Ultrathin Oxide Layer-Wrapped Noble Metal Nanoparticles via Colloidal Electrostatic Self-Assembly for Efficient and Reusable Surface Enhanced Raman Scattering Substrates

SERS of nitro group compounds for sensing of explosives

Detecting small concentrations of nitro-compounds via surface-enhanced Raman spectroscopy (SERS) is reported. In particular, explosive analogues, such as 4-nitrophenol, 1-nitronaphthalene, and 5-nitroisoquinoline, and an explosive material (picric acid) are investigated and prepared by measurements using two different methods. One method involved mixing the analyte with plasmonic silver nanoparticles (Ag NPs) in a solution, followed by subsequent drop-casting of the mixture onto a silicon substrate. In the second method, the analyte solution was drop-casted onto SERS substrates formed by annealing of thin Ag films deposited over self-assembled layers of SiO2 spheres. Both approaches allowed for the SERS detection of analyte concentrations down to 10-4-10-7 M. Furthermore, the possible reasons for the different enhancements of the above analytes as well as their differences in the liquid (drop) and dried states are discussed.

In-situ Surface-Enhanced Raman Spectroscopy Reveals a Mars-van Krevelen-Type Gas Sensing Mechanism in Au@SnO2 Nanoparticle-Based Chemiresistors

Molecular-level understandings of gas sensing mechanisms of oxide-based chemiresistors are significant for designing high-performance gas sensors; however, the mechanisms are still controversial due to the lack of direct experimental evidence. This work demonstrates efficient in situ surface-enhanced Raman spectroscopy (SERS) tracing of the highly representative SnO₂-ethanol gas sensing using Au@SnO₂ nanoparticles (NPs), where the Au core and SnO₂ shell provide SERS activity and a gas sensing response, respectively. The in situ SERS evidence suggests that the sensing follows a Mars-van Krevelen mechanism rather than the prevailing adsorbed oxygen (AO) model. This mechanism is also observed in sensing other gases based on the Au@SnO₂ NPs, showing its universality. This work offers efficient in situ tracing for gas sensing and experimental elucidation of the specific gas sensing mechanism, potentially ending the long-term controversy over the gas sensing mechanisms. Therefore, it is highly significant to this field.

Raman spectroscopy-based adversarial network combined with SVM for detection of foodborne pathogenic bacteria

Raman spectroscopy combined with artificial intelligence algorithms have been widely explored and focused on in recent years for food safety testing. It is still a challenge to overcome the cumbersome culture process of bacteria and the need for a large number of samples, which hinder qualitative analysis, to obtain a high classification accuracy. In this paper, we propose a method based on Raman spectroscopy combined with generative adversarial network and multiclass support vector machine to classify foodborne pathogenic bacteria. 30,000 iterations of generative adversarial network are trained for three strains of bacteria, generative model G generates data similar to the actual samples, discriminant model D verifies the accuracy of the generated data, and 19 feature variables are obtained by selecting the feature bands according to the Raman spectroscopy pattern. Better classification results are obtained by optimising the parameters of the multi-class support vector machine, etc. Our detection and classification method not only solves the problem of needing a large number of samples as training set, but also improves the accuracy of the classification model. Therefore, this GAN-SVM classification model provides a new idea for the detection of bacteria based on Raman spectroscopy technology combined with artificial intelligence algorithms.

Fabrication of ZnO Nanocap-Ordered Arrays with Controllable Amount of Au Nanoparticles Decorated and Their Detection and Degradation Performance for Harmful Molecules

This paper mainly presents a facile and cost-effective method to achieve large-scale ZnO nanocap (ZnO NC)-ordered arrays with a controllable amount of Au nanoparticles (Au NPs) decorated on their surface. The preparation process includes the construction of polystyrene nanosphere (PS) mask, metal deposition, and annealing process. The Au NPs/ZnO NCs have apparent hierarchical structure. Interestingly, the size and number of Au NPs can be controlled by changing the time of Au deposition and the diameter of PSs. Moreover, the Au NP/ZnO NC arrays can be used as a substrate to detect harmful dye molecules based on surface-enhanced Raman scattering (SERS) effect, and show ultrahigh sensitivity with a limit of detection (LoD) of 10^-10 M for crystal violet (CV) molecules. In addition, the above substrate has achieved reusable detection due to their excellent photocatalytic degradation performance for harmful molecules. The finite difference time-domain (FDTD) simulation results have revealed that SERS "hot spots" are almost distributed at the junctions of Au NPs and ZnO NCs. The above results show that the composite substrates have a good prospect in practical applications in the future.

Conductometric Response-Triggered Surface-Enhanced Raman Spectroscopy for Accurate Gas Recognition and Monitoring Based on Oxide-wrapped Metal Nanoparticles

Accurate and efficient gas monitoring is still a challenge because the existing sensing techniques mostly lack specific identification of gases or hardly meet the requirement of real-time readout. Herein, we present a strategy of conductometric response-triggered surface-enhanced Raman spectroscopy (SERS) for such gas monitoring, via designing and using ultrathin oxide-wrapped plasmonic metal nanoparticles (NPs). The oxide wrapping layer can interact with and capture target gaseous molecules and produce the conductometric response, while the plasmonic metal NPs possess strong SERS activity. In this strategy, the conductometric gas sensing is performed throughout the whole monitoring process, and once a conductometric response is generated, it will trigger SERS measurements, which can accurately recognize molecules and hence realize gas monitoring. The feasibility of this strategy has been demonstrated via using ultrathin SnO₂ layer-wrapped Au NP films to monitor gaseous 2-phenylethanethiol molecules. It has been shown that the monitoring is rapid, accurate, and quantifiable. There exist optimal values of working temperature and SnO₂ layer thickness, which are about 100 °C and 2.5 nm, respectively, for monitoring gaseous 2-phenylethanethiol. The monitoring signal intensity has a linear relation with the gas concentration in the range from 1 to 100 ppm on a logarithmic scale. Furthermore, the monitoring limits are at the ppm level for some typical gases, such as 2-phenylethanethiol, cyclohexanethiol, 1-dodecanethiol, and toluene. This study establishes the conductometric response-triggered SERS, which enables accurate gas recognition and real-time monitoring.

Ultrathin layer solid transformation-enabled-surface enhanced Raman spectroscopy for trace harmful small gaseous molecule detection

Detection of trace harmful small gaseous molecules (h-SGMs), based on surface enhanced Raman spectroscopy (SERS), has been expected to be a useful strategy but is challenging due to the extremely small Raman cross section (RCS) and weak metal affinity of the h-SGMs. Here, a new strategy, ultrathin layer solid transformation-enabled (ULSTE)-SERS, is proposed. It uses the chemical reaction between the target h-SGM and an ultrathin layer of solid sensing matter coated on a plasmonic metal SERS substrate. This reaction in situ produces a new solid matter with large RCS, which ensures the detection of trace h-SGMs via SERS. The validity of this strategy has been demonstrated by detecting trace H₂S gas with an ultrathin CuO layer wrapped around Au nanoparticles. Furthermore, this strategy allows fast and ultrasensitive detection. The detection limit can be down to ppb (even ppt) levels with 10 min preprocessing. Importantly, this strategy has good universality for various other h-SGMs, such as SO₂, CS₂, CH₃SH, and HCl, etc., using appropriate sensing matter. Additionally, the ULSTE-SERS is also suitable for unstable molecules and fast portable detection due to the stable solid layer. This work provides highly efficient SERS-based detection of trace h-SGMs, which is easily applied in practical situations.