Results 201 to 210 of about 19,641,006 (303)

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

Risk-sensitive mean-field control of large-scale UAV Swarms for stochastic disaster tracking and robust first response. [PDF]

Sci Rep
Sayeed MA, Sayeed MA, Ahmed T, Bharti AK.   +3 more
europepmc   +1 more source

Assessing Mesoscale Heterogeneities in Hard Carbon Electrodes Through Deep Learning‐Assisted FIB‐SEM Characterization, Manufacturing and Electrochemical Modeling

Advanced Energy Materials, EarlyView.
A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan, Imelda Cardenas‐Sierra, Pei Sun, Hari Raj, Daniele Duranti, Mahnoor Nafees, Edoardo Rossi, Marco Sebastiani, Paul Vigneaux, Martin Petit, Maxime Moreaud, Francisco Fernandez, Alejandro A. Franco   +12 more
wiley   +1 more source

Bacterial Sentience Is Determined by the Stochastic, Chaotic, and Deterministic Behavior of Cytoplasmic Particles. [PDF]

Curr Issues Mol Biol
Dicks LMT, Pohl C, Botha A.
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

Hopf Bifurcation in an Incommensurate Caputo Fractional-Order Computer Virus Epidemic Model with Multiple Time Delays. [PDF]

Entropy (Basel)
Zhong A, Wang C.
europepmc   +1 more source

From Top to Bottom: Manufacturing Process‐Context Aware Resolution of Energy Device Electrodes Through a 3D Diffusion Generative Model

Advanced Energy Materials, EarlyView.
The application of a generative diffusion model, enhanced with a training data augmentation pipeline retaining the manufacturing process context of electrode microstructures, leads to improved fidelity of the through‐plane tortuosity factor in the AI generated samples.
Victor Ramirez‐Camacho, Siwar Ben Hadj Ali, Maxence Desnoyers, Francisco Fernandez, Nassima Benammar, Alejandro A. Franco   +5 more
wiley   +1 more source

Dynamic properties of Kermack-McKendrick-like models. [PDF]

PLoS One
Diallo HA, Ezzinbi K, Outada N, Sallet G.   +3 more
europepmc   +1 more source

Does a Specialized Niche Market Vegetable Processor Enjoy Bargaining Power?

Agribusiness, EarlyView.
ABSTRACT Agribusiness companies may achieve competitive advantage through specialization within niche markets. One such niche is the fresh‐cut fruit and vegetable market, which has been steadily growing in Germany. This study examines whether the specialization of a German fresh‐cut producer grants it with market power within this niche market.
Nikolas Bublik, Franziska Mittag, Laura Hellstern, Sebastian Hess   +3 more
wiley   +1 more source

How AI Can Advance Mathematical Biology: Opportunities, Challenges, and Future Directions. [PDF]

Bull Math Biol
Rabiei K, Rempala GA, Laubenbacher R, Hao W.   +3 more
europepmc   +1 more source