在科技飞速发展的今天，电子器件的性能提升一直是科研人员关注的焦点。其中，电阻式随机存取存储器（RRAM）作为一种具有巨大潜力的存储技术，其性能的优化至关重要。最近，科学家们在有机材料用于RRAM的研究上取得了新进展。研究发现，调节电子供体和电子受体部分之间的共轭桥，对提高有机材料的忆阻性能起着关键作用。为了深入探究这一现象，科学家们设计并合成了四种具有独特共轭桥的供体 - 受体（D - A）有机小分子，分别是4,7 - 双(4 - ((9H - 芴 - 9 - 亚基)(苯基)甲基)苯基)苯并[c][1,2,5]噻二唑（DF - BT）、4,7 - 双((4 - ((9H - 芴 - 9 - 亚基)(苯基)甲基)苯基)乙炔基)苯并[c][1,2,5]噻二唑（DF - ynl - BT）、4,7 - 双(5 - (4 - ((9H - 芴 - 9 - 亚基)(苯基)甲基)苯基)噻吩 - 2 - 基)苯并[c][1,2,5]噻二唑（DF - Th - BT）和4,7 - 双((5 - (4 - ((9H - 芴 - 9 - 亚基)(苯基)甲基)苯基)噻吩 - 2 - 基)乙炔基)苯并[c][1,2,5]噻二唑（DF - Th - ynl - BT）。他们将这些分子作为RRAM器件的活性层，系统研究了共轭桥对电学参数的影响。结果显示，基于DF - BT、DF - ynl - BT和DF - Th - BT的器件呈现出一次写入多次读取（WORM）的特性，而基于DF - Th - ynl - BT的器件则表现出稳定的闪存式开关行为。与DF - BT相比，采用DF - ynl - BT、DF - Th - BT和DF - Th - ynl - BT的存储器件，由于引入了额外的共轭桥，展现出非易失性存储特性，具有更低的阈值电压、更高的开/关电流比、更好的稳定性和均匀性。这一研究成果表明，对D - A分子中的共轭桥进行调控，可以有效调节电阻式存储行为，提升器件性能。更值得一提的是，基于DF - Th - ynl - BT的器件还成功集成到逻辑门电路和显示功能中，显示出其在人工智能（AI）神经网络应用方面的巨大潜力。未来，这一技术有望为电子存储领域带来新的变革。

期刊

ChemPhysMater

标题

Tailoring memory performance via engineering conjugated bridges in benzo[c][1,2,5]thiadiazole based donor–acceptor small molecules

作者

Xianglin Wang, Hong Lian, Liang Zhao, Zhitao Qin, Yongge Yang, Tianxiao Xiao, Shuanglong Wang, Qingchen Dong

摘要

Tuning the conjugated bridges between the electron-donor and electron-acceptor moieties plays a crucial role in enhancing the memristive properties of organic materials, yet it is rarely reported. Herein, we designed and synthesized four donor–acceptor (D-A) organic small molecules, namely 4,7-bis(4-((9H-fluoren-9-ylidene)(phenyl)methyl)phenyl)benzo[c][1,2,5]thiadiazole (DF-BT), 4,7-bis((4-((9H-fluoren-9-ylidene)(phenyl)methyl)phenyl)ethynyl)benzo[c][1,2,5]thiadiazole (DF-ynl-BT), 4,7-bis(5-(4-((9H-fluoren-9-ylidene)(phenyl)methyl)phenyl)thiophen-2-yl)benzo[c][1,2,5]thiadiazole (DF-Th-BT), and 4,7-bis((5-(4-((9H-fluoren-9-ylidene)(phenyl)methyl)phenyl)thiophen-2-yl)ethynyl)benzo[c][1,2,5]thiadiazole (DF-Th-ynl-BT), featuring unique conjugated bridges. These molecules were employed as active layers in resistive random-access memory (RRAM) devices to systematically investigate the influence of conjugation bridges on the electrical parameters. The results revealed that devices based on DF-BT, DF-ynl-BT, and DF-Th-BT exhibited write-once-read-many-times (WORM) characteristics, while the DF-Th-ynl-BT-based device demonstrated stable Flash-type switching behavior. Compared to DF-BT, memory devices utilizing DF-ynl-BT, DF-Th-BT, and DF-Th-ynl-BT, which incorporate additional conjugated bridges, exhibited nonvolatile memory properties with reduced threshold voltages, an improved ON/OFF current ratio, enhanced stability, and better uniformity. These findings demonstrated that tailoring the conjugated bridges in D-A molecules can effectively modulate resistive memory behavior and enhance device performance. Furthermore, the DF-Th-ynl-BT-based device was successfully integrated into logic gate circuits and display functions, highlighting its significant potential for applications in artificial intelligence (AI) neural networks.

原文链接

https://www.sciencedirect.com/science/article/pii/S2772571525000312

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