Novel environment-friendly insulating gas molecule screening method based on deep learning

The invention discloses a novel environment-friendly insulating gas molecule screening method based on deep learning. The novel environment-friendly insulating gas molecule screening method comprises the following steps: establishing a basic library of known gas molecule electrical environment-frien...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: ZHU TAIYUN, ZHU SHAN, LIU WEI, DONG WANGCHAO, YU DENGYANG, XU XIAOXIAO, XU ZHENGJIE, SONG YUMEI, HANG CHEN, MA FENGXIANG, CAO JUN
Format: Patent
Sprache:chi ; eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume
creator ZHU TAIYUN
ZHU SHAN
LIU WEI
DONG WANGCHAO
YU DENGYANG
XU XIAOXIAO
XU ZHENGJIE
SONG YUMEI
HANG CHEN
MA FENGXIANG
CAO JUN
description The invention discloses a novel environment-friendly insulating gas molecule screening method based on deep learning. The novel environment-friendly insulating gas molecule screening method comprises the following steps: establishing a basic library of known gas molecule electrical environment-friendly properties; representing the gas molecules in the basic library by molecular descriptors to generate a molecular data matrix, and dividing the matrix into a training library and a test library; a deep learning model is built, the training library is used for training the deep learning model, and the test library tests the prediction precision of the trained deep learning model until the optimal deep learning model is obtained; generating new small molecular structures in batches from the gas molecules in the basic library through a functional group replacement method, and forming a gas molecule target library; adopting the optimal deep learning model to screen gas molecules in the gas molecule target library, a
format Patent
fullrecord <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN117669342A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN117669342A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN117669342A3</originalsourceid><addsrcrecordid>eNqNirEKwjAURbs4iPoPzw_oUCsVRymKUycnlxKT2xp4eQlJWvDvpeAHOB0456yLZ-dnMEFmG704SC6HaCGGP2QlTayylZFGlch5hp4YlHQEZNEO-e0NvVSCIS9kgEAMFZe6LVaD4oTdj5tif7s-2nuJ4HukoDQEuW-7qjo1zbk-Hi71P88Xin07qg</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Novel environment-friendly insulating gas molecule screening method based on deep learning</title><source>esp@cenet</source><creator>ZHU TAIYUN ; ZHU SHAN ; LIU WEI ; DONG WANGCHAO ; YU DENGYANG ; XU XIAOXIAO ; XU ZHENGJIE ; SONG YUMEI ; HANG CHEN ; MA FENGXIANG ; CAO JUN</creator><creatorcontrib>ZHU TAIYUN ; ZHU SHAN ; LIU WEI ; DONG WANGCHAO ; YU DENGYANG ; XU XIAOXIAO ; XU ZHENGJIE ; SONG YUMEI ; HANG CHEN ; MA FENGXIANG ; CAO JUN</creatorcontrib><description>The invention discloses a novel environment-friendly insulating gas molecule screening method based on deep learning. The novel environment-friendly insulating gas molecule screening method comprises the following steps: establishing a basic library of known gas molecule electrical environment-friendly properties; representing the gas molecules in the basic library by molecular descriptors to generate a molecular data matrix, and dividing the matrix into a training library and a test library; a deep learning model is built, the training library is used for training the deep learning model, and the test library tests the prediction precision of the trained deep learning model until the optimal deep learning model is obtained; generating new small molecular structures in batches from the gas molecules in the basic library through a functional group replacement method, and forming a gas molecule target library; adopting the optimal deep learning model to screen gas molecules in the gas molecule target library, a</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS ; PHYSICS</subject><creationdate>2024</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20240308&amp;DB=EPODOC&amp;CC=CN&amp;NR=117669342A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25543,76293</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20240308&amp;DB=EPODOC&amp;CC=CN&amp;NR=117669342A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>ZHU TAIYUN</creatorcontrib><creatorcontrib>ZHU SHAN</creatorcontrib><creatorcontrib>LIU WEI</creatorcontrib><creatorcontrib>DONG WANGCHAO</creatorcontrib><creatorcontrib>YU DENGYANG</creatorcontrib><creatorcontrib>XU XIAOXIAO</creatorcontrib><creatorcontrib>XU ZHENGJIE</creatorcontrib><creatorcontrib>SONG YUMEI</creatorcontrib><creatorcontrib>HANG CHEN</creatorcontrib><creatorcontrib>MA FENGXIANG</creatorcontrib><creatorcontrib>CAO JUN</creatorcontrib><title>Novel environment-friendly insulating gas molecule screening method based on deep learning</title><description>The invention discloses a novel environment-friendly insulating gas molecule screening method based on deep learning. The novel environment-friendly insulating gas molecule screening method comprises the following steps: establishing a basic library of known gas molecule electrical environment-friendly properties; representing the gas molecules in the basic library by molecular descriptors to generate a molecular data matrix, and dividing the matrix into a training library and a test library; a deep learning model is built, the training library is used for training the deep learning model, and the test library tests the prediction precision of the trained deep learning model until the optimal deep learning model is obtained; generating new small molecular structures in batches from the gas molecules in the basic library through a functional group replacement method, and forming a gas molecule target library; adopting the optimal deep learning model to screen gas molecules in the gas molecule target library, a</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNirEKwjAURbs4iPoPzw_oUCsVRymKUycnlxKT2xp4eQlJWvDvpeAHOB0456yLZ-dnMEFmG704SC6HaCGGP2QlTayylZFGlch5hp4YlHQEZNEO-e0NvVSCIS9kgEAMFZe6LVaD4oTdj5tif7s-2nuJ4HukoDQEuW-7qjo1zbk-Hi71P88Xin07qg</recordid><startdate>20240308</startdate><enddate>20240308</enddate><creator>ZHU TAIYUN</creator><creator>ZHU SHAN</creator><creator>LIU WEI</creator><creator>DONG WANGCHAO</creator><creator>YU DENGYANG</creator><creator>XU XIAOXIAO</creator><creator>XU ZHENGJIE</creator><creator>SONG YUMEI</creator><creator>HANG CHEN</creator><creator>MA FENGXIANG</creator><creator>CAO JUN</creator><scope>EVB</scope></search><sort><creationdate>20240308</creationdate><title>Novel environment-friendly insulating gas molecule screening method based on deep learning</title><author>ZHU TAIYUN ; ZHU SHAN ; LIU WEI ; DONG WANGCHAO ; YU DENGYANG ; XU XIAOXIAO ; XU ZHENGJIE ; SONG YUMEI ; HANG CHEN ; MA FENGXIANG ; CAO JUN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN117669342A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>ZHU TAIYUN</creatorcontrib><creatorcontrib>ZHU SHAN</creatorcontrib><creatorcontrib>LIU WEI</creatorcontrib><creatorcontrib>DONG WANGCHAO</creatorcontrib><creatorcontrib>YU DENGYANG</creatorcontrib><creatorcontrib>XU XIAOXIAO</creatorcontrib><creatorcontrib>XU ZHENGJIE</creatorcontrib><creatorcontrib>SONG YUMEI</creatorcontrib><creatorcontrib>HANG CHEN</creatorcontrib><creatorcontrib>MA FENGXIANG</creatorcontrib><creatorcontrib>CAO JUN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>ZHU TAIYUN</au><au>ZHU SHAN</au><au>LIU WEI</au><au>DONG WANGCHAO</au><au>YU DENGYANG</au><au>XU XIAOXIAO</au><au>XU ZHENGJIE</au><au>SONG YUMEI</au><au>HANG CHEN</au><au>MA FENGXIANG</au><au>CAO JUN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Novel environment-friendly insulating gas molecule screening method based on deep learning</title><date>2024-03-08</date><risdate>2024</risdate><abstract>The invention discloses a novel environment-friendly insulating gas molecule screening method based on deep learning. The novel environment-friendly insulating gas molecule screening method comprises the following steps: establishing a basic library of known gas molecule electrical environment-friendly properties; representing the gas molecules in the basic library by molecular descriptors to generate a molecular data matrix, and dividing the matrix into a training library and a test library; a deep learning model is built, the training library is used for training the deep learning model, and the test library tests the prediction precision of the trained deep learning model until the optimal deep learning model is obtained; generating new small molecular structures in batches from the gas molecules in the basic library through a functional group replacement method, and forming a gas molecule target library; adopting the optimal deep learning model to screen gas molecules in the gas molecule target library, a</abstract><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier
ispartof
issn
language chi ; eng
recordid cdi_epo_espacenet_CN117669342A
source esp@cenet
subjects CALCULATING
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS
PHYSICS
title Novel environment-friendly insulating gas molecule screening method based on deep learning
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-26T22%3A26%3A03IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=ZHU%20TAIYUN&rft.date=2024-03-08&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN117669342A%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true