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Among them, the emerging spiderweb\u2010inspired structures have shown potential for creating artificial microstructures with enhanced tunability and functionality. However, the restricted structural elasticity of current spiderweb\u2010like designs causes limited mechanical performances, especially at the micro\/nanoscale. Here, we employ machine learning and kirigami micro\/nanofabrication to develop an ultraelastic microweb. Data\u2010driven optimizations enable efficient transformation of the natural configuration with limited elasticity into an artificial design with ultrahigh elasticity, achieving a remarkably low stiffness of \u223c0.188 nN\/nm. Both mechanical simulations and experimental characterizations confirm the superior mechanical properties of the optimized microweb, conclusively validating the optimization model with the combination of genetic algorithm and deep learning. Further dynamic vibration analyses reveal ultrasensitive low\u2010frequency mechanical resonances of the microweb, benefited from the greatly enhanced structural elasticity. For proof\u2010of\u2010concept demonstrations, the mass sensing of micro\u2010objects with a high sensitivity of \u22120.801\u00a0kHz\/pg and diversified vibration\u2010resolvable information encryption are realized, respectively. This work establishes a generalizable strategy for creating highly elastic microstructures, with broad implications in the areas of mechanical micro\u2010\/nano\u2010sensors, micro\u2010\/nano\u2010electro\u2010mechanical systems (MEMS\/NEMS), mechanical metamaterials, biological manipulations, information encryptions, and beyond.<\/jats:p>","DOI":"10.1002\/adma.202519941","type":"journal-article","created":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T10:31:01Z","timestamp":1769682661000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Machine Learning\u2010Assisted Ultraelastic and Vibration\u2010Resolvable Microwebs"],"prefix":"10.1002","volume":"38","author":[{"given":"Haozhe","family":"Sun","sequence":"first","affiliation":[{"name":"State Key Laboratory of Chips and Systems for Advanced Light Field Display School of Physics Beijing Institute of Technology Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0467-9191","authenticated-orcid":false,"given":"Xiaorong","family":"Hong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Chips and Systems for Advanced Light Field Display School of Physics Beijing Institute of Technology Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jijie","family":"Tang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Chips and Systems for Advanced Light Field Display School of Physics Beijing Institute of Technology Beijing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weikang","family":"Dong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Chips and Systems for Advanced Light Field Display School of Physics Beijing Institute of Technology Beijing 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