A5068716992- Machine Learning in Materials Science
- Advancements in Battery Materials
- Advanced Battery Technologies Research
- Electronic and Structural Properties of Oxides
- Electron and X-Ray Spectroscopy Techniques
- Advanced Battery Materials and Technologies
Korea Advanced Institute of Science and Technology
2021-2024
Optimizing synthesis parameters is crucial in fabricating an ideal cathode material; however, the design space too vast to be fully explored using Edisonian approach. Here, by clustering eleven domain-expert-derived-descriptors from literature, we use inverse surrogate model build up experimental parameters-property relationship. Without struggling with trial-and-error method, enables variables prediction that serves as effective strategy for retrosynthesis. More importantly, not only did...
Despite their low redox potential and high specific capacity, lithium (Li) metal anodes pose stability safety issues, especially in commercial carbonate-based electrolytes, due to dendritic growth of Li formation unstable solid-electrolyte interphase (SEI). To address these, we adopted AgNO3 as an electrolyte additive electrolyte. Given that has solubility carbonate developed a porous film made silver nitrate (AgNO3)-containing polyacrylonitrile (PAN) nanofibers (AgNO3/PAN) enabling the...
Multiscale and multimodal imaging of material structures properties provides solid ground on which materials theory design can flourish. Recently, KAIST announced 10 flagship research fields, include Materials Revolution: Molecular Modeling, Imaging, Informatics Integration (M3I3). The M3I3 initiative aims to reduce the time for discovery, development based elucidating multiscale processing–structure–property relationship hierarchy, are be quantified understood through a combination machine...
Optimizing synthesis parameters is crucial in fabricating an ideal cathode material; however, the design space too vast to be fully explored using Edisonian approach. Here, by clustering eleven domain-expert-derived-descriptors from literature, we use inverse surrogate model build up experimental parameters-property relationship. Without struggling with trial-and-error method, enables variables prediction that serves as effective strategy for retrosynthesis. More importantly, not only did...