Results 201 to 210 of about 21,334 (306)

Advancing Lithium–Oxygen Batteries: Pioneering Cathode Catalyst Innovation and Artificial Intelligence‐Driven Design Paradigms

Advanced Materials, EarlyView.
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, Chongyang Hao, Karol Viviana Mejia‐Centeno, Malik Dilshad Khan, Shang Wang, Longqiu Li, Yanhong Tian, Andreu Cabot, Qing Sun   +8 more
wiley   +1 more source

Modeling the distribution of soil organic carbon in salt marshes dominated by various plant species along Egypt's Delta coast. [PDF]

BMC Plant Biol
Eid EM, Shahawy AA, Al-Sodany YM, El-Khalafy MM.   +3 more
europepmc   +1 more source

Advances in Magnesium‐Based Thermoelectrics: A Critical Review

Advanced Materials, EarlyView.
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, Li Zhang, Nan‐Hai Li, Yan‐Ling Yang, Xiao‐Lei Shi, Zhi‐Gang Chen   +5 more
wiley   +1 more source

Techno-economic analysis of a power-to-hydrogen system in heavy industries with and without national incentives. [PDF]

PLoS One
Marouani I, Albadran S, Alturki M, Almalaq Y, Alshammari BM, Guesmi T.   +5 more
europepmc   +1 more source

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

Advanced Materials, EarlyView.
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, Jiaxiang Yi, Hieu Nguyen‐Duc, Tien Nu Hoang Lo, Weili Zhao, Chaoqun Dong, Fabien Sorin, Baris Caglar, Lei Wei, Tung Nguyen‐Dang   +9 more
wiley   +1 more source

Techno-Economic Assessment of Industrial Symbiosis Between Steel and Urea Plants: The INITIATE Process. [PDF]

Energy Fuels
Zecca N, Lücking L, van Dijk HAJ, Manzolini G.   +3 more
europepmc   +1 more source

Machine Learning Accelerated Computational Design of Bio‐Inspired Catalysts in the Nitrogen Reduction Reaction

Advanced Materials, EarlyView.
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, Zihan You, Haoran Chen, Qifan Zhong, Rong‐Zhen Liao, Shaoqi Zhan   +5 more
wiley   +1 more source

Integrating resource utilization and bioregenerative life support systems for sustainable space exploration. [PDF]

Front Microbiol
Esposito M, Tonietti L, Santomartino R, Giovannelli D, Chianese E, Rotundi A, Romano I, Poli A, Finore I, Cordone A, Di Donato P.   +10 more
europepmc   +1 more source

Transient Laser‐Shocked Synthesis of Amorphous Layer‐Supported Metal Nanocrystals for Efficient Nitrate Reduction

Advanced Materials, EarlyView.
A general, versatile laser‐shock synthesis process is reported to produce various bimetallic CuNi, CuFe, CuCo, and medium‐entropy CuFeCoNi heterostructures, in which crystalline metal nanoparticles are anchored to amorphous hydroxide supports. During nitrate reduction reaction, the heterostructures undergo dynamic amorphous/crystalline reconstruction ...
Weihua Guo, Jixun Zhang, Siwei Zhang, Yangbo Ma, Yun Song, Jianjun Su, Zihao Li, Yinger Xin, Qiang Zhang, Mingming He, Ruixuan Wang, Rui Xue, Shibo Xi, Ying Wang, Shenlong Zhao, Tao Yang, Zhengxiao Guo, Ben Zhong Tang, Ruquan Ye   +18 more
wiley   +1 more source

Comparative study of machine learning methods for carbon metering in power generation enterprises. [PDF]

Sci Rep
Wang S, Fang B, Zhang J, Xing S, Wu J, Xiao H.   +5 more
europepmc   +1 more source