Results 211 to 220 of about 22,674 (253)

Advancing Gastrointestinal Cancer Risk Prediction With Patient-Centered Machine Learning: Machine Learning Modeling Study. [PDF]

JMIR Med Inform
Baublyte D, Lee J, Gunathilake M, Kim J.
europepmc   +1 more source

Scan‐Path‐ and Initial‐State‐Dependent Superdomain Switching in (111)‐Oriented PZT

Advanced Electronic Materials, EarlyView.
Scan trajectory and initial superdomain topology govern polarization switching in (111)‐oriented PZT. Automated AFM writing, pulsing experiments, and interferometric 3D‐PFM show that raster scans reproducibly stabilize ordered Type‐I stripe superdomains with constrained variant selection, whereas spiral trajectories generate frustrated mixed‐variant ...
Rama Vasudevan, Laveeza Ahmad, Bharat Pant, Ralph Bulanadi, Asraful Haque, Puneet Kaur, Sabine Neumayer, Jan‐Chi Yang, Yongtao Liu, Ye Cao, Stephen Jesse, Marti Checa   +11 more
wiley   +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

Evaluating machine learning algorithms at predicting developmental trajectories using sequential dataset truncation of voluntary alcohol consumption in adolescent mice. [PDF]

PLoS One
Yu N, Buyske S, Qureshi U, Yu L.
europepmc   +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

Adaptive Path Integral Diffusion: AdaPID. [PDF]

Entropy (Basel)
Chertkov M, Behjoo H.
europepmc   +1 more source

Nickel‐Free Synthesis of Poly(pyrene‐4,5,9,10‐tetraone) for Sodium‐based Batteries: Insights into Electrode Architecture and Reversible Na‐ion Insertion

Advanced Energy Materials, EarlyView.
A nickel‐free and practical synthesis strategy to poly(pyrene tetraone) and its integration with a percolated CNTs/Ketjen Black network enables stable cycling and efficient energy storage in a sodium‐based batteries. This work demonstrates how controlling polymer structure and electrode architecture improves ion transport and mitigates dissolution in ...
Md. Adil, Robin Wessling, Nico Kokott, Elena Mena‐Osteritz, Benedikt Prifling, Markus Osenberg, Thomas Diemant, Volker Schmidt, Ingo Manke, Birgit Esser   +9 more
wiley   +1 more source

Population-based variance-reduced evolution over stochastic landscapes. [PDF]

Sci Rep
Pei Z, He X, Pan Y, Peng B, Chen W, Zhou Y.   +5 more
europepmc   +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