Suppr超能文献

利用时域太赫兹光谱技术对 APCVD 生长的单层 MoS2 的新见解。

New insights into APCVD grown monolayer MoS using time-domain terahertz spectroscopy.

机构信息

Photonic Materials Metrology Sub Division, Advanced Materials and Device Metrology Division, CSIR-National Physical Laboratory, Dr. K. S. Krishnan Road, New Delhi, 110012, India.

Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, India.

出版信息

Sci Rep. 2023 Mar 13;13(1):4146. doi: 10.1038/s41598-023-31102-z.

Abstract

In modern era, wireless communications at ultrafast speed are need of the hour and search for its solution through cutting edge sciences is a new perspective. To address this issue, the data rates in order of terabits per second (TBPS) could be a key step for the realization of emerging sixth generation (6G) networks utilizing terahertz (THz) frequency regime. In this context, new class of transition metal dichalcogenides (TMDs) have been introduced as potential candidates for future generation wireless THz technology. Herein, a strategy has been adopted to synthesize high-quality monolayer of molybdenum di-sulfide (MoS) using indigenously developed atmospheric pressure chemical vapor deposition (APCVD) set-up. Further, the time-domain transmission and sheet conductivity were studied as well as a plausible mechanism of terahertz response for monolayer MoS has been proposed and compared with bulk MoS. Hence, the obtained results set a stepping stone to employ the monolayer MoS as potential quantum materials benefitting the next generation terahertz communication devices.

摘要

在现代,超高速无线通信是当前的需求,通过前沿科学来寻找解决方案是一个新的视角。为了解决这个问题,每秒太比特(TBPS)的数据速率可能是利用太赫兹(THz)频率范围实现新兴第六代(6G)网络的关键步骤。在这种情况下,新型过渡金属二硫属化物(TMDs)已被引入作为未来无线太赫兹技术的潜在候选材料。在此,采用了一种策略,使用自主开发的常压化学气相沉积(APCVD)设备合成高质量的单层二硫化钼(MoS)。此外,还研究了时域传输和薄片电导率,并提出了单层 MoS 的太赫兹响应的合理机制,并与体相 MoS 进行了比较。因此,所获得的结果为将单层 MoS 用作潜在的量子材料奠定了基础,这将有益于下一代太赫兹通信设备。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/311b/10011412/fa821e410531/41598_2023_31102_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验