{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T15:58:02Z","timestamp":1791475082257,"version":"4.3.4"},"reference-count":57,"publisher":"Wiley","issue":"56","license":[{"start":{"date-parts":[[2026,8,8]],"date-time":"2026-08-08T00:00:00Z","timestamp":1786147200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,8,8]],"date-time":"2026-08-08T00:00:00Z","timestamp":1786147200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["advanced.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Advanced Materials"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Tactile sensing and perception are fundamental to intelligent interaction with complex environments, yet most artificial sensing systems rely on continuous signal acquisition and centralized electronic computation, resulting in high data redundancy, latency, and limited robustness. In this research, we introduce mechanically encoded materials (MEM) as a sensing\u2010centric paradigm that embeds perception directly into material architecture. Inspired by biological mechanosensory systems, MEM exploits geometry\u2010force\u2010property coupling to selectively transduce mechanical stimuli into discrete binary outputs, enabling event\u2010driven tactile sensing without continuous sampling or intensive electronic processing. By rational design, MEMs are programmed to respond only when external stimuli exceed predefined thresholds, thereby encoding tactile information such as pressure, stiffness, and curvature into binary representations at the material level. Arrays of MEMs with graded thresholds further enable multi\u2010level discrimination of mechanical stimuli solely through mechanical design. We demonstrate the integration of pressure\u2010, stiffness\u2010, and curvature\u2010sensitive MEMs into a compliant gripper, where proprioceptive and tactile perception emerges locally at the sensing interface without CPU\u2010driven computation. This mechano\u2010encoding strategy reduces data bandwidth and sensing latency while enhancing robustness and adaptability under dynamic conditions. By transforming sensing, encoding, and preliminary computation into intrinsic material functions, MEMs establish a general framework for decentralized tactile perception in next\u2010generation intelligent systems.<\/jats:p>","DOI":"10.1002\/adma.74403","type":"journal-article","created":{"date-parts":[[2026,8,8]],"date-time":"2026-08-08T09:20:54Z","timestamp":1786180854000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Mechanically Encoded Materials for Edge Perception"],"prefix":"10.1002","volume":"38","author":[{"given":"Jiangtao","family":"Su","sequence":"first","affiliation":[{"name":"Innovative Centre for Flexible Devices (iFLEX) Max Planck\u2013NTU Joint Lab For Artificial Senses School of Materials Science and Engineering Nanyang Technological University  Singapore Singapore"},{"name":"Singapore\u2010HUJ Alliance for Research and Enterprise (SHARE) CREATE  Singapore 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