{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T07:10:52Z","timestamp":1781334652265,"version":"3.54.1"},"reference-count":66,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2021,7,26]],"date-time":"2021-07-26T00:00:00Z","timestamp":1627257600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>This research work focuses on machine-learning-assisted prediction of the corrosion behavior of laser-powder-bed-fused (LPBF) and postprocessed Inconel 718. Corrosion testing data of these specimens were collected and fit into the following machine learning algorithms: polynomial regression, support vector regression, decision tree, and extreme gradient boosting. The model performance, after hyperparameter optimization, was evaluated using a set of established metrics: R2, mean absolute error, and root mean square error. Among the algorithms, the extreme gradient boosting algorithm performed best in predicting the corrosion behavior, closely followed by other algorithms. Feature importance analysis was executed in order to determine the postprocessing parameters that influenced the most the corrosion behavior in Inconel 718 manufactured by LPBF.<\/jats:p>","DOI":"10.3390\/data6080080","type":"journal-article","created":{"date-parts":[[2021,7,25]],"date-time":"2021-07-25T22:06:21Z","timestamp":1627250781000},"page":"80","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["Machine-Learning-Based Prediction of Corrosion Behavior in Additively Manufactured Inconel 718"],"prefix":"10.3390","volume":"6","author":[{"given":"O. V.","family":"Mythreyi","sequence":"first","affiliation":[{"name":"Department of Engineering Design, Indian Institute of Technology Madras, Chennai 600036, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M. Rohith","family":"Srinivaas","sequence":"additional","affiliation":[{"name":"Department of Metallurgical & Materials Engineering, Indian Institute of Technology Madras, Chennai 600036, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tigga","family":"Amit Kumar","sequence":"additional","affiliation":[{"name":"Gas Turbine Research Establishment Research and Development Organization, Bengaluru 560093, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"R.","family":"Jayaganthan","sequence":"additional","affiliation":[{"name":"Department of Engineering Design, Indian Institute of Technology Madras, Chennai 600036, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,26]]},"reference":[{"key":"ref_1","first-page":"38","article-title":"ASM specialty handbook: Nickel, cobalt, and their alloys","volume":"38","author":"Davis","year":"2001","journal-title":"Choice Rev. Online"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Pint, B., Unocic, K., and Dryepondt, S. (2010, January 10\u201312). Oxidation of Superalloys in Extreme Environments. Proceedings of the 7th International Symposium on Superalloy 718 and Derivatives (2010), Pittsburgh, PA, USA.","DOI":"10.7449\/2010\/Superalloys_2010_861_875"},{"key":"ref_3","unstructured":"Park, M. (2005). ASM Handbook Corrosion: Materials, American society of materials."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Akca, E., and G\u00fcrsel, A. (2017). A Review on Superalloys and IN718 Nickel-Based INCONEL Superalloy. Period. Eng. Nat. Sci. (PEN), 3.","DOI":"10.21533\/pen.v3i1.43"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1016\/j.jmatprotec.2006.04.072","article-title":"High temperature deformation of Inconel 718","volume":"177","author":"Thomas","year":"2006","journal-title":"J. Mater. Process. Technol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1007\/s40195-017-0538-y","article-title":"Performance of Corrosion-Resistant Alloys in Concentrated Acids","volume":"30","author":"Mishra","year":"2017","journal-title":"Acta Met. Sin. Engl. Lett."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1116","DOI":"10.1149\/1.2425932","article-title":"Corrosion of Steels and Nickel Alloys in Superheated Steam Corrosion of Steels and Nickel Alloys in Superheated Steam","volume":"111","author":"Soc","year":"1964","journal-title":"J. Electrochem. Soc."},{"key":"ref_8","unstructured":"Delabrouille, F., Legras, L., Vaillant, F., Scott, P., Viguier, B., and Andrieu, E. (2005, January 14\u201318). Effect of the Chromium Content and Strain on the Corrosion of Nickel Based Alloys in Primary Water of Pressurized Water. Proceedings of the 12th International Conference on Environmental Degradation of Materials in Nuclear Power System\u2013Water Reactors, Salt Lake City, UT, USA."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"721","DOI":"10.5006\/1170","article-title":"Effect of Alloying Elements on Crevice Corrosion Inhibition of Nickel-Chromium-Molybdenum-Tungsten Alloys Under Aggressive Conditions: An Electrochemical Study","volume":"70","author":"Mishra","year":"2014","journal-title":"Corrosion"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.cossms.2019.03.002","article-title":"Revisiting the effects of molybdenum and tungsten alloying on corrosion behavior of nickel-chromium alloys in aqueous corrosion","volume":"23","author":"Cwalina","year":"2019","journal-title":"Curr. Opin. Solid State Mater. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.jmapro.2020.08.029","article-title":"Combination of high feed turning with cryogenic cooling on Haynes 263 and Inconel 718 superalloys","volume":"58","author":"Amigo","year":"2020","journal-title":"J. Manuf. Process."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.powtec.2017.01.030","article-title":"Densification and microstructural investigation of Inconel 718 parts fabricated by selective laser melting","volume":"310","author":"Choi","year":"2017","journal-title":"Powder Technol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1016\/j.msea.2019.05.013","article-title":"Influence of build orientation on microstructure, mechanical and corrosion behavior of Inconel 718 processed by selective laser melting","volume":"760","author":"Du","year":"2019","journal-title":"Mater. Sci. Eng. A"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1016\/j.matdes.2016.11.103","article-title":"Study of selective laser melting (SLM) Inconel 718 part surface improvement by electrochemical polishing","volume":"116","author":"Baicheng","year":"2017","journal-title":"Mater. Des."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1350","DOI":"10.1002\/maco.201810159","article-title":"Effect of heat treatment on the \u03b4 phase distribution and corrosion resistance of selective laser melting manufactured Inconel 718 superalloy","volume":"69","author":"Li","year":"2018","journal-title":"Mater. Corros."},{"key":"ref_16","first-page":"100875","article-title":"Microstructural evolution and corrosion behaviors of Inconel 718 alloy produced by selective laser melting following different heat treatments","volume":"30","author":"Luo","year":"2019","journal-title":"Addit. Manuf."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Calleja-Ochoa, A., Gonzalez-Barrio, H., de Lacalle, N.L., Mart\u00ednez, S., Albizuri, J., and Lamikiz, A. (2021). A New Approach in the Design of Microstructured Ultralight Components to Achieve Maximum Functional Performance. Materials, 14.","DOI":"10.3390\/ma14071588"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Almangour, B. (2018). Additive manufacturing of emerging materials. Addit. Manuf. Emerg. Mater., 1\u2013355.","DOI":"10.1007\/978-3-319-91713-9"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.pmatsci.2017.10.001","article-title":"Additive manufacturing of metallic components\u2013Process, structure and properties","volume":"92","author":"Debroy","year":"2018","journal-title":"Prog. Mater. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"92","DOI":"10.4028\/www.scientific.net\/AMR.227.92","article-title":"Laser-Based Additive Manufacturing of Metals","volume":"227","author":"Kumar","year":"2011","journal-title":"Adv. Mater. Res."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"041101","DOI":"10.1063\/1.4935926","article-title":"Review of selective laser melting: Materials and applications","volume":"2","author":"Yap","year":"2015","journal-title":"Appl. Phys. Rev."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1007\/s40964-019-00099-1","article-title":"Post-processing effects on the surface characteristics of Inconel 718 alloy fabricated by selective laser melting additive manufacturing","volume":"5","author":"Kaynak","year":"2020","journal-title":"Prog. Addit. Manuf."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1588","DOI":"10.1080\/10426914.2016.1257805","article-title":"Effect of different heat treatments on the microstructure and mechanical properties in selective laser melted INCONEL 718 alloy","volume":"32","author":"Raghavan","year":"2017","journal-title":"Mater. Manuf. Process."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"139649","DOI":"10.1016\/j.msea.2020.139649","article-title":"Microstructural evolution and mechanical properties of selective laser melted a nickel-based superalloy after post treatment","volume":"792","author":"Chen","year":"2020","journal-title":"Mater. Sci. Eng. A"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"139735","DOI":"10.1016\/j.msea.2020.139735","article-title":"Comparative study on the microstructure evolution of selective laser melted and wrought IN718 superalloy during subsequent heat treatment process and its effect on mechanical properties","volume":"791","author":"Zhao","year":"2020","journal-title":"Mater. Sci. Eng. A"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"186","DOI":"10.2118\/29784-PA","article-title":"The Impact of Corrosion on Oil and Gas Industry","volume":"11","author":"Kermani","year":"1996","journal-title":"SPE Prod. Facil."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.corsci.2014.04.044","article-title":"Application of corrosion inhibitors for steels in acidic media for the oil and gas industry: A review","volume":"86","author":"Jackson","year":"2014","journal-title":"Corros. Sci."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.reactfunctpolym.2015.08.006","article-title":"Polymeric corrosion inhibitors for the oil and gas industry: Design principles and mechanism","volume":"95","author":"Tiu","year":"2015","journal-title":"React. Funct. Polym."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Groysman, A. (2010). Corrosion for Everybody, Springer.","DOI":"10.1007\/978-90-481-3477-9"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1016\/S0026-0576(00)80461-4","article-title":"Accelerated corrosion testing","volume":"98","author":"Meade","year":"2000","journal-title":"Metal Finish."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1016\/0010-938X(81)90015-9","article-title":"Determination of corrosion rates by electrochemical DC and AC methods","volume":"21","author":"Lorenz","year":"1981","journal-title":"Corros. Sci."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0010-938X(80)90119-5","article-title":"Weight Studies of Atmospheric Corrosion\u2014Loss and Electrochemical Measurements","volume":"20","author":"Mansfeld","year":"1980","journal-title":"Corros. Sci."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Sjding, A.B.J. (1992). Corrosion testing by potentiodynamic polarization in various electrolytes. Corros. Sci., 241\u2013245.","DOI":"10.1016\/0109-5641(92)90093-R"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"3178","DOI":"10.1016\/j.corsci.2005.04.012","article-title":"Tafel slopes and corrosion rates obtained in the pre-Tafel region of polarization curves","volume":"47","author":"Mansfeld","year":"2005","journal-title":"Corros. Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3202","DOI":"10.1016\/j.corsci.2005.05.046","article-title":"Validation of corrosion rates measured by the Tafel extrapolation method","volume":"47","author":"McCafferty","year":"2005","journal-title":"Corros. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1146\/annurev.anchem.012809.102211","article-title":"Electrochemical Impedance Spectroscopy","volume":"3","author":"Chang","year":"2006","journal-title":"Annu. Rev. Anal. Chem."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1917","DOI":"10.1149\/1.2069522","article-title":"Measurement models for electrochemical impedance spectroscopy: I. Demonstration of applicability","volume":"139","author":"Agarwal","year":"1992","journal-title":"J. Electrochem. Soc."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1021\/ac0313973","article-title":"With impedance data, a complete description of an electrochemical system is possible","volume":"75","author":"Park","year":"2003","journal-title":"Anal. Chem."},{"key":"ref_39","unstructured":"Yu, X. (2017). Machine learning application in the life time of materials. arXiv."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1504\/IJOGCT.2014.066304","article-title":"Application of data mining techniques in building predictive models for oil and gas problems: A case study on casing corrosion prediction","volume":"8","author":"Irani","year":"2014","journal-title":"Int. J. Oil Gas Coal Technol."},{"key":"ref_41","first-page":"159","article-title":"Materials discovery and design using machine learning","volume":"3","author":"Liu","year":"2017","journal-title":"J. Mater."},{"key":"ref_42","first-page":"547","article-title":"Machine learning for molecular and materials science","volume":"559","author":"Butler","year":"2018","journal-title":"Nat. Cell Biol."},{"key":"ref_43","first-page":"1","article-title":"A Survey on Data Collection for Machine Learning","volume":"4347","author":"Roh","year":"2019","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Schmidt, J., Marques, M.R.G., Botti, S., and Marques, M.A.L. (2019). Recent advances and applications of machine learning in solid-state materials science. NPJ Comput. Mater., 5.","DOI":"10.1038\/s41524-019-0221-0"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3339474","article-title":"Federated Machine Learning: Concept and Applications","volume":"10","author":"Yang","year":"2019","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41467-020-17112-9","article-title":"Identifying domains of applicability of machine learning models for materials science","volume":"11","author":"Sutton","year":"2020","journal-title":"Nat. Commun."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41524-019-0248-2","article-title":"Reliable and explainable machine-learning methods for accelerated material discovery","volume":"5","author":"Kailkhura","year":"2019","journal-title":"NPJ Comput. Mater."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1016\/j.corsci.2008.10.038","article-title":"Corrosion rate prediction of 3C steel under different seawater environment by using support vector regression","volume":"51","author":"Wen","year":"2009","journal-title":"Corros. Sci."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"669","DOI":"10.1016\/j.corsci.2009.10.024","article-title":"Prediction of corrosion behavior using neural network as a data mining tool","volume":"52","author":"Kamrunnahar","year":"2010","journal-title":"Corros. Sci."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1002\/maco.201911224","article-title":"Machine learning assistance for electrochemical curve simulation of corrosion and its application","volume":"71","author":"Gong","year":"2019","journal-title":"Mater. Corros."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"113627","DOI":"10.1016\/j.jelechem.2019.113627","article-title":"Equivalent circuit model recognition of electrochemical impedance spectroscopy via machine learning","volume":"855","author":"Zhu","year":"2019","journal-title":"J. Electroanal. Chem."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1316","DOI":"10.1016\/j.jclepro.2015.12.009","article-title":"A decision-support model for selecting additive manufacturing versus subtractive manufacturing based on energy consumption","volume":"176","author":"Watson","year":"2018","journal-title":"J. Clean. Prod."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Mythreyi, O.V., Raja, A., Nagesha, B.K., and Jayaganthan, R. (2020). Corrosion Study of Selective Laser Melted IN718 Alloy upon Post Heat Treatment and Shot Peening. Metals, 10.","DOI":"10.3390\/met10121562"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.neucom.2017.11.077","article-title":"Feature selection in machine learning: A new perspective","volume":"300","author":"Cai","year":"2018","journal-title":"Neurocomputing"},{"key":"ref_55","unstructured":"Vafaie, H., and De Jong, K. (1992, January 10\u201311). Genetic Algorithms as a Tool for Feature Selection in Machine Learning. Proceedings of the IEEE International Conference on Tools with Artificial Intelligence, Arlington, VA, USA."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1016\/j.proeng.2012.09.545","article-title":"Modelling using Polynomial Regression","volume":"48","year":"2012","journal-title":"Procedia Eng."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1023\/B:STCO.0000035301.49549.88","article-title":"A tutorial on support vector regression","volume":"14","author":"Smola","year":"2004","journal-title":"Stat. Comput."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1016\/j.asoc.2016.07.007","article-title":"The role of decision tree representation in regression problems\u2014An evolutionary perspective","volume":"48","author":"Czajkowski","year":"2016","journal-title":"Appl. Soft Comput."},{"key":"ref_59","unstructured":"Guttenberg, N. (2018). Learning to generate classifiers. arXiv."},{"key":"ref_60","unstructured":"Zemel, R.S. (2006, January 3\u20136). A Gradient-Based Boosting Algorithm for Regression Problems. Proceedings of the 13th International Conference on Neural Information Processing Systems, Hong Kong, China."},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Chen, T. (2016, January 13\u201317). XGBoost: A Scalable Tree Boosting System. Proceedings of the 22nd Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA.","DOI":"10.1145\/2939672.2939785"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"792","DOI":"10.1016\/j.jallcom.2018.01.159","article-title":"Effect of solution heat treatment on microstructure and electrochemical behavior of electron beam smelted Inconel 718 superalloy","volume":"741","author":"You","year":"2018","journal-title":"J. Alloys Compd."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"4480","DOI":"10.1016\/j.surfcoat.2011.03.080","article-title":"Numerical modelling of shot peening process and corresponding products: Residual stress, surface roughness and cold work prediction","volume":"205","author":"Mylonas","year":"2011","journal-title":"Surf. Coat. Technol."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"6831","DOI":"10.1016\/j.apsusc.2012.03.111","article-title":"Numerical and experimental analysis of surface roughness generated by shot peening","volume":"258","author":"Bagherifard","year":"2012","journal-title":"Appl. Surf. Sci."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"2350","DOI":"10.1016\/j.matdes.2010.12.016","article-title":"Influence of surface roughness on the corrosion behaviour of magnesium alloy","volume":"32","author":"Walter","year":"2011","journal-title":"Mater. Des."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.surfcoat.2019.01.003","article-title":"The effect of surface plastic deformation produced by shot peening on corrosion behavior of a low-alloy steel","volume":"360","author":"Bozkurt","year":"2019","journal-title":"Surf. Coat. Technol."}],"container-title":["Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5729\/6\/8\/80\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:34:48Z","timestamp":1760164488000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5729\/6\/8\/80"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,26]]},"references-count":66,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2021,8]]}},"alternative-id":["data6080080"],"URL":"https:\/\/doi.org\/10.3390\/data6080080","relation":{},"ISSN":["2306-5729"],"issn-type":[{"value":"2306-5729","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,26]]}}}