{"id":1591,"date":"2019-04-24T14:24:00","date_gmt":"2019-04-24T17:24:00","guid":{"rendered":"http:\/\/cine.org.br\/new\/?page_id=1591"},"modified":"2021-04-08T12:03:13","modified_gmt":"2021-04-08T15:03:13","slug":"large-scale-analysis-of-material-properties-through-the-use-of-machine-learning","status":"publish","type":"page","link":"https:\/\/www.cine.org.br\/en\/computacional-material-science-chemistry\/large-scale-analysis-of-material-properties-through-the-use-of-machine-learning\/","title":{"rendered":"Large scale analysis of material properties through the use of machine learning"},"content":{"rendered":"<p><strong>Co-PI:<\/strong>\u00a0<a href=\"http:\/\/buscatextual.cnpq.br\/buscatextual\/visualizacv.do?id=K4766807T5\">Ronaldo Cristiano Prati<\/a>\u00a0\u2013 UFABC \u2013 ronaldo.prati@ufabc.edu.br<\/p>\n<p>The overall objective of this project is the development and application of machine learning algorithms and intelligent data analysis in large datasets of material properties, in property prediction tasks and discovery of knowledge that enable the screening of new materials on a large scale. For this, it is intended to apply these algorithms in public data repositories, as well as datasets collected from calculations of chemical-quantum properties performed by several members of the division.<\/p>\n<hr \/>\n<p><strong>Postdocs<\/strong><\/p>\n<p><a href=\"http:\/\/lattes.cnpq.br\/6047184744431931\">Marinalva Soares<\/a>\u00a0\u2013 UNIFESP<\/p>\n<hr \/>\n<p><strong>PhD Student<\/strong><\/p>\n<p><a href=\"http:\/\/lattes.cnpq.br\/6336353192848542\">Johnatan Mucelini\u00a0<\/a>\u2013 USP \u2013 Institute of Chemistry<\/p>\n<hr \/>\n<p><strong>MSc Student<\/strong><\/p>\n<p><a href=\"http:\/\/lattes.cnpq.br\/9338913733828557\">Luis Cesar Azevedo\u00a0<\/a>\u2013 UFABC<\/p>\n<hr \/>\n<p><strong>Scientific Initiation Student<\/strong><\/p>\n<p><a href=\"http:\/\/lattes.cnpq.br\/9338913733828557\">Danielle Lopes\u00a0<\/a>\u2013 ICMC \u2013 Institute of Mathematical and Computer Sciences<br \/>\n<a href=\"http:\/\/lattes.cnpq.br\/3355654720514392\">Felipe Calderan<\/a>\u00a0&#8211; UNIFESP &#8211; Science and Technology Institute<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Co-PI:\u00a0Ronaldo Cristiano Prati\u00a0\u2013 UFABC \u2013 ronaldo.prati@ufabc.edu.br The overall objective of this project is the development and application of machine learning algorithms and intelligent data analysis in large datasets of material properties, in property prediction tasks and discovery of knowledge that enable the screening of new materials on a large scale. For this, it is intended to apply these algorithms in public data repositories, as well as datasets collected from calculations&#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":1028,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"general_template.php","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"acf":[],"_links":{"self":[{"href":"https:\/\/www.cine.org.br\/en\/wp-json\/wp\/v2\/pages\/1591"}],"collection":[{"href":"https:\/\/www.cine.org.br\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.cine.org.br\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.cine.org.br\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cine.org.br\/en\/wp-json\/wp\/v2\/comments?post=1591"}],"version-history":[{"count":6,"href":"https:\/\/www.cine.org.br\/en\/wp-json\/wp\/v2\/pages\/1591\/revisions"}],"predecessor-version":[{"id":3445,"href":"https:\/\/www.cine.org.br\/en\/wp-json\/wp\/v2\/pages\/1591\/revisions\/3445"}],"up":[{"embeddable":true,"href":"https:\/\/www.cine.org.br\/en\/wp-json\/wp\/v2\/pages\/1028"}],"wp:attachment":[{"href":"https:\/\/www.cine.org.br\/en\/wp-json\/wp\/v2\/media?parent=1591"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}