A Review of Trends in Corrosion-Resistant Structural Steels Research-From Theoretical Simulation to Data-Driven Directions

This paper provides a review of models commonly used over the years in the study of microscopic models of material corrosion mechanisms, data mining methods and the corrosion-resistant performance control of structural steels. The virtual process of material corrosion is combined with experimental d...

Full description

Saved in:
Bibliographic Details
Published in:Materials 2023-04, Vol.16 (9), p.3396
Main Authors: Xu, Di, Pei, Zibo, Yang, Xiaojia, Li, Qing, Zhang, Fan, Zhu, Renzheng, Cheng, Xuequn, Ma, Lingwei
Format: Article
Language:English
Subjects:
Adsorption
Alloying effects
Alloying elements
Analysis
Big Data
Control systems
Corrosion
Corrosion effects
Corrosion mechanisms
Corrosion prevention
Corrosion rate
Corrosion resistance
Corrosion resistant steels
Data mining
Experimental methods
Grain size
Mathematical models
Modelling
R&D
Research & development
Research methodology
Review
Simulation
Software
Steel
Steel, Structural
Structural steels
Trends
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c446t-d4b150008ff0a1dcad3c85f04e64e526ad07fa14128b6c9122075b50390106113
cites cdi_FETCH-LOGICAL-c446t-d4b150008ff0a1dcad3c85f04e64e526ad07fa14128b6c9122075b50390106113
container_end_page
container_issue 9
container_start_page 3396
container_title Materials
container_volume 16
creator Xu, Di
Pei, Zibo
Yang, Xiaojia
Li, Qing
Zhang, Fan
Zhu, Renzheng
Cheng, Xuequn
Ma, Lingwei
description This paper provides a review of models commonly used over the years in the study of microscopic models of material corrosion mechanisms, data mining methods and the corrosion-resistant performance control of structural steels. The virtual process of material corrosion is combined with experimental data to reflect the microscopic mechanism of material corrosion from a nano-scale to macro-scale, respectively. Data mining methods focus on predicting and modeling the corrosion rate and corrosion life of materials. Data-driven control of the corrosion resistance of structural steels is achieved through micro-alloying and organization structure control technology. Corrosion modeling has been used to assess the effects of alloying elements, grain size and organization purity on corrosion resistance, and to determine the contents of alloying elements.
doi_str_mv 10.3390/ma16093396
format article
fullrecord <record><control><sourceid>gale_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10179958</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A749097941</galeid><sourcerecordid>A749097941</sourcerecordid><originalsourceid>FETCH-LOGICAL-c446t-d4b150008ff0a1dcad3c85f04e64e526ad07fa14128b6c9122075b50390106113</originalsourceid><addsrcrecordid>eNpdklFvFCEQx4nR2Kb2xQ9gSHwxJlthYWF5Mpc7qyZNTOr5TDh26NHsQgX2jH562VytVXhgwvzmzwwzCL2k5IIxRd5NhgqiqimeoFOqlGio4vzpI_sEned8S-pijPateo5OmKRStFKeol8rfA0HDz9wdHibIAwZ-4DXMaWYfQzNNWSfiwkFfy1ptmVOZqwmwJhrZAaT7L65THHC2z3EBMXbBfDTPJpSBXCJeGOKaTbJHyDgjU9gF0d-gZ45M2Y4vz_P0LfLD9v1p-bqy8fP69VVYzkXpRn4jnY1-d45YuhgzcBs3znCQXDoWmEGIp2hnLb9TlhF25bIbteR-jmUCErZGXp_1L2bdxMMFkKpNei75CeTfupovP7XE_xe38SDpoRKpbq-Kry5V0jx-wy56MlnC-NoAsQ567anrBOsI7Kir_9Db-OcQq1vodqaj5BdpS6O1I0ZQfvgYn3Y1j3A5G0M4Hy9X0muiJKKLzW8PQbY2pacwD2kT4le5kD_nYMKv3pc8AP6p-vsNyA8rbM</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2812611675</pqid></control><display><type>article</type><title>A Review of Trends in Corrosion-Resistant Structural Steels Research-From Theoretical Simulation to Data-Driven Directions</title><source>Publicly Available Content (ProQuest)</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><creator>Xu, Di ; Pei, Zibo ; Yang, Xiaojia ; Li, Qing ; Zhang, Fan ; Zhu, Renzheng ; Cheng, Xuequn ; Ma, Lingwei</creator><creatorcontrib>Xu, Di ; Pei, Zibo ; Yang, Xiaojia ; Li, Qing ; Zhang, Fan ; Zhu, Renzheng ; Cheng, Xuequn ; Ma, Lingwei</creatorcontrib><description>This paper provides a review of models commonly used over the years in the study of microscopic models of material corrosion mechanisms, data mining methods and the corrosion-resistant performance control of structural steels. The virtual process of material corrosion is combined with experimental data to reflect the microscopic mechanism of material corrosion from a nano-scale to macro-scale, respectively. Data mining methods focus on predicting and modeling the corrosion rate and corrosion life of materials. Data-driven control of the corrosion resistance of structural steels is achieved through micro-alloying and organization structure control technology. Corrosion modeling has been used to assess the effects of alloying elements, grain size and organization purity on corrosion resistance, and to determine the contents of alloying elements.</description><identifier>ISSN: 1996-1944</identifier><identifier>EISSN: 1996-1944</identifier><identifier>DOI: 10.3390/ma16093396</identifier><identifier>PMID: 37176277</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Adsorption ; Alloying effects ; Alloying elements ; Analysis ; Big Data ; Control systems ; Corrosion ; Corrosion effects ; Corrosion mechanisms ; Corrosion prevention ; Corrosion rate ; Corrosion resistance ; Corrosion resistant steels ; Data mining ; Experimental methods ; Grain size ; Mathematical models ; Modelling ; R&amp;D ; Research &amp; development ; Research methodology ; Review ; Simulation ; Software ; Steel ; Steel, Structural ; Structural steels ; Trends</subject><ispartof>Materials, 2023-04, Vol.16 (9), p.3396</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2023 by the authors. 2023</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c446t-d4b150008ff0a1dcad3c85f04e64e526ad07fa14128b6c9122075b50390106113</citedby><cites>FETCH-LOGICAL-c446t-d4b150008ff0a1dcad3c85f04e64e526ad07fa14128b6c9122075b50390106113</cites><orcidid>0000-0001-9672-270X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2812611675/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2812611675?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37176277$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Xu, Di</creatorcontrib><creatorcontrib>Pei, Zibo</creatorcontrib><creatorcontrib>Yang, Xiaojia</creatorcontrib><creatorcontrib>Li, Qing</creatorcontrib><creatorcontrib>Zhang, Fan</creatorcontrib><creatorcontrib>Zhu, Renzheng</creatorcontrib><creatorcontrib>Cheng, Xuequn</creatorcontrib><creatorcontrib>Ma, Lingwei</creatorcontrib><title>A Review of Trends in Corrosion-Resistant Structural Steels Research-From Theoretical Simulation to Data-Driven Directions</title><title>Materials</title><addtitle>Materials (Basel)</addtitle><description>This paper provides a review of models commonly used over the years in the study of microscopic models of material corrosion mechanisms, data mining methods and the corrosion-resistant performance control of structural steels. The virtual process of material corrosion is combined with experimental data to reflect the microscopic mechanism of material corrosion from a nano-scale to macro-scale, respectively. Data mining methods focus on predicting and modeling the corrosion rate and corrosion life of materials. Data-driven control of the corrosion resistance of structural steels is achieved through micro-alloying and organization structure control technology. Corrosion modeling has been used to assess the effects of alloying elements, grain size and organization purity on corrosion resistance, and to determine the contents of alloying elements.</description><subject>Adsorption</subject><subject>Alloying effects</subject><subject>Alloying elements</subject><subject>Analysis</subject><subject>Big Data</subject><subject>Control systems</subject><subject>Corrosion</subject><subject>Corrosion effects</subject><subject>Corrosion mechanisms</subject><subject>Corrosion prevention</subject><subject>Corrosion rate</subject><subject>Corrosion resistance</subject><subject>Corrosion resistant steels</subject><subject>Data mining</subject><subject>Experimental methods</subject><subject>Grain size</subject><subject>Mathematical models</subject><subject>Modelling</subject><subject>R&amp;D</subject><subject>Research &amp; development</subject><subject>Research methodology</subject><subject>Review</subject><subject>Simulation</subject><subject>Software</subject><subject>Steel</subject><subject>Steel, Structural</subject><subject>Structural steels</subject><subject>Trends</subject><issn>1996-1944</issn><issn>1996-1944</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNpdklFvFCEQx4nR2Kb2xQ9gSHwxJlthYWF5Mpc7qyZNTOr5TDh26NHsQgX2jH562VytVXhgwvzmzwwzCL2k5IIxRd5NhgqiqimeoFOqlGio4vzpI_sEned8S-pijPateo5OmKRStFKeol8rfA0HDz9wdHibIAwZ-4DXMaWYfQzNNWSfiwkFfy1ptmVOZqwmwJhrZAaT7L65THHC2z3EBMXbBfDTPJpSBXCJeGOKaTbJHyDgjU9gF0d-gZ45M2Y4vz_P0LfLD9v1p-bqy8fP69VVYzkXpRn4jnY1-d45YuhgzcBs3znCQXDoWmEGIp2hnLb9TlhF25bIbteR-jmUCErZGXp_1L2bdxMMFkKpNei75CeTfupovP7XE_xe38SDpoRKpbq-Kry5V0jx-wy56MlnC-NoAsQ567anrBOsI7Kir_9Db-OcQq1vodqaj5BdpS6O1I0ZQfvgYn3Y1j3A5G0M4Hy9X0muiJKKLzW8PQbY2pacwD2kT4le5kD_nYMKv3pc8AP6p-vsNyA8rbM</recordid><startdate>20230426</startdate><enddate>20230426</enddate><creator>Xu, Di</creator><creator>Pei, Zibo</creator><creator>Yang, Xiaojia</creator><creator>Li, Qing</creator><creator>Zhang, Fan</creator><creator>Zhu, Renzheng</creator><creator>Cheng, Xuequn</creator><creator>Ma, Lingwei</creator><general>MDPI AG</general><general>MDPI</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SR</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>KB.</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-9672-270X</orcidid></search><sort><creationdate>20230426</creationdate><title>A Review of Trends in Corrosion-Resistant Structural Steels Research-From Theoretical Simulation to Data-Driven Directions</title><author>Xu, Di ; Pei, Zibo ; Yang, Xiaojia ; Li, Qing ; Zhang, Fan ; Zhu, Renzheng ; Cheng, Xuequn ; Ma, Lingwei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c446t-d4b150008ff0a1dcad3c85f04e64e526ad07fa14128b6c9122075b50390106113</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Adsorption</topic><topic>Alloying effects</topic><topic>Alloying elements</topic><topic>Analysis</topic><topic>Big Data</topic><topic>Control systems</topic><topic>Corrosion</topic><topic>Corrosion effects</topic><topic>Corrosion mechanisms</topic><topic>Corrosion prevention</topic><topic>Corrosion rate</topic><topic>Corrosion resistance</topic><topic>Corrosion resistant steels</topic><topic>Data mining</topic><topic>Experimental methods</topic><topic>Grain size</topic><topic>Mathematical models</topic><topic>Modelling</topic><topic>R&amp;D</topic><topic>Research &amp; development</topic><topic>Research methodology</topic><topic>Review</topic><topic>Simulation</topic><topic>Software</topic><topic>Steel</topic><topic>Steel, Structural</topic><topic>Structural steels</topic><topic>Trends</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Xu, Di</creatorcontrib><creatorcontrib>Pei, Zibo</creatorcontrib><creatorcontrib>Yang, Xiaojia</creatorcontrib><creatorcontrib>Li, Qing</creatorcontrib><creatorcontrib>Zhang, Fan</creatorcontrib><creatorcontrib>Zhu, Renzheng</creatorcontrib><creatorcontrib>Cheng, Xuequn</creatorcontrib><creatorcontrib>Ma, Lingwei</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Engineered Materials Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>Materials Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Materials</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Xu, Di</au><au>Pei, Zibo</au><au>Yang, Xiaojia</au><au>Li, Qing</au><au>Zhang, Fan</au><au>Zhu, Renzheng</au><au>Cheng, Xuequn</au><au>Ma, Lingwei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Review of Trends in Corrosion-Resistant Structural Steels Research-From Theoretical Simulation to Data-Driven Directions</atitle><jtitle>Materials</jtitle><addtitle>Materials (Basel)</addtitle><date>2023-04-26</date><risdate>2023</risdate><volume>16</volume><issue>9</issue><spage>3396</spage><pages>3396-</pages><issn>1996-1944</issn><eissn>1996-1944</eissn><abstract>This paper provides a review of models commonly used over the years in the study of microscopic models of material corrosion mechanisms, data mining methods and the corrosion-resistant performance control of structural steels. The virtual process of material corrosion is combined with experimental data to reflect the microscopic mechanism of material corrosion from a nano-scale to macro-scale, respectively. Data mining methods focus on predicting and modeling the corrosion rate and corrosion life of materials. Data-driven control of the corrosion resistance of structural steels is achieved through micro-alloying and organization structure control technology. Corrosion modeling has been used to assess the effects of alloying elements, grain size and organization purity on corrosion resistance, and to determine the contents of alloying elements.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>37176277</pmid><doi>10.3390/ma16093396</doi><orcidid>https://orcid.org/0000-0001-9672-270X</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1996-1944
ispartof Materials, 2023-04, Vol.16 (9), p.3396
issn 1996-1944
1996-1944
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10179958
source Publicly Available Content (ProQuest); PubMed Central; Free Full-Text Journals in Chemistry
subjects Adsorption
Alloying effects
Alloying elements
Analysis
Big Data
Control systems
Corrosion
Corrosion effects
Corrosion mechanisms
Corrosion prevention
Corrosion rate
Corrosion resistance
Corrosion resistant steels
Data mining
Experimental methods
Grain size
Mathematical models
Modelling
R&D
Research & development
Research methodology
Review
Simulation
Software
Steel
Steel, Structural
Structural steels
Trends
title A Review of Trends in Corrosion-Resistant Structural Steels Research-From Theoretical Simulation to Data-Driven Directions
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T17%3A28%3A26IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Review%20of%20Trends%20in%20Corrosion-Resistant%20Structural%20Steels%20Research-From%20Theoretical%20Simulation%20to%20Data-Driven%20Directions&rft.jtitle=Materials&rft.au=Xu,%20Di&rft.date=2023-04-26&rft.volume=16&rft.issue=9&rft.spage=3396&rft.pages=3396-&rft.issn=1996-1944&rft.eissn=1996-1944&rft_id=info:doi/10.3390/ma16093396&rft_dat=%3Cgale_pubme%3EA749097941%3C/gale_pubme%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c446t-d4b150008ff0a1dcad3c85f04e64e526ad07fa14128b6c9122075b50390106113%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2812611675&rft_id=info:pmid/37176277&rft_galeid=A749097941&rfr_iscdi=true