Title
Robust Lead-Free Perovskite Nanowire Array-Based Artificial Synapses Exemplifying Gestalt Principle of Closure via a Letter Recognition Scheme
Abstract
The Gestalt principles of perceptual learning elucidate how the human brain categorizes and comprehends a set of visual elements grouped together. One of the principles of Gestalt perceptual learning is the law of closure which propounds that human perception has the proclivity to visualize a fragmented object as a preknown whole by bridging the missing gaps. Herein, a letter recognition scheme emulating the Gestalt closure principle is demonstrated, utilizing artificial synapses made of 3D integrated MA(3)Bi(2)I(9) (MBI) perovskite nanowire (NW) array. The artificial synapses exhibit short-term plasticity (STP) and long-term potentiation (LTP) and a transition from STP to LTP with increasing number of input electrical pulses. Initiatory ab initio molecular dynamics (AIMD) simulations attribute the conductance change in the MBI NW artificial synapses to the rotation of MA(+) clusters, culminating in charge exchange between MA(+) and Bi2I93-. Each device yields 40 conductance states with excellent retention >10(5) s, minimal variation (2 sigma/mean) <10%, and endurance of approximate to 10(5) cycles. MBI NW-based artificial neural network (ANN) is constructed to recognize fragmented letters alike their distinction in unabridged form and also the gradual withering of synaptic connectivity with engendered missing fragments is demonstrated, thereby successfully implementing Gestalt closure principle.
Year
DOI
Venue
2022
10.1002/aisy.202200065
ADVANCED INTELLIGENT SYSTEMS
Keywords
DocType
Volume
artificial synapses, Gestalt principle of closure, letter recognition, perovskite nanowires
Journal
4
Issue
Citations 
PageRank 
7
0
0.34
References 
Authors
0
11
Name
Order
Citations
PageRank
Swapnadeep Poddar100.34
Zhesi Chen200.34
Zichao Ma300.34
Yuting Zhang400.34
Chak Lam Jonathan Chan500.34
Beitao Ren600.34
Qianpeng Zhang700.34
Daquan Zhang800.34
Guozhen Shen900.68
Haibo Zeng104811.46
Zhiyong Fan1121.74