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machine learning
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2023 Roadmap on molecular modelling of electrochemical energy materials
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
Automatic extraction of materials and properties from superconductors scientific literature
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
Machine learning approach for the prediction of electron inelastic mean free paths
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
Essential structural and experimental descriptors for bulk and grain boundary conductivities of Li solid electrolytes
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
Rapid discovery of new Eu2+-activated phosphors with a designed luminescence color using a data-driven approach
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
Automatic Extraction of Materials and Properties from Superconductors Scientific Literature
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
Automatic Identification and Normalisation of Physical Measurements in Scientific Literature
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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