Self healable neuromorphic memtransistor elements for decentralized sensory signal processing in robotics.

Sensory information processing in robot skins currently rely on a centralized approach where signal transduction (on the body) is separated from centralized computation and decision-making, requiring the transfer of large amounts of data from periphery to central processors, at the cost of wiring, latency, fault tolerance and robustness. We envision a decentralized approach where intelligence is embedded in the sensing nodes, using a unique neuromorphic methodology to extract relevant information in robotic skins. Here we specifically address pain perception and the association of nociception with tactile perception to trigger the escape reflex in a sensorized robotic arm. The proposed system comprises self-healable materials and memtransistors as enabling technologies for the implementation of neuromorphic nociceptors, spiking local associative learning and communication. Configuring memtransistors as gated-threshold and -memristive switches, the demonstrated system features in-memory edge computing with minimal hardware circuitry and wiring, and enhanced fault tolerance and robustness.

Field-Driven Athermal Activation of Amorphous Metal Oxide Semiconductors for Flexible Programmable Logic Circuits and Neuromorphic Electronics.

Despite extensive research, large-scale realization of metal-oxide electronics is still impeded by high-temperature fabrication, incompatible with flexible substrates. Ideally, an athermal treatment modifying the electronic structure of amorphous metal oxide semiconductors (AMOS) to generate sufficient carrier concentration would help mitigate such high-temperature requirements, enabling realization of high-performance electronics on flexible substrates. Here, a novel field-driven athermal activation of AMOS channels is demonstrated via an electrolyte-gating approach. Facilitating migration of charged oxygen species across the semiconductor-dielectric interface, this approach modulates the local electronic structure of the channel, generating sufficient carriers for charge transport and activating oxygen-compensated thin films. The thin-film transistors (TFTs) investigated here depict an enhancement of linear mobility from 51 to 105.25 cm2 V-1 s-1 (ionic-gated) and from 8.09 to 14.49 cm2 V-1 s-1 (back-gated), by creating additional oxygen vacancies. The accompanying stochiometric transformations, monitored via spectroscopic measurements (X-ray photoelectron spectroscopy) corroborate the detailed electrical (TFT, current evolution) parameter analyses, providing critical insights into the underlying oxygen-vacancy generation mechanism and clearly demonstrating field-induced activation as a promising alternative to conventional high-temperature annealing strategies. Facilitating on-demand active programing of the operation modes of transistors (enhancement vs depletion), this technique paves way for facile fabrication of logic circuits and neuromorphic transistors for bioinspired computing.

Ultralow Power Dual-Gated Subthreshold Oxide Neuristors: An Enabler for Higher Order Neuronal Temporal Correlations.

Inspired by neural computing, the pursuit of ultralow power neuromorphic architectures with highly distributed memory and parallel processing capability has recently gained more traction. However, emulation of biological signal processing via artificial neuromorphic architectures does not exploit the immense interplay between local activities and global neuromodulations observed in biological neural networks and hence are unable to mimic complex biologically plausible adaptive functions like heterosynaptic plasticity and homeostasis. Here, we demonstrate emulation of complex neuronal behaviors like heterosynaptic plasticity, homeostasis, association, correlation, and coincidence in a single neuristor via a dual-gated architecture. This multiple gating approach allows one gate to capture the effect of local activity correlations and the second gate to represent global neuromodulations, allowing additional modulations which augment their plasticity, enabling higher order temporal correlations at a unitary level. Moreover, the dual-gate operation extends the available dynamic range of synaptic conductance while maintaining symmetry in the weight-update operation, expanding the number of accessible memory states. Finally, operating neuristors in the subthreshold regime enable synaptic weight changes with high gain while maintaining ultralow power consumption of the order of femto-Joules.

Microstructured porous ZnO thin film for increased light scattering and improved efficiency in inverted organic photovoltaics.

Microstructured porous zinc oxide (ZnO) thin film was developed and demonstrated as an electron selective layer for enhancing light scattering and efficiency in inverted organic photovoltaics. High degree of porosity was induced and controlled in the ZnO layer by incorporation of polyethylene glycol (PEG) organic template. Scanning electron microscopy, contact angle and absorption measurements prove that the ZnO:PEG ratio of 4:1 is optimal for the best performance of porous ZnO. Ensuring sufficient pore-filling, the use of porous ZnO leads to a marked improvement in device performance compared to non-porous ZnO, with 35% increase in current density and 30% increase in efficiency. Haze factor studies indicate that the performance improvement can be primarily attributed to the improved light scattering enabled by such a highly porous structure.