{"id":"doi:10.1021/acsami.4c11997","kind":"article","title":"Enhancing Superconductor Critical Temperature Prediction: A Novel Machine Learning Approach Integrating Dopant Recognition","authors":["Chengquan Zhong","Yuelin Wang","Yanwu Long","Jiakai Liu","Kailong Hu","Jingzi Zhang","Junjie Chen","Xi Lin"],"author_count":8,"year":2024,"published":"2024-10-25","venue":"ACS Applied Materials & Interfaces","cited_by":6,"doi":"10.1021/acsami.4c11997","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1021/acsami.4c11997","archive_url":"https://space-kitty.com/papers/doi:10.1021/acsami.4c11997","updated":null,"pmid":"39453724","pmcid":null,"openalex_id":"W4403761383","pdf_url":null,"abstract":null,"abstract_license":null,"license":null,"is_open_access":false,"retracted":false,"peer_reviewed":null,"categories":["Machine Learning in Materials Science"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0).","topics":[{"slug":"superconductor-discovery","name":"Computational & AI-Driven Superconductor Discovery","domain_slug":"superconductivity"}],"cited_in_dossiers":[]}