The additive manufacturing process offers a solution for fabricating complex hollow structures that are challenging to realize through traditional ceramic preparation methods. However，defects are often inevitable during the additive manufacturing process. In this study，silicon carbide ceramics with complex hollow structures are prepared using the stereolithography (SLA) additive manufacturing process. Industrial computed tomography (CT) non-destructive testing techniques are employed to observe and analyze macroscopic defects，such as cracks. The initiation and propagation mechanisms of cracks are investigated，and the influence of structural features on crack propagation is explored. The results indicate that printing corners and holes in the component are weak regions prone to stress concentration，which can lead to crack formation or further cracking. Therefore，particular attention should be paid to the printing process and the removal of residual powder. Through process optimization such as structure optimization and printing speed，especially the optimization of speed gradient in weak areas，it is helpful to avoid the occurrence of defects such as cracks.

Currently, the “one-size-fits-all” therapeutic window strategy for Hemoporfin-mediated photodynamic therapy of port-wine stains overlooks intralesional heterogeneity and interindividual pharmacokinetic differences. Simultaneously, this strategy lacks real-time feedback and personalized adjustment mechanisms. Therefore, the real-time monitoring of hemoporfin distribution in blood vessel and interstitial fluid is very important for finding the best laser illumination time window depended on personalized characterizes including the height, weight and so on. This study developed an ultra-sensitive sensor by integrating surface-enhanced Raman spectroscopy technology with microneedles (SERS-MNs) for monitoring the distribution dynamics of hemoporfin in blood and interstitial fluid within animal skin. Specifically, calcium ions were employed as an aggregating agent to induce the aggregation of gold/silver nanocage particles on the microneedle surface, thereby forming abundant SERS-enhanced “hot spots”. Using this sensor, characteristic Raman fingerprint signals of hemoporfin were successfully obtained for the first time, with a detection limit as low as 50 pg/mL. Furthermore, the SERS-MNs sensor not only quantitatively detected hemoporfin in pig skin but also successfully captured characteristic hemoporfin Raman signals in mouse interstitial fluid, blood, and treated patient blood. This revealed the spatiotemporal distribution mechanism of hemoporfin within the vascular system and interstitial fluid. This advancement will aid in determining the optimal therapeutic window for patients, thereby preventing both overtreatment and undertreatment, ultimately achieve precise therapy characterized by “individualization, visualization, and dynamization”.

The high accuracy in surface-enhanced Raman scattering-lateral flow immunoassays (SERS-LFIAs) is critical for reliable point-of-care testing (POCT) in clinical diagnostics. Conventional approaches are often affected by sampling variability and uneven distribution of immunoprobes, leading to unreliable signal fluctuations. To address this challenge, we developed a high-performance SERS-LFIA strip based on gold nanostars (Au NSs) and integrated it with an artificial intelligence (AI)-powered diagnostic framework. Specifically, Au NSs with exceptional SERS enhancement were synthesized via an optimized "two-step" method and utilized as nanoprobes to construct an influenza B (FluB) SERS-LFIA strip for performance validation. A novel large-area Raman scanning technique was then employed to generate intensity maps depicting the immunoprobe distribution around the test (T) line. A deep residual neural network (ResNet-18) was subsequently applied to analyze these SERS images, minimizing subjective interpretation and significantly improving accuracy. The optimized framework achieved 100% training accuracy and 95% validation accuracy, significantly outperforming conventional peak intensity analysis and support vector machine (SVM)-based full-spectrum discrimination methods. The Au NSs-based SERS-LFIA platform and the optimized ResNet-18 model were integrated into a portable Raman spectrometer to create an automated diagnostic system. To further evaluate the stability and versatility of the system, the detection target was switched to influenza A (FluA) by altering the capture and detection antibodies. This reengineered system demonstrated a 95% accuracy rate in testing 40 simulated human clinical samples. Our work establishes a machine learning-enhanced, automated SERS-LFIA system that leverages Au NSs for superior signal enhancement and utilizes deep learning for robust image analysis. This integrated approach provides a scalable and high-performance POCT framework, paving the way for automated clinical diagnostics. (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)-(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(SERS-LFIA)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(POCT)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic) (Au NSs) (sic)(sic)(sic)(sic)SERS-LFIA(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(AI)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)"(sic)(sic)(sic)"(sic)(sic)(sic)(sic)(sic)(sic)(sic)SERS(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(FluB) SERS-LFIA(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(T(sic))(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(ResNet-18)(sic)(sic)(sic)(sic)SERS(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)100%(sic)(sic)(sic)(sic)(sic)(sic)(sic)95%(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(SVM)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)SERS-LFIA(sic)(sic)(sic)(sic)(sic)(sic)ResNet-18(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(FluA).(sic)(sic)(sic)(sic)(sic)(sic)(sic)40(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)95%(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)SERS-LFIA(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)POCT(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).

Novel Pt-anchored WTe2 nanozyme with peroxidase-like activity enables H2O2 colorimetric detection via spectrophotometry and RF-powered POC using smartphone images (R2 = 0.958), eliminating laboratory instruments.

Lateral flow immunochromatographic assay (LFIA) has been widely used in the point-of-care testing field with fast results readout and portability. Nanozymes-based LFIA strengthened the colorimetric signals of LFIA strips by catalytic oxidation of the colorless substrates into colored substrates, without additional measuring equipment. But the limited specific surface area and functionalized sites of the zero-dimensional and two-dimensional nanozymes restricted their peroxidase-like activity, and the detection sensitivity cannot meet the demand for early diagnosis. Herein, a novel three-dimensional (3D) magnetic multi-metallic nanozyme with excellent superparamagnetism and peroxidase-like activity was developed as a catalytic amplification sensor for the detection of Influenza A (Flu A) viruses. Notably, two-dimensional MoS2 nanosheets with a large surface area were taken as the substrates, which can load abundant magnetic nanoparticles and peroxidase-like nanoparticles (Au@Pt nanoflowers), providing magnetic separation capability and amplifying catalytic activity. Additionally, three metals (Pt, Au, and Ag) contained in these nanozymes further enhanced catalytic performance due to LSPR and the interaction of Pt/Au and Pt/Ag. Based on a magnetic separation and catalytic amplification system, 3D magnetic multi-metallic nanozymes-based LFIA can detect Flu A as low as 0.8 pg/mL within 26 min, 125 times lower than commercial colloidal gold-based LFIA. Moreover, 20 clinical samples infected with Flu A were detected with an accuracy of 100%, and the sensitivity of inactive Flu A viruses was 140 copies/mL. This trifunctional LFIA integrates magnetic separation, colorimetric analysis, and catalytic amplification, exhibiting great potential in a pretreatment- and equipment-free diagnostic method for rapid and accurate diagnosis of Flu A.

Binder jetting (BJ) technology shows great potential for manufacturing large-sized and complex silicon carbide ceramic components. However, the mechanical properties of reaction-bonded silicon carbide (RBSiC) ceramics produced by BJ remain inferior to those fabricated by conventional methods, limiting their practical applications. The use of precursor infiltration and pyrolysis (PIP) with carbon precursors to treat green bodies has emerged as an effective approach for reducing the residual Silicon content and enhancing the performance of RBSiC ceramics. However, too much PIP cycles would not increase further the as-generated carbon content and it is very difficult to evaluating the increased content of PIP-introduced carbon for controlling the PIP cycles. In this study, we introduce the concept of carbon density to evaluating the impregnation process and optimizing the best PIP cycles for improving the mechanical properties of BJ-prepared SiC ceramics. The correlation between carbon density and the mechanical properties of RBSiC was established to elucidate the influence mechanism of carbon density on the mechanical properties of the sintered body, thereby providing a theoretical basis for controlling the impregnation process of RBSiC ceramics. The results demonstrate that increasing carbon density reduces residual silicon content and improves mechanical properties. However, excessively high carbon density may cause channel blockage during silicon infiltration, impairing overall performance. Optimal mechanical properties were achieved at a carbon density of 0.84 g/cm3, with a flexural strength of 320.21 +/- 5.21 MPa and an elastic modulus of 321.65 +/- 8.51 GPa. Therefore, maintaining the carbon density of the impregnated body around this value is essential for producing RBSiC with optimal mechanical performance. The use of carbon density effectively optimizes the polymer impregnation and pyrolysis process, demonstrating promising potential for the industrial production of high-performance RBSiC ceramics.

This perspective commemorates 50 years of surface-enhanced Raman scattering (SERS) by highlighting the paradigm shift toward rationally designed semiconductor substrates, enabling ultrasensitive and molecule-selective detection. Several enhancement strategies have been developed to effectively modulate the electronic band structure and charge transfer (CT) processes, such as energy level customization, amorphization, quasi-metallization, and morphology control, achieving high enhancement factors with good selectivity and stability. Moreover, semiconductor SERS substrates show broad prospects in the fields of bio-sensing and cancer diagnosis. Nevertheless, standardization gaps in substrate reproducibility and data comparability hinder its widespread adoption. Resolving these challenges through multi-stakeholder collaboration is essential to bridge the technology transfer gap and establish SERS as a core platform for next-generation inspection.

To address the pressing thermal management challenges in liquid-cooling data CENTER for artificial intelligence and high-performance computing, this study overcomes the limitations of conventional fabrication methods by innovatively employing Three-dimensional printing (3DP) combined with liquid silicon infiltration (LSI) to fabricate diamond/SiC liquid-cooling devices with TPMS porous flow channels. These bimodal mixture of diamond and SiC powders were successfully printed and densified through LSI. The effects of diamond content and sintering temperature on the microstructure and properties were systematically analyzed. A bimodal powder mixture with 75 vol% diamond achieved a packing density of 58.7% and a green body density of 54.1%. After LSI at 1600 degrees C, the composites demonstrated a maximum thermal conductivity of 300.5 W/m K and a maximum flexural strength of 270.7 MPa. This study confirms that 3DP is a highly promising route for producing highperformance, complex-shaped diamond/SiC components, offering a novel solution for the manufacture of liquid-cooling systems.

Advances in ultra-sensitive surface-enhanced Raman scattering (SERS) substrates and SERS enhancement strategies are the two fundamental pillars for the development of SERS technology. However, broadly applicable strategies that reproducibly achieve order-of-magnitude improvements in SERS sensitivity remain scarce. Herein, we propose an electric-field modulation strategy to simultaneously stimulate photo-electric-induced charge transfer (PEICT) and surface-plasmon enhancement (PESP). This strategy increases the density of states near the EF and induces an upward shift of EF, thereby lowering inter-band transition barriers and promoting surface electron localization. Guided by this strategy, a series of bimetallic MXene SERS-active substrates are theoretically predicted and experimentally reported for the first time. Under cooperative excitation with a 532-nm laser and a 300-V field, Ti2TaC2 achieves a limit of detection (LOD) of 10−13 M and a SERS performance factor (SPF) of 2.3 × 105, a three-orders-of-magnitude gain over laser-only excitation. This strategy provides a broadly applicable route to substantially enhance SERS sensitivity in non-metallic substrates.

We present a versatile method for synthesizing high-quality molybdenum disulfide (MoS2) crystals on graphite foil edges via chemical vapor deposition (CVD). This results in MoS2/graphene heterostructures with precise epitaxial layers and no rotational misalignment, eliminating the need for transfer processes and reducing contamination. Utilizing in situ transmission electron microscopy (TEM) equipped with a nano-manipulator and tungsten probe, we mechanically induce the folding, wrinkling, and tearing of freestanding MoS2 crystals, enabling the real-time observation of structural changes at high temporal and spatial resolutions. By applying a bias voltage through the probe, we measure the electrical properties under mechanical stress, revealing near-ohmic behavior due to compatible work functions. This approach facilitates the real-time study of mechanical and electrical properties of MoS2 crystals and can be extended to other two-dimensional materials, thereby advancing applications in flexible and bendable electronics.

Highly infectious and pathogenic viruses seriously threaten global public health, underscoring the need for rapid and accurate diagnostic methods to effectively manage and control outbreaks. In this study, we developed a comprehensive Surface-Enhanced Raman Scattering–Lateral Flow Immunoassay (SERS-LFIA) detection system that integrates SERS scanning imaging with artificial intelligence (AI)-based result discrimination. This system was based on an ultra-sensitive SERS-LFIA strip with SiO2-Au NSs as the immunoprobe (with a theoretical limit of detection (LOD) of 1.8 pg/mL). On this basis, a negative–positive discrimination method combining SERS scanning imaging with a deep learning model (ResNet-18) was developed to analyze probe distribution patterns near the T line. The proposed machine learning method significantly reduced the interference of abnormal signals and achieved reliable detection at concentrations as low as 2.5 pg/mL, which was close to the theoretical Raman LOD. The accuracy of the proposed ResNet-18 image recognition model was 100% for the training set and 94.52% for the testing set, respectively. In summary, the proposed SERS-LFIA detection system that integrates detection, scanning, imaging, and AI automated result determination can achieve the simplification of detection process, elimination of the need for specialized personnel, reduction in test time, and improvement of diagnostic reliability, which exhibits great clinical potential and offers a robust technical foundation for detecting other highly pathogenic viruses, providing a versatile and highly sensitive detection method adaptable for future pandemic prevention.

The single colorimetric signal readout mode of traditional lateral flow immunoassay (LFIA), which relies on gold nanoparticles (Au NPs), is inadequate to meet the growing demand for detection in terms of sensitivity, accuracy, and flexibility. Herein, we reported a novel colorimetric and photothermal dual-mode LFIA (dLFIA) based on MoS2 nanoflowers for rapid detection of severe acute respiratory syndrome coronavirus 2 nucleocapsid protein (SARS-CoV-2 NP). Benefiting from the strong color-producing ability and near-infrared absorption of MoS2 nanoflowers, the visual limits of detection in colorimetric and photothermal modes were 1 and 0.1 ng/mL, respectively. The limit of detection for quantitative analysis in photothermal mode was 48 pg/mL, with a sensitivity about 10~208 times higher than that of Au NPs-LFIA. Additionally, the dLFIA strips exhibited excellent specificity, good reproducibility, and satisfactory recovery when detected the simulated nasal swab samples, possessing good application prospect.

The inherently poor chemical stability and sensitivity of two-dimensional MXene materials pose significant challenges for their application in non-noble metal surface enhanced Raman scattering (SERS) under harsh conditions. Herein, a novel unfunctionalized Mo4/3B2 MBene with an ultraclean surface is reported as a stable, ultrasensitive SERS substrate for portable detection of environment toxins. The Mo4/3B2 MBene enables the detection of R6G down to 10-11 M with an SPF of 4.23 × 105, surpassing most MXene substrates, and its SERS mechanism is mainly attributed to the synergistic effects of enhanced charge transfer efficiency promoted by the ultraclean surface and vacancy modulated photon induced charge transfer resonance. Moreover, it exhibits excellent long-term SERS enhanced stability, which can maintain 86%, 75%, and 61% of its initial SERS performance after 45 days of storage at room temperature and 14 days of storage at low (-26 °C) and high (100 °C) temperatures. Notably, a portable Raman system based on Mo4/3B2 demonstrates ultrasensitive detection of the ricin A chain in real river water, achieving a concentration limit of 0.01 μg/mL and 97.8% accuracy assisted by the developed Transformer model. This work offers new insights for designing stable and sensitive MBene-based SERS substrates for field-deployable sensing in security and public health scenarios.

Recent advances indicate the surface-enhanced Raman scattering (SERS) sensitivity of semiconductors is generally lower than that of noble metal substrates, and developing ultra-sensitive semiconductor SERS substrates is an urgent task. Here, SnS2 with better SERS performance is screened out from sulfides and selenides by density functional theory (DFT) calculations. Through adjusting the concentration of reactants to control the growth driving force without any surfactants or templates, SnS2 nanostrctures of stacked nanosheets (SNSs), microspheres (MSs) and microflowers (MFs) are developed, which all exhibit ultra-low limit of detections (LODs) of 10(-12), 10(-13), and 10(-11) M, respectively. To the best of our knowledge, the SERS sensitivity of these three kinds of SnS2 nanostrctures are superior to most of the reported pure semiconductors and even can be parallel to the noble metals with a "hot spot" effect. This extraordinary SERS enhancement of SnS2 nanostrctures is originated from the dominated contribution of photo-induced charge transfer (PICT) resonance with different wavelength excitation lasers. Benefitting to the excellent SERS enhanced uniformity, generality, stability, ultra-high sensitivity of SnS2 nanostrctures, and the advantages that the PICT resonance enhancement excited for different probe molecules is not limited by its morphology, it is expected to provide a class of potential commercial SERS-active materials for the practical application of semiconductor-based SERS technology.

Semiconductors are making significant strides in the field of surface enhanced Raman scattering (SERS), but they face challenges due to the difficulty of matching noble metal substrates, as their limited chemical enhancement stems from a low charge transfer (CT) contribution. Mie scattering achieved by designing a laser wavelength comparable morphology provides a supplementary electromagnetic enhancement source for semiconductor substrates. Herein, a Bi2WO6@Bi2O3 SERS substrate composed of Bi2O3 nanopillars wrapped by Bi2WO6 nanoflowers was synthesized using a hydrothermal method and exhibited an ultra-low detection limit of 10-10 M and a superb enhancement factor of 1.88 x 109 when detecting methylene blue (MeB) molecules under a 532 nm laser. The abundant oxygen vacancy defect energy levels in the composite substrate facilitate CT resonance enhancement, spanning from a laser range from 532 nm to 633 nm laser. Though the 633 nm laser is conducive to the strongest CT resonance, the submicron-morphology has considerably enhanced the surrounding electromagnetic field under the 532 nm laser by Mie scattering resonance, contributing to at least 103 Raman signal enhancement and coordinating with the moderate CT resonance and MeB molecular resonance to jointly improve the SERS enhancement. In short, this work demonstrated the considerable potential of Mie scattering by the appearance design to improve the sensitivity of SERS substrates.

The outbreak of novel coronavirus has aroused widespread attention to surface-enhanced Raman scattering (SERS) technology with the rapid and ultra-sensitive detection capability. However, how to find the low-load target viruses by confocal Raman detection with small region in the large virus-distribution area and accurate detect and identify the Raman signal of target viruses interfered by impurities in the complex physiological environments have always been the two major challenges plaguing SERS technology. Herein, a label-free magnetic enrichment SERS detection platform integrating specific capture, enrichment, elution, large-area SERS scanning with AI intelligent analysis was developed to achieve ultra-sensitive detection and accurate identification of target viruses. The detection limit of SARS-CoV-2-BF.7 variants were as low as Ct39, and the blind detection accuracy for 100 clinical suspected SARS-CoV-2 samples could reach 94 %. The detection sensitivity and specificity for the clinical virus samples were 98.08 % (102/104; 95 % CI: 93.26 %-99.47 %, p = 0.0311) and 96.00 % (96/100; 95 % CI:90.16 %-98.43 %, p = 0.0414). Furthermore, a fingerprint Raman database of SARS-CoV-2 variants with functions of data updating and new spectra identification was successfully constructed by the support vector machine model, the identification accuracy for 8 types of SARS-CoV-2 variants was 96.59 %. Meaningfully, the developed SERS detection platform and fingerprint Raman database can be extended to other biomolecules and expected to provide technical reserves for the early warning of sudden unknown pathogenic viruses in the future.

The controlled synthesis and paramagnetic properties of nanosized Zn-Fe-O oxides have been researched by the polyol and the heat treatment processes designed according to drying, annealing, and sintering from low to high temperatures. The structural changes have led to change weak superparamagnetism of nanosized Zn-Fe-O oxides in the forms of hybrid nanosized ZnO/ZnFe2O4 oxides into paramagnetism of nanosized ZnFe2O4 when the as-prepared samples of both ZnO and ZnFe2O4 oxides were isothermally annealed and sintered from low temperature at about 60 °C to high temperature at 950 °C for 2 h during their structural phase transitions in all the measurements of x-ray diffraction (XRD), vibrating sample magnetometer (VSM), scanning electron microscopy (SEM) and SEM/energy dispersive X-ray spectroscopy (EDX) combined methods. Interestingly, it is experimentally confirmed that one original paramagnetic hysteresis consists of paramagnetic segments and closed curves. Both normal and abnormal paramagnetic properties of ZnFe2O4 were carefully investigated.

Motivated by the rapid development of SERS technology, trace detection of various viruses in the sewage and body fluid environments and accurate positive and negative diagnosis of detection samples can be achieved. However, evaluating the environmental survival ability of viruses based on SERS technology remains an unexplored issue, but holds significant guiding significance for effective epidemic prevention and control as well as inactivation treatment. In this work, Au nanoarrays were fabricated on silicon substrates through a simple Ar ion sputtering route as ultra-sensitive SERS chips. With the synergistic contribution of the “lightning rod” effect and the enhanced coupling surface plasmon caused by the nanoarrays, the ultra-sensitive detection of SARS-CoV-2 S protein with a concentration of 1 pg/mL and SERS enhancement factor of 4.89 × 109 can be achieved. Exploration of the environmental survival ability of the SARS-CoV-2 virus indicates that the Raman activity of SARS-CoV-2 S protein exhibited higher temperature tolerance from 0 °C to 60 °C than SARS-CoV S protein, suggesting that the SARS-CoV-2 virus has less temperature influence from increasing air temperature than the SARS-CoV virus to a certain extent, which explains the seasonal recurrence pattern and regional transmission pattern of the novel coronavirus that are different from the SARS virus.

The photothermal effect of surface plasmon has always been restrained because of the energy dissipation when the Incident light is absorbed by the metal nanostructure. The thermal effect of surface plasmon, however, has again attracted extensive attention in recent years. This paper calculates the photothermal effect of metal nanosphere-nanodisc structure based on the previous achievement. This paper shows that under the excitation of the single tightly radially polarized optical beam, the Jhange of surrounding in metal nanostructure, from vacuum to air, has nearly no influence on the near surface electric field Amplitude and the enhancement, especially the resonant wavelength. The nanodise of metal nanostructure produces surface Plasmon breath mode and the nanosphere generates surface plasmon electric dipole moment when the wavelength of single tightly tadially polarized optical beam is 648 nm. There is coupled resonance between the two kinds of modes, which gives rise to the Aear surface electric field amplitude more than 1200 V. m(-1) and the enhancement of 230 timesbetween the disc and the sphere. The temperature in the gap has nearly no change when the interaction time between the incident excitation light and the metal panostructure is about 0 similar to 0.07 ms(0 similar to 1.17 x10(-6) min) but there is a relatively large change of temperature gradient about 10 similar to 400 V.m(-1). The magnitude of temperature gradient could be 402.8 K.m(-1) when the interaction time between the incident Aght and the metal nanosphere-nanodiscreaches 1 mu s. The distribution of near surface electric field in metal nanostructure is very similar to that of magnitude of temperature, because the transformation of energy in incident light to metal nanostructure is painly based on the localized surface plasmon near surface electric field enhancement in metal nanostructure gap. The metal anostructure has the same axial symmetry as the incident excitation light in this paper, this symmetry is beneficial to the energy transformation between the incident light and metal nanostructure, and could make the metal nanostructure into the controllable panoscale heat source.

Gold nanoparticles-based lateral flow immunoassay (Au-LFIA) is a widespread utilization point-of-care testing technology. However, it still faces enormous challenge to meet the growing detection demands of high sensitivity, accuracy, and multi scenario applicability due to the single signal readout mode. Herein, novel wheatgrass-like MoSe2@Pt heterojunctions with excellent peroxidase-like activity, photothermal performance and dispersity was used to construct dual-modal LFIA (dLFIA) for detection of respiratory syncytial virus (RSV). The limit of detection for catalytic colorimetric and temperature signals were determined to be 0.1x105 and 0.02x105 copies/mL, which were over 10-folds and 50-folds more sensitive than conventional Au-LFIA (1x105 copies/mL), respectively. Moreover, support vector machine (SVM) algorithm was applied to recognize the catalytic and photothermal images, achieving the automatic discrimination of disease and improving the accuracy. The accuracy has been improved by 22.5 % and 7.5 % in comparison with the independent catalytic colorimetric and photothermal detection modes, respectively. This work will not only provide a reliable, convenient, and versatile platform for rapid diagnosis of pathogen, but will also promote the application of twodimensional transition metal dichalcogenides composites in LFIA.