Electrical response on the nickel-ion containing organic–inorganic hybrid system for the sensing of dopamine

Ghosh, Sarit K.; Perla, Venkata K.; Mallick, Kaushik

doi:10.1016/j.cplett.2022.139362

Cited by 1 publication

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“…The high-resolution N 1s asymmetric spectrum was deconvoluted, and the two peaks at 398.2 and 400.7 eV appeared, corresponding to the metal−nitrogen and amine forms of nitrogen, respectively (Figure 3B). 41 The high- resolution Ni 2p spectrum was deconvoluted into four peaks (Figure 3C). The peaks positioned at 855.1 and 871.1 eV were generated due to the spin-orbital coupling of Ni 2p 3/2 and 2p 1/2 , respectively.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

“…The XPS wide-range spectrum showed the presence of carbon, nitrogen, sulfur, and nickel in the synthesized material (Figure A). The high-resolution N 1s asymmetric spectrum was deconvoluted, and the two peaks at 398.2 and 400.7 eV appeared, corresponding to the metal–nitrogen and amine forms of nitrogen, respectively (Figure B) . The high-resolution Ni 2p spectrum was deconvoluted into four peaks (Figure C).…”

Section: Resultsmentioning

confidence: 99%

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Ultrafine Nickel Sulfide-Based Bipolar Resistive Switching Device as Artificial Synapses for Neuromorphic Application

Perla

Ghosh

Mallick

2022

ACS Appl. Electron. Mater.

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Biologically inspired systems, particularly those that mimic the nervous system of living beings, are becoming more demanded due to their ability to solve illposed problems such as pattern recognition or communication with the external environment. Memristors are essential components to replicate high-density networks of biological synapses that control the effectiveness of communication among neurons and implement learning capability because of their tunable conductance. In this study, an organic−inorganic hybrid system of hexamethylenediamine-stabilized ultrafine nickel sulfide particles was synthesized by employing a complexation-mediated route.Here, we propose a nickel sulfide-based memristor as an artificial synapse for neuromorphic application. The current−voltage behavior of the device exhibited bipolar resistive switching with a stable ON and OFF state with an ON/OFF ratio value of 2.5 × 10 1 . The high-conductance state of the device showed the Ohmic conduction mechanism, and the low-conductance state of the device exhibited the Fowler−Nordheim tunneling mechanism. Using identical and nonidentical pulses, the synaptic plasticity behavior of the device was investigated, which revealed the inverse-symmetric and mirror-symmetric patterns, respectively. The device mimicked the spiketime-dependent plasticity properties for Hebbian learning with a conductance value change from −86 to 91%. We also designed the spiking neural network, consisting of 18 synapses and 11 integrated firing neurons, based on the winner-take-all strategy for unsupervised feature learning.

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Section: ■ Results and Discussionmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%