We demonstrate an ionic polymer artificial mechanotransducer (i-PAM) capable of simultaneously yielding an efficient wide bandwidth and a blocking force to maximize human tactile recognition in soft tactile feedback. The unique methodology in the i-PAM relies on an ionic interpenetrating nanofibrillar network that is formed at the interface of (i) an ionic thermoplastic polyurethane nanofibrillar matrix with an ionic liquid of 1-ethyl-3-methylimidazolium bis­(trifluoromethylsulfonyl)­imide ([EMIM]+[TFSI]−) and (ii) ionic poly­(3,4-ethylenedioxythiophene):poly­(styrenesulfonic acid) (PEDOT:PSS) conducting polymer electrodes with dimethyl sulfoxide and [EMIM]+[TFSI]− as additives. The i-PAM-based actuator with the ionic PEDOT:PSS exhibits a stable operation up to 200 Hz at low voltage as well as a blocking force of 0.4 mN, which can be potentially adapted to soft tactile feedback. Furthermore, on the basis of this fast i-PAM, we realized alphabet tactile rendering by using a 3 × 3 i-PAM array stimulated by a dc input of 2 V. We believe that our proposed approach can provide a rational guide to the human–machine soft haptic interface.

An interference‐free, flexible multimodal electronic skin matrix (3 × 3 pressure sensor array and four chemical sensors) combined with low‐power, monolithic integrated circuits with coplanar‐type thin‐film transistor arrays is demonstrated to detect mechanical and chemical stimuli simultaneously. This sensing platform is facilitated by a photocrosslinked ionic polymer film including ionic liquids, a solution‐processed amorphous oxide semiconductor, and a protective layer or microhole channel facilitated by a polydimethylsiloxane elastomer film. Consequently, a highly reliable piezocapacitive pressure‐sensing capability under a chemical variation is achieved with an electric double layer mechanism at the interface between the ionic polymer film and electrode. Moreover, selective olfactory detection to various chemicals with high sensitivity is achieved even under a pressing atmosphere via ion–gas interactions in the chemical sensor matrix. The proposed method is expected to contribute toward the practical realization of a new class of multimodal tactile sensors that reflect human–machine interactions.

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