This study constructs for the first time a "0D-2D-2D" multi-dimensional heterojunction by co-loading MoS2 quantum dots (0D) and (001)-exposed TiO2 nanosheets (quasi-2D) onto the surface of MXene-Ti3C2 (2D), thereby breaking away from conventional all-2D heterojunction architecture formed by MoS2 nanosheets and TiO2 nanosheets (generated via in-situ oxidation). Using Ti3AlC2 as the raw material, MXene-Ti3C2 was prepared via an HF etching method, and the (MoS2 QDs + TiO2 NPs)@MXene-Ti3C2 ternary heterojunction nanocomposite was successfully constructed by loading TiO2 nanoparticles and MoS2 quantum dots. Unlike traditional one-step hydrothermal or in-situ oxidation methods, this study adopts a "stepwise assembly" interface engineering strategy: pre-synthesized TiO2 NPs are first anchored onto the MXene surface via physical mixing, followed by uniform dispersion of MoS2 QDs onto the composite surface via electrostatic adsorption. This approach enables precise control over the morphology, crystal phase, and loading amount of each component, avoiding the uncontrollable effects of in-situ reactions on the material structure. On this basis, a "generation-transport-utilization" three-stage cascade charge transport model is proposed and validated: TiO2 NPs generate photogenerated electrons, MXene provides a fast transport channel, and MoS2 QDs serve as terminal electron acceptors and reactive active centers, effectively addressing the severe carrier recombination issue in conventional TiO2-based photocatalysts. The morphology and microstructure of the composite were systematically characterized using SEM, TEM, and XRD. Photocatalytic degradation experiments show that under the (MoS2 QDs (3%) + TiO2 NPs (10%))@Ti3C2 system, the degradation efficiencies for the typical emerging pollutants sulfamethoxazole (SMX), ampicillin (AMP), and ofloxacin (OFL) reach 96.3% (40 min), 97.9% (60 min), and 96.6% (80 min), respectively, significantly outperforming pure Ti3C2 and binary composite control samples. Cyclic stability tests demonstrate that the catalyst maintains high degradation activity after five cycles, exhibiting excellent stability and reusability. This study provides a new strategy for the rational design of multi-dimensional heterojunctions, achieving innovations in material dimensionality combination, charge transport mechanism, and synthesis methodology.

Surface-enhanced Raman scattering (SERS) chips based on porous silicon photonic crystals (PSi PhCs) exhibit excellent optical modulation capability, enabling reamplify Raman signals. However, challenges remain in precisely tuning the bandgap to specific SERS laser wavelengths and constructing high-reflectivity microcavities capable of nanoparticle loading without compromising modulation performance. Here, we propose an effective strategy combining periodic high-low current etching with interval currents, achieving PSi PhCs with bandgaps precisely positioned at 532, 638, and 785 nm and reflectivity exceeding 80%. By adjusting interval current duration, pore size array was freely tuned to form 3D high-reflectivity microcavities with negligible optical loss. Based on this, strongly reductive Si-H bonds generated by etching enabled in situ growth of gold nanoparticles (Au NPs) in the microcavities, yielding Au NPs-X/PSi PhC chips (X = 532, 638, 785 nm) with high-density SERS hotspots while preserving optical modulation. When the SERS laser matched the PhC bandgap, synergistic photonic-plasmonic coupling enhanced the SERS intensity by 4-5 orders of magnitude over conventional Au NPs/Si chips. Finally, leveraging the chip's zero-background advantage, the Au NPs-785/PSi PhC chip matched with a 785 nm portable Raman spectrometer achieved highly sensitive analysis of single-stranded DNA (ss-DNA). This study proposes a feasible method for precise PSi PhC design and microcavity regulation, verifying its potential in biological detection.

Pristine SnO2 is promising for environmental sensing and photocatalysis but is severely constrained by high operating temperatures, poor gas selectivity, and rapid carrier recombination. To overcome these bottlenecks, we construct a multilevel heterojunction by anchoring ReS2 quantum dots and g-C3N4 nanosheets onto hollow spiky SnO2 spheres ((g-C3N4 NSs + ReS2 QDs)@SnO2). Hollow architecture provides a large surface area and light-reflection effects, while the step-like band alignment facilitates charge separation. The optimal composite delivers a high gas response of 301 toward 100 ppm ethylene glycol at 304.8 °C with >95% stability over 60 days. For photocatalysis, it achieves degradation rates of 93.2% (ofloxacin, 120 min), 99.2% (ampicillin, 70 min), and 98.2% (sulfamethoxazole, 60 min) under visible light, with mineralization >80% and stable activity over five cycles. Mechanistic studies reveal directional electron transfer along g-C3N4 → ReS2 → SnO2, with ·O2− as the dominant reactive species. Notably, adsorption energy is not the determining factor for degradation kinetics: AMP exhibits the fastest degradation (k = 0.048 min−1) despite its less negative adsorption energy (−2.957 eV), while OFL shows the strongest adsorption (−3.597 eV) but slowest kinetics (k = 0.021 min−1), highlighting that molecular structural stability plays a more decisive role. This work provides a dual-functional platform integrating sensitive gas detection and efficient photocatalytic pollutant removal.

A novel ternary heterojunction photocatalyst, composed of TiO2 microspheres co-modified with CuS nanoparticles (NPs) and black phosphorus quantum dots (BP QDs), was successfully synthesized via an in-situ precipitation and ultrasound-assisted hydrothermal method. Comprehensive characterization (XRD, SEM/TEM, XPS, EDS, UV-Vis DRS, EIS, PL, BET, FTIR) confirmed the uniform dispersion of CuS NPs and BP QDs on the TiO2 surface and the formation of an effective p-n heterojunction. This synergistic integration significantly narrows the composite bandgap, extends the solar spectral response into the visible region, enhances charge carrier separation, and suppresses charge recombination. As a result, the optimized ternary composites exhibit dramatically superior photocatalytic activity compared to bare TiO2 or binary counterparts (CuS@TiO2, BP QDs@TiO2). Their photocatalytic performance was evaluated through the degradation of Rhodamine B (RhB) and Tetracycline (TC). Specifically, ((CuS (3 %)-BP QDs (2 %))@TiO2) achieved 99.8 % decolorization of RhB within 30 min, with iEESI-MS analysis and carbon content experiments confirming the generation of intermediates and mineralization into small molecules, thereby verifying the photocatalytic degradation of RhB. Meanwhile, ((CuS (3 %) NPs-BP QDs (3 %))@TiO2) achieved 91.9 % degradation of TC within 50 min. This outstanding performance is attributed to optimal band alignment, efficient visible-light harvesting, prolonged charge carrier lifetime, and abundant active sites generated at the stable ternary interface.

In recent years, the application of federated learning to medical image classification has received much attention and achieved some results in the study of semi-supervised problems, but there are problems such as the lack of thorough study of labeled data, and serious model degradation in the case of small batches in the face of the data category imbalance problem. In this paper, we propose a federated learning method using a combination of regularization constraints and pseudo-label construction, where the federated learning framework consists of a central server and local clients containing only unlabeled data, and labeled data are passed from the central server to each local client to take part in semi-supervised training. We first extracted the class imbalance factors from the labeled data to participate in the training to achieve label constraints, and secondly fused the labeled data with the unlabeled data at the local client to construct augmented samples, looped through to generate pseudo-labels. The purpose of combining these two methods is to select fewer classes with higher probability, thus providing an effective solution to the class imbalance problem and improving the sensitivity of the network to unlabeled data. We experimentally validated our method on a publicly available medical image classification data set consisting of 10,015 images with small batches of data. Our method improved the AUC by 7.35% and the average class sensitivity by 1.34% compared to the state-of-the-art methods, which indicates that our method maintains a strong learning capability even with an unbalanced data set with fewer batches of trained models.

Gold nanoparticles/785 porous silicon photonic crystals (Au NPs/785 PSi PhCs) were used as substrates in combination with a low-concentration serum surface-enhanced Raman spectroscopy (SERS) detection scheme to obtain spectral signals from healthy individuals and cervical cancer patients. The best principal component scores were selected by principal component analysis (PCA) combined with linear discriminant analysis (LDA) and support vector machine (SVM) to analyze the spectral differences distinguishing healthy and cervical cancer patients. The accuracy of the two models was 97.9% and 96.9%, respectively. SERS technique based on Au NPs/785 PSi PhCs has great potential to improve the screening of cervical cancer.

The CeO 2 supported multi-nuclear Nb x S y clusters may be very promising HER catalysts.

As a new kind of 2D carbon allotrope, graphdiyne (GDY) has the characteristics of uniform pores and large specific surface area due to its unique electronic space arrangement structure. Therefore, we fabricated a novel gold nanoparticles (Au NPs)/GDY/carbon cloth (CC) SERS substrate by a simple electrodeposition process using GDY nanowall wrapping the CC as support. The effects of electrodeposition conditions on the microstructure and SERS activity of Au NPs/GDY/CC substrate were studied. Under the condition of optimizing deposition time and deposition voltage, the prepared Au NPs/GDY/CC substrate can detect 10-13 M with rhodamine 6G (R6G) as a probe molecule. The maximum enhancement factor (EF) is 2.2 x 1012, and the concentration of R6G is loga-rithmically correlated with the intensity of the SERS band with a linear correlation coefficient (R2) of 0.97036. These indicate that the Au NPs/GDY/CC substrate has good sensitivity. The prepared Au NPs/GDY/CC SERS substrate was applied to the detection of organic dyes of malachite green (MG) and methyl violet (MV) in water, and the detection limits of both can reach 10-9 M. This highly sensitive and high-performance SERS substrate has broad application prospects in the detection of organic dyes.

In this study, the crystal structure as well as electron transport of TiN thin films were evaluated. We used DC reactive magnetron sputtering to deposit a thin layer of polycrystalline titanium nitride (TiN) on a Si (100) substrate starting from elemental Ti in a nitrogen atmosphere. The influence of nitrogen flow rate on the crystal structure, surface morphology, and electron transport of TiN were investigated systematically. It was found that the preferred orientation and conductivity of TiN thin films exhibit strong nitrogen flow rate dependence. The preferred orientation changed from (111) to (200) initially and then changed back to (111) as the nitrogen flow rate increases. However, an increase in the (200) phase leads to higher conductivity and lower surface roughness. At the optimized deposition conditions, ultra-thin (around 30 nm) TiN thin films with a low resistivity of 101.8 μ C·cm and a surface roughness of less than or equal to 0.51 nm were obtained. These superior performances, along with low running costs, suggest that TiN thin films have great potential for use as electrodes in microelectronic devices.

Biomass-derived porous carbon (PC) loaded with precious metals have a synergistic enhancement effect on surface-enhanced Raman scattering (SERS). In this paper, PC containing various functional groups and large specific surface area, good stability and certain biocompatibility were prepared using tomato skins and introduced into the preparation of Ag nanoflowers (NFs) SERS substrates. Rhodamine 6G (R6G) was used as the Raman probe molecule to evaluate the sensing performance of Ag NFs@PC. The results showed that the stable dispersion and protective effect of PC on Ag NPs significantly improved the sensitivity and long-term stability of traditional Ag NFs. In practical application, Ag NFs@PC was further used to successfully achieve the quantitative analysis of trace methylene blue (10 ppt) and malachite green (10 ppt) in a lake water system. Therefore, SERS sensor Ag NFs@PC is expected to become a promising candidate sensor for detecting in the field of environment and food monitoring. Graphical abstract

In order to realize the resource utilization of waste cattail fibres, cattail fibres made of cellulose are simply carbonized into carbon fibres (CFs) at 500 degrees C. The morphology and structure of CFs were analysed by scanning electron microscope, transmission electron microscope, Raman spectrum and Fourier transform infrared spectroscopy. CFs was prepared into a gas sensor for the first time, which showed high selectivity to phenol (C6H6O) vapor among 7 kinds of interferers at room temperature. Over a period of up to five weeks, the responses of CFs-based sensor to C6H6O vapor fluctuated by less than 3%, indicating the excellent long-term stability. The CFs-based sensor also shows the quick response (-20 s), recovery (-2 s) and the high sensitivity to C6H6O (detection limit of 30.8 ppb). The possible sensing mechanism of CFs-based sensor to C6H6O vapor was analysed. This work provides a new method for the resource utilization of waste cattail fibres and the low-cost, high selectively detection of C6H6O vapor at room temperature.

文章以遵义师范学院化学工程与工艺专业"电工电子技术"课程为研究对象,针对课程课时少、内容多的困境及学生学习的心理特点,提出翻转课堂混合式教学模式在该课程中的具体应用和实施策略,使得学生课前对教学目标更为明确,课堂教学更为多样,学生学习过程更易监控.实践表明,采用混合式教学模式可以较好地提升课堂教学质量,为学生后续专业课程的学习打下坚实的基础.

课程思政是高校进行人才培养的内在需求。遵义的地方高校可以充分应用遵义丰富的红色资源，挖掘其中的红色基因，将课程思政教学和红色资源的内涵契合，让课程思政教学更加具有本土性、实践性和创新性。本文从课程思政的视域出发，探究了高校开展红色文化传承的策略，包括利用好本土红色资源、开展体验式、沉浸式教学；建立课程团队，避免单兵作战，共同挖掘红色基因和利用“互联网+”信息化手段，提高教学实效等。

Carbon quantum dots (CQDs) co-doped with N, P and S derived from expired milk was prepared by a simple hydrothermal method. By dipping pure cotton face towel (PCFT) into CQDs ink, a flexible all-biomass CQDs/PCFT sensor was prepared for the first time. Due to the heteroatom doping, extremely small particle size of CQDs and excellent permeability of CQDs/PCFT film, the flexible CQDs/PCFT sensor showed the high sensitivity and bending stability. In the range of 0–60° bending states, the responses of CQDs/PCFT sensor to four target analytes changed by less 5.0%. After 3000 bending of 60°, the maximum change of the response to the target analytes was only 6.4%. Interestingly, due to the abundant functional groups and defects of CQDs, the flexible CQDs/PCFT sensor displayed sensing curves of different shapes for different target analytes. In this way, by establishing a database of sensing curves of target analytes, multiple analytes can be detected discriminatively by relying only on single sensor with the help of image recognition. This work provided a reference for the development of cotton fiber based all biomass flexible gas sensor.

Maojian is one of China’s traditional famous teas. There are many Maojian-producing areas in China. Because of different producing areas and production processes, different Maojian have different market prices. Many merchants will mix Maojian in different regions for profit, seriously disrupting the healthy tea market. Due to the similar appearance of Maojian produced in different regions, it is impossible to make a quick and objective distinction. It often requires experienced experts to identify them through multiple steps. Therefore, it is of great significance to develop a rapid and accurate method to identify different regions of Maojian to promote the standardization of the Maojian market and the development of detection technology. In this study, we propose a new method based on Near infra-red (NIR) with deep learning algorithms to distinguish different origins of Maojian. In this experiment, the NIR spectral data of Maojian from different origins are combined with the back propagation neural network (BPNN), improved AlexNet, and improved RepSet models for classification. Among them, improved RepSet has the highest accuracy of 99.30%, which is 8.67% and 0.70% higher than BPNN and improved AlexNet, respectively. The overall results show that it is feasible to use NIR and deep learning methods to quickly and accurately identify Maojian from different origins and prove an effective alternative method to discriminate different origins of Maojian.

Waste human hair was carbonized into carbon sheets by a simple carbonization method, which was studied as gas sensing materials for the first time. The effect of carbonization temperature on the structure and gas sensing properties of hair-based carbon sheet was studied by scanning electron microscope, X-ray diffraction, infrared spectrum, Raman spectrum, and gas-sensitive tester. The results showed that the carbonization temperature had a significant effect on the structure and gas sensing performance of carbon sheets, which were doped with K, N, P, and S elements during carbonization. However, the sensor of the carbon sheet does not show good selectivity among six target gases. Fortunately, the carbon sheets prepared at different temperatures have different responses to the target gases. The sensor array constructed by the carbon sheets prepared at different temperatures can realize the discriminative detection of a variety of target gases. For the optimized carbon sheet, the theoretical limit of detection of hydrogen peroxide is 0.83 ppm. This work provides a reference for the resource utilization of waste protein and the development of gas sensors.

对气体信号的采集可以更好地分析物质本身,本文设计了一种基于STM32单片机的多路气敏电信号的采集、测量系统,系统采用STM32单片机为系统控制核心.本文从系统需求出发,分析了气敏信号采集的工作原理,设计了相关软硬件程序.测试结果表明,本系统可以较好地采集茶叶等目标的气敏信号,具有较强的应用价值.

As a rapid and non-destructive biological serum detection method, SERS technology was widely used in the screening and medical diagnosis of various diseases by combining the analysis of serum SERS spectrum and multivariate statistical algorithm. Because of the high complexity of serum components and the variability of SERS spectra, which often resulted in the phenomenon that the SERS spectrum of the same biological serum was significantly different due to the different test conditions. In this experiment, through the dilution treatment of the serum and the systematic test of the serum of all concentration gradients with lasers of wavelength of 785, 633 and 532 nm, the most suitable conditions for detecting the serum were investigated. The experimental results showed that only when the serum is diluted to low concentration (10 ppm), the SERS spectrum with high reproducibility and stability could be obtained, furthermore, the low concentration serum had weak tolerance to laser, and 532 nm laser was not suitable for serum detection. In this paper, a set of test scheme for obtaining highly stable serum SERS spectra was established by using high-performance gold nanoparticles (Au NPs) as the active substrate of SERS. Through comparative analysis of SERS spectrum of serum of normal people and cervical cancer, the reliability of the established low-concentration serum test program was verified, as well as its great potential advantages in disease screening and diagnosis.

The uniform dispersion of multi-wall carbon nanotubes (MWNTs) in waterborne polyurethane (WPU) matrix was achieved by in-situ polymerization and latex particles assisted dispersion, endowing the MWNT/WPU composite film with the enhanced tensile strength, elongation at break and thermal stability. Compared with pure WPU, the breaking strength, elongation at break and initial decomposition temperature of the MWNT/WPU composite were increased by 69.6%, 16.4% and 130 degrees C, respectively. The decomposition amount at 400 degrees C of MWNT/WPU composite is only about half that of pure WPU. The latex particles assisted dispersion also effectively improved the exposure rate of MWNTs, making it easier for MWNTs to contact the target gas molecules. Increased exposure rate and uniform dispersion of MWNTs, and rich functional groups of WPU improved the gas sensing performance, making the response of the flexible MWNT/WPU to O3 be 4.1 times of the responses of pure MWNTs. The limit of detection for O3 reached 38.4 ppb. The enhanced mechanical properties endowed the flexible MWNT/ WPU composite with the high bending stability and long-term stability. After one month, the response of the MWNT/WPU was changed by 3% and the responses decreased by no more than 10% after bending 5000 times.

Surface-enhanced Raman scattering (SERS), as a rapid, reliable and non-destructive spectral detection technology, has made a series of breakthrough achievements in screening and pre-diagnosis of various cancerous tumors. In this paper, high-performance gold nanoparticles/785 porous silicon photonic crystals (Au NPs/785 PSi PhCs) active SERS substrates were specially designed for serum testing, and realized highly sensitive detection of serum from healthy people, patients with cervical cancer and breast cancer. Based on the SERS spectra of the three groups of serum, the significant differences between the healthy group and cancer group at 1030 cm−1 and 1051 cm−1 were analyzed, and the similar but different serum SERS spectra of cervical cancer and breast cancer patients were compared. In addition, the spectral difference detected by SERS technology combined with a multivariate statistical algorithm was used to distinguish three kinds of serum. The serum SERS spectral sensitive bands were extracted by recursive weighted partial least squares (rPLS), and the three classification diagnosis models were established by combining orthogonal partial least squares discriminant analysis (OPLS-DA), linear discriminant analysis (LDA) and principal component analysis support vector machine (PCA-SVM) for synchronous classification and discrimination of the three groups of serum. The diagnostic results showed that the overall screening accuracy of three models were 93.28%, 97.77% and 94.78%, respectively. These above results confirmed that the Au NPs/785 PSi PhCs can realize super-sensitive detection of serum, and the established diagnostic model has great potential for pre-diagnosis and simultaneous screening of cervical cancer and breast cancer.