Results 221 to 230 of about 100,154 (263)

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

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

Multifunctional Matrix‐Activated Electrodes Enabling Efficient Proton Transport and Durable Low‐Pt Operation for High‐Temperature Proton Exchange Membrane Fuel Cells

Advanced Energy Materials, EarlyView.
This work introduces a CeHP‐enabled multifunctional matrix‐activated electrode (MME) for high‐temperature PEM fuel cells, forming an electrochemically and mechanically functional matrix within the catalyst layer. The design increases peak power density by 38% and reduces voltage decay by 62% at 240 °C, while using only 40% of the Pt loading of a ...
Gyeongseok Gwak, Sunjin Park, Joonbyum Kim, Hena Lee, Jihyeon Ok, Chae Young Lee, JunHwa Kwon, Jong Geun Seong, Sung Pil Yoon, Suk‐Woo Nam, Hansung Kim, Katie Heeyum Lim, So Young Lee   +12 more
wiley   +1 more source

Nanocrystalline LCO/LLZO Composite Cathode Films for Solid State Batteries

Advanced Energy Materials, EarlyView.
A single precursor solution is solution‐deposited and calcined at only 750°C to yield a dense, nanograined LiCoO2/LLZO composite cathode, in which both phases crystallize independently with minimal interdiffusion. Assembled into all‐solid‐state Li‐metal batteries, the composite delivers 111.7 mAh g−1 initial discharge capacity and retains 93% after 100
Lucie Quincke, Steffen Weinmann, Jesse J. Hinricher, Matteo Galasso, Chiara Althammer, Fran Kurnia, Kun Joong Kim, Wolff‐Ragnar Kiebach, Jennifer L. M. Rupp   +8 more
wiley   +1 more source

Temporary Programs, Lasting Questions: Ad Hoc Assistance in the U.S. Farm Safety Net

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT Large ad hoc assistance programs have returned to U.S. farm policy since 2017, operating alongside a more developed safety net built around federally subsidized crop insurance, Title I commodity programs, and standing disaster assistance. This paper reviews the renewed use of ad hoc assistance, documents its recent scale using USDA data, and ...
Alejandro Plastina, Oranuch Wongpiyabovorn   +1 more
wiley   +1 more source

Accelerating Primary Screening of USP8 Inhibitors from Drug Repurposing Databases with Tree‐Based Machine Learning

Advanced Intelligent Discovery, EarlyView.
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng, Sharon Ai Er Lam, Wei Chun Lim, Hannah Hui Min Toh, Shi Jun Ang   +4 more
wiley   +1 more source

Computer Vision Pipeline for Image Analysis for Freeze‐Fracture Electron Microscopy: Rosette Cellulose Synthase Complexes Case

Advanced Intelligent Discovery, EarlyView.
This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri, Leala Carbonneau, Eric M. Roberts, Alison W. Roberts, Candace H. Haigler, Alexey V. Gulyuk, Yaroslava G. Yingling   +6 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

Taguchi–Bayesian Sampling: A Roadmap for Polymer Database Construction Toward Small Representative Machine Learning

Advanced Intelligent Discovery, EarlyView.
This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley   +1 more source

Real‐Time Multicolor Fluorescence Microscopy via Cross‐Channel Acquisition and Deep‐Learning‐Based Inference

Advanced Intelligent Discovery, EarlyView.
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto, Yuxin Jin, Nicholas Roy, Sarthak Misra   +3 more
wiley   +1 more source