Results 151 to 160 of about 647,862 (252)

How students choose E-learning resources: The importance of ease, familiarity, and convenience. [PDF]

FASEB Bioadv, 2020
Bringman-Rodenbarger L, Hortsch M.
europepmc   +1 more source

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

Development of a suite of short planetary health learning resources by students for students as future health professionals. [PDF]

Front Med (Lausanne)
Pais Rodrigues C, Papageorgiou E, McLean M.   +2 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

3D Technology Development and Dental Education: What Topics Are Best Suited for 3D Learning Resources? [PDF]

Dent J (Basel), 2020
Poblete P, McAleer S, Mason AG.
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

Educating the next generation of radiologists: a comparative report of ChatGPT and e-learning resources [PDF]

Diagn Interv Radiol
Meşe İ, Altıntaş Taşlıçay C, Kuzan BN, Kuzan TY, Sivrioğlu AK.   +4 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

Does personality matter: examining the value of personality insights for personalized nudges that encourage the selection of learning resources. [PDF]

Front Artif Intell
Cardenas Canto P, Dimitrova V, Sherman S, Flint SW.   +3 more
europepmc   +1 more source