Surface ligand engineering of perovskite quantum dots for n-type and stretchable photosynaptic transistor with an ultralow energy consumption

A stretchable n-type photosynaptic device with low energy consumption and high photoresponse is achieved by surface ligand engineering of perovskite quantum dots, ascribing to a superior heterojunction optimization and defect passivation. This strategy exhibits multiwavelength photosynaptic characteristics and effectively emulates learning behaviors, signifying potential significant advancements in soft optoelectronics. [Display omitted] •Surface ligand engineering of perovskite quantum dots optimize the heterojunction.•The photocurrent is improved by defect passivation and interface optimization.•The N-type device performs photocurrent detection (1 ms) and contrast (3.2 × 106).•The N-type device performs superior artificial synapse characteristics.•The learning behavior is achieved by multiple wavelengths and low voltage (50 mV). The escalating demand for high-speed transmission has prompted an exploration into the development of photonic synapses, offering a promising avenue for extending energy-efficient, low data latency in neurologically inspired robotics and neuromorphic network computation. However, the performance of n-type conjugated polymers (CPs)-based transistors with intrinsic stretchability as photonic synapse devices for neuromorphic simulation has been suboptimal. This study introduces a series of surface ligands for perovskite quantum dots (PeQDs) with varying chain lengths and bulkiness of quaternary ammonium bromide to adjust interactions with the n-type CPs, naphthalene-diimide-bithiophene (PNDI2T). The results demonstrate that didodecyldimethylammonium bromide (DDAB) reveals superior defect passivation and optimal ligand bulkiness, enhancing interaction and energy transmission between CPs and PeQDs. Through surface ligand engineering of PeQDs, the PNDI2T/DDAB-QD composite effectively emulates characteristics of photonic synapses under multiwavelength light stimuli and strain; it achieves outstanding performance metrics, comprising the fastest response time (1 ms), highest current contrast (3.2 × 106), paired-pulse facilitation (1.97), ultralow energy consumption (0.16 aJ), and human learning behaviors at an ultralow operating voltage of 50 mV under a 50 % tensile strain. Concisely, leveraging surface ligand engineering of PeQDs proposes a promising strategy for advancing neurologically soft optoelectronics and neuromorphic computation.