Results 131 to 140 of about 167,660 (319)

Degradation Pathways of Silicon‐Based Anodes in Lithium‐Ion Batteries

Advanced Energy Materials, EarlyView.
Silicon‐based anodes undergo degradation through five primary pathways: (1) mechanical and structural deterioration of the active material, (2) loss of electrode integrity and electrical contact, (3) mechanical instability of the solid electrolyte interphase (SEI), characterized by repetitive fracture and deformation, (4) chemical instability of the ...
Yoon Jeong Choi, Ji‐Youn Bae, Ga‐On Park, Seung‐Ho Yu   +3 more
wiley   +1 more source

Performance Improvement of Model‐Free Predictive Current Control for PWM Rectifiers Under Nonideal Power Grids

IET Power Electronics
This paper proposes an improved robust predictive current control strategy, combining an improved ultralocal model with a hybrid space vector modulation (HSVM) scheme.
Xing Wang, Yongchang Zhang, Dian Cao, Lei Han   +3 more
doaj   +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

A Quantitative Lithium Inventory Framework for Anode‐Free Lithium Metal Batteries

Advanced Energy Materials, EarlyView.
A component‐resolved lithium inventory framework quantitatively tracks Li redistribution across the cell in anode‐free NMC622||Cu pouch cells throughout cycling. Three sequential degradation stages are identified: formation‐driven cathode Li depletion, midlife inactive Li0 accumulation, and late‐stage runaway SEI thickening. The cathode, as the sole Li
Wurigumula Bao, Alex Liu, Thomas S. Marchese, Yuanlong Bill Zheng, Weikang Li, Dhevathi Rajan Rajagopalan Kannan, Vallabha Rao Rikka, Vinay Premnath, Judith Jeevarajan, Ying Shirley Meng   +9 more
wiley   +1 more source

Improved power control using optimal adjustable coefficients for three-phase photovoltaic inverter under unbalanced grid voltage. [PDF]

ScientificWorldJournal, 2014
Wang Q, Zhou N, Lou X, Chen X.
europepmc   +1 more source

Adapting to Changing Rainfall and Developing Off‐Farm Employment: Implications for the Adoption of Direct Seeding in Rice Production

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT Rice is the main staple food for more than half of the world's population and the income from rice is an essential source for livelihoods of millions of households. We examine whether direct seed in rice production is an adaptation of rice farmers to rainfall changes and farm labor scarcity.
Manh Hung Do
wiley   +1 more source

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source