Cheng Yinzi, Liu Zongguang, Wang Junzhuan, Xu Jun, Yu Linwei
School of Electronic Science and Engineering/National Laboratory of Solid-State Microstructures, Nanjing University, 210023, Nanjing, China.
College of Physics Science and Technology/Microelectronics Industry Research Institute, Yangzhou University, 225009, Yangzhou, China.
ACS Appl Mater Interfaces. 2024 May 8;16(18):23625-23633. doi: 10.1021/acsami.4c03991. Epub 2024 Apr 29.
Planar silicon nanowires (SiNWs), grown by using low temperature catalytic approaches, are excellent 1D channel materials for developing high-performance logics and sensors. However, a deterministic position and size control of the metallic catalyst droplets, that lead to the growth of SiNWs, remains still a significant challenge for reliable device integration. In this work, we present a convenient but powerful edge-trimming catalyst formation strategy, which can help to produce a rather uniform single-row of indium (In) catalyst droplets of = 67 ± 5 nm in diameter, with an exact one-droplet-on-one-step arrangement. This approach marks a significant achievement in self-assembled catalyst formation and offers a foundation to attain a reliable and scalable growth of density SiNW channels, via an in-plane solid-liquid-solid (IPSLS) mechanism, with a uniform diameter down to = 35 ± 4 nm, and do not rely on high-precision lithography techniques. Prototype SiNW-based field effect transistors (FETs) are also fabricated, with a high / current ratio and small subthreshold swing of >10 and 262 mV·dec, respectively, indicating a reliable new routine to integrate a wide range of SiNW-based logic, sensor, and display applications.
通过低温催化方法生长的平面硅纳米线(SiNWs)是用于开发高性能逻辑器件和传感器的优异一维沟道材料。然而,对于导致SiNWs生长的金属催化剂液滴,实现其确定性的位置和尺寸控制,对于可靠的器件集成而言仍然是一项重大挑战。在这项工作中,我们提出了一种简便而有效的边缘修整催化剂形成策略,该策略有助于生成直径为67±5 nm的相当均匀的单排铟(In)催化剂液滴,且呈精确的一步一滴排列。这种方法在自组装催化剂形成方面取得了重大成果,并为通过面内固-液-固(IPSLS)机制实现密度SiNW沟道的可靠且可扩展生长提供了基础,所生长的SiNW直径均匀,低至35±4 nm,并且不依赖于高精度光刻技术。还制造了基于SiNW的原型场效应晶体管(FET),其开/关电流比高,亚阈值摆幅分别大于10和262 mV·dec,这表明一种可靠的新方法可用于集成各种基于SiNW的逻辑、传感器和显示应用。