Product
Help
Pricing
About
Jobs
Log in
Get started
Author
Add to collection
Erina Fujita
Observed name:
Fujita, Erina
Institution:
Research Organization of Information and Systems
Observed institutions:
National Institute for Materials Science,
The Institute of Statistical Mathematics,
Research Organization of Information and Systems,
The University of Tokyo
ORCID:
0000-0002-0987-5597
Observed ORCID:
0000-0002-0987-5597
OpenAlex ID:
A5078339827
Machine Learning to Predict Quasicrystals from Chemical Compositions
2021
·
Chang Liu
, Erina Fujita
, et al.
·
Advanced Materials
·
65
Starrydata: from published plots to shared materials data
2025
·
Yukari Katsura
, Masaya Kumagai
, et al.
·
Science and Technology of Advanced Materials Methods
·
22
Quasicrystals predicted and discovered by machine learning
2023
·
Chang Liu
, Koichi Kitahara
, et al.
·
Physical Review Materials
·
18
PDF
Comprehensive experimental datasets of quasicrystals and their approximants
2024
·
Erina Fujita
, Chang Liu
, et al.
·
Scientific Data
·
15
Omics-scale polymer computational database transferable to real-world artificial intelligence applications
2025
·
Yoshida, Ryo
, Hayashi, Yoshihiro
, et al.
·
arXiv (Cornell University)
·
12
PDF
Essential structural and experimental descriptors for bulk and grain boundary conductivities of Li solid electrolytes
2020
·
Yen-Ju Wu
, Takehiro Tanaka
, et al.
·
Science and Technology of Advanced Materials
·
11
PDF
Machine Learning to Predict Quasicrystals from Chemical Compositions (Adv. Mater. 36/2021)
2021
·
Chang Liu
, Erina Fujita
, et al.
·
Advanced Materials
·
3
PDF
Innovations and tasks brought by storage and sharing of experimental data in literature
2021
·
Yukari Katsura
, Masaya Kumagai
, et al.
·
The Japan Society of Applied Physics
Establishment of dataset for machine learning of physical properties of quasicrystals and their approximants
2021
·
Erina Fujita
, Yukari Katsura
, et al.
·
The Japan Society of Applied Physics
Show more works
View as search
Works count:
10
Citation count:
147
H-index:
6
I10-index:
6
Year
Topic
Type