Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design
Advanced Science, EarlyView.A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram +4 more
wiley +1 more source
Seizure detection using hierarchical temporal trend integration and self-supervised learning. [PDF]
Sci RepR NA, K SB.
europepmc +1 more source
Advanced Science, EarlyView.A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou +3 more
wiley +1 more source
Advancing morphological profiling with self-supervised learning through comparative insights into representation learning of cellular perturbations. [PDF]
Nat MethodsAbdelmoula WM +8 more
europepmc +1 more source
Advanced Science, EarlyView.Multiferroic order parameters – polarization, magnetization, and ferroelastic strain – are positioned as dynamic design variables for batteries. Their mechanistic roles, practical tuning through fabrication and external fields, and ferroic‐resolved characterization routes are unified into a closed‐loop framework, revealing how coupled ferroic responses
Jiaqi Su +13 more
wiley +1 more source
WAVE: Wall-Aligned Vector Embedding for Self-Supervised Learning of Electrocardiograms. [PDF]
Bioengineering (Basel)Pan S, Liu W, Wu Q, Wang C, Yuan Z.
europepmc +1 more source
Physics‐Informed Neural Network‐Enabled Forward Prediction and Inverse Design of Ring Origami
Advanced Science, EarlyView.This work presents a KRT‐PINN framework that integrates Kirchhoff rod theory with physics‐informed neural networks for the forward prediction and inverse design of ring origami consisting of closed‐loop rods. The framework predicts stable states of segmented rings with prescribed natural‐curvature profiles and determines the natural‐curvature profiles ...
Luyuan Ning +3 more
wiley +1 more source
Learning robust and task-invariant functional representation from fMRI through Siamese self-supervised learning. [PDF]
Med Image AnalWang J +6 more
europepmc +1 more source
Advanced Science, EarlyView.A pneumatically actuated multi‐tissue microphysiological system is integrated with AI‐based machine vision and automatic sampling and replenishment systems. The platform allows for the emulation of translationally relevant long‐term pharmacokinetic exposure scenarios for multiple weeks while enabling longitudinal monitoring of response biomarkers ...
Jibbe Keulen +15 more
wiley +1 more source
UNSURE: self-supervised learning with Unknown Noise level and Stein's Unbiased Risk Estimate
Recently, many self-supervised learning methods for image reconstruction have been proposed that can learn from noisy data alone, bypassing the need for ground-truth references.
13th International Conference on Learning Representations (ICLR 2025) +3 more
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