Mimicking Sensory Adaptation with Dielectric Engineered Organic Transistors

Abstract

Mimicking sensory adaptation with transistors is essential for developing next‐generation smart circuits. A key challenge is how to obtain controllable and reversible short‐term signal decay while simultaneously maintaining long‐term electrical stability. By introducing a buried dynamic‐trapping interface within the dielectric layer, an organic adaptive transistor (OAT) with sensory adaptation functionality is developed. The device induces self‐adaptive interfacial trapping to enable volatile shielding of the gating field, thereby leading to rapid and temporary carrier concentration decay in the conductive channel without diminishing the mobility upon a fixed voltage bias. More importantly, the device exhibits a fine‐tuned decay constant ranging from 50 ms to 5 s, accurately matching the adaptation timescales in bio‐systems. This not only suggests promising applications of OATs in flexible artificial intelligent elements, but also provides a strategy for engineering organic devices toward novel biomimetic functions.

Photoelectric Visual Adaptation Based on 0D‐CsPbBr3‐Quantum‐Dots/2D‐MoS2 Mixed‐Dimensional Heterojunction Transistor

“…Adaptation usually involves the feedback regulation through external stimulus of signal pathways, while other hidden factors can affect the negative feedback response and cause desensitization of the pathway, essentially resetting the baseline of the pathway stimulus so that the same level of response requires a higher intensity input. [ 25–27 ] As shown in Figure 2d, a basic network architecture with negative feedback loop (NFL) can be provided to further understand the accurate adaptation model. [ 25 ] The network architecture consists of three interactive nodes: one node receives input ( X ), one node transmits output ( I ), and the third node can be used as hidden factors ( H ).…”

“…© 2021 Wiley-VCH GmbH requires a higher intensity input. [25][26][27] As shown in Figure 2d, a basic network architecture with negative feedback loop (NFL) can be provided to further understand the accurate adaptation model. [25] The network architecture consists of three interactive nodes: one node receives input (X), one node transmits output (I), and the third node can be used as hidden factors (H).…”

Neuromorphic bioelectronics based on semiconducting polymers

“…Reproduced with permission. 110 Copyright 2019, Wiley-VCH Other complex structures have also been proposed to introduce built-in charge trapping interfaces within the normal gate dielectric layer. Shen et al demonstrated an organic adaptive transistor (OAT) that induced self-adaptive interfacial trapping and, therefore, regulated carrier concentration to enable biological mimetic adaptation behavior.…”

Artificial stimulus-response system capable of conscious response

“…A design of an artificial stimulusresponse system and a device for using it have recently received research attention because such a system can contribute to improving the lives of humans with impaired nervous systems (1)(2)(3)(4)(5)(6)(7)(8). Developments have been made to mimic the human stimulus-response mechanism and to apply them to living organisms (9)(10)(11)(12)(13)(14)(15). Recently, Lee group ( 9) invented an artificial afferent nervous system comprising pressure sensors, an organic ring oscillator, and a synaptic transistor.…”