Results 181 to 190 of about 22,028,757 (282)

A Critical Assessment of Bonding Descriptors for Predicting Materials Properties

open access: yesAdvanced Intelligent Discovery, EarlyView.
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik   +6 more
wiley   +1 more source

Multimodal Learning with Rashomon Analysis for Battery Discharge Capacity Prediction

open access: yesAdvanced Intelligent Discovery, EarlyView.
Multimodal fusion integrates composition, crystal‐structure, and radial‐distribution descriptors to predict battery discharge capacity. Rashomon analysis across near‐optimal models reveals that explanatory variation is structured rather than arbitrary, separating stable mechanistic signals from model‐contingent attributions and providing a more ...
Jue Gong   +4 more
wiley   +1 more source

Accelerating the Discovery of Proton Conducting Electrolytes via Machine Learning‐Enabled Literature Mining

open access: yesAdvanced Intelligent Discovery, EarlyView.
An end‐to‐end knowledge discovery framework is established to automate high‐precision property extraction from small, specialized literature corpora. Utilizing a domain‐specific bidirectional encoder representation from a transformer model and data augmentation, the system accurately extracts and structures electrolyte performance data, ultimately ...
Gaheun Shin   +4 more
wiley   +1 more source

Multiscale and Multi‐Timestep Switching of Multiple Machine Learning Force Fields for Artificial Intelligence‐Driven Materials Simulations

open access: yesAdvanced Intelligent Discovery, EarlyView.
Deep Potential model switching accelerates molecular dynamics by using a faster 4 Å model for most timesteps and periodically applying a high‐accuracy 6 Å model. Validation on solid TiO2 and liquid PEG shows preserved RDF correlations and stable NPT behavior, while NVE energy‐drift analyses identify cases requiring additional validation.
Ryuya Kanda   +6 more
wiley   +1 more source

Robot‐Assisted Measurement of the Critical Micelle Concentration

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The study introduces (SIMO) smart integrator for manual operations, a robotic platform for precise, repeatable determination of (CMC) critical micelle concentration in surfactants. SIMO reduces standard deviation by 80% compared to manual methods. Surfactant, dye, and diluent selection, robotic protocols, and data handling are detailed.
Vincenzo Scamarcio   +3 more
wiley   +1 more source

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