Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Sasaank Bandi"'
Publikováno v:
Machine Learning: Science and Technology, Vol 5, Iss 3, p 030502 (2024)
Machine learning approaches have recently emerged as powerful tools to probe structure-property relationships in crystals and molecules. Specifically, machine learning interatomic potentials (MLIPs) can accurately reproduce first-principles data at a
Externí odkaz:
https://doaj.org/article/6f1f42b032e745f98fe74f037452826a
Autor:
Sasaank Bandi, C. A. Marianetti
Computing phonons from first-principles is typically considered a solved problem, yet inadequacies in existing techniques continue to yield deficient results in systems with sensitive phonons. Here we circumvent this issue using the lone irreducible
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::09627572133ffe58e58eb5e79ed947e0
http://arxiv.org/abs/2210.15636
http://arxiv.org/abs/2210.15636
Autor:
Nandita Das, Salvador Carrillo Moreno, Dong Qian, Ray H. Baughman, Mahmoud Baniasadi, Zhe Xu, Julia Bykova, Zhong Zhou, Yang Xi, Sasaank Bandi, Majid Minary-Jolandan
Publikováno v:
Advanced Engineering Materials. 19:1600570
Hybrid materials of inorganic–organic phases in which each phase provides different functionality are attractive candidates for achieving multifunctionality. Using a layer-by-layer approach, we fabricated sheets of piezoelectric polymer P(VDF-TrFE)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::711465968996582c71993deb418fee0b
https://doi.org/10.1002/adem.201600570
https://doi.org/10.1002/adem.201600570