{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T18:58:35Z","timestamp":1790794715518,"version":"4.1.0"},"reference-count":52,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T00:00:00Z","timestamp":1790467200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T00:00:00Z","timestamp":1790467200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["22269025"],"award-info":[{"award-number":["22269025"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["advanced.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Advanced Science"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Flexible sensing technologies based on triboelectric nanogenerators (TENG) have shown promise for wearable electronics and human\u2011machine interaction. However, existing hydrogel\u2011based TENGs suffer from an inherent trade\u2011off between interfacial adhesion and electrical output, and their material recognition capability is compromised in real\u2011wearing environments due to signal variations. Here, the authors propose a smart glove system integrating a dynamic Ag\n                    <jats:sup>+<\/jats:sup>\n                    \u2500S coordinated hydrogel with a machine\u2011learning\u2011based material recognition framework. Inspired by biological allostery, a \u201csulfur\u2011oxygen competitive coordination\u201d switch is designed using Ag\n                    <jats:sup>+<\/jats:sup>\n                    and a bifunctional small molecule, 5\u2010carboxythiophene\u20102\u2010boronic acid (CTBA). By adjusting the Ag\n                    <jats:sup>+<\/jats:sup>\n                    \/CTBA ratio, the hydrogel reversibly switches between a soft, highly adhesive state and a stiff, mechanically robust state. This enables precise modulation of mechanical, adhesive, and triboelectric properties. A lightweight 1D convolutional neural network (WaveformCNN) is developed to classify contact waveforms. The trained model achieves 99.70% accuracy on laboratory\u2011collected data and 93.35% on real\u2011wear glove data, demonstrating cross\u2011scenario generalization. The hydrogel exhibits graded signal output under different finger bending angles and independent five\u2011finger recognition capability. This work establishes a strategy that bridges molecular coordination design and intelligent tactile perception, offering a new paradigm for self\u2010powered electronic skins, autonomous material identification, and adaptive human\u2013environment interaction in complex scenarios.\n                  <\/jats:p>","DOI":"10.1002\/advs.77707","type":"journal-article","created":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T18:00:31Z","timestamp":1790532031000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Sulfur\u2013Oxygen Competitive Coordination Allosteric Hydrogel for Triboelectric Nanogenerator\u2010Based Intelligent Tactile Recognition"],"prefix":"10.1002","author":[{"given":"Shixia","family":"Lan","sequence":"first","affiliation":[{"name":"Yunnan Key Laboratory of Electromagnetic Materials and Devices School of Materials and Energy Yunnan University  Kunming People's Republic of China"},{"name":"Southwest United Graduate School  Kunming People's Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lin","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Software and AI Yunnan University  Kunming People's Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-5251-9928","authenticated-orcid":false,"given":"Yunyun","family":"Dong","sequence":"additional","affiliation":[{"name":"School of Software and AI Yunnan University  Kunming People's Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9538-5772","authenticated-orcid":false,"given":"Yongyun","family":"Mao","sequence":"additional","affiliation":[{"name":"Yunnan Key Laboratory of Electromagnetic Materials and Devices School of Materials and Energy Yunnan University  Kunming People's Republic of China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0180-9648","authenticated-orcid":false,"given":"Wanbiao","family":"Hu","sequence":"additional","affiliation":[{"name":"Yunnan Key Laboratory of Electromagnetic Materials and Devices School of Materials and Energy Yunnan University  Kunming People's Republic of China"},{"name":"Southwest United Graduate School  Kunming People's Republic of China"},{"name":"School of Engineering Yunnan University  Kunming People's Republic of 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