Synergistic Gating of Electro‐Iono‐Photoactive 2D Chalcogenide Neuristors: Coexistence of Hebbian and Homeostatic Synaptic Metaplasticity

• Published in: Advanced materials (Weinheim) 2018-06, Vol.30 (25), p.e1800220-n/a
• Main Authors: John, Rohit Abraham, Liu, Fucai, Chien, Nguyen Anh, Kulkarni, Mohit R., Zhu, Chao, Fu, Qundong, Basu, Arindam, Liu, Zheng, Mathews, Nripan
• Format: Article
• Language: English
• Subjects: 2D chalcogenides; associative learning; Brain; Chalcogenides; Circuits; Dynamic control; Hebbian synaptic plasticity; homeostatic regulation; Materials science; Molybdenum disulfide; Neuristors; neuromorphic computing; Organic chemistry; Photoconductivity; Signal processing; Synapses; Time dependence
• ISSN: 0935-9648; 1521-4095
• DOI: 10.1002/adma.201800220

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. Emulation of brain‐like signal processing lays the foundation for building artificial neural networks. Exploiting a novel multi‐gated architecture incorporating optoelectronic biases, MoS2 neuristors are utilized to mimic biological synapses with dynamic control of Hebbian metaplasticity and homeostatic regulation. Encompassing higher functionalities into single artificial neurons will mitigate the high‐circuit‐density requirements necessary to match computational complexity of the human brain.