C.E. Okwudire, H.V. Madhyastha, Distributed manufacturing for and by the masses. Science 372, 341–342 (2021). https://doi.org/10.1126/science.abg4924

P. Timmers, There will be no global 6G unless we resolve sovereignty concerns in 5G governance. Nat. Electron. 3, 10–12 (2020). https://doi.org/10.1038/s41928-020-0366-3

C. Chen, S. Ding, J. Wang, Digital health for aging populations. Nat. Med. 29, 1623–1630 (2023). https://doi.org/10.1038/s41591-023-02391-8

Y. Luo, M.R. Abidian, J.-H. Ahn, D. Akinwande, A.M. Andrews et al., Technology roadmap for flexible sensors. ACS Nano 17, 5211–5295 (2023). https://doi.org/10.1021/acsnano.2c12606

Y. Wang, M.L. Adam, Y. Zhao, W. Zheng, L. Gao et al., Machine learning-enhanced flexible mechanical sensing. Nano-Micro Lett. 15, 55 (2023). https://doi.org/10.1007/s40820-023-01013-9

B. Feng, T. Sun, W. Wang, Y. Xiao, J. Huo et al., Venation-mimicking, ultrastretchable, room-temperature-attachable metal tapes for integrated electronic skins. Adv. Mater. 35, 2208568 (2023). https://doi.org/10.1002/adma.202208568

J. Luo, W. Gao, Z.L. Wang, The triboelectric nanogenerator as an innovative technology toward intelligent sports. Adv. Mater. 33, 2004178 (2021). https://doi.org/10.1002/adma.202004178

B. Feng, G. Zou, W. Wang, M. Dong, Y. Xiao et al., A programmable, gradient-composition strategy producing synergistic and ultrahigh sensitivity amplification for flexible pressure sensing. Nano Energy 74, 104847 (2020). https://doi.org/10.1016/j.nanoen.2020.104847

J. Luo, Z. Wang, L. Xu, A.C. Wang, K. Han et al., Flexible and durable wood-based triboelectric nanogenerators for self-powered sensing in athletic big data analytics. Nat. Commun. 10, 5147 (2019). https://doi.org/10.1038/s41467-019-13166-6

M. Wang, Y. Luo, T. Wang, C. Wan, L. Pan et al., Artificial skin perception. Adv. Mater. 33, 2003014 (2021). https://doi.org/10.1002/adma.202003014

F. Sun, Q. Lu, S. Feng, T. Zhang, Flexible artificial sensory systems based on neuromorphic devices. ACS Nano 15, 3875–3899 (2021). https://doi.org/10.1021/acsnano.0c10049

C. Yang, B. Sun, G. Zhou, T. Guo, C. Ke et al., Photoelectric memristor-based machine vision for artificial intelligence applications. ACS Mater. Lett. 5, 504–526 (2023). https://doi.org/10.1021/acsmaterialslett.2c00911

G. Cao, P. Meng, J. Chen, H. Liu, R. Bian et al., 2D material based synaptic devices for neuromorphic computing. Adv. Funct. Mater. 31, 2005443 (2021). https://doi.org/10.1002/adfm.202005443

W. Huang, X. Xia, C. Zhu, P. Steichen, W. Quan et al., Memristive artificial synapses for neuromorphic computing. Nano-Micro Lett. 13, 85 (2021). https://doi.org/10.1007/s40820-021-00618-2

X. Wang, H. Yang, E. Li, C. Cao, W. Zheng et al., Stretchable transistor-structured artificial synapses for neuromorphic electronics. Small 19, 2205395 (2023). https://doi.org/10.1002/smll.202205395

B. Shih, D. Shah, J. Li, T.G. Thuruthel, Y.-L. Park et al., Electronic skins and machine learning for intelligent soft robots. Sci. Robot. 5, eaaz9239 (2020). https://doi.org/10.1126/scirobotics.aaz9239

M. Wang, T. Wang, Y. Luo, K. He, L. Pan et al., Fusing stretchable sensing technology with machine learning for human–machine interfaces. Adv. Funct. Mater. 31, 2008807 (2021). https://doi.org/10.1002/adfm.202008807

S.H. Kwon, L. Dong, Flexible sensors and machine learning for heart monitoring. Nano Energy 102, 107632 (2022). https://doi.org/10.1016/j.nanoen.2022.107632

A. Alagumalai, W. Shou, O. Mahian, M. Aghbashlo, M. Tabatabaei et al., Self-powered sensing systems with learning capability. Joule 6, 1475–1500 (2022). https://doi.org/10.1016/j.joule.2022.06.001

H. Liu, W. Dong, Y. Li, F. Li, J. Geng et al., An epidermal sEMG tattoo-like patch as a new human–machine interface for patients with loss of voice. Microsyst. Nanoeng. 6, 16 (2020). https://doi.org/10.1038/s41378-019-0127-5

S. Chun, W. Son, H. Kim, S.K. Lim, C. Pang et al., Self-powered pressure- and vibration-sensitive tactile sensors for learning technique-based neural finger skin. Nano Lett. 19, 3305–3312 (2019). https://doi.org/10.1021/acs.nanolett.9b00922

R. Kamaleswaran, R. Mahajan, O. Akbilgic, A robust deep convolutional neural network for the classification of abnormal cardiac rhythm using single lead electrocardiograms of variable length. Physiol. Meas. 39, 035006 (2018). https://doi.org/10.1088/1361-6579/aaaa9d

B.-H. Kung, P.-Y. Hu, C.-C. Huang, C.-C. Lee, C.-Y. Yao et al., An efficient ECG classification system using resource-saving architecture and random forest. IEEE J. Biomed. Health Inform. 25, 1904–1914 (2021). https://doi.org/10.1109/JBHI.2020.3035191

Y. Li, G. Shen, Advances in optoelectronic artificial synapses. Cell Rep. Phys. Sci. 3, 101037 (2022). https://doi.org/10.1016/j.xcrp.2022.101037

F. Zhou, Z. Zhou, J. Chen, T.H. Choy, J. Wang et al., Optoelectronic resistive random access memory for neuromorphic vision sensors. Nat. Nanotechnol. 14, 776–782 (2019). https://doi.org/10.1038/s41565-019-0501-3

M.A. Zidan, J.P. Strachan, W.D. Lu, The future of electronics based on memristive systems. Nat. Electron. 1, 22–29 (2018). https://doi.org/10.1038/s41928-017-0006-8

Y. Van De Burgt, A. Melianas, S.T. Keene, G. Malliaras, A. Salleo, Organic electronics for neuromorphic computing. Nat. Electron. 1, 386–397 (2018). https://doi.org/10.1038/s41928-018-0103-3

M. Tsodyks, C. Gilbert, Neural networks and perceptual learning. Nature 431, 775–781 (2004). https://doi.org/10.1038/nature03013

D. Strukov, G. Indiveri, J. Grollier, S. Fusi, Building brain-inspired computing. Nat. Commun. 10, 4838 (2019). https://doi.org/10.1038/s41467-019-12521-x

C. Jiang, J. Liu, L. Yang, J. Gong, H. Wei et al., A flexible artificial sensory nerve enabled by nanop-assembled synaptic devices for neuromorphic tactile recognition. Adv. Sci. 9, 2106124 (2022). https://doi.org/10.1002/advs.202106124

H. Wan, Y. Cao, L.-W. Lo, J. Zhao, N. Sepúlveda et al., Flexible carbon nanotube synaptic transistor for neurological electronic skin applications. ACS Nano 14, 10402–10412 (2020). https://doi.org/10.1021/acsnano.0c04259

D.-G. Seo, Y. Lee, G.-T. Go, M. Pei, S. Jung et al., Versatile neuromorphic electronics by modulating synaptic decay of single organic synaptic transistor: from artificial neural networks to neuro-prosthetics. Nano Energy 65, 104035 (2019). https://doi.org/10.1016/j.nanoen.2019.104035

S.W. Cho, C. Jo, Y.-H. Kim, S.K. Park, Progress of materials and devices for neuromorphic vision sensors. Nano-Micro Lett. 14, 203 (2022). https://doi.org/10.1007/s40820-022-00945-y

N. Dai, I.M. Lei, Z. Li, Y. Li, P. Fang et al., Recent advances in wearable electromechanical sensors—moving towards machine learning-assisted wearable sensing systems. Nano Energy 105, 108041 (2023). https://doi.org/10.1016/j.nanoen.2022.108041

L. Zhang, S. Zhang, C. Wang, Q. Zhou, H. Zhang et al., Highly sensitive capacitive flexible pressure sensor based on a high-permittivity MXene nanocomposite and 3D network electrode for wearable electronics. ACS Sens. 6, 2630–2641 (2021). https://doi.org/10.1021/acssensors.1c00484

J.-L. Meng, T.-Y. Wang, L. Chen, Q.-Q. Sun, H. Zhu et al., Energy-efficient flexible photoelectric device with 2D/0D hybrid structure for bio-inspired artificial heterosynapse application. Nano Energy 83, 105815 (2021). https://doi.org/10.1016/j.nanoen.2021.105815

L. Zhang, Z. Li, J. Yang, J. Zhou, Y. Zhang et al., A fully integrated flexible tunable chemical sensor based on gold-modified indium selenide nanosheets. ACS Sens. 7, 1183–1193 (2022). https://doi.org/10.1021/acssensors.2c00281

B.C. Jang, S. Kim, S.Y. Yang, J. Park, J.-H. Cha et al., Polymer analog memristive synapse with atomic-scale conductive filament for flexible neuromorphic computing system. Nano Lett. 19, 839–849 (2019). https://doi.org/10.1021/acs.nanolett.8b04023

Z. Chen, R. Yu, X. Yu, E. Li, C. Wang et al., Bioinspired artificial motion sensory system for rotation recognition and rapid self-protection. ACS Nano 16, 19155–19164 (2022). https://doi.org/10.1021/acsnano.2c08328

Y. Pei, L. Yan, Z. Wu, J. Lu, J. Zhao et al., Artificial visual perception nervous system based on low-dimensional material photoelectric memristors. ACS Nano 15, 17319–17326 (2021). https://doi.org/10.1021/acsnano.1c04676

X. Wang, K.H. Chan, Y. Cheng, T. Ding, T. Li et al., Light-driven, thin-film robots capable of integrated perception and motility. Adv. Mater. 32, 2000351 (2020). https://doi.org/10.1002/adma.202000351

P. Tan, X. Han, Y. Zou, X. Qu, J. Xue et al., Self-powered gesture recognition wristband enabled by machine learning for full keyboard and multicommand input. Adv. Mater. 34, 2200793 (2022). https://doi.org/10.1002/adma.202200793

K. Zhang, Z. Li, J. Zhang, D. Zhao, Y. Pi et al., Biodegradable smart face masks for machine learning-assisted chronic respiratory disease diagnosis. ACS Sens. 7, 3135–3143 (2022). https://doi.org/10.1021/acssensors.2c01628

M. Zhu, Z. Sun, C. Lee, Soft modular glove with multimodal sensing and augmented haptic feedback enabled by materials’ multifunctionalities. ACS Nano 16, 14097–14110 (2022). https://doi.org/10.1021/acsnano.2c04043

V. Mnih, K. Kavukcuoglu, D. Silver, A.A. Rusu, J. Veness et al., Human-level control through deep reinforcement learning. Nature 518, 529–533 (2015). https://doi.org/10.1038/nature14236

D. Silver, A. Huang, C.J. Maddison, A. Guez, L. Sifre et al., Mastering the game of Go with deep neural networks and tree search. Nature 529, 484–489 (2016). https://doi.org/10.1038/nature16961

M.I. Jordan, T.M. Mitchell, Machine learning: trends, perspectives, and prospects. Science 349, 255–260 (2015). https://doi.org/10.1126/science.aaa8415

F. Cui, Y. Yue, Y. Zhang, Z. Zhang, H.S. Zhou, Advancing biosensors with machine learning. ACS Sens. 5, 3346–3364 (2020). https://doi.org/10.1021/acssensors.0c01424

Y.H. Jung, S.K. Hong, H.S. Wang, J.H. Han, T.X. Pham et al., Flexible piezoelectric acoustic sensors and machine learning for speech processing. Adv. Mater. 32, 1904020 (2020). https://doi.org/10.1002/adma.201904020

Y. LeCun, Y. Bengio, G. Hinton, Deep learning. Nature 521, 436–444 (2015). https://doi.org/10.1038/nature14539

C. Du, G. Zou, B. Feng, J. Huo, A. Zhanwen et al., Predicting effective thermal conductivity of sintered silver by microstructural-simulation-based machine learning. J. Electron. Mater. 52, 2347–2358 (2023). https://doi.org/10.1007/s11664-022-10172-1

M. Mahmood, D. Mzurikwao, Y.-S. Kim, Y. Lee, S. Mishra et al., Fully portable and wireless universal brain–machine interfaces enabled by flexible scalp electronics and deep learning algorithm. Nat. Mach. Intell. 1, 412–422 (2019). https://doi.org/10.1038/s42256-019-0091-7

L. Li, S. Jiang, P.B. Shull, G. Gu, SkinGest: artificial skin for gesture recognition via filmy stretchable strain sensors. Adv. Robot. 32, 1112–1121 (2018). https://doi.org/10.1080/01691864.2018.1490666

C.C. Vu, J. Kim, Highly elastic capacitive pressure sensor based on smart textiles for full-range human motion monitoring. Sens. Actuators A Phys. 314, 112029 (2020). https://doi.org/10.1016/j.sna.2020.112029

V.A. Ho, M. Makikawa, S. Hirai, Flexible fabric sensor toward a humanoid robot’s skin: fabrication, characterization, and perceptions. IEEE Sens. J. 13, 4065–4080 (2013). https://doi.org/10.1109/JSEN.2013.2272336

J. Gu, Z. Wang, J. Kuen, L. Ma, A. Shahroudy et al., Recent advances in convolutional neural networks. Pattern Recognit. 77, 354–377 (2018). https://doi.org/10.1016/j.patcog.2017.10.013

C. Du, G. Zou, A. Zhanwen, B. Lu, B. Feng et al., Highly accurate and efficient prediction of effective thermal conductivity of sintered silver based on deep learning method. Int. J. Heat Mass Transf. 201, 123654 (2023). https://doi.org/10.1016/j.ijheatmasstransfer.2022.123654

F. Wen, Z. Sun, T. He, Q. Shi, M. Zhu et al., Machine learning glove using self-powered conductive superhydrophobic triboelectric textile for gesture recognition in VR/AR applications. Adv. Sci. 7, 2000261 (2020). https://doi.org/10.1002/advs.202000261

A. Graves, A. Mohamed, G. Hinton, Speech recognition with deep recurrent neural networks, in 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (IEEE, Vancouver, BC, Canada, 2013), pp. 6645–6649. https://doi.org/10.1109/ICASSP.2013.6638947

N. Raeis-Hosseini, Y. Park, J.-S. Lee, Flexible artificial synaptic devices based on collagen from fish protein with spike-timing-dependent plasticity. Adv. Funct. Mater. 28, 1800553 (2018). https://doi.org/10.1002/adfm.201800553

D. Sarkar, J. Tao, W. Wang, Q. Lin, M. Yeung et al., Mimicking biological synaptic functionality with an indium phosphide synaptic device on silicon for scalable neuromorphic computing. ACS Nano 12, 1656–1663 (2018). https://doi.org/10.1021/acsnano.7b08272

G.S. Doetsch, Patterns in the brain: neuronal population coding in the somatosensory system. Physiol. Behav. 69, 187 (2000). https://doi.org/10.1016/S0031-9384(00)00201-8

S.L. Jackman, W.G. Regehr, The mechanisms and functions of synaptic facilitation. Neuron 94, 447–464 (2017). https://doi.org/10.1016/j.neuron.2017.02.047

K. Kim, C.-L. Chen, Q. Truong, A.M. Shen, Y. Chen, A carbon nanotube synapse with dynamic logic and learning. Adv. Mater. 25, 1693–1698 (2013). https://doi.org/10.1002/adma.201203116

Y. Park, J.-S. Lee, Artificial synapses with short- and long-term memory for spiking neural networks based on renewable materials. ACS Nano 11, 8962–8969 (2017). https://doi.org/10.1021/acsnano.7b03347

Y. He, Y. Yang, S. Nie, R. Liu, Q. Wan, Electric-double-layer transistors for synaptic devices and neuromorphic systems. J. Mater. Chem. C 6, 5336–5352 (2018). https://doi.org/10.1039/C8TC00530C

A.E. Pereda, Electrical synapses and their functional interactions with chemical synapses. Nat. Rev. Neurosci. 15, 250–263 (2014). https://doi.org/10.1038/nrn3708

Q. Wan, M.T. Sharbati, J.R. Erickson, Y. Du, F. Xiong, Emerging artificial synaptic devices for neuromorphic computing. Adv. Mater. Technol. 4, 1900037 (2019). https://doi.org/10.1002/admt.201900037

Y. Wang, L. Yin, W. Huang, Y. Li, S. Huang et al., Optoelectronic synaptic devices for neuromorphic computing. Adv. Intell. Syst. 3, 2000099 (2021). https://doi.org/10.1002/aisy.202000099

H. Park, Y. Lee, N. Kim, D. Seo, G. Go et al., Flexible neuromorphic electronics for computing, soft robotics, and neuroprosthetics. Adv. Mater. 32, 1903558 (2020). https://doi.org/10.1002/adma.201903558

S.H. Sung, Y. Jeong, J.W. Oh, H.-J. Shin, J.H. Lee et al., Bio-plausible memristive neural components towards hardware implementation of brain-like intelligence. Mater. Today 62, 251–270 (2023). https://doi.org/10.1016/j.mattod.2022.11.022

R. Waser, R. Dittmann, G. Staikov, K. Szot, Redox-based resistive switching memories–nanoionic mechanisms, prospects, and challenges. Adv. Mater. 21, 2632–2663 (2009). https://doi.org/10.1002/adma.200900375

T. Zhang, K. Yang, X. Xu, Y. Cai, Y. Yang et al., Memristive devices and networks for brain-inspired computing. Phys. Status Solidi RRL 13, 1900029 (2019). https://doi.org/10.1002/pssr.201900029

Z. Wen, D. Wu, Ferroelectric tunnel junctions: modulations on the potential barrier. Adv. Mater. 32, 1904123 (2019). https://doi.org/10.1002/adma.201904123

J. Li, C. Ge, J. Du, C. Wang, G. Yang et al., Reproducible ultrathin ferroelectric domain switching for high-performance neuromorphic computing. Adv. Mater. 32, 1905764 (2020). https://doi.org/10.1002/adma.201905764

S. Boyn, J. Grollier, G. Lecerf, B. Xu, N. Locatelli et al., Learning through ferroelectric domain dynamics in solid-state synapses. Nat. Commun. 8, 14736 (2017). https://doi.org/10.1038/ncomms14736

A. Chanthbouala, V. Garcia, R.O. Cherifi, K. Bouzehouane, S. Fusil et al., A ferroelectric memristor. Nat. Mater. 11, 860–864 (2012). https://doi.org/10.1038/nmat3415

C. Ríos, M. Stegmaier, P. Hosseini, D. Wang, T. Scherer et al., Integrated all-photonic non-volatile multi-level memory. Nat. Photon. 9, 725–732 (2015). https://doi.org/10.1038/nphoton.2015.182

Y. Jung, S.-H. Lee, A.T. Jennings, R. Agarwal, Core−shell heterostructured phase change nanowire multistate memory. Nano Lett. 8, 2056–2062 (2008). https://doi.org/10.1021/nl801482z

G.W. Burr, B.N. Kurdi, J.C. Scott, C.H. Lam, K. Gopalakrishnan et al., Overview of candidate device technologies for storage-class memory. IBM J. Res. Dev. 52, 449–464 (2008). https://doi.org/10.1147/rd.524.0449

Y. Van De Burgt, E. Lubberman, E.J. Fuller, S.T. Keene, G.C. Faria et al., A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing. Nat. Mater. 16, 414–418 (2017). https://doi.org/10.1038/nmat4856

B.K. You, J.M. Kim, D.J. Joe, K. Yang, Y. Shin et al., Reliable memristive switching memory devices enabled by densely packed silver nanocone arrays as electric-field concentrators. ACS Nano 10, 9478–9488 (2016). https://doi.org/10.1021/acsnano.6b04578

S. Dai, Y. Zhao, Y. Wang, J. Zhang, L. Fang et al., Recent advances in transistor-based artificial synapses. Adv. Funct. Mater. 29, 1903700 (2019). https://doi.org/10.1002/adfm.201903700

Q. Zhao, W. Wang, F. Carrascoso-Plana, W. Jie, T. Wang et al., The role of traps in the photocurrent generation mechanism in thin InSe photodetectors. Mater. Horiz. 7, 252–262 (2020). https://doi.org/10.1039/C9MH01020C

T. Han, S. Tan, J. Xue, L. Meng, J. Lee et al., Interface and defect engineering for metal halide perovskite optoelectronic devices. Adv. Mater. 31, 1803515 (2019). https://doi.org/10.1002/adma.201803515

S.H. Kim, K. Hong, W. Xie, K.H. Lee, S. Zhang et al., Electrolyte-gated transistors for organic and printed electronics. Adv. Mater. 25, 1822–1846 (2013). https://doi.org/10.1002/adma.201202790

H. Du, X. Lin, Z. Xu, D. Chu, Electric double-layer transistors: a review of recent progress. J. Mater. Sci. 50, 5641–5673 (2015). https://doi.org/10.1007/s10853-015-9121-y

Y. He, L. Zhu, Y. Zhu, C. Chen, S. Jiang et al., Recent progress on emerging transistor-based neuromorphic devices. Adv. Intell. Syst. 3, 2000210 (2021). https://doi.org/10.1002/aisy.202000210

Y. Nishitani, Y. Kaneko, M. Ueda, E. Fujii, A. Tsujimura, Dynamic observation of brain-like learning in a ferroelectric synapse device. Jpn. J. Appl. Phys. 52, 04CE06 (2013). https://doi.org/10.7567/JJAP.52.04CE06

Q. Gao, F. Sun, Y. Li, L. Li, M. Liu et al., Biological tissue-inspired ultrasoft, ultrathin, and mechanically enhanced microfiber composite hydrogel for flexible bioelectronics. Nano-Micro Lett. 15, 139 (2023). https://doi.org/10.1007/s40820-023-01096-4

K. Chen, K. Liang, H. Liu, R. Liu, Y. Liu et al., Skin-inspired ultra-tough supramolecular multifunctional hydrogel electronic skin for human–machine interaction. Nano-Micro Lett. 15, 102 (2023). https://doi.org/10.1007/s40820-023-01084-8

X. Meng, C. Cai, B. Luo, T. Liu, Y. Shao et al., Rational design of cellulosic triboelectric materials for self-powered wearable electronics. Nano-Micro Lett. 15, 124 (2023). https://doi.org/10.1007/s40820-023-01094-6

F. Liu, S. Deswal, A. Christou, Y. Sandamirskaya, M. Kaboli et al., Neuro-inspired electronic skin for robots. Sci. Robot. 7, abl7344 (2022). https://doi.org/10.1126/scirobotics.abl7344

H. Niu, H. Zhang, W. Yue, S. Gao, H. Kan et al., Micro-nano processing of active layers in flexible tactile sensors via template methods: a review. Small 17, 2100804 (2021). https://doi.org/10.1002/smll.202100804

T. Sun, B. Feng, J. Huo, Y. Xiao, J. Peng et al., Switching ultra-stretchability and sensitivity in metal films for electronic skins: a pufferfish-inspired, interlayer regulation strategy. Mater. Horiz. 10, 2525 (2023). https://doi.org/10.1039/D3MH00252G

Z. Shen, F. Liu, S. Huang, H. Wang, C. Yang et al., Progress of flexible strain sensors for physiological signal monitoring. Biosens. Bioelectron. 211, 114298 (2022). https://doi.org/10.1016/j.bios.2022.114298

S. Li, X. Xiao, J. Hu, M. Dong, Y. Zhang et al., Recent advances of carbon-based flexible strain sensors in physiological signal monitoring. ACS Appl. Electron. Mater. 2, 2282–2300 (2020). https://doi.org/10.1021/acsaelm.0c00292

X. Zhao, Z. Deng, Y. Long, B. Feng, X. Jiang et al., Multifunctional sensing platform with pulsed-laser-deposited silver nanoporous structures. Sens. Actuators A Phys. 293, 136–144 (2019). https://doi.org/10.1016/j.sna.2019.04.045

D. Kang, Ultrasensitive mechanical crack-based sensor inspired by the spider sensory system. Nature 516, 222–226 (2014). https://doi.org/10.1038/nature14002

B. Feng, X. Jiang, G. Zou, W. Wang, T. Sun et al., Nacre-inspired, liquid metal-based ultrasensitive electronic skin by spatially regulated cracking strategy. Adv. Funct. Mater. 31, 2102359 (2021). https://doi.org/10.1002/adfm.202102359

H. Sun, K. Dai, W. Zhai, Y. Zhou, J. Li et al., A highly sensitive and stretchable yarn strain sensor for human motion tracking utilizing a wrinkle-assisted crack structure. ACS Appl. Mater. Interfaces 11, 36052–36062 (2019). https://doi.org/10.1021/acsami.9b09229

Y. Wu, H. Liu, S. Chen, X. Dong, P. Wang et al., Channel crack-designed Gold@PU sponge for highly elastic piezoresistive sensor with excellent detectability. ACS Appl. Mater. Interfaces 9, 20098–20105 (2017). https://doi.org/10.1021/acsami.7b04605

Y. Zhou, P. Zhan, M. Ren, G. Zheng, K. Dai et al., Significant stretchability enhancement of a crack-based strain sensor combined with high sensitivity and superior durability for motion monitoring. ACS Appl. Mater. Interfaces 11, 7405–7414 (2019). https://doi.org/10.1021/acsami.8b20768

D. Zhang, Y. Zhong, Y. Wu, X. Zhang, M.D. Dickey et al., Liquid metal elastomer with flytrap-inspired pillar structure for stress sensing. Compos. Sci. Technol. 216, 109066 (2021). https://doi.org/10.1016/j.compscitech.2021.109066

Y. Zhao, M. Ren, Y. Shang, J. Li, S. Wang et al., Ultra-sensitive and durable strain sensor with sandwich structure and excellent anti-interference ability for wearable electronic skins. Compos. Sci. Technol. 200, 108448 (2020). https://doi.org/10.1016/j.compscitech.2020.108448

K.-H. Kim, T.M. Nguyen, S.-H. Ha, E.J. Choi, Y. Kim et al., M13 bacteriophage-assisted morphological engineering of crack-based sensors for highly sensitive and wide linear range strain sensing. ACS Appl. Mater. Interfaces 12, 45590–45601 (2020). https://doi.org/10.1021/acsami.0c13307

Y. Zhao, W. Gao, K. Dai, S. Wang, Z. Yuan et al., Bioinspired multifunctional photonic–electronic smart skin for ultrasensitive health monitoring, for visual and self-powered sensing. Adv. Mater. 33, 2102332 (2021). https://doi.org/10.1002/adma.202102332

Z. Zhou, K. Chen, X. Li, S. Zhang, Y. Wu et al., Sign-to-speech translation using machine-learning-assisted stretchable sensor arrays. Nat. Electron. 3, 571–578 (2020). https://doi.org/10.1038/s41928-020-0428-6

T. Bu, T. Xiao, Z. Yang, G. Liu, X. Fu et al., Stretchable triboelectric-photonic smart skin for tactile and gesture sensing. Adv. Mater. 30, 1800066 (2018). https://doi.org/10.1002/adma.201800066

S. Pyo, J. Lee, K. Bae, S. Sim, J. Kim, Recent progress in flexible tactile sensors for human-interactive systems: from sensors to advanced applications. Adv. Mater. 33, 2005902 (2021). https://doi.org/10.1002/adma.202005902

Z. Shi, L. Meng, X. Shi, H. Li, J. Zhang et al., Morphological engineering of sensing materials for flexible pressure sensors and artificial intelligence applications. Nano-Micro Lett. 14, 141 (2022). https://doi.org/10.1007/s40820-022-00874-w

J.H. Lee, J.S. Heo, Y. Kim, J. Eom, H.J. Jung et al., A behavior-learned cross-reactive sensor matrix for intelligent skin perception. Adv. Mater. 32, 2000969 (2020). https://doi.org/10.1002/adma.202000969

W. Zhong, C. Liu, Q. Liu, L. Piao, H. Jiang et al., Ultrasensitive wearable pressure sensors assembled by surface-patterned polyolefin elastomer nanofiber membrane interpenetrated with silver nanowires. ACS Appl. Mater. Interfaces 10, 42706–42714 (2018). https://doi.org/10.1021/acsami.8b12363

M. Zhu, Y. Yue, Y. Cheng, Y. Zhang, J. Su et al., Hollow MXene sphere/reduced graphene aerogel composites for piezoresistive sensor with ultra-high sensitivity. Adv. Electron. Mater. 6, 1901064 (2020). https://doi.org/10.1002/aelm.201901064

S. Pyo, J.-I. Lee, M.-O. Kim, T. Chung, Y. Oh et al., Development of a flexible three-axis tactile sensor based on screen-printed carbon nanotube-polymer composite. J. Micromech. Microeng. 24, 075012 (2014). https://doi.org/10.1088/0960-1317/24/7/075012

S. Han, C. Liu, Z. Huang, J. Zheng, H. Xu et al., High-performance pressure sensors based on 3D microstructure fabricated by a facile transfer technology. Adv. Mater. Technol. 4, 1800640 (2019). https://doi.org/10.1002/admt.201800640

M.-O. Kim, S. Pyo, Y. Oh, Y. Kang, K.-H. Cho et al., Flexible and multi-directional piezoelectric energy harvester for self-powered human motion sensor. Smart Mater. Struct. 27, 035001 (2018). https://doi.org/10.1088/1361-665X/aaa722

J. Zhu, Y. Zhang, G. Zheng, Y. Ji, K. Dai et al., Microribbon structured polyvinylidene fluoride with high-performance piezoelectricity for sensing application. ACS Appl. Polym. Mater. 3, 2411–2419 (2021). https://doi.org/10.1021/acsapm.1c00012

Y. Qi, M.C. McAlpine, Nanotechnology-enabled flexible and biocompatible energy harvesting. Energy Environ. Sci. 3, 1275 (2010). https://doi.org/10.1039/c0ee00137f

M. Xie, Y. Zhang, M.J. Kraśny, C. Bowen, H. Khanbareh et al., Flexible and active self-powered pressure, shear sensors based on freeze casting ceramic–polymer composites. Energy Environ. Sci. 11, 2919–2927 (2018). https://doi.org/10.1039/C8EE01551A

A. El Kacimi, E. Pauliac-Vaujour, J. Eymery, Flexible capacitive piezoelectric sensor with vertically aligned ultralong GaN wires. ACS Appl. Mater. Interfaces 10, 4794–4800 (2018). https://doi.org/10.1021/acsami.7b15649

T. Yang, H. Pan, G. Tian, B. Zhang, D. Xiong et al., Hierarchically structured PVDF/ZnO core–shell nanofibers for self-powered physiological monitoring electronics. Nano Energy 72, 104706 (2020). https://doi.org/10.1016/j.nanoen.2020.104706

Y. Liu, J.J.S. Norton, R. Qazi, Z. Zou, K.R. Ammann et al., Epidermal mechano-acoustic sensing electronics for cardiovascular diagnostics and human–machine interfaces. Sci. Adv. 2, e1601185 (2016). https://doi.org/10.1126/sciadv.1601185

X. Chen, Q. Zeng, J. Shao, S. Li, X. Li et al., Channel-crack-designed suspended sensing membrane as a fully flexible vibration sensor with high sensitivity and dynamic range. ACS Appl. Mater. Interfaces 13, 34637–34647 (2021). https://doi.org/10.1021/acsami.1c09963

Y.-F. Liu, Q. Liu, Y.-Q. Li, P. Huang, J.-Y. Yao et al., Spider-inspired ultrasensitive flexible vibration sensor for multifunctional sensing. ACS Appl. Mater. Interfaces 12, 30871–30881 (2020). https://doi.org/10.1021/acsami.0c08884

K. Lee, X. Ni, J.Y. Lee, H. Arafa, D.J. Pe et al., Mechano-acoustic sensing of physiological processes and body motions via a soft wireless device placed at the suprasternal notch. Nat. Biomed. Eng. 4, 148–158 (2019). https://doi.org/10.1038/s41551-019-0480-6

Y. Li, Y. Liao, Z. Su, Graphene-functionalized polymer composites for self-sensing of ultrasonic waves: an initiative towards “sensor-free” structural health monitoring. Compos. Sci. Technol. 168, 203–213 (2018). https://doi.org/10.1016/j.compscitech.2018.09.021

M. Liu, Z. Zeng, H. Xu, Y. Liao, L. Zhou et al., Applications of a nanocomposite-inspired in-situ broadband ultrasonic sensor to acousto-ultrasonics-based passive and active structural health monitoring. Ultrasonics 78, 166–174 (2017). https://doi.org/10.1016/j.ultras.2017.03.007

J. Huo, Y. Xiao, T. Sun, G. Zou, D. Shen et al., Femtosecond laser irradiation-mediated MoS2–metal contact engineering for high-performance field-effect transistors and photodetectors. ACS Appl. Mater. Interfaces 13, 54246–54257 (2021). https://doi.org/10.1021/acsami.1c12685

T. Sun, J. Huo, Y. Xiao, L. Liu, B. Feng et al., Atomic bonding-engineered heterogeneous integration of semiconductor nanowires by femtosecond laser irradiation for a miniaturized photodetector. Appl. Surf. Sci. 575, 151709 (2022). https://doi.org/10.1016/j.apsusc.2021.151709

J. Huo, G. Zou, Y. Xiao, T. Sun, B. Feng et al., High performance 1D–2D CuO/MoS2 photodetectors enhanced by femtosecond laser-induced contact engineering. Mater. Horiz. 10, 524–535 (2023). https://doi.org/10.1039/D2MH01088G

J. Huo, G. Zou, Y. Xiao, T. Sun, B. Feng et al., Multifunctional van der Waals heterostructures enabled by femtosecond laser-controlled band alignment engineering. Nano Energy 113, 108548 (2023). https://doi.org/10.1016/j.nanoen.2023.108548

M. Naqi, M. Kaniselvan, S. Choo, G. Han, S. Kang et al., Ultrasensitive multilayer MoS2-based photodetector with permanently grounded gate effect. Adv. Electron. Mater. 6, 1901256 (2020). https://doi.org/10.1002/aelm.201901256

M.Z. Nawaz, L. Xu, X. Zhou, M. Javed, J. Wang et al., Synergistic effect of hybrid CdSe nanobelt/PbI2 flake heterojunction toward drastic performance flexible photodetectors. ACS Appl. Mater. Interfaces 15, 14715 (2023). https://doi.org/10.1021/acsami.2c22219

D. Wu, H. Zhou, Z. Song, M. Zheng, R. Liu et al., Welding perovskite nanowires for stable, sensitive, flexible photodetectors. ACS Nano 14, 2777–2787 (2020). https://doi.org/10.1021/acsnano.9b09315

L. Li, L. Gu, Z. Lou, Z. Fan, G. Shen, ZnO quantum dot decorated Zn2 SnO4 nanowire heterojunction photodetectors with drastic performance enhancement and flexible ultraviolet image sensors. ACS Nano 11, 4067–4076 (2017). https://doi.org/10.1021/acsnano.7b00749

N. Kumar, M. Patel, J. Kim, C. Jeong, C.-P. Wong, Flexible transparent photovoltaics for ultra-UV photodetection and functional UV-shielding based on Ga2O3/Cu2O heterojunction. Appl. Mater. Today 29, 101620 (2022). https://doi.org/10.1016/j.apmt.2022.101620

S. Chen, Z. Lou, D. Chen, G. Shen, An artificial flexible visual memory system based on an UV-motivated memristor. Adv. Mater. 30, 1705400 (2018). https://doi.org/10.1002/adma.201705400

H. Xu, L. Hao, H. Liu, S. Dong, Y. Wu et al., Flexible SnSe photodetectors with ultrabroad spectral response up to 10.6 μm enabled by photobolometric effect. ACS Appl. Mater. Interfaces 12, 35250–35258 (2020). https://doi.org/10.1021/acsami.0c09561

D. Li, J. Du, Y. Tang, K. Liang, Y. Wang et al., Flexible and air-stable near-infrared sensors based on solution-processed inorganic–organic hybrid phototransistors. Adv. Funct. Mater. 31, 2105887 (2021). https://doi.org/10.1002/adfm.202105887

S.D. Petersen, A. Thyssen, M. Engholm, E.V. Thomsen, A flexible infrared sensor for tissue oximetry. Microelectron. Eng. 111, 130–136 (2013). https://doi.org/10.1016/j.mee.2013.03.035

S.A. Dayeh, D.P. Butler, Z. Çelik-Butler, Micromachined infrared bolometers on flexible polyimide substrates. Sens. Actuators A Phys. 118, 49–56 (2005). https://doi.org/10.1016/j.sna.2004.07.009

C. Dai, Y. Liu, D. Wei, Two-dimensional field-effect transistor sensors: the road toward commercialization. Chem. Rev. 122, 10319–10392 (2022). https://doi.org/10.1021/acs.chemrev.1c00924

C. Anichini, W. Czepa, D. Pakulski, A. Aliprandi, A. Ciesielski et al., Chemical sensing with 2D materials. Chem. Soc. Rev. 47, 4860–4908 (2018). https://doi.org/10.1039/C8CS00417J

T.R. Ray, J. Choi, A.J. Bandodkar, S. Krishnan, P. Gutruf et al., Bio-integrated wearable systems: a comprehensive review. Chem. Rev. 119, 5461–5533 (2019). https://doi.org/10.1021/acs.chemrev.8b00573

X. Zhao, Z. Deng, W. Zhao, B. Feng, M. Wang et al., Nanoporous silver using pulsed laser deposition for high-performance oxygen reduction reaction and hydrogen peroxide sensing. Nanoscale 12, 19413–19419 (2020). https://doi.org/10.1039/D0NR05395C

Q. Fan, L. Wang, D. Xu, Y. Duo, J. Gao et al., Solution-gated transistors of two-dimensional materials for chemical and biological sensors: status and challenges. Nanoscale 12, 11364–11394 (2020). https://doi.org/10.1039/D0NR01125H

H.W. Song, W. Choi, T. Jeon, J.H. Oh, Recent advances in smart organic sensors for environmental monitoring systems. ACS Appl. Electron. Mater. 5, 77–99 (2023). https://doi.org/10.1021/acsaelm.2c01315

S. Feng, Z. Lin, X. Gan, R. Lv, M. Terrones, Doping two-dimensional materials: ultra-sensitive sensors, band gap tuning and ferromagnetic monolayers. Nanoscale Horiz. 2, 72–80 (2017). https://doi.org/10.1039/C6NH00192K

Y. Luo, J. Li, Q. Ding, H. Wang, C. Liu et al., Functionalized hydrogel-based wearable gas and humidity sensors. Nano-Micro Lett. 15, 136 (2023). https://doi.org/10.1007/s40820-023-01109-2

L.-X. Ou, M.-Y. Liu, L.-Y. Zhu, D.W. Zhang, H.-L. Lu, Recent progress on flexible room-temperature gas sensors based on metal oxide semiconductor. Nano-Micro Lett. 14, 206 (2022). https://doi.org/10.1007/s40820-022-00956-9

G. Yang, H.-Y. Kim, S. Jang, J. Kim, Transfer-free growth of multilayer graphene using self-assembled monolayers. ACS Appl. Mater. Interfaces 8, 27115–27121 (2016). https://doi.org/10.1021/acsami.6b08974

Y. Xia, J. Wang, J.-L. Xu, X. Li, D. Xie et al., Confined formation of ultrathin ZnO nanorods/reduced graphene oxide mesoporous nanocomposites for high-performance room-temperature NO2 sensors. ACS Appl. Mater. Interfaces 8, 35454–35463 (2016). https://doi.org/10.1021/acsami.6b12501

Y. Dong, X. Zhang, X. Cheng, Y. Xu, S. Gao et al., Highly selective NO2 sensor at room temperature based on nanocomposites of hierarchical nanosphere-like α-Fe2O3 and reduced graphene oxide. RSC Adv. 4, 57493–57500 (2014). https://doi.org/10.1039/C4RA10136G

Q. Fan, J. Li, Y. Zhu, Z. Yang, T. Shen et al., Functional carbon quantum dots for highly sensitive graphene transistors for Cu2+ ion detection. ACS Appl. Mater. Interfaces 12, 4797–4803 (2020). https://doi.org/10.1021/acsami.9b20785

W. Dang, L. Manjakkal, W.T. Navaraj, L. Lorenzelli, V. Vinciguerra et al., Stretchable wireless system for sweat pH monitoring. Biosens. Bioelectron. 107, 192–202 (2018). https://doi.org/10.1016/j.bios.2018.02.025

P. Zhou, Z. Zhang, F. Mo, Y. Wang, A review of functional hydrogels for flexible chemical sensors. Adv. Sens. Res. (2023). https://doi.org/10.1002/adsr.202300021

Y. Lu, G. Yang, Y. Shen, H. Yang, K. Xu, Multifunctional flexible humidity sensor systems towards noncontact wearable electronics. Nano-Micro Lett. 14, 150 (2022). https://doi.org/10.1007/s40820-022-00895-5

F. Yuan, Y. Xia, Q. Lu, Q. Xu, Y. Shu et al., Recent advances in inorganic functional nanomaterials based flexible electrochemical sensors. Talanta 244, 123419 (2022). https://doi.org/10.1016/j.talanta.2022.123419

D.K. Ban, Y. Liu, Z. Wang, S. Ramachandran, N. Sarkar et al., Direct DNA methylation profiling with an electric biosensor. ACS Nano 14, 6743–6751 (2020). https://doi.org/10.1021/acsnano.9b10085

H. Li, W. Shi, J. Song, H.-J. Jang, J. Dailey et al., Chemical and biomolecule sensing with organic field-effect transistors. Chem. Rev. 119, 3–35 (2019). https://doi.org/10.1021/acs.chemrev.8b00016

S.D. Calisgan, V. Rajaram, S. Kang, A. Risso, Z. Qian et al., Micromechanical switch-based zero-power chemical detectors for plant health monitoring. J. Microelectromech. Syst. 29, 755–761 (2020). https://doi.org/10.1109/JMEMS.2020.3007309

Y. Qiao, J. Luo, T. Cui, H. Liu, H. Tang et al., Soft electronics for health monitoring assisted by machine learning. Nano-Micro Lett. 15, 66 (2023). https://doi.org/10.1007/s40820-023-01029-1

Y. Fang, Y. Zou, J. Xu, G. Chen, Y. Zhou et al., Ambulatory cardiovascular monitoring via a machine-learning-assisted textile triboelectric sensor. Adv. Mater. 33, 2104178 (2021). https://doi.org/10.1002/adma.202104178

Z. Zhang, T. He, M. Zhu, Z. Sun, Q. Shi et al., Deep learning-enabled triboelectric smart socks for IoT-based gait analysis and VR applications. Npj Flex. Electron. 4, 29 (2020). https://doi.org/10.1038/s41528-020-00092-7

M. Wang, Z. Yan, T. Wang, P. Cai, S. Gao et al., Gesture recognition using a bioinspired learning architecture that integrates visual data with somatosensory data from stretchable sensors. Nat. Electron. 3, 563–570 (2020). https://doi.org/10.1038/s41928-020-0422-z

K. Kim, M. Sim, S. Lim, D. Kim, D. Lee et al., Tactile avatar: tactile sensing system mimicking human tactile cognition. Adv. Sci. 8, 2002362 (2021). https://doi.org/10.1002/advs.202002362

N. Bokka, V. Selamneni, P. Sahatiya, A water destructible SnS2 QD/PVA film based transient multifunctional sensor and machine learning assisted stimulus identification for non-invasive personal care diagnostics. Mater. Adv. 1, 2818–2830 (2020). https://doi.org/10.1039/D0MA00573H

Y. Kim, M. Mahmood, Y. Lee, N.K. Kim, S. Kwon et al., All-in-One, wireless, stretchable hybrid electronics for smart, connected, and ambulatory physiological monitoring. Adv. Sci. 6, 1900939 (2019). https://doi.org/10.1002/advs.201900939

Z. Zeng, Z. Huang, K. Leng, W. Han, H. Niu et al., Nonintrusive monitoring of mental fatigue status using epidermal electronic systems and machine-learning algorithms. ACS Sens. 5, 1305–1313 (2020). https://doi.org/10.1021/acssensors.9b02451

T. Jin, Z. Sun, L. Li, Q. Zhang, M. Zhu et al., Triboelectric nanogenerator sensors for soft robotics aiming at digital twin applications. Nat. Commun. 11, 5381 (2020). https://doi.org/10.1038/s41467-020-19059-3

F. Wen, Z. Zhang, T. He, C. Lee, AI enabled sign language recognition and VR space bidirectional communication using triboelectric smart glove. Nat. Commun. 12, 5378 (2021). https://doi.org/10.1038/s41467-021-25637-w

S. Sundaram, P. Kellnhofer, Y. Li, J.-Y. Zhu, A. Torralba et al., Learning the signatures of the human grasp using a scalable tactile glove. Nature 569, 698–702 (2019). https://doi.org/10.1038/s41586-019-1234-z

Q. Hu, X. Tang, W. Tang, A smart chair sitting posture recognition system using flex sensors and FPGA implemented artificial neural network. IEEE Sens. J. 20, 8007–8016 (2020). https://doi.org/10.1109/JSEN.2020.2980207

Z. Zhang, Q. Shi, T. He, X. Guo, B. Dong et al., Artificial intelligence of toilet (AI-Toilet) for an integrated health monitoring system (IHMS) using smart triboelectric pressure sensors and image sensor. Nano Energy 90, 106517 (2021). https://doi.org/10.1016/j.nanoen.2021.106517

J. Zeng, J. Zhao, T. Bu, G. Liu, Y. Qi et al., A flexible tribotronic artificial synapse with bioinspired neurosensory behavior. Nano-Micro Lett. 15, 18 (2023). https://doi.org/10.1007/s40820-022-00989-0

S.-Y. Yun, J.-K. Han, S.-W. Lee, J.-M. Yu, S.-B. Jeon et al., Self-aware artificial auditory neuron with a triboelectric sensor for spike-based neuromorphic hardware. Nano Energy 109, 108322 (2023). https://doi.org/10.1016/j.nanoen.2023.108322

Q. Liu, L. Yin, C. Zhao, Z. Wu, J. Wang et al., All-in-one metal-oxide heterojunction artificial synapses for visual sensory and neuromorphic computing systems. Nano Energy 97, 107171 (2022). https://doi.org/10.1016/j.nanoen.2022.107171

H. Wan, J. Zhao, L.-W. Lo, Y. Cao, N. Sepúlveda et al., Multimodal artificial neurological sensory–memory system based on flexible carbon nanotube synaptic transistor. ACS Nano 15, 14587–14597 (2021). https://doi.org/10.1021/acsnano.1c04298

C. Ban, X. Min, J. Xu, F. Xiu, Y. Nie et al., An artificial olfactory memory system for monitoring and recording of volatile organic compounds. Adv. Mater. Technol. 6, 2100366 (2021). https://doi.org/10.1002/admt.202100366

L. Yang, Z. Wang, S. Zhang, Y. Li, C. Jiang et al., Neuromorphic gustatory system with salt-taste perception, information processing, and excessive-intake warning capabilities. Nano Lett. 23, 8–16 (2023). https://doi.org/10.1021/acs.nanolett.2c02775

Y. Kim, A. Chortos, W. Xu, Y. Liu, J.Y. Oh et al., A bioinspired flexible organic artificial afferent nerve. Science 360, 998–1003 (2018). https://doi.org/10.1126/science.aao0098

K. He, Y. Liu, M. Wang, G. Chen, Y. Jiang et al., An artificial somatic reflex arc. Adv. Mater. 32, 1905399 (2020). https://doi.org/10.1002/adma.201905399

Z. Gao, S. Chen, R. Li, Z. Lou, W. Han et al., An artificial olfactory system with sensing, memory and self-protection capabilities. Nano Energy 86, 106078 (2021). https://doi.org/10.1016/j.nanoen.2021.106078

L. Liu, W. Xu, Y. Ni, Z. Xu, B. Cui et al., Stretchable neuromorphic transistor that combines multisensing and information processing for epidermal gesture recognition. ACS Nano 16, 2282–2291 (2022). https://doi.org/10.1021/acsnano.1c08482

Y. Luo, Y. Li, P. Sharma, W. Shou, K. Wu et al., Learning human–environment interactions using conformal tactile textiles. Nat. Electron. 4, 193–201 (2021). https://doi.org/10.1038/s41928-021-00558-0

G. Loke, T. Khudiyev, B. Wang, S. Fu, S. Payra et al., Digital electronics in fibres enable fabric-based machine-learning inference. Nat. Commun. 12, 3317 (2021). https://doi.org/10.1038/s41467-021-23628-5

K.K. Kim, I. Ha, M. Kim, J. Choi, P. Won et al., A deep-learned skin sensor decoding the epicentral human motions. Nat. Commun. 11, 2149 (2020). https://doi.org/10.1038/s41467-020-16040-y

Q. Wu, Y. Qiao, R. Guo, S. Naveed, T. Hirtz et al., Triode-mimicking graphene pressure sensor with positive resistance variation for physiology and motion monitoring. ACS Nano 14, 10104–10114 (2020). https://doi.org/10.1021/acsnano.0c03294

L. Su, Q. Xiong, H. Wang, Y. Zi, Porous-structure-promoted tribo-induced high-performance self-powered tactile sensor toward remote human–machine interaction. Adv. Sci. 9, 2203510 (2022). https://doi.org/10.1002/advs.202203510

B.C.-K. Tee, A. Chortos, A. Berndt, A.K. Nguyen, A. Tom et al., A skin-inspired organic digital mechanoreceptor. Science 350, 313–316 (2015). https://doi.org/10.1126/science.aaa9306

Q. Hua, J. Sun, H. Liu, R. Bao, R. Yu et al., Skin-inspired highly stretchable and conformable matrix networks for multifunctional sensing. Nat. Commun. 9, 244 (2018). https://doi.org/10.1038/s41467-017-02685-9

S. Seo, S.-H. Jo, S. Kim, J. Shim, S. Oh et al., Artificial optic-neural synapse for colored and color-mixed pattern recognition. Nat. Commun. 9, 5106 (2018). https://doi.org/10.1038/s41467-018-07572-5

H. Wang, Q. Zhao, Z. Ni, Q. Li, H. Liu et al., A ferroelectric/electrochemical modulated organic synapse for ultraflexible, artificial visual-perception system. Adv. Mater. 30, 1803961 (2018). https://doi.org/10.1002/adma.201803961

S.M. Kwon, S.W. Cho, M. Kim, J.S. Heo, Y. Kim et al., Environment-adaptable artificial visual perception behaviors using a light-adjustable optoelectronic neuromorphic device array. Adv. Mater. 31, 1906433 (2019). https://doi.org/10.1002/adma.201906433

J.H. Koo, S. Jeong, H.J. Shim, D. Son, J. Kim et al., Wearable electrocardiogram monitor using carbon nanotube electronics and color-tunable organic light-emitting diodes. ACS Nano 11, 10032–10041 (2017). https://doi.org/10.1021/acsnano.7b04292

P. Bach-y-Rita, S.W. Kercel, Sensory substitution and the human–machine interface. Trends Cogn. Sci. 7, 541–546 (2003). https://doi.org/10.1016/j.tics.2003.10.013

W. Yan, G. Noel, G. Loke, E. Meiklejohn, T. Khudiyev et al., Single fibre enables acoustic fabrics via nanometre-scale vibrations. Nature 603, 616–623 (2022). https://doi.org/10.1038/s41586-022-04476-9

W. Wang, G. Pedretti, V. Milo, R. Carboni, A. Calderoni et al., Learning of spatiotemporal patterns in a spiking neural network with resistive switching synapses. Sci. Adv. 4, eaat4752 (2018). https://doi.org/10.1126/sciadv.aat4752

Y.H. Jung, B. Park, J.U. Kim, T. Kim, Bioinspired electronics for artificial sensory systems. Adv. Mater. 31, 1803637 (2019). https://doi.org/10.1002/adma.201803637

Z. Song, Y. Tong, X. Zhao, H. Ren, Q. Tang et al., A flexible conformable artificial organ-damage memory system towards hazardous gas leakage based on a single organic transistor. Mater. Horiz. 6, 717–726 (2019). https://doi.org/10.1039/C8MH01577E

Q. Shi, Z. Sun, X. Le, J. Xie, C. Lee, Soft robotic perception system with ultrasonic auto-positioning and multimodal sensory intelligence. ACS Nano 17, 4985–4998 (2023). https://doi.org/10.1021/acsnano.2c12592

G. Li, S. Liu, L. Wang, R. Zhu, Skin-inspired quadruple tactile sensors integrated on a robot hand enable object recognition. Sci. Robot. 5, eabc8134 (2020). https://doi.org/10.1126/scirobotics.abc8134

W. Yang, M. Xie, X. Zhang, X. Sun, C. Zhou et al., Multifunctional soft robotic finger based on a nanoscale flexible temperature–pressure tactile sensor for material recognition. ACS Appl. Mater. Interfaces 13, 55756–55765 (2021). https://doi.org/10.1021/acsami.1c17923

L.-Y. Zhou, Q. Gao, J.-F. Zhan, C.-Q. Xie, J.-Z. Fu et al., Three-dimensional printed wearable sensors with liquid metals for detecting the pose of snakelike soft robots. ACS Appl. Mater. Interfaces 10, 23208–23217 (2018). https://doi.org/10.1021/acsami.8b06903

L. Lindenroth, S. Bano, A. Stilli, J.G. Manjaly, D. Stoyanov, A fluidic soft robot for needle guidance and motion compensation in intratympanic steroid injections. IEEE Robot. Autom. Lett. 6, 871–878 (2021). https://doi.org/10.1109/LRA.2021.3051568

L. Gu, S. Poddar, Y. Lin, Z. Long, D. Zhang et al., A biomimetic eye with a hemispherical perovskite nanowire array retina. Nature 581, 278–282 (2020). https://doi.org/10.1038/s41586-020-2285-x

Y. Pei, Z. Li, B. Li, Y. Zhao, H. He et al., A multifunctional and efficient artificial visual perception nervous system with Sb2Se3/CdS-Core/Shell (SC) nanorod arrays optoelectronic memristor. Adv. Funct. Mater. 32, 2203454 (2022). https://doi.org/10.1002/adfm.202203454

R. Bao, J. Tao, J. Zhao, M. Dong, J. Li et al., Integrated intelligent tactile system for a humanoid robot. Sci. Bull. 68, 1027–1037 (2023). https://doi.org/10.1016/j.scib.2023.04.019

C. Dai, C. Ye, J. Ren, S. Yang, L. Cao et al., Humanoid ionotronic skin for smart object recognition and sorting. ACS Mater. Lett. 5, 189–201 (2023). https://doi.org/10.1021/acsmaterialslett.2c00783

L. Massari, G. Fransvea, J. D’Abbraccio, M. Filosa, G. Terruso et al., Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin. Nat. Mach. Intell. 4, 425–435 (2022). https://doi.org/10.1038/s42256-022-00487-3