Results 261 to 270 of about 204,781 (309)

Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization

Advanced Electronic Materials, EarlyView.
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali, David Lehninger, Florencio Sánchez, Ignasi Fina   +3 more
wiley   +1 more source

Autoencoder-Enhanced Convolutional Neural Networks for Plantar Pressure-Based Gait Pattern Recognition: Model Development and Cross-Validated Evaluation Study. [PDF]

JMIR Form Res
Chang CC, Lung CW, Jan YK, Lu QQ, Wang YY, Chen YS, Liau BY.   +6 more
europepmc   +1 more source

Linear and Programmable Long‐Term Plasticity in PECVD Amorphous SiC Memristors

Advanced Electronic Materials, EarlyView.
Stoichiometry‐engineered PECVD amorphous SiC memristors exhibit highly linear and programmable long‐term synaptic plasticity with a nonlinearity as low as 0.08. By controlling the local bonding environment, stable multilevel conductance updates are achieved, enabling robust neural‐network classification on MNIST and CIFAR‐10 and highlighting amorphous ...
Qin Liu, Omesh Kapur, Bohao Ding, Fangnan Chen, Bingkai Ding, Ruomeng Huang, C. H. Kees de Groot   +6 more
wiley   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Deep learning and eye tracking: Convolutional neural networks provide converging evidence for experience-driven attention within visual search. [PDF]

Behav Res Methods
Crotty N, Doyle A, Volkova K, Massa N, Benson NC, Grubb MA.   +5 more
europepmc   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

A scalable multimodal framework for learning engagement recognition using three-dimensional convolutional neural networks and semi-automatic annotation. [PDF]

Front Artif Intell
Lin KC, Tseng CC, Wu J.
europepmc   +1 more source

Surface Acidity Engineering: From Fundamental Insights to Universal Design Rules for Electrocatalytically and Electrically Active Oxides

Advanced Energy Materials, EarlyView.
This comprehensive review highlights surface acidity engineering as a versatile strategy to modulate surface charge and boost catalytic performance in functional oxides. It explores recent advances in practical implementation, structural reconstruction approaches, and mechanistic origins from diverse complementary viewpoints.
Gyu Rac Lee, Harry L. Tuller
wiley   +1 more source

A novel hybrid customized color correction and Recurrent Convolutional Neural Networks approach for underwater image enhancement. [PDF]

Sci Rep
Natarajan D, Sudhakaran P, Bereznychenko V.   +2 more
europepmc   +1 more source