Results 91 to 100 of about 4,959 (254)

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

Disorder‐Driven Ionic Mobility Edge and Localization‐Driven Dendrite Formation in Solid Electrolytes

Advanced Energy Materials, EarlyView.
Migration‐barrier disorder localizes ionic transport into a sparse percolation backbone. Current and electric‐field focusing at filament tips promote fractal dendrite growth and suppress the critical current density according to jcrit = j0 exp(−σEeff/kBT).
Dongwook Lee, Jiwon Seo
wiley   +1 more source

Pricing Dynamics in the US Hemp Market: A Vertical Price Transmission Analysis of the Hemp Value Chain

Agribusiness, EarlyView.
ABSTRACT The US hemp market is a new and nascent industry that has been devoid of research for about half a century. This study examined the effects of exogenous shock on price at each phase of the value chain—Farm (hemp biomass), and its impact on prices at other phases of the value chain—Intermediary Processor (crude cannabidiol hemp) and Final ...
Solomon Odiase, Tyler Mark, Patalee Buddhika Appuhamilage   +2 more
wiley   +1 more source

The Geography of Success: A Spatial Analysis of Export Intensity in the Italian Wine Industry

Agribusiness, EarlyView.
ABSTRACT This paper investigates the paradox of how Italy's fragmented, SME‐dominated wine industry achieves global export success. Moving beyond purely firm‐centric explanations, we test whether export intensity is spatially dependent, clustering geographically in regional ecosystems.
Nicolas Depetris Chauvin, Jonas Di Vita
wiley   +1 more source

Machine Learning‐Assisted Second‐Order Perturbation Theory for Chemical Potential Correction Toward Hubbard U Determination

Advanced Intelligent Discovery, EarlyView.
In this work, the Doubao large language model (LLM) is involved in the formula derivation processes for Hubbard U determination regarding the second‐order perturbations of the chemical potential. The core ML tool is optimized for physical domain knowledge, which is not limited to parameter prediction but rather serves as an interactive physical theory ...
Mingzi Sun, Tong Wu, Baian Chen, Zikang Li, Qiuyang Lu, Lu Lu, Hon Ho Wong, Cheuk Hei Chan, Bolong Huang   +8 more
wiley   +1 more source

DeepMapper: Attention‐Based AutoEncoder for System Identification in Wound Healing and Stage Prediction

Advanced Intelligent Discovery, EarlyView.
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu, Ksenia Zlobina, Michael Briden, Oscar Avalos, Héctor Carrión, Sebastian Osorio, Hsin‐ya Yang, Alexandra Nava, Michelle D. Bagood, Marco Rolandi, Roslyn Rivkah Isseroff, Marcella Gomez   +11 more
wiley   +1 more source

A Theorem on Prime Numbers

, 2003
The theorem presented in this paper allows the creation of large prime numbers (of order up to o(n^2)) given a table of all primes up to n.
openaire   +2 more sources

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

Reinforcing Particle Architectural Stability of Li‐Rich Cathode With Enhanced Anionic Redox Reaction Reversibility

Angewandte Chemie, EarlyView.
In this work, we establish a direct correlation between internal compactness and particle architectural stability, identifying it as a key descriptor of cathode structural integrity. Simultaneously, the capacity contribution and compensation mechanism of ARR are resolved, revealing that the extent of irreversible capacity loss is governed by both the ...
Yizhen Huang, Bixian Ying, Chunpu Li, Maolin Yang, Kang Zhang, Guifan Zeng, Jiyuan Xue, Yuan Tian, Wei Li, Chunjing Hu, Tao Zeng, Peng Zhang, Chao Li, Yinguo Xiao, Huaqiang Chen, Tian Qiu, Stefan Schuppler, Peter Nagel, Jin Yi, Changming Qu, Jia‐Wei Wang, Fanghua Ning, Qingsong Wang, Yu Qiao, Shi‐Gang Sun   +24 more
wiley   +2 more sources

A Breadth‐First Pruned‐Enriched Rosenbluth Method for Force–Extension Simulations of Confined Semiflexible Chains

Advanced Intelligent Discovery, EarlyView.
The behaviors of semiflexible polymers such as DNA and protein are often reshaped by coupled interactions. Monte Carlo simulations assist in studying these systems. This work recasts the traditional chain‐growth strategy into a new framework: a fixed number of chains grow synchronously, while less relevant chains to the target system are removed and ...
Yihan Zhao, Jizeng Wang
wiley   +1 more source