Dynamic Surface-enhanced Raman Spectroscopy Research Articles

Photoactive Au@MoS2 Micromotors for Dynamic Surface-Enhanced Raman Spectroscopy Sensing.

Photophoretic Au@MoS2 micromotors are used as smart mobile substrates for dynamic surface-enhanced Raman spectroscopy (SERS) sensing. The photophoretic capabilities and swarming-like propulsion of the micromotors allow for their schooling and accumulation in the measuring spot, increasing the density of SERS-active gold nanoparticles for Raman mapping and, simultaneously, the preconcentration of the target analyte. The generation of "hot-microflake spots" directly in the Raman irradiation point results in a 15-18-fold enhancement in the detection of crystal violet without the requirement for additional external sources for propulsion. Moreover, the reproducible collective micromotor motion does not depend on the exact position of the laser spot concerning individual micromotors, which greatly simplifies the experimental setup, avoiding the requirements of sophisticated equipment. The strategy was further applied for the detection of malachite green and paraquat with a good signal enhancement. The new on-the-move-based SERS strategy holds great promise for on-site detection with portable instrumentation in a myriad of environmental monitoring and clinical applications.

Dynamic surface-enhanced Raman spectroscopy and positively charged probes for rapid detection and accurate identification of fungal spores in infected apples via deep learning methods

Fungal infections pose a significant threat to apples; therefore, the detection of fungal spores is imperative for controlling infection spread and ensuring food safety. In this study, dynamic surface-enhanced Raman spectroscopy (D-SERS) and positively charged probes were developed to detect and identify the fungal spores via deep learning methods. Firstly, the gold nanorods were modified with cysteamine to develop the positively charged SERS probes, enhancing the capture of fungal spores by promoting interactions with the negatively charged cell wall. Then, the probes and D-SERS were combined to measure the SERS spectra of fungal spores, and the optimal spectral signals were obtained under the metastable state of D-SERS from wet to dry. This was due to capillary forces inducing nanoparticles to form a large number of 3D hot spots, resulting in significant enhancement. Spores of Aspergillus flavus, Rhizopus stolonifer, and Botrytis cinerea can be easily detected with excellent SERS signals from infected apples after simple separation through filtration and centrifugation. Furthermore, the best recognition model was developed by ZFNet, a powerful deep learning method, with the accuracies in the training set, validation set, and prediction set of 100%, 99.44%, and 99.44%, respectively. The proposed method provides a simple, rapid, and accurate approach for the detection and identification of fungal infections in apples, and can be extended to other agricultural products.

Real-Time Monitoring of a Single Molecule in Sub-nanometer Space by Dynamic Surface-Enhanced Raman Spectroscopy.

In biology and chemistry, the ultimate goal is to monitor single molecules without labels. However, long-term monitoring of label-free molecules remains a challenge. Here, on the basis of the photothermal effect of gold nanorods (GNRs), we developed a platform for monitoring of a single molecule employing surface-enhanced Raman spectroscopy (SERS). Laser re-irradiation forms 1.0 nm gaps between GNRs, allowing us to observe single crystal violet (CV) molecules blinking for up to 4 min with dynamic surface-enhanced Raman spectroscopy (D-SERS). Bianalyte experiments confirm single-molecule features at CV concentrations of 10-14 M. Combining density functional theory (DFT) calculations with a free CV molecule observed in millisecond D-SERS, we propose that CV molecules can be confined to sub-nanometer space and the orientation of an individual CV moving in the range of 50-90° can be dynamically captured by D-SERS. This will provide a novel idea for effective exploration of the temporal and spatial dynamic processes of different reactions.

An autofocusing method for dynamic surface-enhanced Raman spectroscopy detection realized by optimized hill-climbing algorithm with long time stable hotspots

In the manual dynamic surface-enhanced Raman spectroscopy (D-SERS) detection process, it is difficult to focus on sample drop due to the constantly changing hotspot and easy judgment method. In this paper, we proposed an automatic focusing method based on long time stable hotspot with aid of optimization of hill-climbing algorithm and achieved on a designed device. First, set up a high temperature accelerating evaporation process to obtain hotspot and then cool to a low temperature rapidly to maintain it. Then, the spectral intensity was used as a focus of feedback signal in optimized hill-climbing algorithm to drive the sample stage to move up and down to adjust the depth of the laser on the samples to realize automatic focusing. As a result, the hotspot can be maintained for 5 min, and the autofocusing result can be achieved within 9 s, while the sensitivity was improved with two orders of magnitude in D-SERS detection of crystal violet (CV) compared with manual focusing.

On-site detection of pyrene from mixture with ppb level sensitivity by plasmonic TLC-DSERS

Polycyclic aromatic hydrocarbons are a kind of persistent organic pollutants, which bring harmful effects to the ecological environment and human health. Therefore, it is critical to identify PAHs. In this study, we developed a highly efficient device for on-site identification of pyrene in edible oil using high performance plasmonic thin layer chromatography (PTLC) and dynamic surface-enhanced Raman spectroscopy (DSERS). PAHs in the mixture sample were efficiently separated on the PTLC plate and visualized under UV light, in which the plasmonic feature of the stationary phase could enhance the fluorescence of PAH. Then DSERS measurement was developed on a portable Raman spectrometer. The smaller size of Au NPs in the stationary phase could provide a lower theoretical plate height and provide higher separation efficiency. The sensitivity of the PTLC-DSERS method is down to 0.1 ppb, that nearly 4 orders of magnitude higher than current TLC-SERS method. The results indicate that this PTLC-DSERS method has the potential for on-site and sensitive identification of pyrene in the mixture.

Dynamic surface-enhanced Raman spectroscopy of DNA oligomer with a single hotspot from a gold nanoparticle dimer.

Various nanostructures for single-molecule surface-enhanced Raman spectroscopy (SERS) have been fabricated through a random aggregation process using nanoparticles that can stochastically generate multiple hotspots in the laser spot. This leads to multiple molecule detection. In this study, a single gold nanoparticle (AuNP) dimer with a single hotspot was fabricated in a laser spot controlling the position and orientation on a silicon substrate using a nanotrench-guided self-assembly. The Raman peaks of deoxyribonucleic acid (DNA) were dynamically observed, indicating a single DNA oligomer detection composed of adenine, guanine, cytosine, phosphate, and deoxyribose.

Differentiation of different antifungals with various mechanisms using dynamic surface-enhanced Raman spectroscopy combined with machine learning

With the increase in mortality caused by pathogens worldwide and the subsequent serious drug resistance owing to the abuse of antibiotics, there is an urgent need to develop versatile analytical techniques to address this public issue. Vibrational spectroscopy, such as infrared (IR) or Raman spectroscopy, is a rapid, noninvasive, nondestructive, real-time, low-cost, and user-friendly technique that has recently gained considerable attention. In particular, surface-enhanced Raman spectroscopy (SERS) can provide a highly sensitive readout for bio-detection with ultralow or even trace content. Nevertheless, extra attachment cost, nonaqueous acquisition, and low reproducibility require the conventional SERS (C-SERS) to further optimize the conditions. The emergence of dynamic SERS (D-SERS) sheds light on C-SERS because of the dispensable substrate design, superior enhancement and stability of Raman signals, and solvent protection. The powerful sensitivity enables D-SERS to perform only with a portable Raman spectrometer with moderate spatial resolution and precision. Moreover, the assistance of machine learning methods, such as principal component analysis (PCA), further broadens its research depth through data mining of the information within the spectra. Therefore, in this study, D-SERS, a portable Raman spectrometer, and PCA were used to determine the phenotypic variations of fungal cells Candida albicans (C. albicans) under the influence of different antifungals with various mechanisms, and unknown antifungals were predicted using the established PCA model. We hope that the proposed technique will become a promising candidate for finding and screening new drugs in the future.

Single-Molecule Level Rare Events Revealed by Dynamic Surface-Enhanced Raman Spectroscopy.

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool to monitor various interfacial behaviors providing molecular level information with high spatial and temporal resolutions. However, it is a challenge to obtain SERS spectra with high quality for analytes having a weak binding affinity with plasmonic nanostructures due to the short dwell time of the analyte on the surface. Here, we employed dynamic SERS, an acquisition method consisting of the rapid acquisition of a series of consecutive SERS spectra, to study the adsorption/desorption behavior of R6G on Ag surfaces. We demonstrated that the signal-noise ratio of SERS spectra of mobile molecules can be improved by dynamic SERS even when the acquisition time cannot catch up with the diffusion time of the molecule. More interestingly, we captured the neutral R6G0 state (spectroscopically different from the dominated positive R6G+ state) of R6G at the single-molecule level, which is a rare molecule event hardly detectable by traditional SERS. Dynamic SERS provides near real-time molecular vibrational information with an improved signal-noise ratio, which opens a new avenue to capture metastable or rare molecule events for the comprehensive understanding of interfacial processes related to catalysis and life science.

Cys-functionalized AuNP substrates for improved sensing of the marine toxin STX by dynamic surface-enhanced Raman spectroscopy.

Saxitoxin (STX) as one of the most harmful and typical paralytic shellfish toxins, is posing a serious threat to environmental and human health, thus it is essential to develop a sensitive and reliable analytical method for STX detection. Herein, we proposed a strategy for rapid and sensitive detection of STX with surface-enhanced Raman spectroscopy (SERS), by employing cysteine modified gold nanoparticles (Cys-AuNPs) as SERS probe to capture STX molecules through electrostatic interactions and multiple hydrogen bonds between Cys and STX molecules. Moreover, the XPS and zeta potential results indicated that Cys could bond to AuNPs through Au-S bonds and the addition of STX could induce the efficient aggregation of Cys-AuNPs owing to the presence of electrostatic interactions and multiple hydrogen bonds between Cys and STX molecules. Furthermore, considering the high sensitivity and stability of the dynamic surface-enhanced Raman spectroscopy (D-SERS) strategy with the formation of a 3D hotspot matrix, the highly sensitive detection of STX was realized to a level of 1 × 10-7M by using the D-SERS strategy. Consequently, Cys-AuNPs as high affinity substrates can provide high sensitivity for the detection of STX through the D-SERS strategy. Graphical abstract.

Dynamic surface-enhanced Raman spectroscopy for the detection of acephate residue in rice by using gold nanorods modified with cysteamine and multivariant methods

Dynamic surface-enhanced Raman spectroscopy (D-SERS) was employed for the rapid detection of acephate in rice with simply regulated gold nanorods. Gold nanorods modified with cysteamine were prepared to circumvent the weak affinity of acephate molecules to the gold surface for a gigantic and stable enhancement. D-SERS was adopted to measure spectra of acephate residue at a range of 100.2–0.5 mg/L in rice samples, and the low residue of 0.5 mg/L can be still detected. Multivariant methods in machine or deep learning were used to develop the regression models for the automatic analysis of acephate residue level. Partial least squares regression and principal component analysis obtained the optimal performance with the root-mean-square error (RMSE) of validation of 5.4776, coefficient of determination (R2) of validation of 0.9560, RMSE of prediction of 6.2845, and R2 of prediction of 0.9541. Thus, the proposed method provides accurate and sensitive detection for acephate in rice.

Synergistic effect between silver nanoparticles and antifungal agents on Candida albicans revealed by dynamic surface-enhanced Raman spectroscopy

Identifying the mechanisms of action of new potential antibiotics is a necessary but time-consuming and costly process. We have developed an ultra-rapid, highly sensitive, and reproducible dynamic surface-enhanced Raman spectroscopy (D-SERS) method to discriminate and evaluate the sensitivity of Candida albicans to antifungal agents with different mechanisms by using silver nanoparticles (Ag NPs). Although Ag NPs have been used conventionally for the enhancement of Raman signals, the accompanying influence of Ag NPs on the microbes has not been investigated. Herein, surface charge and concentration of Ag NPs are likely to be the main influencing factors. Then different concentrations of Ag NPs with the same surface charge as C. albicans were prepared to find the optimal conditions for enhancement of Raman signals while minimally affecting tested fungi. Spectral variations were observed with increasing concentrations of Ag NPs, as well as those of antifungal agents, including echinocandin and azole drugs. The results indicated that the combination of sub-lethal Ag NPs and echinocandin drugs revealed potent synergistic effects against fungi. This could be explained by the metabolism of fungi, the result of which has also been verified by transmission electron microscopy (TEM). Lastly, the combination of sub-lethal Ag NPs and echinocandin drugs was used for a mammalian cell toxicity assay to demonstrate whether the optimal combination could cause lower cytotoxicity to mammalian cells. This work opens a window not only for the evaluation of antifungal agents with different mechanisms, but also for the clinical treatment of fungal infections or even new drug development.

Fast detection of fenthion on fruit and vegetable peel using dynamic surface-enhanced Raman spectroscopy and random forests with variable selection

Dynamic surface-enhanced Raman spectroscopy (D-SERS) based on the state change of the substrate not only significantly enhances but also provides a highly reproducible Raman signal. Hence, we develop a fast and accurate method for the detection of fenthion on fruit and vegetable peel using D-SERS and random forests (RF) with variable selection. With uniform Ag nanoparticles, the dynamic spectra of fenthion solution at different concentrations were obtained using D-SERS, and fenthion solution greater than or equal to 0.05mg/L can be detected. Then, the quantitative analysis models of fenthion were developed by RF with variable selection for spectra of different range. The model of best performance is developed by RF and spectra of characteristic range with higher RF importance (top 40%), and the root mean square error of cross-validation is 0.0101mg/L. Moreover, the fenthion residue of tomato, pear, and cabbage peel were extracted by a swab dipped in ethanol and analyzed using the above method to further validate the practical effect. Compared to gas chromatography, the maximal relative deviation is below 12.5%, and the predicted recovery is between 87.5% and 112.5%. Accordingly, D-SERS and RF with variable selection can realize the fast, simple, ultrasensitive, and accurate analysis of fenthion residue on fruit and vegetable peel.

Dynamic surface-enhanced Raman spectroscopy and Chemometric methods for fast detection and intelligent identification of methamphetamine and 3, 4-Methylenedioxy methamphetamine in human urine

Conventional Surface-Enhanced Raman Spectroscopy (SERS) for fast detection of drugs in urine on the portable Raman spectrometer remains challenges because of low sensitivity and unreliable Raman signal, and spectra process with manual intervention. Here, we develop a novel detection method of drugs in urine using chemometric methods and dynamic SERS (D-SERS) with mPEG-SH coated gold nanorods (GNRs). D-SERS combined with the uniform GNRs can obtain giant enhancement, and the signal is also of high reproducibility. On the basis of the above advantages, we obtained the spectra of urine, urine with methamphetamine (MAMP), urine with 3, 4-Methylenedioxy Methamphetamine (MDMA) using D-SERS. Simultaneously, some chemometric methods were introduced for the intelligent and automatic analysis of spectra. Firstly, the spectra at the critical state were selected through using K-means. Then, the spectra were proposed by random forest (RF) with feature selection and principal component analysis (PCA) to develop the recognition model. And the identification accuracy of model were 100%, 98.7% and 96.7%, respectively. To validate the effect in practical issue further, the drug abusers'urine samples with 0.4, 3, 30ppm MAMP were detected using D-SERS and identified by the classification model. The high recognition accuracy of >92.0% can meet the demand of practical application. Additionally, the parameter optimization of RF classification model was simple. Compared with the general laboratory method, the detection process of urine's spectra using D-SERS only need 2 mins and 2μL samples volume, and the identification of spectra based on chemometric methods can be finish in seconds. It is verified that the proposed approach can provide the accurate, convenient and rapid detection of drugs in urine.

Highly sensitive on-site detection of drugs adulterated in botanical dietary supplements using thin layer chromatography combined with dynamic surface enhanced Raman spectroscopy

The phenomenon of botanical dietary supplements (BDS) doped with illegal adulterants has become a serious problem all over the world, which could cause great threat to human’s health. Therefore, it is of great value to identify BDS. Herein, we put forward a highly sensitive method for on-site detection of antitussive and antiasthmatic drugs adulterated in BDS using thin layer chromatography (TLC) combined with dynamic surface enhanced Raman spectroscopy (DSERS). Adulterants in BDS were separated on a TLC plate and located under UV illumination. Then DSERS detection was performed using a portable Raman spectrometer with 50% glycerol silver colloid serving as DSERS active substrate. Here, the effects of different solvents on detection efficacy were evaluated using phenformin hydrochloride (PHE) as a probe. It was shown that 50% glycerol resulted in higher SERS enhancement and relatively higher stability. Moreover, practical application of this novel TLC–DSERS method was demonstrated with rapid analysis of real BDS samples and one sample adulterated with benproperine phosphate (BEN) was found. Furthermore, the obtained result was verified by ultra performance liquid chromatography-quadrupole time of flight mass spectrometry (UPLC–QTOF/MS). The sensitivity of the TLC–DSERS technique is 1–2 orders of magnitude higher than that of TLC–SERS technique. The results turned out that this combined method would have good prospects for on-site and sensitive detection of adulterated BDS.

ChemInform Abstract: A Dynamic Surface Enhanced Raman Spectroscopy Method for Ultra‐Sensitive Detection: From the Wet State to the Dry State

AbstractReview: 50 refs.

Detection and Direct Readout of Drugs in Human Urine Using Dynamic Surface-Enhanced Raman Spectroscopy and Support Vector Machines

A new, novel, rapid method to detect and direct readout of drugs in human urine has been developed using dynamic surface-enhanced Raman spectroscopy (D-SERS) with portable Raman spectrometer on gold nanorods (GNRs) and a classification algorithm called support vector machines (SVM). The high-performance GNRs can generate gigantic enhancement and the SERS signals obtained using D-SERS on it have high reproducibility. On the basis of this feature of D-SERS, we have obtained SERS spectra of urine and urine containing methamphetamine (MAMP). SVM model was built using these data for fast identified and visual results. This general method was successfully applied to the detection of 3, 4-methylenedioxy methamphetamine (MDMA) in human urine. To verify the accuracy of the model, drug addicts' urine containing MAMP were detected and identified correctly and rapidly with accuracy more than 90%. The detection results were displayed directly without analysis of their SERS spectra manually. Compared with the conventional method in lab, the method only needs a 2 μL sample volume and takes no more than 2 min on the portable Raman spectrometer. It is anticipated that this method will enable rapid, convenient detection of drugs on site for the police.

A dynamic surface enhanced Raman spectroscopy method for ultra-sensitive detection: from the wet state to the dry state.

Surface-enhanced Raman spectroscopy (SERS) has been demonstrated to be an excellent analytical tool for a wide range of research and practical applications owing to its ability to achieve highly sensitive detection and provide fingerprint information for analytes. Improving the sensitivity of SERS is beneficial for the rapid analysis of target molecules in various systems, where the ultimate goal is to obtain quantitative analysis and detection. Considerable efforts have been made to develop new methods for SERS detection that improve upon its high sensitivity and reproducibility. In this tutorial review, we first introduce the traditional methods for SERS detection and then report in detail on the features of a new strategy for implementing SERS. This new method, namely, a dynamic surface-enhanced Raman spectroscopy method proposed by our group, is based on state translation nanoparticle-enhanced Raman spectroscopy (STNERS) from the wet state to the dry state. Notably, during this process, a three-dimensional (3D) hotspot matrix that can hold hotspots between every two adjacent particles in 3D space, with minimal polydispersity of the particle size and maximal uniformity of the interparticle distance, can be simply achieved. Experiments and applications using STNERS are reviewed starting with an investigation of STNERS mechanisms and a discussion of sample preparation. Next, evidence of the advantages of STNERS and practical applications are discussed. Finally, the future outlook for STNERS and the development of STNERS as an ultra-sensitive detection method are also discussed.

A novel paper rag as ‘D-SERS’ substrate for detection of pesticide residues at various peels

Many important considerations in the design of practical Surface enhanced Raman spectroscopy (SERS) substrates are necessary, such as the low cost, simple preparation, mass production and high efficiency of sample collection, which the conventional rigid substrates are lack of. In this work, practical SERS substrates based on deposition of silver nanoparticles (Ag NPs) on commercially available low-cost filter paper were prepared by simple silver mirror reaction in a large scale, and utilized for rapid, portable and accurate identification and detection of pesticide residues at various peels. Compared with conventional substrates, this novel SERS substrate dramatically enhanced the sample collection efficiency by simply swabbing paper-based device across different surfaces without destroying the sample, meanwhile avoiding the substrate signal of real-world samples. Considering their low cost, portability, simplicity and high sample collection efficiency, Ag NP-decorated filter paper, as practical SERS substrate, are used in solving critical problems for detection of pesticide residues at various peels. SERS experiments were carried out on Ag NP-decorated filter paper combined with ‘dynamic SERS’ (D-SERS) due to its high detection sensitivity. The excellent detection performance of the Ag NP-based filter paper was demonstrated by detection thiram and paraoxon residues at various peels. Besides, the stability and reproducibility of the practical substrates were also involved.

Polystyrene/Ag nanoparticles as dynamic surface-enhanced Raman spectroscopy substrates for sensitive detection of organophosphorus pesticides

We report the use of Polystyrene/Ag (PS/Ag) nanoparticles as dynamic surface-enhanced Raman spectroscopy (dynamic-SERS) substrates for sensitive detection of low levels of organophosphorus pesticides. The PS particles clearly observed using Raman microscopy provide the masterplate for in situ growth of Ag NPs, leading to multiple active sites for SERS measurements. Besides obtaining the fingerprints of target molecules and recording time-resolved Raman spectra, this dynamic-SERS method can be used as an ultra-sensitive analytical technique which can enhance 1–2 orders of magnitude the signals of analytes in comparison to that of the traditional methods. On the other hand, importantly, it shows much better correlations between concentration and intensity than does the conventional SERS technique so that it can build the foundation for quantitative analysis of analytes. The as-prepared individual PS/Ag nanoparticle has been demonstrated for the sensitive detection of organophosphorus paraoxon and sumithion. SERS spectra are acquired at different concentrations of each pesticide and linear calibration curves are obtained by monitoring the strongest intensity value of bands arising from stronger stretching mode as a function of analyte concentration. The limits of detection and limits of quantitation are reported for two pesticides. The limit of detection for paraoxon is 96nM (0.026ppm) and for sumithion is 34nM (0.011ppm). The limits of quantitation are 152nM (0.042ppm) and 57nM (0.016ppm) for paraoxon and sumithion, respectively. It can be seen that these two organophosphorus pesticides can be detected in the low nM range based on this dynamic-SERS analytical method. Also, in the real sample experiments of paraoxon and sumithion, the results confirm that this dynamic-SERS technique would have potential applicability for quantitative analysis with slight interference.

A new-type dynamic SERS method for ultrasensitive detection

In this study, we proposed a simple and ultrasensitive approach called dynamic surface-enhanced Raman spectroscopy, which has been experimentally and theoretically demonstrated. The signal for rhodamine 6G is at least four orders of magnitude higher than that for the traditional method. A series of experiments have been exploited so as to verify the universality of our strategies. The results highlight a rapid and effective method in addictive narcotics residue apparatus, pesticide residue, crime scene or other public security field. Copyright © 2012 John Wiley & Sons, Ltd.