Brain‐Inspired Organic Electronics: Merging Neuromorphic Computing and Bioelectronics Using Conductive Polymers

Abstract

Neuromorphic computing offers the opportunity to curtail the huge energy demands of modern artificial intelligence (AI) applications by implementing computations into new, brain‐inspired computing architectures. However, the lack of fabrication processes able to integrate several computing units into monolithic systems and the need for new, hardware‐tailored training algorithms still limit the scope of application and performance of neuromorphic hardware. Recent advancements in the field of organic transistors present new opportunities for neuromorphic systems and smart sensing applications, thanks to their unique properties such as neuromorphic behavior, low‐voltage operation, and mixed ionic‐electronic conductivity. Organic neuromorphic transistors push the boundaries of energy efficient brain‐inspired hardware AI, facilitating decentralized on‐chip learning and serving as a foundation for the advancement of closed‐loop intelligent systems in the next generation. The biocompatibility and dual ionic‐electronic conductivity of organic materials introduce new prospects for biointegration and bioelectronics. Their ability to sense and regulate biosystems, as well as their neuro‐inspired functions can be combined with neuromorphic computing to create the next‐generation of bioelectronics. These systems will be able to seamlessly interact with biological systems and locally compute biosignals in a relevant matter.

Physical Reservoir Computing Enabled by Solitary Waves and Biologically Inspired Nonlinear Transformation of Input Data

“…While the biophysical origin of the restoration of the missing fundamental continues to be a subject of debate, it has been suggested that it can be explained by nonlinear and chaotic effects [17]. Nonlinear processes in biological neural systems have also motivated research on artificial neural networks that exploit the nonlinear properties of diverse mathematical models and physical systems [18][19][20][21][22][23][24][25][26][27][28][29].…”

Natural and Synthetic Polymers for Biomedical and Environmental Applications

“…Polymeric materials have great potential in tissue engineering thanks to their biodegradability, processing, and property design flexibility [ 59 ]. Moreover, polymers may be used to regulate cell function.…”

“…Moreover, polymers may be used to regulate cell function. Stem cells are a promising option for tissue engineering since they uniquely self-renew and differentiate into various lineages, such as neurogenic, osteogenic, chondrogenic, and myogenic, under proper stimulation from extracellular components [ 59 ]. Due to their properties, stem cells and polymeric materials are critical design choices.…”

Reservoir Computing Using Measurement-Controlled Quantum Dynamics

“…In Figure 2, the occupation probabilities P(n, σ) for the first six Fock states are depicted as a function of β. These probabilities exhibit a nonlinear response and, for values of β within the range [10,15], there is a nonzero occupation probability for all Fock bases |nσ⟩ ∈ |00⟩ . .…”

“…However, to accomplish a computational task of arbitrary complexity, they may require impracticably large resources such as time and memory. To overcome this challenge, unconventional [1,2] and neuromorphic [3][4][5][6][7][8][9][10] approaches to computer engineering and data processing were proposed based on the idea that a computer should imitate the operation of a biological brain [11,12].…”