Fuchun Zhang

Pure and nominally Zn-modified SnO₂ nanostructures were synthesized by a one-step hydrothermal route and evaluated as chemiresistive sensors for ethylene glycol (EG). Zn addition was associated with a change from relatively thick nanoplates to finer nanosheet-like units, while X-ray diffraction retained the rutile SnO₂ pattern. At 100 °C, the Zn-containing sensor gave responses of 81.19 toward 50 ppm EG and 208.07 toward 130 ppm EG; the latter was approximately 12 times the response of pure SnO₂ within the same concentration series. At 50 ppm, its response and recovery times were 153 and 42 s, respectively. The EG response remained measurable from 20 to 80% relative humidity. Density-of-states calculations for pristine SnO₂(110) and an idealized Zn-substituted slab showed a redistribution of orbital-projected states, offering a qualitative electronic perspective on the sensing behavior.

Two‐dimensional (2D) semiconductors are highly desirable for broadband photodetection but are often constrained by their limited optical absorption and inefficient exciton dissociation. In this study, we report a donor–acceptor‐engineered 2D conjugated coordination polymer (c‐CP), Ni‐TABQ (TABQ = tetraaminobenzoquinone), as a narrow‐bandgap semiconductor. The TABQ ligands integrate electron‐rich amino donors and electron‐deficient quinone carbonyl acceptors within the same molecular backbone, endowing the Ni‐TABQ lattice with strong intramolecular charge‐transfer absorption and a built‐in driving force for charge separation. Benefiting from strong broadband absorption and high charge‐carrier mobility, the vapor‐phase‐grown Ni‐TABQ thin films enable photodetection from 350 to 1400 nm under a 3 V bias, with a measurable response tail above 1150 nm, further achieving a responsivity of up to 3.1 A W ⁻¹ , a specific detectivity of up to 6.58 × 10 ¹⁰ Jones (625 nm at ∼85 µW cm ⁻² ), and a response time of ∼206 µs, while maintaining stable operation at 3 V over 8500 s of continuous cycling. These metrics compare favorably with state‐of‐the‐art broadband photodetectors based on standalone 2D materials, establishing donor–acceptor molecular engineering within the 2D metal‐organic lattice as an effective strategy for advancing high‐performance 2D optoelectronic devices.

Tubular g-C₃N₄ represents an attractive structural motif for sophisticated photocatalytic applications, a merit derived from its multiscale pore configuration that accelerates reactant diffusion, the influence of quantum size effects on its electronic bands, which refines photoexcited carrier kinetics, and the oriented charge movement enabled by its distinctive geometric asymmetry. This review not only consolidates recent breakthroughs in synthesis methodologies spanning template-directed and template-free routes, which precisely engineer tube dimensions, wall thickness, and compartmentalization, but also critically analyzes how each modification strategy, including morphological control, elemental doping, defect engineering, and heterojunction construction, concurrently enhances specific surface area, broadens light absorption range, improves carrier mobility, increases active site density, strengthens redox capability, promotes photo-Fenton efficiency, and prolongs carrier lifetime, thereby significantly boosting photocatalytic performance. Future efforts must address scalable green synthesis, atomic-level strain engineering, and operando mechanistic studies to accelerate industrial deployment of these multifunctional materials.

This study uses acustom-made acetone gas sensor array to collect response curve data under various experimental conditions, constructing a small-sample sensor dataset. To address the challenges of machine learning modeling with limited sample sizes, we propose a Transformer-based diffusion model (TFDM) that generates high-quality response curves and corresponding conditions (gas concentration and temperature) from raw experimental data. The model incorporates physical prior information such as shape regularization, smoothness constraints, and non-negative constraints to enhance the physical consistency and waveform fidelity of generated data, thereby expanding dataset scale. We apply backpropagation neural networks (BPNN), long short-term memory networks (LSTM), and convolutional neural networks (CNN) for acetone concentration prediction. Experimental results demonstrate that TFDM-generated data significantly improves prediction accuracy: compared to models trained solely on the original dataset, the root mean square error (RMSE) decreases by 25.08%,26.88%, and 27.17% for all three models, respectively, while the coefficient of determination (R2) increases by 0.11,0.16, and 0.14 (R2TFDM−R2origin). The predictive performance further improves with the integration of physical constraint strategies. These findings validate TFDM's effectiveness in small-sample learning for gas sensor applications and highlight its practical deployment potential.

Despite the remarkable advancement of metal halide perovskite solar cells (PSCs) achieving power conversion efficiencies (PCEs) reaching 27.3%, suppressing nonradiative recombination at critical interfaces remains pivotal to unlocking their full performance potential and ensuring operational longevity. A promising solution lies in interfacial engineering, as exemplified by self-assembled molecular interlayers designed for defect passivation. Here, we propose hydroxylamine-O-sulfonic acid (HOSA) as a multifunctional molecular bridge at the tin oxide (SnO₂)/perovskite buried interface. Experimental and computational analyses reveal that HOSA’s sulfonic acid (−SO₃H) and amine (−NH₂) groups anchor to SnO₂ via ester linkages and coordinate with undercoordinated Pb²⁺ defects in the perovskite, respectively. This dual-interaction mechanism simultaneously passivates interfacial traps, enhances charge extraction kinetics, and promotes perovskite crystallization with reduced lattice strain. Consequently, the HOSA-modified devices achieve a champion PCE of 24.22%, surpassing the reference cells (22.34%) while delivering enhanced durability: unencapsulated devices retain 78% of initial efficiency under continuous 1 sun illumination (500 h) and 71% after thermal aging (65 °C, N₂, 1000 h). This work underscores the efficacy of rationally engineered molecular interlayers in harmonizing interfacial energetics and defect dynamics for high-performance perovskite photovoltaics.

We employed density functional theory (DFT) to investigate the effect of tungsten (W) doping on the crystal structure, electronic properties, and optical response of Bi₂MoO_6−xW_xO₆. The results show that W doping retains the Aurivillius orthorhombic lattice structure while inducing localized distortions. All doping systems retain semiconductor characteristics with a band gap ranging from 2.11 to 2.26 eV. The valence band is mainly composed of O-2p orbitals, while the conduction band consists of Mo-4d and W-5d states. As W doping increases, the influence of W-5d states near the conduction band edge intensifies, modulating the electronic structure. Optical calculations show that W doping shifts the absorption edge and allows for precise adjustment of the absorption threshold in the visible light range. These findings provide insight into how W doping affects the electronic and optical properties of γ-Bi₂MoO₆ and offer a theoretical basis for improving Bi₂MoO₆-based photocatalytic materials.