{"_buckets": {"deposit": "ee6f1c28-dd65-44da-a2dd-056c20f5e31a"}, "_deposit": {"created_by": 17, "id": "2004227", "owner": "17", "owners": [17], "owners_ext": {"displayname": "repository", "username": "repository"}, "pid": {"revision_id": 0, "type": "depid", "value": "2004227"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:02004227", "sets": []}, "author_link": [], "control_number": "2004227", "item_1615768549627": {"attribute_name": "出版タイプ", "attribute_value_mlt": [{"subitem_version_resource": "http://purl.org/coar/version/c_ab4af688f83e57aa", "subitem_version_type": "AM"}]}, "item_1629683748249": {"attribute_name": "日付", "attribute_value_mlt": [{"subitem_date_issued_datetime": "2023-09-01", "subitem_date_issued_type": "Available"}]}, "item_9_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2022-09", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "9", "bibliographicPageStart": "2200302", "bibliographicVolumeNumber": "5", "bibliographic_titles": [{"bibliographic_title": "Advanced Theory and Simulations", "bibliographic_titleLang": "en"}]}]}, "item_9_description_4": {"attribute_name": "内容記述", "attribute_value_mlt": [{"subitem_description": "The macroscopic distribution of fluid flows, which affect the quality of final products for various kinds of materials, is often difficult to describe in mathematical formulae and hinders the implementation of empirical knowledge in scaling up. In the present study, the characteristics of the flow distribution in silicon carbide (SiC) solution growth are described by using the position of the saddle point and the solution growth conditions are optimized by computational fluid dynamics simulation, machine learning, and a genetic algorithm. As a result, the candidates of the optimal condition for the solution growth of 6-in. SiC crystals are successfully obtained from the empirical knowledge gained from 3-in. crystal growth, by adding the topological description to the objective function. The present design of the objective function using the topological description can possibly be applied to other crystal growth or materials processing problems and to overcome scale-up difficulties, which can facilitate the rapid development of functional materials such as SiC wafers for power device applications.", "subitem_description_language": "en", "subitem_description_type": "Abstract"}]}, "item_9_publisher_32": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "Wiley", "subitem_publisher_language": "en"}]}, "item_9_relation_43": {"attribute_name": "関連情報", "attribute_value_mlt": [{"subitem_relation_type": "isVersionOf", "subitem_relation_type_id": {"subitem_relation_type_id_text": "https://doi.org/10.1002/adts.202200302", "subitem_relation_type_select": "DOI"}}]}, "item_9_rights_12": {"attribute_name": "権利", "attribute_value_mlt": [{"subitem_rights": "\"This is the peer reviewed version of the following article: [ Isono, M., Harada, S., Kutsukake, K., Yokoyama, T., Tagawa, M., Ujihara, T., Optimization of Flow Distribution by Topological Description and Machine Learning in Solution Growth of SiC. Adv. Theory Simul. 2022, 5, 2200302. https://doi.org/10.1002/adts.202200302], which has been published in final form at [https://doi.org/10.1002/adts.202200302]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.\"", "subitem_rights_language": "en"}]}, "item_9_source_id_7": {"attribute_name": "収録物識別子", "attribute_value_mlt": [{"subitem_source_identifier": "2513-0390", "subitem_source_identifier_type": "PISSN"}]}, "item_access_right": {"attribute_name": "アクセス権", "attribute_value_mlt": [{"subitem_access_right": "embargoed access", "subitem_access_right_uri": "http://purl.org/coar/access_right/c_f1cf"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Isono, Masaru", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Harada, Shunta", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Kutsukake, Kentaro", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Yokoyama, Tomoo", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Tagawa, Miho", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Ujihara, Toru", "creatorNameLang": "en"}]}]}, "item_files": {"attribute_name": "ファイル情報", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2023-09-01"}], "displaytype": "detail", "download_preview_message": "Download / Preview is available from 2023/8/31.", "file_order": 0, "filename": "SH220609_rev2.pdf", "filesize": [{"value": "2.3 MB"}], "format": "application/pdf", "future_date_message": "Download is available from 2023/8/31.", "is_thumbnail": false, "mimetype": "application/pdf", "size": 2300000.0, "url": {"objectType": "fulltext", "url": "https://nagoya.repo.nii.ac.jp/record/2004227/files/SH220609_rev2.pdf"}, "version_id": "e546e22c-5a24-4be1-b307-189989380f29"}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_resource_type": {"attribute_name": "資源タイプ", "attribute_value_mlt": [{"resourcetype": "journal article", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_title": "Optimization of Flow Distribution by Topological Description and Machine Learning in Solution Growth of SiC", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "Optimization of Flow Distribution by Topological Description and Machine Learning in Solution Growth of SiC", "subitem_title_language": "en"}]}, "item_type_id": "40001", "owner": "17", "path": ["675"], "permalink_uri": "http://hdl.handle.net/2237/0002004227", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2022-11-29"}, "publish_date": "2022-11-29", "publish_status": "0", "recid": "2004227", "relation": {}, "relation_version_is_last": true, "title": ["Optimization of Flow Distribution by Topological Description and Machine Learning in Solution Growth of SiC"], "weko_shared_id": -1}