{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T07:42:44Z","timestamp":1777016564343,"version":"3.51.4"},"reference-count":32,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2022,12,20]],"date-time":"2022-12-20T00:00:00Z","timestamp":1671494400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF-2020R1A2C3004885"],"award-info":[{"award-number":["NRF-2020R1A2C3004885"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF-2020R1A4A2002728"],"award-info":[{"award-number":["NRF-2020R1A4A2002728"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["advanced.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Advanced Intelligent Systems"],"published-print":{"date-parts":[[2023,1]]},"abstract":"<jats:sec><jats:label\/><jats:p>Atomic force microscopy (AFM) is routinely used as a metrological tool among diverse scientific and engineering disciplines. A typical AFM, however, is intrinsically limited by low throughput and is inoperable under extreme conditions. Thus, this work attempts to provide an alternative to a conventional optical microscope (OM) by training a deep learning model to predict surface topography from surface OM images. The feasibility of this novel methodology is shown with germanium\u2010on\u2010nothing (GON) samples, which are self\u2010assembled structures that undergo surface and sub\u2010surface morphological transformations upon high\u2010temperature annealing. Their transformed surface topographies are predicted based on the OM\u2010AFM correlation of three different surfaces, bearing an error of about 15% with a 1.72\u00d7 resolution upscale from OM to AFM. The OM\u2010based approach brings about significant improvement in topography measurement throughput (equivalent to OM acquisition rate, up to 200 frames per second) and area (\u22481\u2009mm<jats:sup>2<\/jats:sup>). Furthermore, this method is operable even under extreme environments when an in\u2009situ measurement is impossible. Based on such competence, the model's simultaneous application in further specimen analysis, namely surface morphological classification and simulation of dynamic surfaces\u2019 transformation is also demonstrated.<\/jats:p><\/jats:sec>","DOI":"10.1002\/aisy.202200317","type":"journal-article","created":{"date-parts":[[2022,12,20]],"date-time":"2022-12-20T15:45:33Z","timestamp":1671551133000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Predicting AFM Topography from Optical Microscope Images Using Deep\u2010Learning"],"prefix":"10.1002","volume":"5","author":[{"given":"Jaewoo","family":"Jeong","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering Korea Advanced Institute of Science and Technology  291, Daehak-ro Yuseong-gu Daejeon 34141 Republic of Korea"},{"name":"Center for Extreme Thermal Physics and Manufacturing Korea Advanced Institute of Science and Technology  291, Daehak-ro Yuseong-gu Daejeon 34141 Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Taeyeong","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering Korea Advanced Institute of Science and Technology  291, Daehak-ro Yuseong-gu Daejeon 34141 Republic of Korea"},{"name":"Center for Extreme Thermal Physics and Manufacturing Korea Advanced Institute of Science and Technology  291, Daehak-ro Yuseong-gu Daejeon 34141 Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bong Jae","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering Korea Advanced Institute of Science and Technology  291, Daehak-ro Yuseong-gu Daejeon 34141 Republic of Korea"},{"name":"Center for Extreme Thermal Physics and Manufacturing Korea Advanced Institute of Science and Technology  291, Daehak-ro Yuseong-gu Daejeon 34141 Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7880-8657","authenticated-orcid":false,"given":"Jungchul","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering Korea Advanced Institute of Science and Technology  291, Daehak-ro Yuseong-gu Daejeon 34141 Republic of Korea"},{"name":"Center for Extreme Thermal Physics and Manufacturing Korea Advanced Institute of Science and Technology  291, Daehak-ro Yuseong-gu Daejeon 34141 Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2022,12,20]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1039\/C9NR10316C"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/smll.200700527"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms14222"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1002\/smll.202102977"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/aelm.202100684"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1063\/1.4978285"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmapro.2021.04.051"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCST.2018.2879939"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-79139-8"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1002\/jemt.22945"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1002\/smll.202103779"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1002\/adts.201800137"},{"key":"e_1_2_8_14_1","unstructured":"Thorlabs Fast Frame Rate CCD Scientific Camera for Microscopy https:\/\/www.thorlabs.com\/catalogpages\/Obsolete\/2020\/340x-CL.pdf(accessed: November 2022)."},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.joule.2019.05.013"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1021\/acs.nanolett.5b03703"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.vacuum.2022.111101"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/JMEMS.2019.2927466"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-018-0239-0"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-48444-2"},{"key":"e_1_2_8_21_1","doi-asserted-by":"publisher","DOI":"10.1002\/smtd.202100223"},{"key":"e_1_2_8_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/JMEMS.2021.3139094"},{"key":"e_1_2_8_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2528162"},{"key":"e_1_2_8_24_1","unstructured":"X.Glorot Y.Bengio Proc. 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