Surface-Enhanced Raman Scattering (SERS) technology, as a powerful tool to identify molecular species by collecting molecular spectral signals at the single-molecule level, has achieved substantial progresses in the fields of environmental science, medical diagnosis, food safety, and biological analysis. As deepening research is delved into SERS sensing, more and more high-performance or multifunctional SERS substrate materials emerge, which are expected to push Raman sensing into more application fields. Especially in the field of biological analysis, intrinsic and extrinsic SERS sensing schemes have been widely used and explored due to their fast, sensitive and reliable advantages. Herein, recent developments of SERS substrates and their applications in biomolecular detection (SARS-CoV-2 virus, tumor etc.), biological imaging and pesticide detection are summarized. The SERS concepts (including its basic theory and sensing mechanism) and the important strategies (extending from nanomaterials with tunable shapes and nanostructures to surface bio-functionalization by modifying affinity groups or specific biomolecules) for improving SERS biosensing performance are comprehensively discussed. For data analysis and identification, the applications of machine learning methods and software acquisition sources in SERS biosensing and diagnosing are discussed in detail. In conclusion, the challenges and perspectives of SERS biosensing in the future are presented.

The current COVID-19 pandemic urges the extremely sensitive and prompt detection of SARS-CoV-2 virus. Here, we present a Human Angiotensin-converting-enzyme 2 (ACE2)-functionalized gold “virus traps” nanostructure as an extremely sensitive SERS biosensor, to selectively capture and rapidly detect S-protein expressed coronavirus, such as the current SARS-CoV-2 in the contaminated water, down to the single-virus level. Such a SERS sensor features extraordinary 10⁶-fold virus enrichment originating from high-affinity of ACE2 with S protein as well as “virus-traps” composed of oblique gold nanoneedles, and 10⁹-fold enhancement of Raman signals originating from multi-component SERS effects. Furthermore, the identification standard of virus signals is established by machine-learning and identification techniques, resulting in an especially low detection limit of 80 copies mL⁻¹ for the simulated contaminated water by SARS-CoV-2 virus with complex circumstance as short as 5 min, which is of great significance for achieving real-time monitoring and early warning of coronavirus. Moreover, here-developed method can be used to establish the identification standard for future unknown coronavirus, and immediately enable extremely sensitive and rapid detection of novel virus.

Highlights Ag/BP-NS exhibit remarkable surface-enhanced Raman scattering performance with single-molecule detection ability. This remarkable enhancement can be attributed to the synergistic resonance enhancement of R6G molecular resonance, photo-induced charge transfer resonance and electromagnetic resonance. A new polarization-mapping method was proposed, which can quickly screen out single-molecule signals and prove that the obtained spectra are emitted by single molecule. The recognition of different tumor exosomes can be realized combining the method of machine learning. AbstractSection Abstract Single-molecule detection and imaging are of great value in chemical analysis, biomarker identification and other trace detection fields. However, the localization and visualization of single molecule are still quite a challenge. Here, we report a special-engineered nanostructure of Ag nanoparticles embedded in multi-layer black phosphorus nanosheets (Ag/BP-NS) synthesized by a unique photoreduction method as a surface-enhanced Raman scattering (SERS) sensor. Such a SERS substrate features the lowest detection limit of 10^–20 mol L⁻¹ for R6G, which is due to the three synergistic resonance enhancement of molecular resonance, photo-induced charge transfer resonance and electromagnetic resonance. We propose a polarization-mapping strategy to realize the detection and visualization of single molecule. In addition, combined with machine learning, Ag/BP-NS substrates are capable of recognition of different tumor exosomes, which is meaningful for monitoring and early warning of the cancer. This work provides a reliable strategy for the detection of single molecule and a potential candidate for the practical bio-application of SERS technology.

Since the initial discovery of surface-enhanced Raman scattering (SERS) in the 1970s, it has exhibited a huge potential application in many fields due to its outstanding advantages. Since the ultra-sensitive noble metallic nanostructures have increasingly exposed themselves as having some problems during application, semiconductors have been gradually exploited as one of the critical SERS substrate materials due to their distinctive advantages when compared with noble metals. ZnO is one of the most representative metallic oxide semiconductors with an abundant reserve, various and cost-effective fabrication techniques, as well as special physical and chemical properties. Thanks to the varied morphologies, size-dependent exciton, good chemical stability, a tunable band gap, carrier concentration, and stoichiometry, ZnO nanostructures have the potential to be exploited as SERS substrates. Moreover, other distinctive properties possessed by ZnO such as biocompatibility, photocatcalysis and self-cleaning, and gas- and chemo-sensitivity can be synergistically integrated and exerted with SERS activity to realize the multifunctional potential of ZnO substrates. In this review, we discuss the inevitable development trend of exploiting the potential semiconductor ZnO as a SERS substrate. After clarifying the root cause of the great disparity between the enhancement factor (EF) of noble metals and that of ZnO nanostructures, two specific methods are put forward to improve the SERS activity of ZnO, namely: elemental doping and combination of ZnO with noble metals. Then, we introduce a distinctive advantage of ZnO as SERS substrate and illustrate the necessity of reporting a meaningful average EF. We also summarize some fabrication methods for ZnO nanostructures with varied dimensions (0–3 dimensions). Finally, we present an overview of ZnO nanostructures for the versatile SERS application.

Poor flowability of printable powders and long preparation cycles are the main challenges in selective laser sintering (SLS) of chopped carbon fiber reinforced silicon carbide composites (SiC composites) with complex structures. In this study, we develop an efficient and novel processing route in the fabrication of lightweight SiC composites via SLS of phenolic resin (PR) and C_f powders with the addition of α-SiC particles combined with one-step reactive melt infiltration (RMI). The effects of α-SiC addition on the microstructural evolution of the C_f/SiC/PR printed bodies, C_f/SiC/C green bodies, and derived SiC composites were investigated. The results indicate that the added α-SiC particles play an important role in enhancing the flowability of raw powders, reducing porosity, increasing the reliability of the C_f/SiC/C green bodies, and contributing to improving the microstructure homogeneity and mechanical properties of the SiC composites. The maximum density, flexural strength, and fracture toughness of the SiC composites are 2.749±0.006 g×cm⁻³, 266±5 MPa, and 3.30±0.06 MPa·m^1/2, respectively. The coefficient of thermal expansion (CTE) of the SiC composites is approximately 4.29×10⁻⁶ K⁻¹ from room temperature (RT) to 900 °C, and the thermal conductivity is in the range of 80.15-92.48 W·m⁻¹·K⁻¹ at RT. The high-temperature strength of the SiC composites increase to 287±18 MPa up to 1200 °C. This study provides a novel as well as a feasible tactic for the preparation of high-quality printable powders as well as lightweight, high strength, and high thermal conductivity SiC composites with complex structures by SLS and RMI.