The widespread application of zinc-air batteries (ZABs) relies on robust and cost-effective oxygen reduction reaction (ORR) catalysts. While Co-based single-atom catalysts (SACs) offer superior selectivity and stability over traditional Fe–N–C counterparts, boosting their intrinsic ORR activity remains a formidable challenge. Here, we alleviate the scaling-relation constraint among ORR intermediates by precisely engineering the coordination symmetry of Co SACs. Through a novel mild annealing strategy, we incorporated boron into the first and second coordination shells of Co centers to construct a typical asymmetric Co–N3B–O local environment. The first-shell B/O coordination modulates the electronic structure of the Co center, while the hydrogen bond between *OOH and the coordinated O atom further stabilizes the key intermediate, thereby synergistically enhancing ORR activity. Implemented in ZABs, our Co-BCN-950 catalyst delivers outstanding performance, achieving a peak power density of 216 mW cm−2—a 43
Temperature, as a fundamental thermodynamic variable, governs processes from cellular metabolism to microelectronics, necessitating precise, remote, and non-contact thermometry. Lanthanide-based luminescence thermometry has emerged as a leading platform, capitalizing on sharp line-like emission, microsecond-to-millisecond excited-state lifetimes, exceptional photostability, and thermally coupled levels (TCLs) that enable self-referenced ratiometric readout with high spatiotemporal resolution. This review presents a comprehensive overview spanning from fundamental photophysics and emerging lanthanide-based luminescence thermometric materials to cutting-edge applications. It details the underlying electronic energy-level structure and luminescence processes, systematically classifies thermometric mechanisms into TCL-based Boltzmann ratiometry, non-TCL strategies, lifetime-based approaches, and hybrid schemes, and establishes standardized performance metrics for objective cross-comparison. Beyond surveying six major material classes, the review highlights pivotal innovations such as anti-thermal-quenching (ATQ) strategies, a paradigm shift from single-parameter relative sensitivity to a multi-metric evaluation framework, and the integration of emerging platforms such as metal-organic frameworks and hybrid composites. Frontier applications in single-cell metabolic imaging, microelectronic thermal management, and aerodynamic thermal protection are showcased. Current challenges, including thermal quenching, limited quantum efficiency, and inadequate reproducibility, are critically examined, and forward-looking perspectives on ATQ development, multi-parameter co-optimization, and application-oriented standardized characterization protocols are outlined. This review offers a timely and valuable resource for accelerating the design and deployment of next-generation lanthanide luminescence thermometers.
Development of flexible materials integrating broadband electromagnetic wave (EMW) absorption, infrared stealth, and hydrophobicity is required for complex environments. In this work, flexible SiTiOC ceramic fiber felts embedded with Sn nanoparticles were fabricated via electrospinning followed by in-situ carbothermal reduction. The metallic Sn promotes carbon graphitization, forming a three-dimensional conductive network and establishing heterogeneous interfaces within the SiTiOC matrix. First-principles calculations indicate that the work function gradient (ΦSn < ΦC) drives electron migration at the Sn/C interface, inducing interfacial polarization, while turbostratic carbon in the SiTiOC phase provides defect dipole polarization. The fiber felt exhibits an effective absorption bandwidth of 7.3 GHz at a thickness of 3.75 mm. The material integrates radar-infrared compatible stealth through low thermal conductivity and low emissivity, with a water contact angle exceeding 138°. These results provide an interface engineering strategy for multifunctional stealth materials in complex environments.
Till now, traditional room-temperature infrared (IR) stealth materials often suffer from high glossiness and poor environmental tolerance. While ABO3 perovskites offer flexible structural tunability and high stability, their intrinsic room-temperature IR emissivity remains impractically high. Moreover, the fundamental correlation between localized nanoscale lattice distortions, electron transitions, and macroscopic IR radiation characteristics remains an unresolved core issue. Herein, we propose an atomic-level structural modulation strategy in Sm1−xSrxCoO3 perovskites to achieve exceptional room-temperature IR stealth. By systematically introducing Sr doping, we induce high-concentration Co3+/Co4+ mixed valence states and localized oxygen vacancy enrichment. This nanoscale defect engineering significantly reduces the band gap and accelerates carrier migration via double-exchange interactions, fundamentally enhancing electron transitions and macroscopic conductivity. Consequently, the room-temperature infrared emissivity of the optimal doping component in the 8–14 µm wavelength range decreased significantly from 0.752 for the undoped sample to 0.224. This value reached a relatively low level in the perovskite ceramic system and demonstrated excellent thermal camouflage properties. Density functional theory (DFT) calculations reveal that optimal Sr doping (x = 0.5) effectively breaks local crystal symmetry, induces nanoscale charge rearrangement, and broadens the electron transition effect. Coupled with remarkable environmental tolerance, this synergistic nanoscale electronic and structural modulation provides a compelling paradigm for designing advanced, highly stable low-infrared stealth materials.
药物载体的理性设计受到药物分子结构、 表面化学及载体孔结构参数共同决定的高维设计空间限制. 针对介孔二氧化硅纳米颗粒(MSNs)载药体系中载药量预测与配方筛选困难的问题, 本文构建了一种用于MSNs载药排序的图学习网络(graph-learning-based network for drug-loading ranking in MSNs, GNDR), 用于预测载药量(DLC)并对潜在优选配方进行排序. GNDR融合预训练分子表示、 迁移学习与贝叶斯优化, 可实现表面改性剂和载药参数的协同推荐. 基于骨架划分的10折交叉验证结果表明, GNDR具有稳定的排序性能(Spearman’s ρ = 0.78), 且整体表现优于基于分子指纹和仅基于条件变量的基线模型. 对128种抗炎药的虚拟筛选进一步表明, MPTMS是提高载药性能的优选改性剂. 随后, 在独立合成的单孔MSNs体系中, 以布洛芬和地塞米松为模型药物开展实验验证, 结果证实了模型预测的改性剂排序趋势. 上述结果表明, GNDR可为MSN配方设计中实验搜索空间的缩减与候选体系的快速筛选提供有效工具.
