RESUMEN
Emulation of brain-like signal processing is the foundation for development of efficient learning circuitry, but few devices offer the tunable conductance range necessary for mimicking spatiotemporal plasticity in biological synapses. An ionic semiconductor which couples electronic transitions with drift-diffusive ionic kinetics would enable energy-efficient analog-like switching of metastable conductance states. Here, ionic-electronic coupling in halide perovskite semiconductors is utilized to create memristive synapses with a dynamic continuous transition of conductance states. Coexistence of carrier injection barriers and ion migration in the perovskite films defines the degree of synaptic plasticity, more notable for the larger organic ammonium and formamidinium cations than the inorganic cesium counterpart. Optimized pulsing schemes facilitates a balanced interplay of short- and long-term plasticity rules like paired-pulse facilitation and spike-time-dependent plasticity, cardinal for learning and computing. Trained as a memory array, halide perovskite synapses demonstrate reconfigurability, learning, forgetting, and fault tolerance analogous to the human brain. Network-level simulations of unsupervised learning of handwritten digit images utilizing experimentally derived device parameters, validates the utility of these memristors for energy-efficient neuromorphic computation, paving way for novel ionotronic neuromorphic architectures with halide perovskites as the active material.
RESUMEN
Thin-film transistors (TFTs) with high electrical performances (mobility > 10 cm2/V s, Vth < 1 V, SS < 1 V/decade, on/off ratio ≈ 106) obtained from the silicon- and oxide-based single-crystalline semiconductor materials require high processing temperature and hence are not suitable for flexible electronics. Amorphous oxide-based transparent electronic devices are attractive to meet emerging technological demands where crystalline oxide-/silicon-based architectures cannot provide a solution. Here, we tackle this problem by using a novel amorphous oxide semiconducting material-namely, indium tungsten oxide (IWO)-as the active channel in flexible TFTs (FTFTs). Post-annealing temperature as low as 270 °C for amorphous IWO thin films deposited by radio frequency sputtering at room temperature could result in smooth morphology ( Rrms ≈ 0.42 nm), good adhesion, and high carrier density ( n ≈ 7.19 × 1018 cm-3). Excellent TFT characteristics of flexible devices could be achieved with linear field effect mobility µFE ≈ 25.86 cm2/V s, subthreshold swing SS ≈ 0.30 V/decade, threshold voltage Vth ≈ -1.5 V, and on/off ratio Ion/ Ioff ≈ 5.6 × 105 at 3 V and stable operation during bending of the FTFT. Additionally, IWO TFTs were implemented as synapses, the building block for neuromorphic computing. Paired-pulse facilitation up to 138% was observed and showed an exponential decay resembling chemical synapses. Utilizing this characteristic, a high-pass dynamic temporal filter was devised providing increased gain from 1.55 to 21 when frequency was raised from 22 to 62 Hz. The high performance and stability of flexible TFTs obtained with IWO films demonstrate their promise for low-voltage electronic applications.
RESUMEN
Emulation of brain-like signal processing with thin-film devices can lay the foundation for building artificially intelligent learning circuitry in future. Encompassing higher functionalities into single artificial neural elements will allow the development of robust neuromorphic circuitry emulating biological adaptation mechanisms with drastically lesser neural elements, mitigating strict process challenges and high circuit density requirements necessary to match the computational complexity of the human brain. Here, 2D transition metal di-chalcogenide (MoS2 ) neuristors are designed to mimic intracellular ion endocytosis-exocytosis dynamics/neurotransmitter-release in chemical synapses using three approaches: (i) electronic-mode: a defect modulation approach where the traps at the semiconductor-dielectric interface are perturbed; (ii) ionotronic-mode: where electronic responses are modulated via ionic gating; and (iii) photoactive-mode: harnessing persistent photoconductivity or trap-assisted slow recombination mechanisms. Exploiting a novel multigated architecture incorporating electrical and optical biases, this incarnation not only addresses different charge-trapping probabilities to finely modulate the synaptic weights, but also amalgamates neuromodulation schemes to achieve "plasticity of plasticity-metaplasticity" via dynamic control of Hebbian spike-time dependent plasticity and homeostatic regulation. Coexistence of such multiple forms of synaptic plasticity increases the efficacy of memory storage and processing capacity of artificial neuristors, enabling design of highly efficient novel neural architectures.
RESUMEN
Challenges associated with the mechanical fracture of electrical conductors have hindered the realization of truly flexible high performance wearable electronics. Here, transparent healable electrodes have been developed and examined to alleviate these problems. The composite electrode features a layer of an interconnecting AgNW network on a polyurethane film modified with Diels-Alder adducts (PU-DA). Surface modification using hydrophilic molecules improved adhesion of the AgNW network and resulted in mechanically robust flexible electrodes with a figure of merit sheet resistance of 13.3 Ω â¡-1 and 77% transmittance at 550 nm. Transparent and flexible healable heaters (TFHH) with good mechanical and thermal stability were fabricated using these electrodes for potential applications in thermochromics, electrically driven displays and defrosters. The PU-DA TFHHs exhibited high Joule heating temperatures of 102 °C with a low operation voltage (6 V), fast thermal response (150 s) and enhanced robustness to endure large repeated mechanical strain for over 500 bending cycles with a small variance in resistance (<10%). After deliberate damage by a knife cut, the electrodes were healed and recovered to their original conductivity via a simple heat treatment at 120 °C. Uniquely, the healing process can also be triggered by utilising electrical power.
RESUMEN
Emulation of biological synapses is necessary for future brain-inspired neuromorphic computational systems that could look beyond the standard von Neuman architecture. Here, artificial synapses based on ionic-electronic hybrid oxide-based transistors on rigid and flexible substrates are demonstrated. The flexible transistors reported here depict a high field-effect mobility of ≈9 cm2 V-1 s-1 with good mechanical performance. Comprehensive learning abilities/synaptic rules like paired-pulse facilitation, excitatory and inhibitory postsynaptic currents, spike-time-dependent plasticity, consolidation, superlinear amplification, and dynamic logic are successfully established depicting concurrent processing and memory functionalities with spatiotemporal correlation. The results present a fully solution processable approach to fabricate artificial synapses for next-generation transparent neural circuits.