Optical determination of layered-materials InSe thickness via RGB contrast method and regression analysis

Author:

Lu Yi-YingORCID,Yu Hsiao-Ching,Wang You-Xin,Hung Chih-Keng,Chen You-Ren,Jhou Jie,Yen Peter Tsung-WenORCID,Hsu Jui-Hung,Sankar RamanORCID

Abstract

Abstract Indium selenide (InSe) features intriguing thickness-dependent optoelectronic properties, and a simple, and precise way to identify the thickness is essential for the rapid development of InSe research. Here, a red, green, and blue (RGB) color contrast method with regression analysis for quantitative correlation of three optical contrasts from RGB channels with the InSe thickness (1–35 nm), is demonstrated. The lower accuracy of the thickness identification obtained from the individual channels was discussed. Moreover, the effective refractive indices in the three RGB regions can be extracted from the Fresnel equation and numerical analysis by finding the best fit to the experimental optical contrast. After further consideration of the wavelength-dependent refractive indices, the slope of the regression line between the estimated thickness and that obtained from the atomic force microscope was improved from 1.59 ± 0.05 to 0.97 ± 0.02. The complex refractive index spectra of InSe (1–10 layers) generated from ab initio numerical calculation results were also adopted to identify the InSe thickness. Compared to dispersion, the evolution of the band structure had less effect on thickness identification. This work could be extended to other layered materials, facilitate the thickness-dependent study of layered materials, and expedite the realization of their practical applications.

Funder

Academia Sinica

Ministry of Science and Technology of Taiwan

Publisher

IOP Publishing

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Mechanics of Materials,General Materials Science,General Chemistry,Bioengineering

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3