{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T14:55:54Z","timestamp":1786978554739,"version":"build-2736575974"},"reference-count":47,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2023,9,10]],"date-time":"2023-09-10T00:00:00Z","timestamp":1694304000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004189","name":"Max-Planck-Gesellschaft","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004189","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Small"],"published-print":{"date-parts":[[2024,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Bioinspired fibrillar structures are promising for a wide range of disruptive adhesive applications. Especially micro\/nanofibrillar structures on gecko toes can have strong and controllable adhesion and shear on a wide range of surfaces with residual\u2010free, repeatable, self\u2010cleaning, and other unique features. Synthetic dry fibrillar adhesives inspired by such biological fibrils are optimized in different aspects to increase their performance. Previous fibril designs for shear optimization are limited by predefined standard shapes in a narrow range primarily based on human intuition, which restricts their maximum performance. This study combines the machine learning\u2010based optimization and finite\u2010element\u2010method\u2010based shear mechanics simulations to find shear\u2010optimized fibril designs automatically. In addition, fabrication limitations are integrated into the simulations to have more experimentally relevant results. The computationally discovered shear\u2010optimized structures are fabricated, experimentally validated, and compared with the simulations. The results show that the computed shear\u2010optimized fibrils perform better than the predefined standard fibril designs. This design optimization method can be used in future real\u2010world shear\u2010based gripping or nonslip surface applications, such as robotic pick\u2010and\u2010place grippers, climbing robots, gloves, electronic devices, and medical and wearable devices.<\/jats:p>","DOI":"10.1002\/smll.202304437","type":"journal-article","created":{"date-parts":[[2023,9,10]],"date-time":"2023-09-10T22:50:31Z","timestamp":1694386231000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Machine Learning\u2010Based Shear Optimal Adhesive Microstructures with Experimental Validation"],"prefix":"10.1002","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6328-7868","authenticated-orcid":false,"given":"Cem Balda","family":"Dayan","sequence":"first","affiliation":[{"name":"Physical Intelligence Department Max Planck Institute for Intelligent Systems  70569 Stuttgart 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