Emergent Photoneuromorphic Properties Driven by Defect‐Mediated Trap States in Ternary Copper Chalcogenide Nanocrystals

Neuromorphic devices offer a promising approach to overcoming the Von Neumann Bottleneck by combining sensing and processing. Most of these devices rely on bipolar resistance switching behavior arising from conductive filament formation, controlled by the electrical stimulus. Here, we report a solution‐processed photoneuromorphic system based on zero‐dimensional ternary copper chalcogenide (Cu 2 SnS 3 ) nanocrystals (CTS NCs) that operates under optical stimulus. These CTS NCs contain crystalline faults, which provide electronic trap states in the mid‐bandgap region. The charge transport in this CTS NC‐based thin film is critically governed by defect‐induced electronic states that generate Persistent Photoconductivity, responsible for synaptic emulation. A simple two‐terminal in‐plane artificial synaptic device successfully replicates fundamental biological functions, including short‐term and long‐term plasticity and paired‐pulse facilitation with an index of 167.1 ± 7.1%. We rigorously demonstrate adherence to the Hebbian learning rules through various plasticity protocols and learning curve saturation. The analysis of photocurrent rise and decay shows how learning and forgetting behaviors change with frequency and number of repetitions. Notably, we emulate the biological “savings effect,” where the relearning process requires ∼37% fewer optical pulses than the initial learning phase, accompanied by enhanced memory retention. These devices also exhibit Pavlovian conditioning, a classic example of associative learning.