Results 61 to 70 of about 9,690 (264)

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

The expression of certainty and uncertainty in Italian speaking children

Ricerche di Pedagogia e Didattica, 2014
Epistemic modality expresses the speaker’s attitude of certainty/uncertainty toward the fact/event mentioned in the proposition. In conversation, the use of epistemic modality informs the listener on how much s/he should rely on the pieceof information ...
Maria Silvia Barbieri
doaj   +1 more source

Extension Economists: Valued in Mission, Penalized in Practice

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT As the public engagement arm of the land‐grant mission, we argue that Extension faculty in US agricultural economics departments face an identity crossroads as they struggle for institutional support. Specifically, we argue that Extension economists function as boundary‐spanning professionals within academic structures that often devalue ...
Trey Malone, Craig W. Carpenter, Courtney Bir, Andrew J. Van Leuven, Rebecca Wasserman‐Olin, Wendong Zhang   +5 more
wiley   +1 more source

Epistemic stance markers in corporate social responsibility reports: a discourse analysis of energy sector communications

Frontiers in Communication
This study examines epistemic stance markers (ESM) in Corporate Social Responsibility (CSR) reports, focusing on how energy companies manage uncertainty and establish credibility in sustainability communications.
Shuai Liu
doaj   +1 more source

Multimodal Learning with Rashomon Analysis for Battery Discharge Capacity Prediction

Advanced Intelligent Discovery, EarlyView.
Multimodal fusion integrates composition, crystal‐structure, and radial‐distribution descriptors to predict battery discharge capacity. Rashomon analysis across near‐optimal models reveals that explanatory variation is structured rather than arbitrary, separating stable mechanistic signals from model‐contingent attributions and providing a more ...
Jue Gong, Lejia Wang, Tianqing Zhu, Keith Butler, Sichao Li   +4 more
wiley   +1 more source

When clients (or psychotherapists) say “I don’t know”: unknowledge or uncertainty?

Gestalt Theory
Viewing psychotherapy conversations from an epistemic perspective involves analysing how psychotherapist and client manage their knowledge, insufficient knowledge (uncertainty) and lack of knowledge (unknowledge).
Zuczkowski Andrzej, Stemberger Gerhard
doaj   +1 more source

A Cognitive Framework for Analysis and Treatment of Uncertainty in Prognostics

Chemical Engineering Transactions, 2013
Uncertainties exist in fault prognostics systems can lead to inaccurate results and this will lead to unnecessary or delay maintenance activities.
B. Sun, T. Liu, S. Liu, Q. Feng
doaj   +1 more source

Artificial Intelligence‐Driven Network Pharmacology: A Methodological Paradigm Shift Bridging Traditional Wisdom and Modern Science

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence is redefining network pharmacology (NP). By integrating knowledge graph engineering, geometric deep learning, multiomics anchoring, and generative reasoning, AI‐driven NP (AI‐NP) transforms static target mapping into dynamic, predictive modeling.
Cong Wang, Sile Hu, Rigahai Ji, Riguna A, Siqige Hao, Ma Zhuo, Yi‐Hung Chen, Bisihalatu Hu, Ulana Bai, Xigui Hada   +9 more
wiley   +1 more source

Predicting Performance of Hall Effect Ion Source Using Machine Learning

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park, Guentae Doh, Dongho Lee, Youngho Kim, Changmin Shin, Su‐Jin Shin, Young‐Chul Ghim, Sanghoo Park, Wonho Choe   +8 more
wiley   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source