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However, the optimization performance of generative networks is restricted by the increasing discrepancy between the optimized input and the prescribed input domain as the design loop increases. Herein, a correction technique is incorporated into generative deep neural network (GDNN) and generative deep convolutional neural network (GDCNN). The correction is performed by pulling the machine learning (ML)\u2010optimized inputs back to the prescribed domain at certain interval during the optimization process instead of only postprocessing at the end. A DM system with two phases, i.e., the matrix phase and the pore phase, is used for the structural design. The datasets are produced using a numerical model and describe the relationship between the material structure and the elastic modulus and tensile strength. The results show that the optimization effectiveness of corrected GDNN\/GDCNN significantly improves given the fact that more structures converge to the best structures and fewer nonrepetitive structures are left after optimization, which helps to search for the best structures and decreases the computational burden when verifying the ML\u2010recommended structures. The corrected GDNN and GDCNN also manage to find structures with higher tensile strength in the new inverse design.<\/jats:p><\/jats:sec>","DOI":"10.1002\/aisy.202200333","type":"journal-article","created":{"date-parts":[[2022,11,24]],"date-time":"2022-11-24T12:30:05Z","timestamp":1669293005000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Inverse Design of Digital Materials Using Corrected Generative Deep Neural Network and Generative Deep Convolutional Neural Network"],"prefix":"10.1002","volume":"5","author":[{"given":"Zhi","family":"Wan","sequence":"first","affiliation":[{"name":"Faculty of Civil Engineering and Geosciences Delft University of Technology  2628 CN Delft The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2445-3878","authenticated-orcid":false,"given":"Ze","family":"Chang","sequence":"additional","affiliation":[{"name":"Faculty of Civil Engineering and Geosciences Delft University of Technology  2628 CN Delft The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yading","family":"Xu","sequence":"additional","affiliation":[{"name":"Faculty of Civil Engineering and Geosciences Delft University of Technology  2628 CN Delft The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yitao","family":"Huang","sequence":"additional","affiliation":[{"name":"Faculty of Civil Engineering and Geosciences Delft University of Technology  2628 CN Delft The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1299-1449","authenticated-orcid":false,"given":"Branko","family":"\u0160avija","sequence":"additional","affiliation":[{"name":"Faculty of Civil Engineering and Geosciences Delft University of Technology  2628 CN Delft The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2022,11,24]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cemconcomp.2015.04.012"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41524-021-00695-2"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.engfracmech.2022.108624"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.compositesb.2021.109314"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.matt.2020.04.019"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2019.112790"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0008-8846(98)00165-3"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.matdes.2020.108509"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/adma.201904845"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cemconcomp.2021.104295"},{"key":"e_1_2_8_12_1","unstructured":"Y.Zhang B.Wallace(Preprint) arXiv:1510.03820 v1 submitted: Oct. 2015."},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1039\/C8MH00653A"},{"key":"e_1_2_8_14_1","volume-title":"Machine Learning: An Artificial Intelligence Approach","author":"Michalski R. 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