{"id":"doi:10.1016/j.matpr.2020.10.091","kind":"article","title":"Prediction study on critical temperature (C) of different atomic numbers superconductors (both gaseous/solid elements) using machine learning techniques","authors":["G. Revathy","Velayutham Rajendran","P. Sathish Kumar"],"author_count":3,"year":2020,"published":"2020-11-17","venue":"Materials Today Proceedings","cited_by":7,"doi":"10.1016/j.matpr.2020.10.091","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.matpr.2020.10.091","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.matpr.2020.10.091","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W3101014691","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":[]}