Multifunctional synaptic learning and neuromorphic computing using crystalline TiOx/NiOx heterojunction-based memory devices
Abstract
An attempt is made here to mimic different properties of biological synapses using Ag/TiOx/NiOx/p++-Si memristor structure by studying its different transport properties under dc and pulsed bias. The presence of crystalline NiOx with smaller gains is found to be helpful to get TiOx deposited on its top with crystalline properties and larger grains. The heterostructure offers stable bipolar forming free non-volatile resistive switching characteristics under reverse biased condition with gradual set and reset features. These devices are also able to successfully implement the classical Pavlov's learning, study artificial nociceptor and Morse code detection. While incorporating synaptic weights derived from the measured conductance programming pulse relationship, an artificial neural network achieves nearly 95\% accuracy in MNIST digit recognition. In brief, NiOx/TiOx heterojunction plays the pivotal role in getting such reproducible I−V characteristics for mimicking different properties of biological synapses.
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BibTeX
@misc{manna2026multifunctional,
title = {{Multifunctional synaptic learning and neuromorphic computing using crystalline TiO$_x$/NiO$_x$ heterojunction-based memory devices}},
author = {Dip Manna and Koushik Mondal and Subhajit Karmakar and Pawan Kumar Ojha and Sourav Roy and Biswarup Satpati and Prasanta Karmakar and Supratic Chakraborty},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.11992},
eprint = {2610.11992},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.11992},
}
RIS
TY - UNPB
TI - Multifunctional synaptic learning and neuromorphic computing using crystalline TiO_x/NiO_x heterojunction-based memory devices
AU - Dip Manna
AU - Koushik Mondal
AU - Subhajit Karmakar
AU - Pawan Kumar Ojha
AU - Sourav Roy
AU - Biswarup Satpati
AU - Prasanta Karmakar
AU - Supratic Chakraborty
PY - 2026
DA - 2026/10/08
PB - arXiv
DO - 10.48550/arxiv.2610.11992
UR - https://arxiv.org/abs/2610.11992
AB - An attempt is made here to mimic different properties of biological synapses using Ag/TiO_x/NiO_x/p^++-Si memristor structure by studying its different transport properties under dc and pulsed bias. The presence of crystalline NiO_x with smaller gains is found to be helpful to get TiO_x deposited on its top with crystalline properties and larger grains. The heterostructure offers stable bipolar forming free non-volatile resistive switching characteristics under reverse biased condition with gradual set and reset features. These devices are also able to successfully implement the classical Pavlov's learning, study artificial nociceptor and Morse code detection. While incorporating synaptic weights derived from the measured conductance programming pulse relationship, an artificial neural network achieves nearly 95\% accuracy in MNIST digit recognition. In brief, NiO_x/TiO_x heterojunction plays the pivotal role in getting such reproducible I−V characteristics for mimicking different properties of biological synapses.
ER -