main role of MOFs in SERS substrates as well as their typical categories and structures, construction methods, and representative applications in food-contaminant detection. First, the primary roles of MOFs in SERS substrates are briefly introduced. Next, a comprehensive overview of the typical categories and structures of MOF-based SERS substrates is discussed. Subsequently, a fundamental view of the general construction methods for MOF-based SERS substrates is presented. Next, the main applications of MOF-based SERS substrates for food-contaminant detection are summarised. Finally, challenges and perspectives, including improvements in SERS performance and stability, and the unification of SERS mechanisms, are addressed and discussed.

Direct Writing of SERS Substrates Using Femtosecond Laser Pulses

Achieving a high-density, repeatable, and uniform distribution of "hotspots" across the entire surface-enhanced Raman scattering (SERS) substrate is a current challenge in facilitating the efficient preparation of large-area SERS substrates. In this study, we aim to produce homogeneous surface-enhanced Raman scattering (SERS) substrates based on the strong interaction between femtosecond laser pulses and a thin film of colloidal gold nanoparticles (AuNPs). The SERS substrate we obtained consists of irregularly shaped and sharp-edged gold nanoparticle aggregates with specially extruding features; meanwhile, a large number of three-dimensional AuNP stacks are produced. The advantages of such configurations lie in the production of a high density of hotspots, which can significantly improve the SERS performance. When the laser fluence is 5.6 mJ/cm2, the substrate exhibits the best SERS enhancement effect, and a strong SERS signal can still be observed when testing the concentration of R6G at 10-8 mol/L. The enhancement factor of such SERS substrates prepared using femtosecond laser direct writing is increased by 3 orders of magnitude compared to the conventional furnace annealing process. Furthermore, the relative standard deviation for the intensities of the SERS signals was measured to be 5.1% over an area of 50 × 50 μm2, indicating a highly homogeneous SERS performance and excellent potential for practical applications.

"One-Pot" Readout Cyano-Programmable SERS-Encoded Platform Enables Ultrasensitive and Interference-Free Detection of Multitarget Bioamines

Surface-enhanced Raman spectroscopy (SERS) detection platforms with high signal-to-noise ratio in the "biological-silent" region (1800-2800 cm-1) are presently being developed for sensing and imaging applications, overcoming the limitations of traditional SERS studies in the "fingerprint" region. Herein, a series of cyano-programmable Raman reporters (RRs) operating in the "biological-silent" region were designed based on 4-mercaptobenzonitrile derivatives and then embedded in core-shell Au@Ag nanostars using a "bottom-up" strategy to provide SERS enhancement and encapsulation protection. The approach enabled the "one-pot" readout interference-free detection of multiple bioamines (histamine, tyramine, and β-phenethylamine) based on aptamer-driven magnetic-induced technology. Three cyano-encoded SERS tags resulted in separate SERS signals for histamine, tyramine, and β-phenethylamine at 2220, 2251, and 2150 cm-1, respectively. A target-specific aptamer-complementary DNA competitive binding strategy allowed the formation of microscale core-satellite assemblies between Fe3O4-based magnetic beads and the SERS tags, enabling multiple SERS signals to be observed simultaneously under a 785 nm laser excitation laser. The LODs for detection of the three bioamines were 0.61 × 10-5, 2.67 × 10-5, and 1.78 × 10-5 mg L-1, respectively. The SERS-encoded platform utilizing programmable reporters provides a fast and sensitive approach for the simultaneous detection of multiple biomarkers, paving the way for routine SERS analyses of multiple analytes in complex matrices.

Comparison of the analytical performance of two different electrochemical sensors based on a composite of gold nanorods with carbon nanomaterials and PEDOT:PSS for the sensitive detection of nitrite in processed meat products

Herein, two platforms for electrochemical sensors were developed based on a combination of gold nanorods (AuNRs) with electrochemically reduced graphene oxide (ErGO) or with multiwalled carbon nanotubes (MWCNTs) and PEDOT:PSS for nitrite detection. The first and second electrodes were denoted as AuNRs/ErGO/PEDOT:PSS/GCE and AuNRs/MWCNT/PEDOT:PSS/GCE, respectively. Both materials for electrode modifiers were then characterized using UV-Vis and Raman spectroscopy, SEM, and HR-TEM. In addition, both sensors exhibit good electrochemical and electroanalytical performance for nitrite detection when investigated using voltammetric techniques. The synergistic effect between the AuNRs and their composites enhanced the electrocatalytic activity toward nitrite oxidation compared with the unmodified electrode, and the electroanalytical performance of the second electrode was superior to the first electrode. This is because the high surface area and conductivity of the MWCNTs in the second electrode provide the highest electrochemically active area (0.1510 cm2) among the other electrodes. Moreover, the second electrode exhibited a higher value for the surface coverage and the diffusion coefficient than the first electrode for nitrite detection. The electroanalytical performances of the first and second electrode for nitrite detection in terms of concentration range are 0.8-100 μM and 0.2-100 μM, limit of detection (0.2 μM and 0.08 μM), and measurement sensitivity (0.0451 μA μM-1 cm-2 and 0.0634 μA μM-1 cm-2). Good selectivity was also shown from both sensors in the presence of NaCl, Na2SO4, Na3PO4, MgSO4, NaHCO3, NaNO3, glucose, and ascorbic acid as interfering species for nitrite detection. Furthermore, both sensors were employed to detect nitrite as a food preservative in the beef sample, and the results showed no significant difference compared with the spectrophotometric technique. These results indicate that both proposed nitrite sensors may be further applied as promising electrochemical sensing platforms for in situ nitrite detection.

A Tunable Threshold Colorimetric DNA Logic Gate for Intuitive Assessment of Chemical Contaminant Exceedance

Current molecular logic gates are predominantly focused on the qualitative assessment of target presence, which has certain limitations in scenarios requiring quantitative assessment, such as chemical contaminant monitoring. To bridge this gap, we have developed a novel DNA logic gate featuring a tunable threshold, specifically tailored to the limits of contaminants. At the core of this logic gate is a DNA-gold nanoparticle (AuNP) hybrid film that incorporates aptamer sequences to selectively bind to acetamiprid (ACE) and atrazine (ATR). Upon interaction with these contaminants, the film degrades, releasing AuNPs that, in the presence of Hg2+, catalyze the oxidation of TMB, resulting in a visible blue coloration on test paper. This aptamer-enabled process effectively establishes an OR logic gate, with ACE and ATR as inputs and the appearance of blue color as the output. A key innovation of our system is its tunable input threshold. By adjusting the concentration of Hg2+, we can fine-tune the color mutation points to match the input threshold to predefined limits, such as Maximum Residue Limits (MRLs). This alignment allows semiquantitative assessment of contaminant levels, providing intuitive visual feedback of contaminant exceedance. Validation experiments with spiked samples confirm its accuracy and reliability by closely matching HPLC results. Therefore, our colorimetric DNA logic gate is emerging as a promising tool for easy and semiquantitative monitoring of chemical contaminants across diverse applications.

Design and Construction of the Uranyl Coordination Polymer with Multifunction Stimulus Response: Fluorescent Sensors for Halide Ions and Photochromism

It can provide ideas for the use of uranium elements in the treatment of spent fuel from nuclear wastewater to explore the application potential of uranium element. Thus, it is necessary to research the structure and properties of a novel uranyl coordination polymer (CP) for uranium recovery and reuse. Herein, we designed and prepared a new uranyl CP U-CMNDI based on UO22+ and H2CMNDI (H2CMNDI = N, N'-bis(carboxymethyl)-1,4,5,8-naphthalenediimide). Structural analysis shows that two uranyl ions are connected by two parallel deprotonated CMNDI ligands to form a discrete uranyl dimer structure. U-CMNDI can act as a potential stimulus-responsive halide ion sensor by a fluorescence "turn on" response in water. The limit of detection for fluoride (F-), bromide (Br-), iodide (I-), and chloride (Cl-) is 5.00, 5.32, 5.49, and 5.73 μM, respectively. The fluorescence "turn on" behavior is based on the photoinduced electron transfer (PET) mechanism between halide ions and electron-deficient NDI cores. In addition, U-CMNDI demonstrates a color response to ultraviolet light, exhibiting reversible photochromic behavior with a notable color change. The color change mechanism can contribute to the PET process and the radical process.

Magnetic-Plasmonic Nanocomposites as Versatile Substrates for Surface-enhanced Raman Scattering (SERS) Spectroscopy

Surface-enhanced Raman scattering (SERS) spectroscopy, a highly sensitive technique for detecting trace-level analytes, relies on plasmonic substrates. The choice of substrate, its morphology, and the excitation wavelength are crucial in SERS applications. To address advanced SERS requirements, the design and use of efficient nanocomposite substrates have become increasingly important. Notably, magnetic-plasmonic (MP) nanocomposites, which combine magnetic and plasmonic properties within a single particle system, stand out as promising nanoarchitectures with versatile applications in nanomedicine and SERS spectroscopy. In this review, we present an overview of MP nanocomposite fabrication methods, explore surface functionalization strategies, and evaluate their use in SERS. Our focus is on how different nanocomposite designs, magnetic and plasmonic properties, and surface modifications can significantly influence their SERS-related characteristics, thereby affecting their performance in specific applications such as separation, environmental monitoring, and biological applications. Reviewing recent studies highlights the multifaceted nature of these materials, which have great potential to transform SERS applications across a range of fields, from medical diagnostics to environmental monitoring. Finally, we discuss the prospects of MP nanocomposites, anticipating favorable developments that will make substantial contributions to various scientific and technological areas.

Self-assembled core-shell nanoparticles with embedded internal standards for SERS quantitative detection and identification of nicotine released from snus products

Surface enhanced Raman spectroscopy (SERS) is a unique analytical technique with excellent performance in terms of sensitivity, non-destructive detection and resolution. However, due to the randomness and poor repeatability of hot spot distribution, SERS quantitative analysis is still challenging. Meanwhile, snus is a type of tobacco product that can release nicotine and other components in the mouth without burning, and the rapid detection technique based on SERS can reliably evaluate the amount of nicotine released from snus, which is of great significance for understanding its characteristics and regulating its components. Herein, the strategy was proposed to solve the feasibility of SERS quantitative detection based on self-assembled core-shell nanoparticles with embedded internal standards (EIS) due to EIS signal can effectively correct SERS signal fluctuations caused by different aggregation states and measurement conditions, thus allowing reliable quantitative SERS analysis of targets with different surface affinity. By means of process control, after the Au nanoparticles (Au NPs) were modified with 4-Mercaptobenzonitrile (4-MBN) as internal standard molecules, Ag shell with a certain thickness was grown on the surface of the AuNP@4-MBN, and then the Au@4-MBN@Ag NPs were used to regulate and control the assembly of liquid-liquid interface. The high-density nano-arrays assembled at the liquid-liquid interface ensure high reproducibility as SERS substrates, and which could be used for SERS detection of nicotine released from snus products. In addition, time-mapping research shows that this method can also be used to dynamically monitor the release of nicotine. Moreover, such destruction-free evaluation of the release of nicotine from snus products opens up new perspectives for further research about the impact of nicotinoids-related health programs.

Rapid detection of residual chlorpyrifos and pyrimethanil on fruit surface by surface-enhanced Raman spectroscopy integrated with deep learning approach

Chlorpyrifos and pyrimethanil are widely used insecticides/fungicides in agriculture. The residual pesticides/fungicides remaining in fruits and vegetables may do harm to human health if they are taken without notice by the customers. Therefore, it is important to develop methods and tools for the rapid detection of pesticides/fungicides in fruits and vegetables, which are highly demanded in the current markets. Surface-enhanced Raman spectroscopy (SERS) can achieve trace chemical detection, while it is still a challenge to apply SERS for the detection and identification of mixed pesticides/fungicides. In this work, we tried to combine SERS technique and deep learning spectral analysis for the determination of mixed chlorpyrifos and pyrimethanil on the surface of fruits including apples and strawberries. Especially, the multi-channel convolutional neural networks-gate recurrent unit (MC-CNN-GRU) classification model was used to extract sequence and spatial information in the spectra, so that the accuracy of the optimized classification model could reach 99% even when the mixture ratio of pesticide/fungicide varied considerably. This work therefore demonstrates an effective application of using SERS combined deep learning approach in the rapid detection and identification of different mixed pesticides in agricultural products.

Selective surface enhanced Raman detection and effective photocatalytic degradation of sulfonamides antibiotic based on a flexible three-dimensional chitosan/carbon nitride/silver substrate

The prevalence of sulfonamide residues in aquatic environments poses serious environmental risks, and the sensitive detection and effective degradation of sulfonamides have attracted widespread attention. Here, the environmentally friendly chitosan (CS)/carbon nitride (CN) with three-dimensional porous structure is fabricated by freeze-drying method, and subsequently a new bifunctional flexible substrate (CS/CN/Ag) is prepared by anchoring of small sized AgNPs (6 ∼ 12 nm) on CS/CN. Importantly, the CS/CN/Ag substrate shows high adsorption capacity (∼ 83.06%) for sulfamethoxazole (SMX) solution within 20 mins and the limit of detection can be as low as 7.46 × 10-9 mol·L-1 with an enhancement factor of 3.3 × 105. Also, the CS/CN/Ag substrate displays highly selective for surface-enhanced Raman spectroscopy (SERS) detection of sulfonamides and also shows excellent SERS response for SMX in hospital wastewater samples. In addition, the photocatalytic degradation efficiency of SMX could reach as high as 99.22% within 20 mins of irradiation and the CS/CN/Ag still maintains outstanding photocatalytic performance after six cycles. Moreover, the Ag content in the CS/CN/Ag substrate is only 2.35%, and also the CS/CN/Ag exhibits good uniformity, repeatability, recyclability and stability. Therefore, this flexible and cost-effectively substrate of CS/CN/Ag shows great potential for the simultaneous SERS detection and photocatalytic degradation of pollutants in actual wastewater samples.

Impact of nanotechnology on progress of flow methods in chemical analysis: A review

In evolution of instrumentation for analytical chemistry as crucial technological breakthroughs should be considered a common introduction of electronics with all its progress in integration, and then microprocessors which was followed by a widespread computerization. It is seems that a similar role can be attributed to the introduction of various elements of modern nanotechnology, observed with a fast progress since beginning of this century. It concerns all areas of the applications of analytical chemistry, including also progress in flow analysis, which are being developed since the middle of 20th century. Obviously, it should not be omitted the developed earlier and analytically applied planar structures like lipid membranes or self-assembled monolayers They had essential impact prior to discoveries of numerous extraordinary nanoparticles such as fullerenes, carbon nanotubes and graphene, or nanocrystalline semiconductors (quantum dots). Mostly, due to catalytic effects, significantly developed surface and the possibility of easy functionalization, their application in various stages of flow analytical procedures can significantly improve them. The application of new nanomaterials may be used for the development of new detection methods for flow analytical systems in macro-flow setups as well as in microfluidics and lateral flow immunoassay tests. It is also advantageous that quick flow conditions of measurements may be helpful in preventing unfavorable agglomeration of nanoparticles. A vast literature published already on this subject (e.g. almost 1000 papers about carbon nanotubes and flow-injection analytical systems) implies that for this reviews it was necessary to make an arbitrary selection of reported examples of this trend, focused mainly on achievements reported in the recent decade.

Microfluidic integrated D-shaped optical fiber SERS probe with high sensitivity and ability of multi-molecule detection

In order to enhance the sensitivity, integration, and practical application capability of Raman detection systems, we propose a multi-channel microfluidic integrated D-shaped optical fiber SERS (Surface-enhanced Raman scattering) probe structure. Firstly, a microfluidic polydimethylsiloxane (PDMS) channel was fabricated using a self-designed multi-channel microfluidic template. Secondly, a uniform layer of silver nanoparticles was deposited on the D-shaped optical fiber using the liquid-liquid interface method. Finally, the D-shaped optical fiber was plasma-bonded to the multi-channel microfluidic channel and a cover glass, resulting in a microfluidic integrated D-shaped optical fiber SERS probe. The prepared sample exhibited excellent detection performance for R6G (rhodamine 6 G) with a detection limit as low as 10-11 mol/L and an enhancement factor of 1.14 × 109. Moreover, the multi-channel configuration enables simultaneous detection of multiple molecules, demonstrating excellent multi-channel multiplexing capability.

The volatile release evaluation of nicotine from snus products under different storage conditions based on surface-enhanced Raman spectroscopy technology

Surface enhanced Raman spectroscopy (SERS) is a highly sensitive analytical detection technique that provides unique chemical and structural information on target molecules. Snus is a type of tobacco product that can release nicotine and other components under certain humidity and temperature without burning, and the evaluation of its nicotine release under different storage conditions is very important for understanding its characteristics, regulating its components, and setting reasonable storage conditions. Herein, by means of an artificial climate box and suction extraction device, the volatile release evaluations of nicotine from snus products under different storage conditions were performed based on Fe3O4 microparticles coated with Au nanorods and Au nanoparticles (Fe3O4@AuNRsNPs) as SERS substrates combined with a capillary. The Fe3O4@AuNRsNPs assemblies can be fixed in the inner wall of the capillary with the aid of an external magnetic field, which improved the maneuverability of the SERS substrates. By comparing the intensities of the spectral peaks of the symmetrical breathing of the pyridine moiety of nicotine molecules with increasing temperature and humidity, which could significantly accelerate the volatile release of a small amount of nicotine, the nicotine release under different conditions could be evaluated. Based on this strategy, it was possible to obtain the storage or placement conditions of the product. The results of this study provide a reference to clarify the volatile release of nicotine under various storage conditions, which is helpful for better regulation of the levels of nicotine in snus. Moreover, such destruction-free evaluation of the volatile release of nicotine from snus products under different storage conditions opens up new perspectives for further research about the impact of nicotinoids on smokers' health and cessation programs.

Preparation of SiO2@Au Nanoparticle Photonic Crystal Array as Surface-Enhanced Raman Scattering (SERS) Substrate

Surface-enhanced Raman scattering technology plays a prominent role in spectroscopy. By introducing plasmonic metals and photonic crystals as a substrate, SERS signals can achieve further enhancement. However, the conventional doping preparation methods of these SERS substrates are insufficient in terms of metal-loading capacity and the coupling strength between plasmonic metals and photonic crystals, both of which reduce the SERS activity and reproducibility of SERS substrates. In this work, we report an approach combining spin-coating, surface modification, and in situ reduction methods. Using this approach, a photonic crystal array of SiO2@Au core-shell structure nanoparticles was prepared as a SERS substrate (SiO2@Au NP array). To study the SERS properties of these substrates, Rhodamine 6G was employed as the probe molecule. Compared with a Au-SiO2 NP array prepared using doping methods, the SiO2@Au NP array presented better SERS properties, and it reproduced the SERS spectra after one month. The detection limit of the Rhodamine 6G on SiO2@Au NP array reached 1 × 10-8 mol/L; furthermore, the relative standard deviation (9.82%) of reproducibility and the enhancement factor (1.51 × 106) were evaluated. Our approach provides a new potential option for the preparation of SERS substrates and offers a potential advantage in trace contaminant detection, and nondestructive testing.