Results 141 to 150 of about 12,297 (303)

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

Smart grids for rural conditions and e-mobility - Applying power routers, batteries and virtual power plants [PDF]

, 2016
Significant reductions of greenhouse gas emission by use of renewable energy sources belong to the common targets of the European Union. Smart grids address intelligent use and integration of conventional and renewable generation in combination with ...
Boehner, Volker, Franz, P., Gallart, R, Girbau Llistuella, Francesc, Hanson, J., Martínez, S., Sumper, Andreas   +6 more
core  

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

Coupling Impedance Modeling Analysis of Grid-Connected Inverters Under Three-Phase Voltage Unbalance

Energies
Under the condition of asymmetric system voltage, grid-connected inverters exhibit obvious sequence impedance frequency coupling characteristics, which can easily lead to resonance and the misoperation of protection and control devices. Currently, targeted quantitative analyses are insufficient.
Yang Liu, Haidong Yu, Qihang Wu, Bin Wang, Lisheng Li, Wenbin Liu   +5 more
openaire   +2 more sources

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

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Electroactive Metal–Organic Frameworks Enabling Unidirectional Electrochemical Capacitors and Logic Gates (MOF‐CAPode)

Angewandte Chemie, EarlyView.
MOF‐CAPodes are introduced by pairing various p‐MOFs with an n‐MOF as electrode materials in a battery‐like assembly. The devices achieve high figures of merit (RRI = 23.5; RRII = 94.4%) and perform excellently in prototypical logic gates (AND, OR) highlighting a new direction for ionological systems based on electroactive MOFs.
Tim Engelhardt, Leonid Shupletsov, Christin Gellrich, Cécilia Bauden, Przemyslaw Galek, Ahmed Bahrawy, Sonila Xhafa, Irena Senkovska, Julia Grothe, Stefan Kaskel   +9 more
wiley   +2 more sources