Results 201 to 210 of about 13,536,213 (255)

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

Evolution of networks in virtual reality: A scalable framework for studying social dynamics of small groups. [PDF]

PLoS One
Park R, Miller MR, Han E, DeVeaux C, Bailenson JN, Ram N.   +5 more
europepmc   +1 more source

30p-JE-13 Hydrodynamical Regime and Self - Similarity Laws in Stochastic Processes

Meeting Abstracts of the Physical Society of Japan, 1987
openaire   +1 more source

Oxygen‐Scavenging‐Driven Interlayer Engineering for Balancing Linearity and Retention in IGZO Synaptic Memristors

Advanced Electronic Materials, EarlyView.
Oxygen‐scavenging‐induced self‐formed interlayers regulate Schottky‐barrier modulation in IGZO memristors, producing a fundamental trade‐off between synaptic update linearity and retention. A preserved AlOx interlayer moderates voltage distribution and enables gradual, nearly linear conductance updates, whereas a soft‐broken SiO2 interlayer provides a ...
Jae Woo Lee, Dong Hyeop Shin, Seung Joo Myoung, Soohong Eo, Wonjung Kim, Seeun Lee, Changwook Kim, Junjong Lee, Yoon Jung Lee, Sung‐Jin Choi, Sungjun Kim, Dae Hwan Kim   +11 more
wiley   +1 more source

Scaling and self-similarity in the formation of the embryonic epigenome. [PDF]

Nat Phys
Olmeda F, Lohoff T, Kafetzopoulos I, Clark SJ, Benson L, Santos F, Krueger F, Walker S, Reik W, Rulands S.   +9 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

Measuring human behavior through controlled perturbations: a framework for reconstructing behavioral systems. [PDF]

Front Psychol
Cipresso P.
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

Effects of correlated collisions and intermittency on the growth of lucky droplets. [PDF]

Proc Natl Acad Sci U S A
Bätge T, Zierenberg J, Wilczek M.
europepmc   +1 more source

What Really Drives Agri‐Environment‐Climate Measures' Adoption? Mandatory Requirements, Behavioral Traits, and Structural Factors in the CAP Green Architecture

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT To increase farmer adoption of green practices, the EU Common Agricultural Policy includes both mandatory (conditionality) and voluntary instruments (eco‐schemes–ECS– and more demanding, multi‐annual agri‐environment‐climate measures –AECM–). Building on the experiment of Barreiro‐Hurle et al.
L. Sanchez‐Mata, M. Rodríguez‐Entrena, M. Espinosa‐Goded, F. J. Dessart, J. Barreiro‐Hurlé   +4 more
wiley   +1 more source