OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!
If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.
Requested Article:
SuperMat: construction of a linked annotated dataset from superconductors-related publications
Luca Foppiano, Sae Dieb, Akira Suzuki, et al.
Science and Technology of Advanced Materials Methods (2021) Vol. 1, Iss. 1, pp. 34-44
Open Access | Times Cited: 13
Luca Foppiano, Sae Dieb, Akira Suzuki, et al.
Science and Technology of Advanced Materials Methods (2021) Vol. 1, Iss. 1, pp. 34-44
Open Access | Times Cited: 13
Showing 13 citing articles:
Mining experimental data from materials science literature with large language models: an evaluation study
Luca Foppiano, G. Lambard, Toshiyuki Amagasa, et al.
Science and Technology of Advanced Materials Methods (2024) Vol. 4, Iss. 1
Open Access | Times Cited: 5
Luca Foppiano, G. Lambard, Toshiyuki Amagasa, et al.
Science and Technology of Advanced Materials Methods (2024) Vol. 4, Iss. 1
Open Access | Times Cited: 5
Probe microscopy is all you need *
Sergei V. Kalinin, Rama K. Vasudevan, Yongtao Liu, et al.
Machine Learning Science and Technology (2023) Vol. 4, Iss. 2, pp. 023001-023001
Open Access | Times Cited: 11
Sergei V. Kalinin, Rama K. Vasudevan, Yongtao Liu, et al.
Machine Learning Science and Technology (2023) Vol. 4, Iss. 2, pp. 023001-023001
Open Access | Times Cited: 11
3DSC - a dataset of superconductors including crystal structures
Timo Sommer, Roland Willa, Jörg Schmalian, et al.
Scientific Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 9
Timo Sommer, Roland Willa, Jörg Schmalian, et al.
Scientific Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 9
Automatic extraction of materials and properties from superconductors scientific literature
Luca Foppiano, Pedro Baptista de Castro, Pedro Ortiz Suarez, et al.
Science and Technology of Advanced Materials Methods (2022) Vol. 3, Iss. 1
Open Access | Times Cited: 12
Luca Foppiano, Pedro Baptista de Castro, Pedro Ortiz Suarez, et al.
Science and Technology of Advanced Materials Methods (2022) Vol. 3, Iss. 1
Open Access | Times Cited: 12
XERUS: An Open‐Source Tool for Quick XRD Phase Identification and Refinement Automation
Pedro Baptista de Castro, Kensei Terashima, Miren Garbiñe Esparza Echevarría, et al.
Advanced Theory and Simulations (2022) Vol. 5, Iss. 5
Open Access | Times Cited: 8
Pedro Baptista de Castro, Kensei Terashima, Miren Garbiñe Esparza Echevarría, et al.
Advanced Theory and Simulations (2022) Vol. 5, Iss. 5
Open Access | Times Cited: 8
Structuring superconductor data with ontology: reproducing historical datasets as knowledge bases
Masashi Ishii, Koichi Sakamoto
Science and Technology of Advanced Materials Methods (2023) Vol. 3, Iss. 1
Open Access | Times Cited: 4
Masashi Ishii, Koichi Sakamoto
Science and Technology of Advanced Materials Methods (2023) Vol. 3, Iss. 1
Open Access | Times Cited: 4
Machine Learning Accelerated Design of High-Temperature Ternary and Quaternary Nitride Superconductors
Md Tohidul Islam, Qinrui Liu, Scott Broderick
Applied Sciences (2024) Vol. 14, Iss. 20, pp. 9196-9196
Open Access | Times Cited: 1
Md Tohidul Islam, Qinrui Liu, Scott Broderick
Applied Sciences (2024) Vol. 14, Iss. 20, pp. 9196-9196
Open Access | Times Cited: 1
Superconductor Discovery in the Emerging Paradigm of Materials Informatics
Tran Doan Huan, Dam Hieu, Christopher Künneth, et al.
Chemistry of Materials (2024) Vol. 36, Iss. 22, pp. 10939-10966
Open Access | Times Cited: 1
Tran Doan Huan, Dam Hieu, Christopher Künneth, et al.
Chemistry of Materials (2024) Vol. 36, Iss. 22, pp. 10939-10966
Open Access | Times Cited: 1
Semi-automatic staging area for high-quality structured data extraction from scientific literature
Luca Foppiano, Tomoya MATO, Kensei Terashima, et al.
Science and Technology of Advanced Materials Methods (2023) Vol. 3, Iss. 1
Open Access | Times Cited: 2
Luca Foppiano, Tomoya MATO, Kensei Terashima, et al.
Science and Technology of Advanced Materials Methods (2023) Vol. 3, Iss. 1
Open Access | Times Cited: 2
Mining experimental data from Materials Science literature with Large Language Models
Luca Foppiano, G. Lambard, Toshiyuki Amagasa, et al.
arXiv (Cornell University) (2024)
Open Access
Luca Foppiano, G. Lambard, Toshiyuki Amagasa, et al.
arXiv (Cornell University) (2024)
Open Access
Integrating machine learning with advanced processing and characterization for polycrystalline materials: a methodology review and application to Iron-based Supercon.Ductors
Akiyasu Yamamoto, Akinori Yamanaka, K. Iida, et al.
Science and Technology of Advanced Materials (2024) Vol. 26, Iss. 1
Open Access
Akiyasu Yamamoto, Akinori Yamanaka, K. Iida, et al.
Science and Technology of Advanced Materials (2024) Vol. 26, Iss. 1
Open Access
Superconductivity information extraction from the literature: A new corpus and its evaluations
Kyosuke Yamaguchi, Ryoji Asahi, Yutaka Sasaki
Advanced Engineering Informatics (2022) Vol. 54, pp. 101768-101768
Open Access | Times Cited: 2
Kyosuke Yamaguchi, Ryoji Asahi, Yutaka Sasaki
Advanced Engineering Informatics (2022) Vol. 54, pp. 101768-101768
Open Access | Times Cited: 2
Semi-automatic staging area for high-quality structured data extraction from scientific literature
Luca Foppiano, Tomoya MATO, Kensei Terashima, et al.
arXiv (Cornell University) (2023)
Open Access
Luca Foppiano, Tomoya MATO, Kensei Terashima, et al.
arXiv (Cornell University) (2023)
Open Access
