Variable Learning‐Memory Behavior from π‐Conjugated Ligand to Ligand‐Containing Cobalt(II) Complex^†

Abstract

Comprehensive Summary In the information‐explosion era, developing novel algorithms and memristive devices has become a promising concept for next‐generation capacity enlargement technology. Organic small molecule‐based devices displaying superior learning‐memory performance have attracted much attention, except for the existence of poor heat‐resilience and mediocre conductivity. In this paper, a strategy of transforming an organic‐type data‐storage material to metal complex is proposed to resolve these intrinsic issues. A pristine NDI‐derivative (NIPy) and its corresponding Co(II) complex (CoNIPy) are synthesized for the purpose of electrical property investigation. CoNIPy complex‐based memristive device exhibits superior ternary WORM memory performance compared with the binary behavior of NIPy, including >104 s of reading, lower threshold voltage (Vth), 1: 102: 105 of OFF/ON1/ON2 current ratio, and long‐term stability in heating environment. The variable learning‐memory behavior can be attributed to the enhanced ligand‐to‐metal charge transfer (LMCT) and improved redox activity after the introduction of central metal atom and coordination bond. These studies on material innovation and optimal performance are of great importance not only for environmentally‐robust memristive devices but also for practical application of a host of organic electronic devices.

Organic iontronic memristors for artificial synapses and bionic neuromorphic computing

“…96 By utilizing diethylmethyl(2-methoxyethyl)ammonium bis(trifluoromethylsulfonyl)imide (DEME-TFSI), an ionic liquid known for its flexibility, it was able to fine-tune the memory behavior of the device. The device exhibits excellent switching stability and retention, with the HRS and the LRS lasting for a minimum of 150 cycles when subjected to a readout voltage of 1.0 V. Additionally, the device successfully passed a hold test lasting 10 5 s. This research demonstrates that integrating memristors into computing systems can lead to high-density storage capabilities and advanced artificial intelligence processing (Fig. 5d).…”

“…These newly-designed materials and their doped complexes have significantly enhanced device performance, making them suitable for various applications, including neuromorphic computing, artificial intelligence, energy storage, and so on. 150 In this review, we introduced the basic concept and synthetic methods of OIMs, and discussed the various applications of OIM-based memristors. Their advantages relative to other memristors were also highlighted.…”

Carbon Nanodots Memristor: An Emerging Candidate toward Artificial Biosynapse and Human Sensory Perception System

“…To date, a wide range of inorganic and organic memristive materials have been intensively studied, including inorganic oxides, [ 5 ] phase‐change materials, [ 6 ] organic small molecules, [ 4 , 7 ] polymers, [ 8 ] organic nanocrystals, [ 9 ] semiconductor quantum dots (SQDs), [ 10 ] van der Waals and 2D materials, [ 11 ] novel carbon materials, [ 12 ] biomaterials, [ 13 ] MXenes, [ 14 ] ferroelectric materials, [ 15 ] perovskites, [ 16 ] as well as their hybrid composites. [ 17 ] For organic memristive materials, one of the challenges is their insufficient stability and low tolerance to ambient conditions, whereas inorganic memristive materials are limited by their poor flexibility and tunability. By contrast, the emerging solution‐processable carbon nanodots (CDs) exhibit unique physicochemical and photochemical properties, such as excellent charge storage capability, tunable energy level, and photo‐/electro‐luminescence, offering an appealing path to achieve high‐performance photosensitive logic sensors and electronic devices.…”

Rational design of a Ru(ii) complex with a donor–acceptor–donor structure for organic resistive memory devices

“…The development of novel memory devices with excellent performance has been in urgent demand owing to the explosive growth of information data. 1–14 Recently, organic resistive memory devices have become promising choices for future information storage technology due to their simple device structure, excellent downscaling potential, and high storage density. 15–19 They can realize binary or even multi-level storage based on the conductive switching effects of the active materials rather than the amount of charge stored in cells, which is expected to overcome the physical limitation of Moore's law.…”