Surface-enhanced Raman spectroscopy: benefits, trade-offs and future developments

Wrinkle-bioinspired silver nanowire surface enhanced Raman scattering sensors for pesticide molecule detection

We demonstrate wrinkle-bioinspired flexible SERS sensor covered by silver nanowire (AgNWs) network for the detection of pesticide molecules. Compared with the silver film deposition substrates, the wrinkle-bioinspired AgNWs SERS substrates show stronger SERS effect, which were attributed to the electromagnetic field enhancement posed by the relatively high density "hot spots" of AgNWs. In order to investigate the adsorption performance of wrinkle-bioinspired flexible sensors, we measured the corresponding contact angles of AgNWs on the substrate surfaces before and after plasma treatment and found that the AgNWs treated with plasma are more hydrophilic than that without plasma treatment. Additionally, the wrinkle-bioinspired SERS sensors show different SERS activities under different tensile strain, and the 10^-6 mol/L concentration of Rhodamine dye (R6G) molecules can be detected by portable Raman spectra, reducing greatly detection cost. The surface plasmon resonance of AgNWs is induced by adjusting the deformation of AgNWs substrate, enhancing the SERS signal. This reliability of wrinkle-bioinspired SERS sensors is further verified by in situ detection of pesticide molecules.

High-Speed Spectral Characterization of Single-Molecule SERS Fluctuations

The concept of plasmonic "hotspots" is central to the broad field of nanophotonics. In surface-enhanced Raman scattering (SERS), hotspots can increase Raman scattering efficiency by orders of magnitude. Hotspot dimensions may range from a few nanometers down to the atomic scale and are able to generate SERS signals from single molecules. However, these single-molecule SERS signals often show significant fluctuations, and the concept of intense, localized, yet static hotspots has come into question. Recent experiments have shown these SERS intensity fluctuations (SIFs) to occur over an extremely wide range of timescales, from seconds to microseconds, due to the various physical mechanisms causing SERS and the dynamic nature of light-matter interaction at the nanoscale. The underlying source of single-molecule SERS fluctuations is therefore likely to be a complex interplay of several different effects at different timescales. A high-speed acquisition system that captures a full SERS spectrum with microsecond time resolution can therefore provide information about these dynamic processes. Here, we show an acquisition system that collects at a rate of 100,000 SERS spectra per second, allowing high-speed characterization. We find that while each individual SIF event will enhance a different portion of the SERS spectrum, including a single peak, over 10s to 100s of microseconds, the SIF events overall do not favor one region of the spectrum over another. These high-speed SIF events can therefore occur with relatively equal probability over a broad spectral range, covering both the anti-Stokes and the Stokes sides of the spectrum, sometimes leading to anomalously large anti-Stokes peaks. This indicates that both temporally and spectrally transient hotspots drive the SERS fluctuations at high speeds.

Atomic layer deposition assisted non-destructive strategy for cleaning Ag dendrites based SERS substrates

Ag dendrites have recently been widely reported due to their excellent surface-enhanced Raman scattering (SERS) properties. However, prepared pristine Ag dendrites are usually contaminated by organic impurities, which has a huge negative impact on their Raman detection and greatly limits their practical applications. In this paper, we reported a facile strategy to obtain clean Ag dendrites by high temperature decomposition of organic impurities. With the assistance of ultra-thin coating via atomic layer deposition (ALD), the nanostructure of Ag dendrites can be retained at high temperature. SERS activity can be recovered after etching ALD coating. Chemical composition tests indicate that the organic impurities can be effectively removed. As a result, the clean Ag dendrites can obtain more clearly discernible Raman peaks and lower limits of detection than the pristine Ag dendrites. Furthermore, it was demonstrated that this strategy is also applicable to clean other substrates, such as gold nanoparticles. Therefore, high temperature annealing with the help of ALD sacrifice coating is a promising and non-destructive strategy to clean the SERS substrates.

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.

Challenges of the Effectiveness of Traumatic Brain Injuries Biomarkers in the Sports-Related Context

Traumatic brain injury affects 69 million people every year. One of the main limitations in managing TBI patients is the lack of univocal diagnostic criteria, including the absence of standardized assessment methods and guidelines. Computerized axial tomography is the first-choice examination, despite the limited prevalence of positivity; moreover, its performance is undesirable due to the risk of radiological exposure, prolonged stay in emergency departments, inefficient use of resources, high cost, and complexity. Furthermore, immediacy and accuracy in diagnosis and management of TBIs are critically unmet medical needs. Especially in the context of sports-associated TBI, there is a strong need for prognostic indicators to help diagnose and identify at-risk subjects to avoid their returning to play while the brain is still highly vulnerable. Fluid biomarkers may emerge as new prognostic indicators to develop more accurate prediction models, improving risk stratification and clinical decision making. This review describes the current understanding of the cellular sources, temporal profile, and potential utility of leading and emerging blood-based protein biomarkers of TBI; its focus is on biomarkers that could improve the management of mild TBI cases and can be measured readily and directly in the field, as in the case of sports-related contexts.

Point-of-care community drug checking technologies: an insider look at the scientific principles and practical considerations

Drug checking is increasingly being explored outside of festivals and events to be an ongoing service within communities, frequently integrated within responses to illicit drug overdose. The choice of instrumentation is a common question, and the demands on these chemical analytical instruments can be challenging as illicit substances may be more complex and include highly potent ingredients at trace levels. The answer remains nuanced as the instruments themselves are not directly comparable nor are the local demands on the service, meaning implementation factors heavily influence the assessment and effectiveness of instruments. In this perspective, we provide a technical but accessible introduction to the background of a few common drug checking methods aimed at current and potential drug checking service providers. We discuss the following tools that have been used as part of the Vancouver Island Drug Checking Project in Victoria, Canada: immunoassay test strips, attenuated total reflection IR-absorption spectroscopy, Raman spectroscopy from powder samples, surface-enhanced Raman scattering in a solution of colloidal gold nanoparticles, and gas chromatography-mass spectrometry. Using four different drug mixtures received and tested at the service, we illustrate the strengths, limitations, and capabilities of such instruments, and expose the scientific theory to give further insight into their analytical results. Each case study provides a walk-through-style analysis for a practical comparison between data from several different instruments acquired on the same sample. Ideally, a single instrument would be able to achieve all of the objectives of drug checking. However, there is no clear instrument that ticks every box; low cost, portable, rapid, easy-to-use and provides highly sensitive identification and accurate quantification. Multi-instrument approaches to drug checking may be required to effectively respond to increasingly complex and highly potent substances demanding trace level detection and the potential for quantification.

Gold Nanotriangle-Assembled Nanoporous Structures for Electric Field-Assisted Surface-Enhanced Raman Scattering Detection of Adenosine Triphosphate

A reliable, rapid, cost-effective, and simple method for the detection of biomolecules would greatly promote the research of analytical detection of single molecules. A nanopore-based analytical technique is promising for detecting biomolecules. Conventional electrochemical nanopores cannot distinguish biomolecules precisely because of their fast translocation speed and limited electrochemical information. Therefore, it is highly desirable to develop electrochemical surface-enhanced Raman scattering (SERS) nanopores to obtain multidimensional information. Herein, we designed and fabricated gold nanotriangle (AuNT)-assembled porous structures at the tip of a glass capillary using dithiol adenosine triphosphate (ATP) aptamers as cross-linking molecules. The AuNTs exhibited an edge length of 57.3 ± 6.2 nm and thickness of about 15 nm. The gold nanoporous structure (GPS) showed a strong ion rectification even at a high concentration of electrolyte (2 M) and a high SERS activity. Based on these designed structures, SERS and electrochemistry techniques were combined to control the rapid movement of ATP to the vicinity of the GPS by an applied potential of +1 V, where ATP was concentrated by ATP aptamers and the molecular signals were amplified by SERS. As a result, the GPS successfully detected ATP at a concentration as low as 10^-7 M.

Stable and Reusable Lace-like Black Silicon Nanostructures Coated with Nanometer-Thick Gold Films for SERS-Based Sensing

We propose a simple, fast, and low-cost method for producing Au-coated black Si-based SERS-active substrates with a proven enhancement factor of 10⁶. Room temperature reactive ion etching of silicon wafer followed by nanometer-thin gold sputtering allows the formation of a highly developed lace-type Si surface covered with homogeneously distributed gold islands. The mosaic structure of deposited gold allows the use of Au-uncovered Si domains for Raman peak intensity normalization. The fabricated SERS substrates have prominent uniformity (with less than 6% SERS signal variations over large areas, 100 × 100 μm²). It has been found that the storage of SERS-active substrates in an ambient environment reduces the SERS signal by less than 3% in 1 month and not more than 40% in 20 months. We showed that Au-coated black Si-based SERS-active substrates can be reused after oxygen plasma cleaning and developed relevant protocols for removing covalently bonded and electrostatically attached molecules. Experiments revealed that the Raman signal of 4-MBA molecules covalently bonded to the Au coating measured after the 10th cycle was just 4 times lower than that observed for the virgin substrate. A case study of the reusability of the black Si-based substrate was conducted for the subsequent detection of 10^-5 M doxorubicin, a widely used anticancer drug, after the reuse cycle. The obtained SERS spectra of doxorubicin were highly reproducible. We demonstrated that the fabricated substrate permits not only qualitative but also quantitative monitoring of analytes and is suitable for the determination of concentrations of doxorubicin in the range of 10^-9-10^-4 M. Reusable, stable, reliable, durable, low-cost Au-coated black Si-based SERS-active substrates are promising tools for routine laboratory research in different areas of science and healthcare.

Trends in digital detection for the quality and safety of herbs using infrared and Raman spectroscopy

Herbs have been used as natural remedies for disease treatment, prevention, and health care. Some herbs with functional properties are also used as food or food additives for culinary purposes. The quality and safety inspection of herbs are influenced by various factors, which need to be assessed in each operation across the whole process of herb production. Traditional analysis methods are time-consuming and laborious, without quick response, which limits industry development and digital detection. Considering the efficiency and accuracy, faster, cheaper, and more environment-friendly techniques are highly needed to complement or replace the conventional chemical analysis methods. Infrared (IR) and Raman spectroscopy techniques have been applied to the quality control and safety inspection of herbs during the last several decades. In this paper, we generalize the current application using IR and Raman spectroscopy techniques across the whole process, from raw materials to patent herbal products. The challenges and remarks were proposed in the end, which serve as references for improving herb detection based on IR and Raman spectroscopy techniques. Meanwhile, make a path to driving intelligence and automation of herb products factories.

SERS-based detection of 5-S-cysteinyl-dopamine as a novel biomarker of Parkinson's disease in artificial biofluids

The early detection of Parkinson's disease (PD) can significantly improve treatment and quality of life in patients. 5-S-Cysteinyl-dopamine (CDA) is a key metabolite of high relevance for the early detection of PD. Therefore, its sensitive detection with fast and robust methods can improve its use as a biomarker. In this work we show the potentialities of label-free SERS spectroscopy in detecting CDA in aqueous solutions and artificial biofluids, with a simple, fast and sensitive approach. We present a detailed experimental SERS band assignment of CDA employing silver nanoparticle (AgNP) substrates in aqueous media, which was supported by theoretical calculations and simulated Raman and SERS spectra. The tentative orientation of CDA over the AgNP was also studied, indicating that catechol and carboxylic acid play a key role in the metallic surface adsorption. Moreover, we showed that SERS can allow us to identify CDA in aqueous media at low concentration, leading to the identification of some of its characteristic bands in pure water and in synthetic cerebrospinal fluid (SCSF) below 1 × 10^-8 M, while its band identification in simulated urine (SUR) can be reached at 1 × 10^-7 M. In conclusion, we show that CDA can be suitably detected by means of label-free SERS spectroscopy, which can significantly improve its sensitive detection for further analytical studies as a novel biomarker and further clinical diagnosis in PD patients.

3D plasmonic coral nanoarchitecture paper for label-free human urine sensing and deep learning-assisted cancer screening

Practical human biofluid sensing requires a sensor device to differentiate patients from the normal group with high sensitivity and specificity. Label-free molecular identification from human biofluids allows direct classification of abnormal samples, providing insights for disease diagnosis and finding of new biomarkers. Here, we introduce a label-free surface-enhanced Raman scattering sensor based on a three-dimensional plasmonic coral nanoarchitecture (3D-PCN), which has strong electromagnetic field enhancement through multiple hot spots. The 3D-PCN was synthesized on a paper substrate via direct one-step gold reduction, forming a coral-like nanoarchitecture with high absorption property for biofluids. This was fabricated as a urine test strip and then integrated with a handheld Raman system to develop an on-site urine diagnostic platform. The developed platform successfully classified the human prostate and pancreatic cancer urines in a label-free method supported by two types of deep learning networks, with high clinical sensitivity and specificity. Our technology has the potential to be utilized not only for urinary cancer diagnosis but also for various human biofluid sensing systems as a future point-of-care testing platform.

Deep learning approach to overcome signal fluctuations in SERS for efficient On-Site trace explosives detection

Surface-enhanced Raman spectroscopy (SERS) is an improved Raman spectroscopy technique to identify the analyte under study uniquely. At the laboratory scale, SERS has realised a huge potential to detect trace analytes with promising applications across multiple disciplines. However, onsite detection with SERS is still limited, given the unwanted glitches of signal reliability and blinking. SERS has inherent signal fluctuations due to multiple factors such as analyte adsorption, inhomogeneous distribution of hotspots, molecule orientation etc. making it a stochastic process. Given these signal fluctuations, validating a signal as a representation of the analyte often relies on an expert's knowledge. Here we present a neural network-aided SERS model (NNAS) without expert interference to efficiently identify reliable SERS spectra of trace explosives (tetryl and picric acid) and a dye molecule (crystal violet). The model uses the signal-to-noise ratio approach to label the spectra as representative (RS) and non-representative (NRS), eliminating the reliability of the expert. Further, experimental conditions were systematically varied to simulate general variations in SERS instrumentation, and a deep-learning model was trained. The model has been validated with a validation set followed by out-of-sample testing with an accuracy of 98% for all the analytes. We believe this model can efficiently bridge the gap between laboratory and on-site detection using SERS.

Emergence of Raman Spectroscopy as a Probing Tool for Theranostics

Although medical advances have increased our grasp of the amazing morphological, genetic, and phenotypic diversity of diseases, there are still significant technological barriers to understanding their complex and dynamic character. Specifically, the complexities of the biological systems throw a diverse set of challenges in developing efficient theranostic tools and methodologies that can probe and treat pathologies. Among several emerging theranostic techniques such as photodynamic therapy, photothermal therapy, magnetic resonance imaging, and computed tomography, Raman spectroscopy (RS) is emerging as a promising tool that is a label-free, cost-effective, and non-destructive technique. It can also provide real-time diagnostic information and can employ multimodal probes for detection and therapy. These attributes make it a perfect candidate for the analytical counterpart of the existing theranostic probes. The use of biocompatible nanomaterials for the fabrication of Raman probes provides rich structural information about the biological molecules, cells, and tissues and highly sensitive information down to single-molecule levels when integrated with advanced RS tools. This review discusses the fundamentals of Raman spectroscopic tools such as surface-enhanced Raman spectroscopy and Resonance Raman spectroscopy, their variants, and the associated theranostic applications. Besides the advantages, the current limitations, and future challenges of using RS in disease diagnosis and therapy have also been discussed.

Recent Advances in Green Metallic Nanoparticles for Enhanced Drug Delivery in Photodynamic Therapy: A Therapeutic Approach

Globally, cancer is one of the leading causes of death among men and women, it is characterized by the unregulated proliferation of tumor cells. Some of the common risk factors associated with cancer development include the consistent exposure of body cells to carcinogenic agents such as alcohol, tobacco, toxins, gamma rays and alpha particles. Besides the above-mentioned risk factors, conventional therapies such as radiotherapy, and chemotherapy have also been linked to the development of cancer. Over the past decade, tremendous efforts have been invested in the synthesis of eco-friendly green metallic nanoparticles (NPs), and their medical application. Comparatively, metallic NPs have greater advantages over conventional therapies. Additionally, metallic NPs can be functionalized with different targeting moieties e.g., liposomes, antibodies, folic acid, transferrin, and carbohydrates. Herein, we review and discuss the synthesis, and therapeutic potential of green synthesized metallic NPs for enhanced cancer photodynamic therapy (PDT). Finally, the advantages of green hybridized activatable NPs over conventional photosensitizers (PSs) and the future perspectives of nanotechnology in cancer research are discussed in the review. Furthermore, we anticipate that the insights offered in this review will inspire the design and development of green nano-formulations for enhanced image-guided PDT in cancer treatment.

FDTD Simulations for Rhodium and Platinum Nanoparticles for UV Plasmonics

The article describes the results of finite-difference time-domain (FDTD) mathematical modeling of electromagnetic fields distortion near the surfaces of two transition metals: rhodium (Rh) and platinum (Pt) on glass (SiO₂) substrates. Results were compared with calculated optical properties of classical SERS generating metals (Au and Ag). We have performed FDTD-based theoretical calculations for UV SERS-active nanoparticles (NPs) and structures based on hemispheres of Rh and Pt and planar surfaces, consisting of single NPs with varied gaps between them. The results have been compared with gold stars, silver spheres and hexagons. The prospects of the theoretical approach for single NPs and planar surfaces modeling to evaluate optimal field amplification and light scattering parameters have been shown. The presented approach could be applied as a basis for performing the methods of controlled synthesis for LPSR tunable colloidal and planar metal-based biocompatible optical sensors for UV and deep-UV plasmonics. The difference between UV-plasmonic NPs and plasmonics in a visible range has been evaluated.

Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques

Surface-enhanced Raman spectroscopy/scattering (SERS) has evolved into a popular tool for applications in biology and medicine owing to its ease-of-use, non-destructive, and label-free approach. Advances in plasmonics and instrumentation have enabled the realization of SERS's full potential for the trace detection of biomolecules, disease diagnostics, and monitoring. We provide a brief review on the recent developments in the SERS technique for biosensing applications, with a particular focus on machine learning techniques used for the same. Initially, the article discusses the need for plasmonic sensors in biology and the advantage of SERS over existing techniques. In the later sections, the applications are organized as SERS-based biosensing for disease diagnosis focusing on cancer identification and respiratory diseases, including the recent SARS-CoV-2 detection. We then discuss progress in sensing microorganisms, such as bacteria, with a particular focus on plasmonic sensors for detecting biohazardous materials in view of homeland security. At the end of the article, we focus on machine learning techniques for the (a) identification, (b) classification, and (c) quantification in SERS for biology applications. The review covers the work from 2010 onwards, and the language is simplified to suit the needs of the interdisciplinary audience.

Black Silicon: Breaking through the Everlasting Cost vs. Effectivity Trade-Off for SERS Substrates

Black silicon (bSi) is a highly absorptive material in the UV-vis and NIR spectral range. Photon trapping ability makes noble metal plated bSi attractive for fabrication of surface enhanced Raman spectroscopy (SERS) substrates. By using a cost-effective room temperature reactive ion etching method, we designed and fabricated the bSi surface profile, which provides the maximum Raman signal enhancement under NIR excitation when a nanometrically-thin gold layer is deposited. The proposed bSi substrates are reliable, uniform, low cost and effective for SERS-based detection of analytes, making these materials essential for medicine, forensics and environmental monitoring. Numerical simulation revealed that painting bSi with a defected gold layer resulted in an increase in the plasmonic hot spots, and a substantial increase in the absorption cross-section in the NIR range.

Flexible Substrate of Cellulose Fiber/Structured Plasmonic Silver Nanoparticles Applied for Label-Free SERS Detection of Malathion

Surface-enhanced Raman scattering (SERS) is considered an efficient technique providing high sensitivity and fingerprint specificity for the detection of pesticide residues. Recent developments in SERS-based detection aim to create flexible plasmonic substrates that meet the requirements for non-destructive analysis of contaminants on curved surfaces by simply wrapping or wiping. Herein, we reported a flexible SERS substrate based on cellulose fiber (CF) modified with silver nanostructures (AgNS). A silver film was fabricated on the membrane surface with an in situ silver mirror reaction leading to the formation of a AgNS-CF substrate. Then, the substrate was decorated through in situ synthesis of raspberry-like silver nanostructures (rAgNS). The SERS performance of the prepared substrate was tested using 4-mercaptobenzoic acid (4-MBA) as a Raman probe and compared with that of the CF-based plasmonic substrates. The sensitivity of the rAgNS/AgNS-CF substrate was evaluated by determining the detection limit of 4-MBA and an analytical enhancement factor, which were 10 nM and ~10⁷, respectively. Further, the proposed flexible rAgNS/AgNS-CF substrate was applied for SERS detection of malathion. The detection limit for malathion reached 0.15 mg/L, which meets the requirements about its maximum residue level in food. Thus, the characteristics of the rAgNS/AgNS-CF substrate demonstrate the potential of its application as a label-free and ready-to-use sensing platform for the SERS detection of trace hazardous substances.

Rapid fabrication of the Au hexagonal cone arrays for SERS applications

This study performed trace detection using surface-enhanced Raman scattering (SERS) on Au hexagonal cone arrays (Au-HCAs). Uniform porous anodized aluminum oxide (AAO) templates were used, and an Ag film with a cone cavity was prepared using a thermal deposition technique. Next, a series of homogeneous Au-HCAs were prepared controllably via electrodeposition growth technology. The prepared Au-HCAs were used as SERS substrates, and according to the experimental results, the optimal electrodeposition time is 600 s. At this time, Au-HCAs had the highest SERS activity. The detection limit of R6G was 10^-9 M, exhibiting high reproducibility and high uniformity at 10^-6 M, indicating that Au-HCAs had good stability. Moreover, a good linear correlation between the Raman intensity and the molecular concentration endowed Au-HCAs with good quantitative analysis ability. Therefore, the Au-HCAs exhibited great potential for qualitative and quantitative detection.

Electrochemically assisted wide area Raman with standard curved surface quantification method

Reproducibility is still a great challenge for surface-enhanced Raman scattering (SERS), because the uncontrollable fabrication of SERS substrates or the uneven distribution of samples on the substrate result in the signal fluctuation with or between the substrates. Herein, a novel SERS quantitative method with good reproducibility was proposed. It is based on the basic principle that the SERS signal intensity is not only related to electromagnetic enhancement and the concentration of sample, but also related to the specific surface area of the substrate. The surface area information of the substrate is obtained through electrochemical technology, and then introduced into the standard curve with the linear relationship of concentration of sample and SERS intensity as a new variable to obtain a 3D standard curved surface, which effectively corrects the signal difference between the substrates, and combines the wide area Raman method to reduce the difference within the substrate, thereby improving the reproducibility of SERS quantitative detection. Using malachite green (MG) as the probe molecule and using cyclic voltammetry to calculate the substrate area fitted plane model (CV-standard curved surface), the root mean square error (RMSE) of the predicted result is 0.26 and the relative error (RE) is 0.25. It shows that the detection error significantly reduces comparing with the traditional standard curve method. Also, the proposed method can be used in other SERS quantitative detection and has potential application prospects.

Self-assembly of Au nanocrystals into large-area 3-D ordered flexible superlattice nanostructures arrays for ultrasensitive trace multi-hazard detection

Plasmonic nanoparticles that self-assemble into highly ordered superlattice nanostructures hold substantial promise for facilitating ultra-trace surface-enhanced Raman scattering (SERS) detection. Herein, we propose a boiling-point evaporation method to synthesize ordered monocrystal-like superlattice Au nanostructures (OML-Au NTs) with a polyhedral morphology. Combined with thermal nanoimprint technology, OML-Au NTs were directly transferred to impact-resistant polystyrene (IPS) flexible SERS substrates, the obtained flexible substrates (donated as OML-Au NTs/IPS) detection limit for R6G molecules as low as 10^-13 M. These results were confirmed by simulating the electromagnetic field distribution of ordered/unordered two-dimensional single-layer and three-dimensional aggregated gold nanostructures. The OML-Au NTs/IPS substrates were successfully used to detect and quantify three commonly-used agricultural pesticides, achieving detection limits as low as 10^-11 M and 10^-12 M, and in situ real-time detection limit reached 0.24 pg/cm² for thiram on apple peels, which was 3 orders of magnitude lower than the current detection limit. In addition, the Raman intensity from multiple locations showed a relative standard deviation lower than 7 %, exhibiting the reliability necessary for practical applications. As a result, this research demonstrates a highly reproducible method to enable the development of plasmonic nanomaterials with flexible superstructures.

Cancer Treatment Using Different Shapes of Gold-Based Nanomaterials in Combination with Conventional Physical Techniques

The conventional methods of cancer treatment and diagnosis, such as radiotherapy, chemotherapy, and computed tomography, have developed a great deal. However, the effectiveness of such methods is limited to the possible failure or collateral effects on the patients. In recent years, nanoscale materials have been studied in the field of medical physics to develop increasingly efficient methods to treat diseases. Gold nanoparticles (AuNPs), thanks to their unique physicochemical and optical properties, were introduced to medicine to promote highly effective treatments. Several studies have confirmed the advantages of AuNPs such as their biocompatibility and the possibility to tune their shapes and sizes or modify their surfaces using different chemical compounds. In this review, the main properties of AuNPs are analyzed, with particular focus on star-shaped AuNPs. In addition, the main methods of tumor treatment and diagnosis involving AuNPs are reviewed.

Machine learning-augmented surface-enhanced spectroscopy toward next-generation molecular diagnostics

The world today is witnessing the significant role and huge demand for molecular detection and screening in healthcare and medical diagnosis, especially during the outbreak of COVID-19. Surface-enhanced spectroscopy techniques, including Surface-Enhanced Raman Scattering (SERS) and Infrared Absorption (SEIRA), provide lattice and molecular vibrational fingerprint information which is directly linked to the molecular constituents, chemical bonds, and configuration. These properties make them an unambiguous, nondestructive, and label-free toolkit for molecular diagnostics and screening. However, new issues in molecular diagnostics, such as increasing molecular species, faster spread of viruses, and higher requirements for detection accuracy and sensitivity, have brought great challenges to detection technology. Advancements in artificial intelligence and machine learning (ML) techniques show promising potential in empowering SERS and SEIRA with rapid analysis and automatic data processing to jointly tackle the challenge. This review introduces the combination of ML and SERS/SEIRA by investigating how ML algorithms can be beneficial to SERS/SEIRA, discussing the general process of combining ML and SEIRA/SERS, highlighting the molecular diagnostics and screening applications based on ML-combined SEIRA/SERS, and providing perspectives on the future development of ML-integrated SEIRA/SERS. In general, this review offers comprehensive knowledge about the recent advances and the future outlook regarding ML-integrated SEIRA/SERS for molecular diagnostics and screening.

An experimental guide to in operando electrochemical Raman spectroscopy

Electrochemical Raman spectroscopy can provide valuable insights into electrochemical reaction mechanisms. However, it also shows various pitfalls and challenges. This paper gives an overview of the necessary theoretical background, crucial practical considerations for successful measurement, and guidance for in situ/in operando electrochemical Raman spectroscopy. Several parameters must be optimized for suitable reaction and measurement conditions. From the experimental side, considerations for the setup, suitable signal enhancement methods, choice of material, laser, and objective lens are discussed. Different interface phenomena are reviewed in the context of data interpretation and evaluation.

Graphical Abstract

SARS-CoV-2 proteins monitored by long-range surface plasmon field-enhanced Raman scattering with hybrid bowtie nanoaperture arrays and nanocavities

The identification of biomacromolecules by using surface-enhanced Raman scattering (SERS) remains a challenge because of the near-field effect of traditional substrates. Long-range surface plasmon resonance (LRSPR) is a special type of surface optical phenomenon that provides higher electromagnetic field enhancement and longer penetration depth than conventional surface plasmon resonance. To break the limit of SERS detection distance and obtain a SERS substrate with increased enhancement ability, a bowtie nanoaperture array was sandwiched between two symmetric dielectric environments. Then, an Au mirror was inserted to form a metal-insulator-metal configuration. Finite-difference time-domain simulations revealed that numerous hybrid modes can be provided by this novel configuration (denoted as long-range SERS [LR-SERS] substrate). In particular, the LRSPR mode can be excited and reach the maximum value through the regulation of the polarizations of the incident light and the geometrical parameters of the LR-SERS substrate. The optimized LR-SERS substrate was then applied to detect SARS-CoV-2 spike (S) and nucleocapsid (N) proteins. This substrate displayed ultralow detection limits of ∼9.2 and ∼11.3 pg mL^-1 for the S and N proteins, respectively. Moreover, with the help of principal component analysis and receiver operating characteristic methods, our fabricated sensors exhibited excellent selectivity and hold great potential for the diagnosis of SARS-CoV-2 proteins in real samples.

Plasmonic Array at the Liquid-Liquid Interface: A Dual-Mode Optical Sensing Platform for Multianalytes

Analyte-triggered nanoparticle (NP) assemblies in bulk colloidal suspension have been extensively utilized in various optical sensors. Nevertheless, the assembling process is still limited by the slow diffusion dynamics of NPs and the low concentration of analytes in trace detections, which hinders further improvement of the sensitivity and repeatability of the sensors. In this work, by functionalizing the gold NPs with specific ligands, we constructed a dual-mode optical sensing platform for multianalytes based on the plasmonic NP array at the liquid-liquid interface. Through emulsification, the NP diffusion kinetics are boosted for several orders, and the NPs are condensed from the bulk aqueous phase to the liquid-liquid interface as a plasmonic array. The as-formed metasurface generates major reflectance and surface-enhanced Raman scattering changes in response to analytes, providing two optical sensing modes. As prototypes, cysteine and glucose are selected as the target molecules, achieving the limit of detection as 193 ± 2 and 297 ± 12 pM, respectively.

Size-independent quantification of nanoplastics in various aqueous media using surfaced-enhanced Raman scattering

In this work, we successfully developed an intriguing preparation strategy to reduce the size-dependent effect of nanoplastics (NPLs), which is the limitation of NPLs quantification by surface-enhanced Raman scattering (SERS). This simple and low-cost technique enabled us to quantify different sizes (i.e., 100, 300, 600, and 800 nm) of polystyrene nanospheres (PS NSs) in various aqueous media. The SERS substrate was simply prepared by sputtering gold particles to cover on a glass cover slide. By dissolving PS NSs in toluene and preconcentrating by coffee-ring effect, SERS measurement can quantify NPLs at a very low concentration with a limit of detection (LOD) of approximately 0.10-0.26 μg/mL. The experiment was also conducted in the presence of interferences, including salts, sugars, amino acids, and detergents. The method was validated for quantitative analysis using a mixture of 100-, 300-, 600-, and 800-nm PS NSs in a ratio of 1:1:1:1 in real-world media (i.e., tap water, mineral water, and river water), which successfully approaches the evaluation of PS NSs in the range of 10-40 µg/mL with an LOD of approximately 0.32-0.52 µg/mL.

Core-shell Au@ZIF-67-based pollutant monitoring of thiram and carbendazim pesticides

A sensitive and stable substrate plays a vital role in the Raman spectroscopic techniques as an analytical method for detecting pesticides effectively from the environment. Enhancing signals from nanoparticles are weak and inconsistent in repeatability since analytes tend to degrade quickly under laser exposure. Herein, a novel substrate of Au@ZIF-67 is prepared on octahedral AuNPs by trapping pesticide molecules with small three-dimensional volumes by the flexibility of ZIF-67 for rapid detection with high sensitivity and stability. The two types of thiram and carbendazim pesticides, which are environmental pollutants that affect biodiversity, were successfully absorbed in Au@ZIF-67 nanostructures by adsorption-desorption equilibrium for analytical purposes in Raman spectroscopy. Spectra calculations of the thiram and carbendazim molecules on 8 atoms of Au using DFT were compared with the experimental data. The SERS enhancement factors for thiram and carbendazim were estimated to be 1.91 × 10⁸ and 3.12 × 10⁸, respectively, with the LOD values of trace amounts of ∼10^-10 mol L^-1. The novel substrate of Au@ZIF-67 is a propitious platform for detecting thiram and carbendazim in trace amounts, providing a helpful strategy for detecting residues with high performance in the environment at the laboratory and practical scales.

Fast Track Diagnostic Tools for Clinical Management of Sepsis: Paradigm Shift from Conventional to Advanced Methods

Sepsis is one of the deadliest disorders in the new century due to specific limitations in early and differential diagnosis. Moreover, antimicrobial resistance (AMR) is becoming the dominant threat to human health globally. The only way to encounter the spread and emergence of AMR is through the active detection and identification of the pathogen along with the quantification of resistance. For better management of such disease, there is an essential requirement to approach many suitable diagnostic techniques for the proper administration of antibiotics and elimination of these infectious diseases. The current method employed for the diagnosis of sepsis relies on the conventional culture of blood suspected infection. However, this method is more time consuming and generates results that are false negative in the case of antibiotic pretreated samples as well as slow-growing microbes. In comparison to the conventional method, modern methods are capable of analyzing blood samples, obtaining accurate results from the suspicious patient of sepsis, and giving all the necessary information to identify the pathogens as well as AMR in a short period. The present review is intended to highlight the culture shift from conventional to modern and advanced technologies including their limitations for the proper and prompt diagnosing of bloodstream infections and AMR detection.

Enhanced Sum Frequency Generation for Monolayers on Au Relative to Silica: Local Field Factors and SPR Effect

Using metals as signal magnified substrates, surface plasmon-enhanced sum frequency generation (SFG) vibrational spectroscopy is a promising technique to probe weak molecular-level signals at surfaces and interfaces. In this study, the vibrational signals of the n-alkane monolayer on the gold (Au) and silica substrates are investigated using the broadband femtosecond SFG. The enhancement factors are discovered to be up to ∼1076 and ∼31 for the methyl symmetric and asymmetric stretching (ss and as) modes of the monolayer, respectively. By systematically analyzing the second-order nonlinear susceptibility tensor components (χ_ijks), the Fresnel coefficients (F_ijks), and the surface plasmon resonance (SPR) effect, we find that the interplay between F_ijk and χ_ijk terms and the SPR effect dominate the SFG signal enhancement. Our study reveals that the relative contributions of different influencing factors (i.e., Fresnel coefficients and SPR) to the SFG signal enhancement provide an approach to interpreting enhanced SFG vibrational signals detected from probe molecules on distinct substrates and may finally guide the design of the experimental methodology to improve the detection sensitivity and signal-to-noise ratio.

Strategies and Challenges of Identifying Nanoplastics in Environment by Surface-Enhanced Raman Spectroscopy

Nanoplastics (<1000 nm) have been evidenced to be universal in a variety of environmental media. They pose a potential cytotoxicity and health risk due to their tiny size, which allows them to easily penetrate biological barriers and enter cells. Here, we briefly review the various prevalent analytical techniques or tools for identifying nanoplastics, and further move to focus on their advantages and disadvantages. Surface-enhanced Raman spectroscopy (SERS) has been implemented for the identification of individual nanoparticles because of its high sensitivity to molecules and ease of rapid characterization. Therefore, we introduce the SERS technique in the following aspects, (1) principles of SERS; (2) strategies and advances in SERS detection of nanoplastics; and (3) applying SERS to real environmental samples. We put our effort into the summarization of efficient SERS substrates that essentially enable the better detection of nanoplastics, and extend to discuss how the reported nanoplastics pretreatment methodologies can bring SERS analysis to practical applications. A further step moving forward is to investigate the problems and challenges of currently applied SERS detection methods and to look at future research needs in nanoplastics detection employing SERS analysis.

Plasmon-driven catalytic reactions in optoplasmonic sandwich hybrid structure

As an interesting phenomenon in the field of surface enhanced Raman spectroscopy (SERS), the plasmon-driven catalytic reaction (PDSC) induced by plasmonic hot electrons has great value in the research of novel properties of surface plasmons and accuracy of SERS applications. In this work, an optoplasmonic sandwich hybrid structure is proposed for studying PDSC of p-aminothiophenol (PATP) molecules, which is composed of Au film, metal organic frameworks (MOFs) nanoparticles, zeolithic imidazolate (ZIF-8), and single S i O ₂ microsphere (Au f i l m@M O F s@S i O ₂). In order to analyze the novel, to the best of our knowledge, phenomenon of the PDSC in this micro-nano structure, the hot electron generation in the MOF without the plasmonic core is carried out by combining the plasmonic enhancement of gold film with the light concentration of microspheres. Experimental data show that the PDSC reactions is dependent on the size of the MOFs nanoparticle and the size of the S i O ₂ microsphere, which is confirmed by the electromagnetic field simulation of the finite-difference time-domain method (FDTD). Our work not only strengthens the understanding of surface plasmon in optoplasmonic hybrid structures but also has broad application prospects in the SERS and plasmon-driven catalytic fields.

The Application of Nanotechnology for Quantification of Circulating Tumour DNA in Liquid Biopsies: A Systematic Review

Technologies for quantifying circulating tumour DNA (ctDNA) in liquid biopsies could enable real-time measurements of cancer progression, profoundly impacting patient care. Sequencing methods can be too complex and time-consuming for regular point-of-care monitoring, but nanotechnology offers an alternative, harnessing the unique properties of objects tens to hundreds of nanometres in size. This systematic review was performed to identify all examples of nanotechnology-based ctDNA detection and assess their potential for clinical use. Google Scholar, PubMed, Web of Science, Google Patents, Espacenet and Embase/MEDLINE were searched up to 23rd March 2021. The review identified nanotechnology-based methods for ctDNA detection for which quantitative measures (e.g., limit of detection, LOD) were reported and biologically relevant samples were used. The pre-defined inclusion criteria were met by 66 records. LODs ranged from 10 zM to 50nM. 25 records presented an LOD of 10fM or below. Nanotechnology-based approaches could provide the basis for the next wave of advances in ctDNA diagnostics, enabling analysis at the point-of-care, but none are currently used clinically. Further work is needed in development and validation; trade-offs are expected between different performance measures e.g., number of sequences detected and time to result.

Mesoporous silica coated core-shell nanoparticles substrate for size-selective SERS detection of chloramphenicol

With the growing popularity of the non-destructive technique, surface-enhanced Raman spectroscopy (SERS) demands a highly sensitive and reproducible plasmonic nanoparticles substrate. In this study, a novel bimetallic core-shell nanoparticles (Au@Ag@mSiO₂NP) substrate consisting of a gold core, silver shell, and a mesoporous silica coating was synthesized. The mesoporous coating structure was created by employing template molecules such as surfactant and their subsequent removal allowing selective screening based on the size of analyte molecules. Results showed that the plasmonic substrate could selectively enhance small molecules by preventing large macromolecules to reach the exciting zone of the substrate core, achieving the detection of chloramphenicol in milk samples with a detection limit of 6.68 × 10^-8 M. Moreover, the mesoporous coating provided additional stability to the Au@Ag nanoparticles, leading to the reusability of the substrate. Thus, this work offered a simple and smart Au@Ag@mSiO₂NP substrate for effective SERS detection of analytes.

Raman spectroscopy for profiling physical and chemical properties of atmospheric aerosol particles: A review

Atmosphere aerosols have significant impact on human health and the environment. Aerosol particles have a number of characteristics that influence their health and environmental effects, including their size, shape, and chemical composition. A great deal of difficulty is associated with quantifying and identifying atmospheric aerosols because these parameters are highly variable on a spatial and temporal scale. An important component of understanding aerosol fate is Raman Spectroscopy (RS), which is capable of resolving chemical compositions of individual particles. This review presented strategic techniques, especially RS methods for characterizing atmospheric aerosols. The nature and properties of atmospheric aerosols and their influence on environment and human health were briefly described. Analytical methodologies that offer insight into the chemistry and multidimensional properties of aerosols were discussed. In addition, perspectives for practical applications of atmospheric aerosols using RS are featured.

Sulfur Vacancy-Rich CuS for Improved Surface-Enhanced Raman Spectroscopy and Full-Spectrum Photocatalysis

There are growing interests in the development of bifunctional semiconducting nanostructures for photocatalysis and real-time monitoring of degradation process on catalysts. Defect engineering is a low-cost approach to manipulating the properties of semiconductors. Herein, we prepared CuS nanoplates by a hydrothermal method at increasing amounts of thioacetamide (CS-1, CS-2, and CS-3) and investigated the influence of sulfur vacancy (V_s) on surface-enhanced Raman spectroscopy (SERS) and photocatalysis performance. SERS intensity of 4-nitrobenzenethiol on CS-3 is 346 and 17 times that of CS-1 and CS-2, respectively, and enhancement factor is 1.34 × 10⁴. Moreover, SERS is successfully applied to monitor the photodegradation of methyl orange. In addition, CS-3 also exhibited higher efficiency of Cr(VI) photoreduction than CS-1 and CS-2, and removal rate is 88%, 96%, and 73% under 2 h UV, 4 h visible, and 4 h near-infrared illumination, respectively. A systematic study including electron paramagnetic resonance spectra, photoelectrochemical measurements, and nitrogen adsorption isotherms were conducted to investigate the underlying mechanism. This work may help to understand the impact of vacancy defect on SERS and photocatalysis, and provide an effective and low-cost approach for the design of multifunctional materials.

Unraveling the Gas-Sensing Mechanisms of Lead-Free Perovskites Supported on Graphene

Lead halide perovskites have been attracting great attention due to their outstanding properties and have been utilized for a wide variety of applications. However, the high toxicity of lead promotes an urgent and necessary search for alternative nanomaterials. In this perspective, the emerging lead-free perovskites are an environmentally friendly and harmless option. The present work reports for the first time gas sensors based on lead-free perovskite nanocrystals supported on graphene, which acts as a transducing element owing to its high and efficient carrier transport properties. The use of nanocrystals enables achieving excellent sensitivity toward gas compounds and presents better properties than those of bulky perovskite thin films, owing to their quantum confinement effect and exciton binding energy. Specifically, an industrially scalable, facile, and inexpensive synthesis is proposed to support two different perovskites (Cs3CuBr5 and Cs2AgBiBr6) on graphene for effectively detecting a variety of harmful pollutants below the threshold limit values. H2 and H2S gases were detected for the first time by utilizing lead-free perovskites, and ultrasensitive detection of NO2 was also achieved at room temperature. In addition, the band-gap type, defect tolerance, and electronic surface traps at the nanocrystals were studied in detail for understanding the differences in the sensing performance observed. Finally, a comprehensive sensing mechanism is proposed.

Nanomaterials meet surface-enhanced Raman scattering towards enhanced clinical diagnosis: a review

Surface-enhanced Raman scattering (SERS) is a very promising tool for the direct detection of biomarkers for the diagnosis of i.e., cancer and pathogens. Yet, current SERS strategies are hampered by non-specific interactions with co-existing substances in the biological matrices and the difficulties of obtaining molecular fingerprint information from the complex vibrational spectrum. Raman signal enhancement is necessary, along with convenient surface modification and machine-based learning to address the former issues. This review aims to describe recent advances and prospects in SERS-based approaches for cancer and pathogens diagnosis. First, direct SERS strategies for key biomarker sensing, including the use of substrates such as plasmonic, semiconductor structures, and 3D order nanostructures for signal enhancement will be discussed. Secondly, we will illustrate recent advances for indirect diagnosis using active nanomaterials, Raman reporters, and specific capture elements as SERS tags. Thirdly, critical challenges for translating the potential of the SERS sensing techniques into clinical applications via machine learning and portable instrumentation will be described. The unique nature and integrated sensing capabilities of SERS provide great promise for early cancer diagnosis or fast pathogens detection, reducing sanitary costs but most importantly allowing disease prevention and decreasing mortality rates.

In-situ Raman spectroscopic insight into charge delocalization-improved electrical conductivity in metal-cyanide frameworks

Porous crystalline materials (PCMs) have attracted widespread attention due to their high porosity and chemical tunability. To solve the problem of the low electrical conductivity of traditional PCMs, a guest-promoted approach has been developed to impart electrical conductivity, whereas microscopic understanding of this process from experiments is largely lacking. Here we use in-situ electrochemical surface-enhanced Raman spectroscopy (EC-SERS) to investigate the microscopic mechanism of the enhanced electrical conductivity in metal-cyanide frameworks, in Prussian Blue (PB), induced by alkali metal ions. The EC-SERS result demonstrates that the charge is localized around the iron atom in PB and becomes delocalized on the CN bond after insertion of the alkali metal ions, verified by density functional theory (DFT) calculations. The enhanced electrical conductivity of PCMs promoted by the guest via the through-bond mechanism instead of the through-space hopping mechanism in pristine PB, offers a new approach to develop conductive PCMs.

Toward Quantitative Surface-Enhanced Raman Scattering with Plasmonic Nanoparticles: Multiscale View on Heterogeneities in Particle Morphology, Surface Modification, Interface, and Analytical Protocols

Surface-enhanced Raman scattering (SERS) provides significantly enhanced Raman scattering signals from molecules adsorbed on plasmonic nanostructures, as well as the molecules' vibrational fingerprints. Plasmonic nanoparticle systems are particularly powerful for SERS substrates as they provide a wide range of structural features and plasmonic couplings to boost the enhancement, often up to >10⁸-10¹⁰. Nevertheless, nanoparticle-based SERS is not widely utilized as a means for reliable quantitative measurement of molecules largely due to limited controllability, uniformity, and scalability of plasmonic nanoparticles, poor molecular modification chemistry, and a lack of widely used analytical protocols for SERS. Furthermore, multiscale issues with plasmonic nanoparticle systems that range from atomic and molecular scales to assembled nanostructure scale are difficult to simultaneously control, analyze, and address. In this perspective, we introduce and discuss the design principles and key issues in preparing SERS nanoparticle substrates and the recent studies on the uniform and controllable synthesis and newly emerging machine learning-based analysis of plasmonic nanoparticle systems for quantitative SERS. Specifically, the multiscale point of view with plasmonic nanoparticle systems toward quantitative SERS is provided throughout this perspective. Furthermore, issues with correctly estimating and comparing SERS enhancement factors are discussed, and newly emerging statistical and artificial intelligence approaches for analyzing complex SERS systems are introduced and scrutinized to address challenges that cannot be fully resolved through synthetic improvements.

Three-Dimensional Surface-Enhanced Raman Scattering Platform with Hotspots Built by a Nano-mower for Rapid Detection of MRSA

Methicillin-resistant Staphylococcus aureus (MRSA) has become one of the greatest threats to human health due to its strong drug resistance, wide distribution range, and high infection rate. Rapid identification of MRSA strains is very important for accurate diagnosis and early treatment of MRSA infections. Here, we introduced an Exo III-assisted nanomotor mower to build 3D hotspots for rapid detection of MRSA by surface-enhanced Raman scattering (SERS). As the bacteria bound to the aptamer, two trigger chains were released from the double-stranded structure, and the nano-mowers were activated by opening a hairpin probe on gold nanoparticles (AuNPs). With the continued cleavage of Exo III and cyclic release of the trigger chain, multiple hairpin DNAs on the AuNPs were cleaved to increase the motor power. The resulting nano-mower continued slicing protective DNA from larger AuNPs, exposing the AuNPs. Without the protection of DNA, Mg²⁺ in the buffer induced spontaneous aggregation of the AuNPs, and a large number of hotspots were formed for SERS measurements. Under optimal conditions, MRSA can be detected within 40 min, and the concentration of MRSA showed a good linear relationship with the SERS intensity at 1342 cm^-1, with a limit of detection as low as 1 CFU/mL and a wide linear range (10⁰ to 10⁷ CFU/mL). This strategy creates a rapid bacterial detection method that performs well on actual samples utilizing portable Raman spectroscopy instruments, with potential applications in food detection, water detection, clinical treatment, and diagnosis.

Superhydrophobic 3D-Assembled Metallic Nanoparticles for Trace Chemical Enrichment in SERS Sensing

The performance of surface-enhanced Raman spectroscopy (SERS) is determined by the interaction between highly diluted analytes and boosted localized electromagnetic fields in nanovolumes. Although superhydrophobic surfaces are developed for analyte enrichment, i.e., to concentrate and transfer analytes toward a specific position, it is still challenging to realize reproducible, uniform, and sensitive superhydrophobic SERS substrates over large scales, representing a major barrier for practical sensing applications. To overcome this challenge, a superhydrophobic SERS chip that combines 3D-assembled gold nanoparticles on nanoporous substrates is proposed, for a strong localized field, with superhydrophobic surface treatment for analyte enrichment. Intriguingly, by concentrating droplets in the volume of 40 µL, the sensitivity of 1 nm is demonstrated using 1,2-bis(4-pyridyl)-ethylene molecules. In addition, this unique chip demonstrates a relative standard deviation (RSD) of 2.2% in chip-to-chip reproducibility for detection of fentanyl at 1 µg mL^-1 concentration, revealing its potential for quantitative sensing of chemicals and drugs. Furthermore, the trace analysis of fentanyl and fentanyl-heroin mixture in human saliva is realized after a simple pretreatment process. This superhydrophobic chip paves the way toward on-site and real-time drug sensing to tackle many societal issues like drug abuse and the opioid crisis.

Chromophoric Ion Receptor-Decorated Porous Monolithic Polymer for the Solid-State Naked Eye Sensing of Hg(II): An Experimental and Theoretical Approach

The current work presents a perspective to obliterate toxic Hg(II) from an aqueous environment, a strategic environmental remediation and decontamination measure. We report a simple, efficient, and reusable solid-state visual sensing strategy for the selective detection and quantitative recovery of ultratrace Hg(II). The capture of Hg(II) ions was effectuated using a macro-/mesoporous polymer monolith uniformly decorated with an azo-based chromophoric ion receptor, i.e., 7-((1H-benzo[d]imidazol-2-yl)diazenyl)quinolin-8-ol (BIDQ). The porous polymer template was synthesized through free radical polymerization of gylcidylmethacrylate and ethylene glycol dimethacrylate, leading to distinct structural and surface properties that offer exclusive solid-state colorimetric selectivity for Hg(II) upon restricted spatial dispersion of the ion receptor. The sensor provides a broad linear response range of 1-200 μg/L, with an outstanding detection limit of 0.2 μg/L for Hg(II) ions, thus effectuating reliable and reproducible sensing. Optimizing analytical parameters such as solution pH, receptor concentration, sensor quantity, kinetics, temperature, and matrix interference proved to be promising for the real-time monitoring of toxic mercury ions from aqueous/industrial systems, with maximum response in the pH range of 7.5-8.0, with a response time of ≤80 s. Density functional theory (DFT) calculations were employed to study the electronic structure of BIDQ upon chelating with Hg(II) ions, using 6-311G and LAND2Z basis sets.

Spectroscopic characterization and in vitro studies of biological activity of bradykinin derivatives

Eleven multiple analogs of bradykinin-a peptide that is a natural ligand of B1 and B2 receptors but does not bind or activate the B1 receptor unless Arg⁹ is removed from the sequence by the action of carboxypeptidase N-were synthesized. Their biological activity was examined on T-REx cell lines expressing B1 or B2 receptors using the intracellular IP1 assay. The mRNA expression of B1R and B2R in the lysate of tumor cell lines, e.g., U87-MG (human astrocytoma), SHP-77 (human small cell lung cancer), and H4 (human brain glioma), was determined. For five B1R antagonists, adsorption at the liquid/solid interface (Au nanoparticles (AuNPs) served as the solid surface) was discussed in terms of the vibrations of molecular fragments (structural factors) responsible for the biological properties of these analogs.

Single-model multi-tasks deep learning network for recognition and quantitation of surface-enhanced Raman spectroscopy

Surface-enhanced Raman scattering (SERS) spectroscopy analysis has long been the central task of nanoscience and nanotechnology to realize the ultrasensitive recognition/quantitation applications. Recently, the blooming of artificial intelligence algorithms provides an edge tool to revolutionize the spectroscopy analysis, especially for multiple substances analysis and large-scale data handling. In this study, a single-model multi-tasks deep learning network is proposed to simultaneously achieve the qualitative recognition and quantitative analysis of SERS spectroscopy. The SERS spectra of two kinds of hypoglycemic drugs (PHE, ROS) and the corresponding mixtures are collected, respectively, with the concentration grade from 10^-4 M to 10^-8 M. Based on the SERS spectroscopy dataset, the loss functions and hyperparameters of the multi-tasks classifications model are optimized, and the recognition accuracies are tested by simulation experiments. It is demonstrated that the accuracy rates of qualitative and quantitative analysis can reach up to 99.0% and 98.4%, respectively. Moreover, the practical feasibility of this multi-tasks model is demonstrated by using it to achieve qualitative and quantitative analysis of PHE and ROS in complex serum matrix. Overall, this single-model multi-tasks deep learning network shows significant potential for the recognition and quantitation of SERS spectroscopy, which provides the algorithmic and experimental basis for large-scale and multiple substances SERS spectra analysis.