{"id":6636,"date":"2026-07-16T15:00:05","date_gmt":"2026-07-16T06:00:05","guid":{"rendered":"https:\/\/www-dsc.naist.jp\/dsc_naist\/?p=6636"},"modified":"2026-08-06T14:54:56","modified_gmt":"2026-08-06T05:54:56","slug":"dsc-internal-talk-in-july2026","status":"publish","type":"post","link":"https:\/\/www-dsc.naist.jp\/dsc_naist\/en\/dsc-internal-talk-in-july2026\/","title":{"rendered":"DSC internal talk in July"},"content":{"rendered":"<p>Prof. Mikiya Fujii gave a lecture in July.<\/p>\n<p>The details are as follows.<\/p>\n<p>====================<\/p>\n<p>Prof. Mikiya Fujii (Materials Informatics Laboratory)<\/p>\n<p>TITLE:<br \/>\nAnalysis of Variability Factors in Low-Cost Automated Chemical Experiments<\/p>\n<p>ABSTRACT\uff1a<\/p>\n<p>Low-cost automated chemical experiment systems are attractive because of their accessibility, but limited control precision often leads to large experimental variability. In this study, we analyzed variability factors in an automated system for titanium oxide thin-film fabrication using heteroscedastic Gaussian process regression. The analysis identified factors related to both performance improvement and variability increase, and suggested that spatial inhomogeneity is one of the major sources of variability in the system.<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n<div class=\"block-list-appender wp-block\" tabindex=\"-1\" contenteditable=\"false\" data-block=\"true\">\n<div class=\"block-editor-default-block-appender\" data-root-client-id=\"\">\n<p class=\"block-editor-default-block-appender__content\" tabindex=\"0\" role=\"button\" aria-label=\"\u30c7\u30d5\u30a9\u30eb\u30c8\u30d6\u30ed\u30c3\u30af\u3092\u8ffd\u52a0\">\u00a0<\/p>\n<\/div>\n<\/div>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Prof. Mikiya Fujii gave a lecture in July. The details are as follows. ==================== Prof. Mikiya Fujii (Materials Informatics Laboratory) TITLE: Analysis of Variability Factors in Low-Cost Automated Chemical Experiments ABSTRACT\uff1a Low-cost automated chemical experiment systems are attractive because of their accessibility, but limited control precision often leads to large experimental variability. In this study, [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_locale":"en_US","_original_post":"https:\/\/www-dsc.naist.jp\/dsc_naist\/?p=6633","_links_to":"","_links_to_target":""},"categories":[3],"tags":[],"event_taxonomy":[15],"acf":[],"_links":{"self":[{"href":"https:\/\/www-dsc.naist.jp\/dsc_naist\/wp-json\/wp\/v2\/posts\/6636"}],"collection":[{"href":"https:\/\/www-dsc.naist.jp\/dsc_naist\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www-dsc.naist.jp\/dsc_naist\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www-dsc.naist.jp\/dsc_naist\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www-dsc.naist.jp\/dsc_naist\/wp-json\/wp\/v2\/comments?post=6636"}],"version-history":[{"count":3,"href":"https:\/\/www-dsc.naist.jp\/dsc_naist\/wp-json\/wp\/v2\/posts\/6636\/revisions"}],"predecessor-version":[{"id":6642,"href":"https:\/\/www-dsc.naist.jp\/dsc_naist\/wp-json\/wp\/v2\/posts\/6636\/revisions\/6642"}],"wp:attachment":[{"href":"https:\/\/www-dsc.naist.jp\/dsc_naist\/wp-json\/wp\/v2\/media?parent=6636"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www-dsc.naist.jp\/dsc_naist\/wp-json\/wp\/v2\/categories?post=6636"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www-dsc.naist.jp\/dsc_naist\/wp-json\/wp\/v2\/tags?post=6636"},{"taxonomy":"event_taxonomy","embeddable":true,"href":"https:\/\/www-dsc.naist.jp\/dsc_naist\/wp-json\/wp\/v2\/event_taxonomy?post=6636"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}