Detection of nanoplastics based on surface-enhanced Raman scattering with silver nanowire arrays on regenerated cellulose films

A review on nanomaterial-based SERS substrates for sustainable agriculture

The agricultural sector plays a pivotal role in driving the economy of many developing countries. Any dent in this economical structure may have a severe impact on a country's population. With rising climate change and increasing pollution, the agricultural sector is experiencing significant damage. Over time this cumulative damage will affect the integrity of food crops and create food security issues around the world. Therefore, an early warning system is needed to detect possible stress on food crops. Here we present a review of the recent developments in nanomaterial-based Surface Enhanced Raman Spectroscopy (SERS) substrates which could be utilized to monitor agricultural crop responses to natural and anthropogenic stress. Initially, our review delves into diverse and cost-effective strategies for fabricating SERS substrates, emphasizing their intelligent utilization across various agricultural scenarios. In the second phase of our review, we spotlight the specific application of SERS in addressing critical food security issues. By detecting nutrients, hormones, and effector molecules in plants, SERS provides valuable insights into plant health. Furthermore, our exploration extends to the detection of contaminants, chemicals, and foodborne pathogens within plants, showcasing the versatility of SERS in ensuring food safety. The cumulative knowledge derived from these discussions illustrates the transformative potential of SERS in bolstering the agricultural economy. By enhancing precision in nutrient management, monitoring plant health, and enabling rapid detection of harmful substances, SERS emerges as a pivotal tool in promoting sustainable and secure agricultural practices. Its integration into agricultural processes not only augments productivity but also establishes a robust defence against potential threats to crop yield and food quality. As SERS continues to evolve, its role in shaping the future of agriculture becomes increasingly pronounced, promising a paradigm shift in how we approach and address challenges in food production and safety.

In situ surface-enhanced Raman spectroscopy for the detection of nanoplastics: A novel approach inspired by the aging of nanoplastics

Nanoplastics (NPs) present a hidden risk to organisms and the environment via migration and enrichment. Detecting NPs remains challenging because of their small size, low ambient concentrations, and environmental variability. There is an urgency to exploit detection approaches that are more compatible with real-world environments. Herein, this study provides a surface-enhanced Raman spectroscopy (SERS) technique for the in situ reductive generation of silver nanoparticles (Ag NPs), which is based on photoaging-induced modifications in NPs. The feasibility of generating Ag NPs on the surface of NPs was derived by exploring the photoaging mechanism, which was then utilized to SERS detection. The approach was applied successfully for the detection of polystyrene (PS), polyvinyl chloride (PVC), and polyethylene terephthalate (PET) NPs with excellent sensitivity (e.g., as low as 1 × 10-6 mg/mL for PVC NPs, and an enhancement factor (EF) of up to 2.42 × 105 for small size PS NPs) and quantitative analytical capability (R2 > 0.95579). The method was successful in detecting NPs (PS NPs) in lake water. In addition, satisfactory recoveries (93.54-105.70 %, RSD < 12.5 %) were obtained by spiking tap water as well as lake water, indicating the applicability of the method to the actual environment. Therefore, the proposed approach offers more perspectives for testing real environmental NPs.

Field-Assisted Efficient Capturing and Analysis of Airborne Nanoparticulate Matter Using a Multifunctional Nanoporous Membrane

As the potential adverse health and environmental effects of nanoscale pollutants have garnered significant attention, the demand for monitoring and capturing ultrafine particulate matter has been growing. With the rise in ultrafine dust emissions, this issue has become increasingly important. However, submicron particles require advanced strategies to be captured because of their limited inertial effect. For example, electrostatic air filters have been investigated for their improved performance in the fine particle regime. On the other hand, Raman spectroscopy was proposed as a promising analytical strategy for aerosol particles because it can be used to conveniently detect analytes in a label-free manner. Thus, the synergistic integration of these strategies can open new applications for addressing environment-related challenges. This study presents a multifunctional approach for achieving both air filtration and surface-enhanced Raman scattering (SERS) for analyte identification. We propose a nanoporous membrane composed of a thin gold layer, copper, and copper oxide to provide the desired functions. The structures are produced by performing scalable electrodeposition and subsequent electron-beam evaporation, attaining an excellent filtration efficiency of 95.9% with an applied voltage of 5 kV for 300 nm KCl particles and a pressure drop of 121 Pa. Raman intensity measurements confirm that the nanodendritic surface of the membrane intensifies the Raman signals and allows for the detection of 10 μL of nanoplastic particle dispersion with a concentration of 50 μg/mL. Rhodamine 6G aerosol stream with an approximate particle deposition rate of 0.040 × 106 mm-2·min-1 is also identified in a minimum detectable time of 50 s. The membrane is shown to be recyclable owing to its structural robustness in organic solvents. In addition, the fatigue resistance of the structure is evaluated through 22,000 iterative loading cycles at a pressure of 177 kPa. No performance degradation is observed after the fatigue loading.

One-step synthesized multisize AuAg alloy nanoparticles with high SERS sensitivity in directly detecting SARS-CoV-2 spike protein

The coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in widespread disease transmission, challenging the stability of global healthcare systems. Surface-enhanced Raman scattering (SERS) as an easy operation, fast, and low-cost technology illustrates a good potential in detecting SARS-CoV-2. In the study, one-step fabrication of gold-silver alloy nanoparticles (AuAgNPs) with adjustable metal proportions and diameters is employed as SERS substrates. The angiotensin-converting enzyme 2 (ACE2) functionalized AuAgNPs are applied as sensor surfaces to detect SARS-CoV-2 S protein. By optimizing the SERS substrates, ACE2/Au35Ag65NPs illustrate higher performance in detecting the SARS-CoV-2 S protein with a limit of detection (LOD) of 10 fg/mL in both phosphate-buffered saline (PBS) and pharyngeal swabs solution (PSS). It also provides excellent reproducibility with a relative standard deviation (RSD) of 7.7 % and 7.9 %, respectively. This easily preparable and highly reproducible SERS substrate has good potential in the practical application of detecting SARS-CoV-2.

A green approach to nanoplastic detection: SERS with untreated filter paper for polystyrene nanoplastics

Plastic pollution at the nanoscale continues to pose adverse effects on environmental sustainability and human health. However, the detection of nanoplastics (NPLs) remains challenging due to limitations in methodology and instrumentation. Herein, a "green approach" for surface-enhanced Raman spectroscopy (SERS) was exploited to detect polystyrene nanospheres (PSNSs) in water, employing untreated filter paper and a simple syringe-filtration set-up. This SERS protocol not only enabled the filtration of nano-sized PSNSs, which are smaller than the pore size of the ordinary filter paper, but also offered SERS enhancement by utilizing quasi-spherical-shaped silver nanoparticles (AgNPs) as the SERS-active substrate. The filtering of NPLs was accomplished by adding an aggregating agent to the nanoparticle mixture, which caused the aggregation of NPLs and AgNPs, resulting in a larger cluster and more hot spots for SERS detection. The optimal aggregating agent and its concentration, as well as the volume ratio between the AgNPs and NPLs, were also optimized. This SERS method successfully detected and quantified PSNSs of various sizes (i.e., 100, 300, 460, 600, and 800 nm) down to a limit of detection (LOD) of about 0.31 μg mL-1. The method was also validated against the presence of several interferents (i.e., salts, sugars, amino acids, and surfactants) and was proven practical, as evidenced by the detection of 800nm PSNSs in drinking and tap water (LODs of 1.47 and 1.55 μg mL-1, respectively).

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

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

Construction of PCR-SERS Method for Detection of Vibrio parahaemolyticus

A paper-based surface enhancement of a Raman scattering substrate consisting of silver-nanowires stacked on glass-fiber filter paper was prepared. At the same time, the DNA-embedding molecule Eva Green was introduced as a signaling molecule for surface-enhanced Raman scattering (SERS) detection. Polymerase chain reaction (PCR) was used to amplify target genes and the method was developed into a rapid molecular diagnostic system. The total detection time of the developed detection method was 40 min, including 30 min of PCR amplification and 10 min of SERS measurement. After 30 PCR cycles, bacterial DNA with an initial concentration of 20 fg/μL and a bacterial suspension with an initial concentration of 7.2 × 101 CFUs/mL could be detected. When the enrichment culture time was 4 h, target bacteria with an initial contamination inoculation volume of 1.5 CFUs/mL could be detected in artificially contaminated samples. The method is fast and highly sensitive, and has not been applied to the detection of V. parahaemolyticus.

Green and sustainable self-cleaning flexible SERS base: Utilized for cyclic-detection of residues on apple surface

Advances in flexible SERS substrates has made it possible to approach the ultimate goal of rapid in-situ monitoring of fruit and vegetable safety, but its vulnerability under laser ablation results in low utilization. In order to solve this problem, a 3D framework of TiO2-doped PVDF\PVP polymer was utilized to self-assemble gold-silver core-shell nanorods (Au@Ag NRs) to prepare a flexible SERS substrate with good physical stability and self-cleaning properties. This substrate showed excellent detection limit and recyclability after the detection of three pesticide residues in apple peel. The LOD of methyl-parathion (MP) was as low as 0.037 ng/cm2, with an RSD of 5.61 % for 5 cycle-detection. The recoveries of two additional pesticides thiram (TMTD) and chlorpyrifos (CPF) were 86.32 %-112.47 %. We hoped that this research will contribute to providing a recyclable and facile method for in-situ analysis of fruit and vegetable surface residues and functional manufacture of flexible SERS substrates.

Quantitative analysis of microplastics in water environments based on Raman spectroscopy and convolutional neural network

With the increasing interest in microplastics (MPs) pollutants, quantitative analysis of MPs in water environment is an important issue. Vibrational spectroscopy, represented by Raman spectroscopy, is widely used in MP detection because they can provide unique fingerprint characteristics of chemical components of MPs, but it is difficult to provide quantitative information. In this paper, an ingenious method for quantitative analysis of MPs in water environment by combining Raman spectroscopy and convolutional neural network (CNN) is proposed. It is innovatively proposed to collect the average mapping spectra (AMS) of the samples to improve the uniformity of Raman spectroscopy detection, and to increase the effective detection range of concentration by filtering different volumes of the same MP solutions. In order to verify the universality and effectiveness of the proposed method, 6 different sizes of Polyethylene (PE) MPs were used as detection objects and mixed into 5 different actual water environments. The R2 and RMSE of CNN for identifying the concentration of PE solutions could reach 0.9972 and 0.033, respectively. Meanwhile, by comparing machine learning models such as Random Forest (RF) and Support Vector Machine (SVM) were compared, and CNN combined with Raman spectroscopy has significant advantages in identifying the concentration of MPs.

Silver nanostars arrayed on GO/MWCNT composite membranes for enrichment and SERS detection of polystyrene nanoplastics in water

Nanoplastic water contamination has become a critical environmental issue, highlighting the need for rapid and sensitive detection of nanoplastics. In this study, we aimed to prepare a graphene oxide (GO)/multiwalled carbon nanotube (MWCNT)-silver nanostar (AgNS) multifunctional membrane using a simple vacuum filtration method for the enrichment and surface-enhanced Raman spectroscopy (SERS) detection of polystyrene (PS) nanoplastics in water. AgNSs, selected for the size and shape of nanoplastics, have numerous exposed Raman hotspots on their surface, which exert a strong electromagnetic enhancement effect. AgNSs were filter-arrayed on GO/MWCNT composite membranes with excellent enrichment ability and chemical enhancement effects, resulting in the high sensitivity of GO/MWCNT-AgNS membranes. When the water samples flowed through the portable filtration device with GO/MWCNT-AgNS membranes, PS nanoplastics could be effectively enriched, and the retention rate for 50 nm PS nanoplastics was 97.1 %. Utilizing the strong SERS effect of the GO/MWCNT-AgNS membrane, we successfully detected PS nanoparticles with particle size in the range of 50-1000 nm and a minimum detection concentration of 5 × 10-5 mg/mL. In addition, we detected 50, 100, and 200 nm PS nanoplastics at concentrations as low as 5 × 10-5 mg/mL in real water samples using spiking experiments. These results indicate that the GO/MWCNT-AgNS membranes paired with a portable filtration device and Raman spectrometer can effectively enrich and rapidly detect PS nanoplastics in water, which has great potential for on-site sensitive water quality safety evaluation.

Submicron- and nanoplastic detection at low micro- to nanogram concentrations using gold nanostar-based surface-enhanced Raman scattering (SERS) substrates

The presence of submicron- (1 μm-100 nm) and nanoplastic (<100 nm) particles within various sample matrices, ranging from marine environments to foods and beverages, has become a topic of increasing interest in recent years. Despite this interest, very few analytical techniques are known that allow for the detection of these small plastic particles in the low concentration ranges that they are anticipated to be present at. Research focused on optimizing surface-enhanced Raman scattering (SERS) to enhance signal obtained in Raman spectroscopy has been shown to have great potential for the detection of plastic particles below conventional resolution limits. In this study, we produce SERS substrates composed of gold nanostars and assess their potential for submicron- and nanoplastic detection. The results show 33 nm polystyrene could be detected down to 1.25 μg mL-1 while 36 nm poly(ethylene terephthalate) was detected down to 5 μg mL-1. These results confirm the promising potential of the gold nanostar-based SERS substrates for nanoplastic detection. Furthermore, combined with findings for 121 nm polypropylene and 126 nm polyethylene particles, they highlight potential differences in analytical performance that depend on the properties of the plastics being studied.

Label-Free Surface-Enhanced Raman Scattering Detection of Fire Blight Pathogen Using a Pathogen-Specific Bacteriophage

Fire blight is one of the most devastating plant diseases, causing severe social and economic problems. Herein, we report a novel method based on label-free surface-enhanced Raman scattering (SERS) combined with an Erwinia amylovora-specific bacteriophage that allows detecting efficiently fire blight bacteria E. amylovora for the first time. To achieve the highest SERS signals for E. amylovora, we synthesized and compared plasmonic nanoparticles (PNPs) with different sizes, i.e., bimetallic gold core-silver shell nanoparticles (Au@AgNPs) and monometallic gold nanoparticles (AuNPs) and utilized the coffee-ring effect for the self-assembly of PNPs and enrichment of fire blight bacteria. Furthermore, we investigated the changes in the SERS spectra of E. amylovora after incubation with an E. amylovora-specific bacteriophage, and we found considerable differences in the SERS signals as a function of the bacteriophage incubation time. The results indicate that our bacteriophage-based label-free SERS analysis can specifically detect E. amylovora without the need for peak assignment on the SERS spectra but simply by monitoring the changes in the SERS signals over time. Therefore, our facile method holds great potential for the label-free detection of pathogenic bacteria and the investigation of viral-bacterial interactions.

Transparent regenerated cellulose film containing azobenzene group with reversible stimulus discoloration property

The cellulose film, exhibiting color alterations in response to external stimuli, presents itself as a promising functional material. In this study, a universal dissolution-regeneration technique was employed to manufacture a transparent, regenerated cellulose film, characterized by its reversible multi-stimulus discoloration property. This functional cellulose film, endowed with both photochromic and acid-chromic attributes, was synthesized through the introduction of a cellulose-grafted azobenzene derivative into the cellulose solution. The hue of a cellulose film irradiated with ultraviolet light could be inverted upon exposure to visible light or heat. Furthermore, when subject to heating, irradiation, or immersion in an acidic medium, this functional film demonstrated pronounced transparency. The acid-chromic behavior of the film was readily discernible when exposed to highly concentrated acidic aqueous solutions. Both the photochromic and acid-chromic phenomena were discernable to the unaided eye. After ten cycles, no fading of the reversible discoloration properties of the material occurred. This transparent regenerated cellulose film stands as a viable candidate for applications in optical data storage, intelligent switches, and sensors, owing to its capacity for reversible stimulus-triggered discoloration.

Honeycomb-like AgNPs@TiO2 array SERS sensor for the quantification of micro/nanoplastics in the environmental water samples

There has been a growing concern over the micro/nanoplastics pollution and treatment. The fast qualitative and quantitative analysis of these small plastic particles is the crucial issues. Herein, a novel honeycomb-like AgNPs@TiO2 array-based surface-enhanced Raman scattering (SERS) sensor was developed for efficient identification and analysis of the micro/nanoplastics in the environmental water samples. The plasmonic AgNPs were uniformly anchored within the periodic TiO2 nanocage arrays to form a AgNPs@TiO2 array. The dual enhancement mechanisms in the AgNPs@TiO2 hybrid structure endow the SERS sensor high sensitivity to detect trace amount of micro/nanoplastics down to 50 μg/mL with a hand-held Raman spectrometer. Further, this SERS sensor successfully discerns two-component mixtures of the micro/nanoplastics due to the fingerprint feature. In addition, the superior reproducibility (RSD of 9.69%) of the SERS sensor assures the quantitative detection reliability, realizing quantitative analysis of Polystyrene (PS) microplastics in tap water, lake water, soil water and seawater with detection limits of 100 μg/mL, 100 μg/mL, 100 μg/mL, 100 μg/mL and 250 μg/mL, respectively. The recovery rates of PS microspheres in four water environments ranged from 97.6% to 109.7%, with the RSD ranging from 0.49% to 10.23%. This honeycomb AgNPs@TiO2 array sensor provides a promising application prospect in the detection of micro/nanoplastics contaminants from the environmental water.

Component identification for the SERS spectra of microplastics mixture with convolutional neural network

With the increasing interest in microplastics (MPs) pollutants, relevant detection technologies are also developing. In MPs analysis, vibrational spectroscopy represented by surface-enhanced Raman spectroscopy (SERS) is widely used because they can provide unique fingerprint characteristics of chemical components. However, it is still a challenge to separate various chemical components from the SERS spectra of MPs mixture. In this study, it is innovatively proposed to combine the convolutional neural networks (CNN) model to simultaneously identify and analyze each component in the SERS spectra of six common MPs mixture. Different from the traditional method, which requires a series of spectral preprocessing such as baseline correction, smoothing and filtering, the average identification accuracy of MP components is as high as 99.54 % after the unpreprocessed spectral data is trained by CNN, which is better than other classical algorithms such as support vector machine (SVM), principal component analysis linear discriminant analysis (PCA-LDA), partial least squares discriminant analysis (PLS-DA), Random Forest (RF), and K Near Neighbor (KNN), with or without spectral preprocessing. The high accuracy shows that CNN can be used to quickly identify MPs mixture with unpreprocessed SERS spectra data.

Dark background-surface enhanced Raman spectroscopic detection of nanoplastics: Thermofluidic strategy

This study aims to develop a cost-effective and time-efficient method for detecting nanoplastics, which have recently garnered significant attention due to their potential harmful impact on the water environment (XiaoZhi, 2021; Gigault et al., 2021; Mitrano et al., 2021; Ferreira et al., 2019). Although several techniques are available to accumulate data on microplastics, there is currently no universally accepted analytical technique for detecting nanoplastics (Gigault et al., 2021; Mitrano et al., 2021; Mitrano et al., 2019; Cai et al., 2021a; Allen et al., 2022). In this study, we have developed a substrate that exhibits Surface-enhanced Raman scattering (SERS) (Zhou et al., 2021; Lv et al., 2020; Lê et al., 2021; Hu et al., 2022; Chang et al., 2022; Yang et al., 2022; Xu et al., 2020; Jeon et al., 2021; Lee and Fang, 2022; Vélez-Escamilla and Contreras-Torres, 2022; Liu et al., 2022; Xie et al., 2023) activity over a large area and a dark background in optical (darkfield mode) vision, enabling the detection of sparkling nanoplastics on the substrate. This darkfield-based strategy allows for the point-by-point detection of single nanoplastics, offering cost and time-saving advantages over other resource-intensive analytical techniques. Our findings reveal the presence of PP nanoplastics in commonly used laboratory equipment, individual PE nanoplastics from a hot water-contained commercial paper cup, and the first detection of natural nanoplastics in coastal seawater. We believe that this technique will have a universal application in establishing a global map of nanoplastics and advancing our understanding of the environmental life cycle of plastics.

Hydrophobicity-driven self-assembly of nanoplastics and silver nanoparticles for the detection of polystyrene microspheres using surface enhanced Raman spectroscopy

Microplastics (MPs) and Nanoplastics (NPs) accumulated in the environment have been identified as a major global issue due to their potential harm to wildlife. Current research in the detection of MPs is well established. However, the detection of NPs remains challenging. The aim of this paper is to investigate the detection of polystyrene (PS) NPs on a super-hydrophobic substrate using surface-enhanced Raman spectroscopy (SERS) technology after high-speed centrifugation of PS NPs and AgNPs. The hydrophobic substrate reduces the contact area of droplet, concentrating PS NPs and AgNPs on a small spot, which eliminates the random distribution of nano particles. The condensed PS NPs and AgNPs improve the SERS intensity, reproductivity and detection sensitivity. The results show that SERS measurement on a hydrophobic substrate could significantly improve the detection sensitivity of PS NPs, with the detection limits of PS NPs as low as 0.5 mg/L (500 nm PS NPs) and 1 mg/L (100 nm PS NPs). The study provides an effective and rapid method for the detection of NPs at trace concentration, demonstrating more possibility for the future detection of trace NPs in the aquatic environment.

Imaging and identification of single nanoplastic particles and agglomerates

Pollution by nanoplastic is a growing environmental and health concern. Currently the extent of nanoplastic in the environment can only be cumbersomely and indirectly estimated but not measured. To be able to quantify the extent of the problem, detection methods that can identify nanoplastic particles that are smaller than 1 [Formula: see text]m are critically needed. Here, we employ surface-enhanced Raman scattering (SERS) to image and identify single nanoplastic particles down to 100 nm in size. We can differentiate between single particles and agglomerates and our method allows an improvement in detection speed of [Formula: see text] compared to state-of-the art surface-enhanced Raman imaging. Being able to resolve single particles allows to measure the SERS enhancement factor on individual nanoplastic particles instead of averaging over a concentration without spatial information. Our results thus contribute to the better understanding and employment of SERS for nanoplastic detection and present an important step for the development of future sensors.

Raman spectra characterization of size-dependent aggregation and dispersion of polystyrene particles in aquatic environments

Aqueous environments are generally thought to be a source of pooling and re-distribution for both micro-plastics (MPs) and nano-plastics (NPs); however, significantly less data on NPs than MPs have been reported. The occurrence of salts, proteins, and other organic matter may promote or inhibit the aggregation of NPs to form agglomeration particles, making their detection more difficult. In this study, 80 and 500 nm polystyrene nano-plastics (PS-NPs) modified by four different functional groups (PS-Bare, PS-COOH, PS-NH₂, and PS-CHO-500 nm) were selected to mimic the flocculation and/or sedimentation of NPs in salts (NaCl, CaCl₂, and Na₂SO₄) and protein solutions. The results showed that the 80 nm PS-NPs are only colloidal in pure water. All four strong electrolyte solutions that were tested significantly promoted the aggregation of PS-NPs, including those that were protein-coated. In addition, 500 nm PS-CHO did not flocculate but gradually settled into sedimentation. Therefore, Raman spectrometry can be used to analyze assembled PS-NPs, but is not suitable for analyzing normal PS-NPs. By combining fractal morphology, this study provides insight into the comprehensive analysis of PS-NPs in water solutions, including the digestion of biological samples.

Controllable preparation of mesoporous spike gold nanocrystals for surface-enhanced Raman spectroscopy detection of micro/nanoplastics in water

Microplastics and nanoplastics are emerging classes of environmental contaminants that pose significant threats to human health. In particular, small nanoplastics (<1 μm) have drawn considerable attention owing to their adverse effects on human health; for example, nanoplastics have been found in the placenta and blood. However, reliable detection techniques are lacking. In this study, we developed a fast detection method that combines membrane filtration technology and surface-enhanced Raman spectroscopy (SERS), which can simultaneously enrich and detect nanoplastics with sizes as small as 20 nm. First, we synthesized spiked gold nanocrystals (Au NCs), achieving a controlled preparation of thorns ranging from 25 nm to 200 nm and regulating the number of thorns. Subsequently, mesoporous spiked Au NCs were homogeneously deposited on a glass fiber filter membrane to form an Au film as a SERS sensor. The Au-film SERS sensor achieved in-situ enrichment and sensitive SERS detection of micro/nanoplastics in water. Additionally, it eliminated sample transfer and prevented the loss of small nanoplastics. Using the Au-film SERS sensor, we detected 20 nm to 10 μm standard polystyrene (PS) microspheres with a detection limit of 0.1 mg/L. We also realized the detection of 100 nm PS nanoplastics at the 0.1 mg/L level in tap water and rainwater. This sensor provides a potential tool for rapid and susceptible on-site detection of micro/nanoplastics, especially small-sized nanoplastics.

Nanowire-in-bowl-shaped piezoelectric cavity structure for SERS directional detection of nanoplastics less than 50 nm

The accurate detection of nanoplastics is crucial due to their harmful effects on the environment and human beings. However, there is a lack of detection methods for nanoplastics smaller than 50 nm. In this research, we successfully constructed an Ag/CuO nanowire (NW)/BaTiO₃@Polyvinylidene fluoride (PVDF) Bowl-shaped substrate with a nanowire-in-Bowl-shaped piezoelectric cavity structure that can modulate surface-enhanced Raman scattering (SERS) by the piezoelectric effect by the virtue of the tip effect of the CuO NW and light focusing effect of the Bowl-shaped cavity. Due to its unique nanowire-in-Bowl-shaped structure and piezoelectrically modifiable ability, nanoplastics less than 50 nm were successfully detected and quantitatively analyzed. We believe that the Ag/CuO NW/BaTiO₃@PVDF Bowl-shaped substrate can provide an efficient, accurate, and feasible way to achieve qualitative and quantitative detection of nanoplastics.

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.

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.

Spectro-Microscopic Techniques for Studying Nanoplastics in the Environment and in Organisms

Nanoplastics (NPs), small (<1 μm) polymer particles formed from bulk plastics, are a potential threat to human health and the environment. Orders of magnitude smaller than microplastics (MPs), they might behave differently due to their larger surface area and small size, which allows them to diffuse through organic barriers. However, detecting NPs in the environment and organic matrices has proven to be difficult, as their chemical nature is similar to these matrices. Furthermore, as their size is smaller than the (spatial) detection limit of common analytical tools, they are hard to find and quantify. We highlight different micro-spectroscopic techniques utilized for NP detection and argue that an analysis procedure should involve both particle imaging and correlative or direct chemical characterization of the same particles or samples. Finally, we highlight methods that can do both simultaneously, but with the downside that large particle numbers and statistics cannot be obtained.

Assembling nanocelluloses into fibrous materials and their emerging applications

Nanocelluloses, derived from various plants or specific bacteria, represent the renewable and sophisticated nano building blocks for emerging functional materials. Especially, the assembly of nanocelluloses as fibrous materials can mimic the structural organization of their natural counterparts to integrate various functions, thus holding great promise for potential applications in various fields, such as electrical device, fire retardance, sensing, medical antibiosis, and drug release. Due to the advantages of nanocelluloses, a variety of fibrous materials have been fabricated with the assistance of advanced techniques, and their applications have attracted great interest in the past decade. This review begins with an overview of nanocellulose properties followed by the historical development of assembling processes. There will be a focus on assembling techniques, including traditional methods (wet spinning, dry spinning, and electrostatic spinning) and advanced methods (self-assembly, microfluidic, and 3D printing). In particular, the design rules and various influencing factors of assembling processes related to the structure and function of fibrous materials are introduced and discussed in detail. Then, the emerging applications of these nanocellulose-based fibrous materials are highlighted. Finally, some perspectives, key opportunities, and critical challenges on future research trends within this field are proposed.

Flexible surface-enhanced Raman scatting substrates: recent advances in their principles, design strategies, diversified material selections and applications

Surface-enhanced Raman scattering (SERS) is widely used as a powerful analytical technology in cutting-edge areas such as food safety, biology, chemistry, and medical diagnosis, providing ultra-fast, ultra-sensitive, nondestructive characterization and achieving ultra-high detection sensitivity even down to the single-molecule level. Development of Raman spectroscopy is strongly dependent on high-performance SERS substrates, which have long evolved from the early days of rough metal electrodes to periodic nanopatterned arrays building on solid supporting substrates. For rigid SERS substrates, however, their applications are restricted by sophisticated pretreatments for detecting solid samples with non-planar surfaces. It is therefore essential to reassert the principles in constructing flexible SERS substrates. Herein, we comprehensively review the state-of-the-art in understanding, preparing and using flexible SERS. The basic mechanisms behind the flexible SERS are briefly outlined, typical design strategies are highlighted and diversified selection of materials in preparing flexible SERS substrates are reviewed. Then the recent achievements of various interdisciplinary applications based on flexible SERS substrates are summarized. Finally, the challenges and perspectives for future evolution of flexible SERS and their applications are demonstrated. We propose new research directions focused on stimulating the real potential of SERS as an advanced analytical technique for commercialization.

Identification of Trace Polystyrene Nanoplastics Down to 50 nm by the Hyphenated Method of Filtration and Surface-Enhanced Raman Spectroscopy Based on Silver Nanowire Membranes

Nanoplastics are emerging pollutants that pose potential threats to the environment and organisms. However, in-depth research on nanoplastics has been hindered by the absence of feasible and reliable analytical methods, particularly for trace nanoplastics. Herein, we propose a hyphenated method involving membrane filtration and surface-enhanced Raman spectroscopy (SERS) to analyze trace nanoplastics in water. In this method, a bifunctional Ag nanowire membrane was employed to enrich nanoplastics and enhance their Raman spectra in situ, which omitted sample transfer and avoided losing smaller nanoplastics. Good retention rates (86.7% for 50 nm and approximately 95.0% for 100-1000 nm) and high sensitivity (down to 10^-7 g/L for 50-1000 nm and up to 10⁵ SERS enhancement factor) of standard polystyrene (PS) nanoplastics were achieved using the proposed method. PS nanoplastics with concentrations from 10^-1 to 10^-7 g/L and sizes ranging from 50 to 1000 nm were successfully detected by Raman mapping. Moreover, PS micro- and nanoplastics in environmental water samples collected from the seafood market were also detected at the μg/L level. Consequently, the proposed method provides more possibilities for analyzing low-concentration nanoplastics in aquatic environments with high enrichment efficiency, minimal sample loss, and high sensitivity.

Advanced microplastic monitoring using Raman spectroscopy with a combination of nanostructure-based substrates

Micro(nano)plastic (MNP) pollutants have not only impacted human health directly, but are also associated with numerous chemical contaminants that increase toxicity in the natural environment. Most recent research about increasing plastic pollutants in natural environments have focused on the toxic effects of MNPs in water, the atmosphere, and soil. The methodologies of MNP identification have been extensively developed for actual applications, but they still require further study, including on-site detection. This review article provides a comprehensive update on the facile detection of MNPs by Raman spectroscopy, which aims at early diagnosis of potential risks and human health impacts. In particular, Raman imaging and nanostructure-enhanced Raman scattering have emerged as effective analytical technologies for identifying MNPs in an environment. Here, the authors give an update on the latest advances in plasmonic nanostructured materials-assisted SERS substrates utilized for the detection of MNP particles present in environmental samples. Moreover, this work describes different plasmonic materials-including pure noble metal nanostructured materials and hybrid nanomaterials-that have been used to fabricate and develop SERS platforms to obtain the identifying MNP particles at low concentrations. Plasmonic nanostructure-enhanced materials consisting of pure noble metals and hybrid nanomaterials can significantly enhance the surface-enhanced Raman scattering (SERS) spectra signals of pollutant analytes due to their localized hot spots. This concise topical review also provides updates on recent developments and trends in MNP detection by means of SERS using a variety of unique materials, along with three-dimensional (3D) SERS substrates, nanopipettes, and microfluidic chips. A novel material-assisted spectral Raman technique and its effective application are also introduced for selective monitoring and trace detection of MNPs in indoor and outdoor environments.

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A gold nanoparticle doped flexible substrate for microplastics SERS detection

Due to overuse of plastic products, decomposed microplastics (MPs) are widely spread in aquatic ecosystems, and will cause irreparable harm to the human body through the food chain. Traditional MP detection methods require cumbersome sample pre-processing procedures and complex instruments, so there is an urgent demand to develop methods to achieve simple on-site detection. Herein, a simple, sensitive, accurate, and stable MP detection method based on surface-enhanced Raman scattering (SERS) is investigated. Considering the hydrophobic problems of MPs, gold nanoparticle (AuNP) doped filter paper as a flexible SERS substrate is applied to capture MPs in the fiber pores. Benefitting from the electromagnetic (EM) hot spots generated by AuNPs, the Raman signal of MPs can be effectively enhanced. Meanwhile, the flexible SERS substrate has good sensitivity to a minimum detectable concentration of 0.1 g L^-1 for polyethylene terephthalate (PET) in water, and the maximum enhancement factor (EF) can reach 360.5. Furthermore, the practicability of the developed method has been proved by the successful detection of MPs in tap water and pond water. This research provides an easy process, high sensitivity, and good reproducibility method for MP detection.

Applications of surface-enhanced Raman spectroscopy in environmental detection

As the human population grows, the anthropogenic impacts from various agricultural and industrial processes produce unwanted contaminants in the environment. The accurate, sensitive and rapid detection of such contaminants is vital for human health and safety. Surface-enhanced Raman spectroscopy (SERS) is a valuable analytical tool with wide applications in environmental contaminant monitoring. The aim of this review is to summarize recent advancements within SERS research as it applies to environmental detection, with a focus on research published or accessible from January 2021 through December 2021 including early-access publications. Our goal is to provide a wide breadth of information that can be used to provide background knowledge of the field, as well as inform and encourage further development of SERS techniques in protecting environmental quality and safety. Specifically, we highlight the characteristics of effective SERS nanosubstrates, and explore methods for the SERS detection of inorganic, organic, and biological contaminants including heavy metals, pharmaceuticals, plastic particles, synthetic dyes, pesticides, viruses, bacteria and mycotoxins. We also discuss the current limitations of SERS technologies in environmental detection and propose several avenues for future investigation. We encourage researchers to fill in the identified gaps so that SERS can be implemented in a real-world environment more effectively and efficiently, ultimately providing reliable and timely data to help and make science-based strategies and policies to protect environmental safety and public health.

Detecting polystyrene nanoplastics using filter paper-based surface-enhanced Raman spectroscopy

This work presents a novel filter paper-based method using surface-enhanced Raman spectroscopy (SERS), for detecting polystyrene nanoplastics (PSNPs).

Nanotechnology in food and water security: on-site detection of agricultural pollutants through surface-enhanced Raman spectroscopy

Agricultural pollutants are harmful components threatening human health, wildlife, the environment, and the ecosystem. To avoid their exposure, developing prevention and detection systems with high sensitivity and selectivity is required. Most conventional methods, including molecular and chromatographic techniques, cannot be adopted for outdoor on-site detection even though they can provide sensitive and selective detection. Thus, detection platforms that can provide on-site detection via miniaturized and high throughput systems should be developed. As an alternative method, surface-enhanced Raman scattering (SERS) provides unique information about the substances in the presence of plasmonic nanostructures, and it can be portable with the use of portable detection systems and spectrometers. In this study, on-site detection of agricultural pollutants through SERS is reviewed. Three different types of agricultural pollutants were pointed out. On-site detection of biological pollutants, including bacteria and viruses, is reviewed as the first type of pollutant. As a second type, the detection of pesticides, antibiotics, and additives are focused on as chemical pollutants. The third group includes the detection of microplastics and also nanoparticles from the environment.