Results 231 to 240 of about 827,082 (307)
This review summarizes the principles and challenges of nonaqueous lithium‐oxygen batteries and recent advances in cathode catalysts, including carbon‐based materials, metals, oxides, sulfides, nitrides, carbides, and redox mediators. It highlights emerging design strategies and artificial intelligence‐driven approaches, emphasizing data‐assisted ...
Yuqing Yao +8 more
wiley +1 more source
The causality problem in climate anxiety research. [PDF]
Vergunst F.
europepmc +1 more source
Advances in Magnesium‐Based Thermoelectrics: A Critical Review
Magnesium‐based thermoelectric materials have emerged as promising candidates for low‐to‐mid‐temperature energy conversion due to their abundance, low cost, and competitive performance. This review summarizes recent advances in Mg3X2, MgAgSb, and Mg2X systems, covering transport mechanisms, fabrication strategies, stability challenges, and device ...
Li‐Min Zhang +5 more
wiley +1 more source
Editorial: When children also shape the family environment. [PDF]
Ystrom E.
europepmc +1 more source
Ultrathin lithium metal anodes (≤15 µm) offer a promising route to high‐energy‐density batteries due to their high capacity and low potential. This review presents design principles for ultrathin Li, evaluates fabrication strategies, and discusses challenges in liquid and solid‐state cells.
Cheng Wang +9 more
wiley +1 more source
Development and psychometric validation of an innovative instrument to assess musculoskeletal disorder prevention behaviors in the petrochemical industry (PREMOVE). [PDF]
Moradi Z +3 more
europepmc +1 more source
Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung +9 more
wiley +1 more source
We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano +5 more
wiley +1 more source
An open-source optimization model for sustainable open-pit mine production scheduling. [PDF]
Lotsu JS, Bimpong GY, Boakye K.
europepmc +1 more source
A deep learning inverse‐design framework is established to create versatile reconfigurable terahertz metadevices. By synergizing deep learning with phase‐change materials, this approach enables on‐demand customization of multidimensional electromagnetic responses.
Yisheng Dong +11 more
wiley +1 more source

