Index Catalog // MDR

Description/Abstract:: Overall, this roadmap originating from 20 groups in 11 countries serves as a gateway for both the experts and the beginners to have a qui...
Keyword:: density-functional theory, electrocatalysis, electrochemical energy storage, electrochemical interfaces, machine learning, and molecular dynamics simulation
Resource Type:: Article
Author:: Chao Zhang, Jun Cheng, Yiming Chen, Maria K Y Chan, Qiong Cai, Rodrigo P Carvalho, Cleber F N Marchiori, Daniel Brandell, C Moyses Araujo, Ming Chen, Xiangyu Ji, Guang Feng, Kateryna Goloviznina, Alessandra Serva, Mathieu Salanne, Toshihiko Mandai, Tomooki Hosaka, Mirna Alhanash, Patrik Johansson, Yun-Ze Qiu, Hai Xiao, Michael Eikerling, Ryosuke Jinnouchi, Marko M Melander, Georg Kastlunger, Assil Bouzid, Alfredo Pasquarello, Seung-Jae Shin, Minho M Kim, Hyungjun Kim, Kathleen Schwarz, and Ravishankar Sundararaman
Journal:: Journal of Physics-Energy
Date Uploaded:: 05/03/2024

Description/Abstract:: The automatic extraction of materials and related properties from the scientific literature is gaining attention in data-driven materials...
Keyword:: Materials informatics, NLP, TDM, machine learning, and superconductors
Resource Type:: Journal
Author:: Luca Foppiano, Pedro Baptista Castro, Pedro Ortiz Suarez, Kensei Terashima, Yoshihiko Takano, and Masashi Ishii
Journal:: SCIENCE AND TECHNOLOGY OF ADVANCED MATERIALS: METHODS
Date Uploaded:: 26/12/2023

Description/Abstract:: The prediction of electron inelastic mean free paths (IMFPs) from simple material parameters is a challenging problem in studies using el...
Keyword:: inelastic mean free path and machine learning
Resource Type:: Article
Author:: Xun Liu, Lihao Yang, Zhufeng Hou, Bo Da, Kenji Nagata, Hideki Yoshikawa, Shigeo Tanuma, Yang Sun, and Zejun Ding
Date Uploaded:: 11/04/2023

Description/Abstract:: We present a computational approach for identifying the important descriptors of the ionic conductivities of lithium solid electrolytes. ...
Keyword:: Ionic conductivity, machine learning, grain boundary, ionic conductor, Li battery, grain size, and descriptor
Resource Type:: Article
Author:: Yen-Ju Wu, Takehiro Tanaka, Tomoyuki Komori, Mikiya Fujii, Hiroshi Mizuno, Satoshi Itoh, Tadanobu Takada, Erina Fujita, and Yibin Xu
Date Uploaded:: 21/03/2023
Date Modified:: 23/03/2023

Description/Abstract:: For rapid and efficient development of new phosphors, a suitable method that proposes promising candidates is expected to focus time-cons...
Keyword:: Eu2+, emission spectrum, luminescence, machine learning, materials design, and phosphor
Resource Type:: Article
Author:: Yukinori Koyama, Hidekazu Ikeno, Masamichi Harada, Shiro Funahashi, Takashi Takeda, and Naoto Hirosaki
Date Uploaded:: 20/01/2023
Date Modified:: 25/03/2024

Description/Abstract:: The automatic extraction of materials and related properties from the scientific literature is gaining attention in data-driven materials...
Keyword:: tdm, machine learning, materials science, superconductors, and database
Resource Type:: Article
Author:: Foppiano Luca, Pedro Baptista de Castro, Pedro Ortiz Suarez, Kensei Terashima, Yoshihiko Takano, and Masashi Ishii
Date Uploaded:: 11/10/2022
Date Modified:: 08/11/2022

Description/Abstract:: We present Grobid-quantities, an open-source application for extracting and normalising measurements from scientific and patent literatur...
Keyword:: machine learning, physical quantities, and tdm
Resource Type:: Conference Proceeding
Author:: FOPPIANO, Luca, ROMARY, Laurent, ISHII, Masashi, and TANIFUJI, Mikiko
Journal:: DocEng '19: Proceedings of the ACM Symposium on Document Engineering 2019
Date Uploaded:: 15/01/2021
Date Modified:: 01/07/2021

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