Organic Circuits and Systems for Neuromorphic Perception for Soft Robotics and Soft Functional Materials

Soft robots, machines made from soft and compliant materials, aim to address limitations of hard and rigid robots critical when working in close contact with humans or other applications that require soft and conformal form factor. However, at present, the majority of sensors, actuators, and electronics used in control of soft robots still relies on hard and rigid materials. We present an update of our efforts to develop soft and flexible functional materials, with embedded sensors and neuromorphic electronics, as building blocks of soft robotics and soft functional materials.<br/><br/>We employed various deposition techniques, including direct ink writing, inkjet printing, and fused deposition modeling three-dimensional printing, to fabricate piezoelectric PVdF force/pressure and temperature sensors. We developed new methods of improving sensor sensitivity, including electric poling, that allow for embedding force / pressure sensors with structure of any arbitrary 3D shape [1, 2]. We also developed a low cost, impedance-based chemical aqueous ammonia sensor [3]. In addition, we have developed a new technique to additively manufacture organic electronics, for future integration with sensors and structures [4] for soft robots and soft functional materials.<br/><br/>Neuromorphic electronics, largely based on Spiking Neural Networks (SNN), provide distributed computation to emulate brain processing principles. With synapses and somas as their essential components, they function based on modulation of spike frequency and pulse width. Characterized by low power consumption, a target application of SNN hardware implementation, known as neuromorphic systems, are embedded computing [4]. However, they are typically implemented using hard, rigid, and non-biocompatible silicon technology, incompatible with brain's soft tissue.<br/><br/>In soft organic electronics, we have fabricated physically flexible, spiking somatic [5] and synaptic [6, 7] circuits. Complimentary p- and n-type organic transistors were fabricated on 50 μm thin Polyimide substrates, with DNTT and PDI8-CN2 used as p- and n-type organic semiconductors, and Parylene diX-SR as the transistor and fabrication-integrated capacitor dielectric. Results show that organic spiking Integrate-and-Fire Axon-Hillock [5] artificial soma integrates input currents and produces proportional output spikes. Also, organic Log-Domain Integrator [6] and Differential-Pair Integrator [7] synaptic circuits produce proportional output currents based on continuously tunable synaptic weights. Other critical tunable circuit functions, including gain, time-constant, and synaptic capacitance, are also shown. Synaptic circuit response due to input spikes of different frequencies are also demonstrated. These neuromorphic primitives can be used for constructing an entire spiking neuron, as well as a network of such neurons. We also demonstrated sub-300 nm thin organic circuits, including multi-stage amplifiers and ring oscillators, for future use in neuromorphic computing in robotics applications [8, 9].<br/><br/>[1] J. Fan, et al., <i>Adv. Eng. Mat.</i>, <b>24</b>, 2200485 (doi: 10.1002/adem.202200485), 2022.<br/>[2] J. Fan, et al., <i>Add. Manu.</i>, <b>60</b>, 103248 (doi: 10.1016/j.addma.2022.103248), 2022.<br/>[3] K. Vyshniakova, et al., <i>ECS Meet.</i>, MA2021-01, 1541 (doi: 10.1149/MA2021-01571541mtgabs), 2021.<br/>[3] H. Bai, et al., <i>J. Mat. Chem. C</i>, <b>10</b> (30), 10973-10980 (doi: 10.1039/D2TC00948J), 2022.<br/>[4] Y. Yang, et al., <i>Eng. App of Art Int</i>, <b>126</b>, 106838 (doi: 10.1016/j.engappai.2023.106838), 2023.<br/>[5] M.J.M. Hosseini, et al., <i>J. Phys. D: Appl. Phys.</i>, <b>54</b>, 104004 (doi: 10.1088/1361-6463/abc585), 2021.<br/>[6] M.J.M. Hosseini, et al., <i>Adv. Ele. Mat.</i>, <b>8</b>, 2100724 (doi: 10.1002/aelm.202100724), 2022.<br/>[7] M.J.M. Hosseini, et al., <i>Neuro. Comp. Eng.</i>, <b>2</b>, 034009 (doi: 10.1088/2634-4386/ac830c), 2022.<br/>[8] M.J.M. Hosseini, et al., <i>npj Flex. Ele.,</i> <b>7</b>, 38 (doi: 10.1038/s41528-023-00267-y) 2023.<br/>[9] Y. Yang, et al., <i>Eng. App. of Art. Int.</i>, <b>126</b>, 106838, (doi: 10.1016/j.engappai.2023.106838), 2023.