{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T20:26:33Z","timestamp":1772828793400,"version":"3.50.1"},"reference-count":29,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,6,17]],"date-time":"2022-06-17T00:00:00Z","timestamp":1655424000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,6,17]],"date-time":"2022-06-17T00:00:00Z","timestamp":1655424000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100000780","name":"European Commission","doi-asserted-by":"publisher","award":["101007430 (COAT4LIFE)"],"award-info":[{"award-number":["101007430 (COAT4LIFE)"]}],"id":[{"id":"10.13039\/501100000780","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["npj Mater Degrad"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>The large amount of corrosion inhibition efficiencies in literature, calls for a more efficient way to organize, access and compare this information. The CORDATA open data management application (<jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/datacor.shinyapps.io\/cordata\/\">https:\/\/datacor.shinyapps.io\/cordata\/<\/jats:ext-link>) can help select appropriate corrosion inhibitors for application specific challenges.<\/jats:p>","DOI":"10.1038\/s41529-022-00259-9","type":"journal-article","created":{"date-parts":[[2022,6,17]],"date-time":"2022-06-17T10:04:33Z","timestamp":1655460273000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["CORDATA: an open data management web application to select corrosion inhibitors"],"prefix":"10.1038","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0685-3675","authenticated-orcid":false,"given":"Tiago L. P.","family":"Galv\u00e3o","sequence":"first","affiliation":[]},{"given":"In\u00eas","family":"Ferreira","sequence":"additional","affiliation":[]},{"given":"Alena","family":"Kuznetsova","sequence":"additional","affiliation":[]},{"given":"Gerard","family":"Novell-Leruth","sequence":"additional","affiliation":[]},{"given":"Ci","family":"Song","sequence":"additional","affiliation":[]},{"given":"Christian","family":"Feiler","sequence":"additional","affiliation":[]},{"given":"Sviatlana V.","family":"Lamaka","sequence":"additional","affiliation":[]},{"given":"Cla\u00fadia","family":"Rocha","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5721-2280","authenticated-orcid":false,"given":"Frederico","family":"Maia","sequence":"additional","affiliation":[]},{"given":"Mikhail L.","family":"Zheludkevich","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5993-1385","authenticated-orcid":false,"given":"Jos\u00e9 R. B.","family":"Gomes","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7584-4641","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Tedim","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,6,17]]},"reference":[{"key":"259_CR1","doi-asserted-by":"publisher","first-page":"1099","DOI":"10.1111\/j.0272-4332.2004.00512.x","volume":"24","author":"RM Park","year":"2004","unstructured":"Park, R. M. et al. Hexavalent chromium and lung cancer in the chromate industry: a quantitative risk assessment. Risk Anal. 24, 1099 (2004).","journal-title":"Risk Anal."},{"key":"259_CR2","unstructured":"Still, C. Boeing names CSIRO a supplier of the year. CSIRO https:\/\/www.csiro.au\/en\/News\/News-releases\/2017\/Boeing-names-CSIRO-a-supplier-of-the-year (2017)."},{"key":"259_CR3","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1016\/j.corsci.2016.02.008","volume":"106","author":"DA Winkler","year":"2016","unstructured":"Winkler, D. A. et al. Using high throughput experimental data and in silico models to discover alternatives to toxic chromate corrosion inhibitors. Corros. Sci. 106, 229 (2016).","journal-title":"Corros. Sci."},{"key":"259_CR4","doi-asserted-by":"publisher","first-page":"3146","DOI":"10.1016\/j.corsci.2010.05.018","volume":"52","author":"S Kallip","year":"2010","unstructured":"Kallip, S., Bastos, A. C., Zheludkevich, M. L. & Ferreira, M. G. S. A multi-electrode cell for high-throughput SVET screening of corrosion inhibitors. Corros. Sci. 52, 3146 (2010).","journal-title":"Corros. Sci."},{"key":"259_CR5","doi-asserted-by":"publisher","first-page":"2457","DOI":"10.1016\/j.electacta.2009.12.013","volume":"55","author":"SJ Garc\u00eda","year":"2010","unstructured":"Garc\u00eda, S. J. et al. The influence of pH on corrosion inhibitor selection for 2024-T3 aluminium alloy assessed by high-throughput multielectrode and potentiodynamic testing. Electrochim. Acta 55, 2457 (2010).","journal-title":"Electrochim. Acta"},{"key":"259_CR6","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1016\/j.corsci.2012.01.016","volume":"58","author":"PA White","year":"2012","unstructured":"White, P. A. et al. A new high-throughput method for corrosion testing. Corros. Sci. 58, 327 (2012).","journal-title":"Corros. Sci."},{"key":"259_CR7","doi-asserted-by":"publisher","first-page":"7647","DOI":"10.1039\/C9NJ06456G","volume":"44","author":"PA White","year":"2020","unstructured":"White, P. A. et al. Towards materials discovery: assays for screening and study of chemical interactions of novel corrosion inhibitors in solution and coatings. N. J. Chem. 44, 7647 (2020).","journal-title":"N. J. Chem."},{"key":"259_CR8","doi-asserted-by":"publisher","first-page":"108377","DOI":"10.1016\/j.corsci.2019.108377","volume":"165","author":"AV Zabula","year":"2020","unstructured":"Zabula, A. V. et al. Screening of molecular lanthanide corrosion inhibitors by a high-throughput method. Corros. Sci. 165, 108377 (2020).","journal-title":"Corros. Sci."},{"key":"259_CR9","doi-asserted-by":"publisher","first-page":"2184","DOI":"10.1016\/j.corsci.2011.02.040","volume":"53","author":"TG Harvey","year":"2011","unstructured":"Harvey, T. G. et al. The effect of inhibitor structure on the corrosion of AA2024 and AA7075. Corros. Sci. 53, 2184 (2011).","journal-title":"Corros. Sci."},{"key":"259_CR10","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1016\/j.corsci.2017.07.011","volume":"128","author":"SV Lamaka","year":"2017","unstructured":"Lamaka, S. V. et al. Comprehensive screening of Mg corrosion inhibitors. Corros. Sci. 128, 224 (2017).","journal-title":"Corros. Sci."},{"key":"259_CR11","doi-asserted-by":"publisher","first-page":"553","DOI":"10.3390\/met7120553","volume":"7","author":"DA Winkler","year":"2017","unstructured":"Winkler, D. A. Predicting the performance of organic corrosion inhibitors. Metals 7, 553 (2017).","journal-title":"Metals"},{"key":"259_CR12","doi-asserted-by":"publisher","first-page":"3349","DOI":"10.1039\/C3GC42540A","volume":"16","author":"DA Winkler","year":"2014","unstructured":"Winkler, D. A. et al. Towards chromate-free corrosion inhibitors: structure\u2013property models for organic alternatives. Green. Chem. 16, 3349 (2014).","journal-title":"Green. Chem."},{"key":"259_CR13","doi-asserted-by":"publisher","first-page":"5624","DOI":"10.1021\/acs.jpcc.9b09538","volume":"124","author":"TLP Galv\u00e3o","year":"2020","unstructured":"Galv\u00e3o, T. L. P., Novell-Leruth, G., Kuznetsova, A., Tedim, J. & Gomes, J. R. B. Elucidating structure-property relationships in aluminum alloy corrosion inhibitors by machine learning. J. Phys. Chem. C. 124, 5624 (2020).","journal-title":"J. Phys. Chem. C."},{"key":"259_CR14","doi-asserted-by":"publisher","first-page":"108856","DOI":"10.1016\/j.corsci.2020.108856","volume":"179","author":"A Kokalj","year":"2021","unstructured":"Kokalj, A. et al. Simplistic correlations between molecular electronic properties and inhibition efficiencies: Do they really exist? Corros. Sci. 179, 108856 (2021).","journal-title":"Corros. Sci."},{"key":"259_CR15","doi-asserted-by":"publisher","first-page":"16660","DOI":"10.1039\/C4TA03414G","volume":"2","author":"M Breedon","year":"2014","unstructured":"Breedon, M., Per, M. C., Cole, I. S. & Barnard, A. S. Molecular ionization and deprotonation energies as indicators of functional coating performance. J. Mater. Chem. A 2, 16660 (2014).","journal-title":"J. Mater. Chem. A"},{"key":"259_CR16","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/j.chemosphere.2016.06.044","volume":"160","author":"M Fernandez","year":"2016","unstructured":"Fernandez, M., Breedon, M., Cole, I. S. & Barnard, A. S. Modeling corrosion inhibition efficacy of small organic molecules as non-toxic chromate alternatives using comparative molecular surface analysis (CoMSA). Chemosphere 160, 80 (2016).","journal-title":"Chemosphere"},{"key":"259_CR17","doi-asserted-by":"publisher","first-page":"410","DOI":"10.1016\/j.matdes.2016.09.084","volume":"112","author":"FF Chen","year":"2016","unstructured":"Chen, F. F. et al. Correlation between molecular features and electrochemical properties using an artificial neural network. Mater. Des. 112, 410 (2016).","journal-title":"Mater. Des."},{"key":"259_CR18","doi-asserted-by":"publisher","first-page":"53","DOI":"10.3389\/fmats.2019.00053","volume":"6","author":"T W\u00fcrger","year":"2019","unstructured":"W\u00fcrger, T. et al. Data science based Mg corrosion engineering. Front. Mater. 6, 53 (2019).","journal-title":"Front. Mater."},{"key":"259_CR19","doi-asserted-by":"publisher","first-page":"108245","DOI":"10.1016\/j.corsci.2019.108245","volume":"163","author":"C Feiler","year":"2020","unstructured":"Feiler, C. et al. In silico screening of modulators of magnesium dissolution. Corros. Sci. 163, 108245 (2020).","journal-title":"Corros. Sci."},{"key":"259_CR20","doi-asserted-by":"publisher","DOI":"10.1038\/s41529-020-00148-z","volume":"5","author":"T W\u00fcrger","year":"2021","unstructured":"W\u00fcrger, T. et al. Exploring structure-property relationships in magnesium dissolution modulators. npj Mater. Degrad. 5, 1 (2021).","journal-title":"npj Mater. Degrad."},{"key":"259_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41524-021-00658-7","volume":"7","author":"EJ Schiessler","year":"2021","unstructured":"Schiessler, E. J. et al. Predicting the inhibition efficiencies of magnesium dissolution modulators using sparse machine learning models. npj Comput. Mater. 7, 1 (2021).","journal-title":"npj Comput. Mater."},{"key":"259_CR22","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1080\/1478422X.2020.1754600","volume":"55","author":"AE Somers","year":"2020","unstructured":"Somers, A. E. et al. Advances in the development of rare earth metal and carboxylate compounds as corrosion inhibitors for steel. Corros. Eng. Sci. Technol. 55, 311 (2020).","journal-title":"Corros. Eng. Sci. Technol."},{"key":"259_CR23","doi-asserted-by":"publisher","first-page":"C3131","DOI":"10.1149\/2.0181911jes","volume":"166","author":"I Milo\u0161ev","year":"2019","unstructured":"Milo\u0161ev, I. et al. Electrochemical, surface-analytical, and computational DFT study of alkaline etched aluminum modified by carboxylic acids for corrosion protection and hydrophobicity. J. Electrochem. Soc. 166, C3131 (2019).","journal-title":"J. Electrochem. Soc."},{"key":"259_CR24","doi-asserted-by":"publisher","first-page":"061509","DOI":"10.1149\/1945-7111\/ab829d","volume":"167","author":"I Milo\u0161ev","year":"2020","unstructured":"Milo\u0161ev, I. et al. The effect of anchor group and alkyl backbone chain on performance of organic compounds as corrosion inhibitors for aluminum investigated using an integrative experimental-modeling approach. J. Electrochem. Soc. 167, 061509 (2020).","journal-title":"J. Electrochem. Soc."},{"key":"259_CR25","doi-asserted-by":"publisher","first-page":"071506","DOI":"10.1149\/1945-7111\/ac0d3d","volume":"168","author":"I Milo\u0161ev","year":"2021","unstructured":"Milo\u0161ev, I. et al. The effects of perfluoroalkyl and alkyl backbone chains, spacers, and anchor groups on the performance of organic compounds as corrosion inhibitors for aluminum investigated using an integrative experimental-modeling approach. J. Electrochem. Soc. 168, 071506 (2021).","journal-title":"J. Electrochem. Soc."},{"key":"259_CR26","doi-asserted-by":"publisher","first-page":"20273","DOI":"10.1021\/jacs.0c09105","volume":"142","author":"SM Moosavi","year":"2020","unstructured":"Moosavi, S. M., Jablonka, K. M. & Smit, B. The role of machine learning in the understanding and design of materials. J. Am. Chem. Soc. 142, 20273 (2020).","journal-title":"J. Am. Chem. Soc."},{"key":"259_CR27","volume":"6","author":"LB Coelho","year":"2022","unstructured":"Coelho, L. B. et al. Reviewing machine learning of corrosion prediction in a data-oriented perspective. npj Mater. Degrad. 6, 1 (2022).","journal-title":"npj Mater. Degrad."},{"key":"259_CR28","unstructured":"R Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing https:\/\/www.r-project.org\/ (2021)."},{"key":"259_CR29","unstructured":"Chang, W. et al. Shiny: Web Application Framework for R. R Studio https:\/\/shiny.rstudio.com\/ (2021)."}],"container-title":["npj Materials Degradation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41529-022-00259-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41529-022-00259-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41529-022-00259-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,24]],"date-time":"2022-11-24T14:01:27Z","timestamp":1669298487000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41529-022-00259-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,17]]},"references-count":29,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,12]]}},"alternative-id":["259"],"URL":"https:\/\/doi.org\/10.1038\/s41529-022-00259-9","relation":{},"ISSN":["2397-2106"],"issn-type":[{"value":"2397-2106","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6,17]]},"assertion":[{"value":"11 April 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 May 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 June 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"48"}}