De Pamphilis Luca, Ma Sihang, Dahiya Abhishek Singh, Christou Adamos, Dahiya Ravinder
James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, U.K.
Bendable Electronics and Sustainable Technologies (BEST) Group, Department of Electrical and Computer Engineering, Northeastern University, Boston, Massachusetts 02115, United States.
ACS Appl Mater Interfaces. 2024 Nov 6;16(44):60394-60403. doi: 10.1021/acsami.4c07172. Epub 2024 Oct 25.
Large area electronics (LAE) with the capability to sense and retain information are crucial for advances in applications such as wearables, digital healthcare, and robotics. The big data generated by these sensor-laden systems need to be scaled down or processed locally. In this regard, brain-inspired computing and in-memory computing have attracted considerable interest. However, suitable architectures have mainly been developed using costly and resource-intensive conventional lithography-based methods. There is a need for the development of innovative, resource-efficient fabrication routes that enable such devices and concepts. Herein, we present ZnO nanowire (NW)-based memristors on a polyimide substrate fabricated by a LAE-compatible and resource-efficient route comprising solution processing and printing technologies. High-resolution "drop-on-demand" and "direct ink write" printers are employed to deposit metallic layers (silver and gold) and a ZnO seed layer, needed for the site-selective growth of ZnO NWs via a low-cost hydrothermal method. The printed memristors show high bipolar resistance switching (ON/OFF ratio >10) between two nonvolatile states and consistent switching at ultralow voltages (all devices showed switching at amplitudes <200 mV), with the best performing device showing consistent cycled resistance switching over 4 orders of magnitude with SET and RESET voltages of about 71 and -57 mV, respectively. Thus, the presented devices offer reliable high resistance switching at the lowest reported voltage for printed memristors and prove to be competitive with many conventional nanofabrication-based devices. The presented results show the potential printed memristors technology holds for large-area, low-voltage sensing applications such as electronic skin.
具备传感和信息存储能力的大面积电子器件(LAE)对于可穿戴设备、数字医疗保健和机器人技术等应用的发展至关重要。这些充满传感器的系统产生的大数据需要进行缩减或本地处理。在这方面,受大脑启发的计算和内存计算引起了广泛关注。然而,合适的架构主要是使用基于传统光刻的昂贵且资源密集型方法开发的。需要开发创新的、资源高效的制造路线来实现此类器件和概念。在此,我们展示了一种基于氧化锌纳米线(NW)的忆阻器,该忆阻器位于聚酰亚胺基板上,通过一种与LAE兼容且资源高效的路线制造,该路线包括溶液处理和印刷技术。采用高分辨率的“按需滴涂”和“直接墨水书写”打印机来沉积金属层(银和金)以及氧化锌籽晶层,这是通过低成本水热法进行氧化锌纳米线的位点选择性生长所必需的。印刷忆阻器在两个非易失性状态之间显示出高双极电阻切换(开/关比>10),并且在超低压下具有一致的切换(所有器件在幅度<200 mV时均显示切换),性能最佳的器件在约71 mV和 -57 mV的设置和重置电压下显示出超过4个数量级的一致循环电阻切换。因此,所展示的器件在已报道的印刷忆阻器最低电压下提供可靠的高电阻切换,并且被证明与许多基于传统纳米制造的器件具有竞争力。所展示的结果表明了印刷忆阻器技术在诸如电子皮肤等大面积、低电压传感应用中的潜力。