Self-powered graphene-silicon photodetectors with hBN passivation

Photodetectors are emerging technologies used in telecommunications, optoelectronics, and sensing. Significant research has been conducted on improving the performance of Silicon (Si)- based optoelectronic devices such as photodetectors and solar cells. Typically, conventional photodetectors require...

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Main Author: Low, Kelly Khe Li
Other Authors: Kim Munho
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2024
Subjects:
Online Access:https://hdl.handle.net/10356/181748
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1817482024-12-20T15:45:50Z Self-powered graphene-silicon photodetectors with hBN passivation Low, Kelly Khe Li Kim Munho School of Electrical and Electronic Engineering munho.kim@ntu.edu.sg Engineering Self-powered photodetectors Surface passivation Graphene Silicon Photodetectors are emerging technologies used in telecommunications, optoelectronics, and sensing. Significant research has been conducted on improving the performance of Silicon (Si)- based optoelectronic devices such as photodetectors and solar cells. Typically, conventional photodetectors require an external voltage for operation, necessitating large packaging to accommodate the operating circuit. In contrast, Self-powered photodetector can operate without requiring an external energy source, offering significantly benefit emerging technologies like the Internet of Things (IoT), autonomous systems, and wearable devices. Therefore, the development of self-powered photodetector is crucial for reducing power consumption in devices, and it shows promise as a tool that can drive economic and technical growth and improve human lives Bachelor's degree 2024-12-17T12:02:32Z 2024-12-17T12:02:32Z 2024 Final Year Project (FYP) Low, K. K. L. (2024). Self-powered graphene-silicon photodetectors with hBN passivation. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/181748 https://hdl.handle.net/10356/181748 en P2018-231 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
Self-powered photodetectors
Surface passivation
Graphene
Silicon
spellingShingle Engineering
Self-powered photodetectors
Surface passivation
Graphene
Silicon
Low, Kelly Khe Li
Self-powered graphene-silicon photodetectors with hBN passivation
description Photodetectors are emerging technologies used in telecommunications, optoelectronics, and sensing. Significant research has been conducted on improving the performance of Silicon (Si)- based optoelectronic devices such as photodetectors and solar cells. Typically, conventional photodetectors require an external voltage for operation, necessitating large packaging to accommodate the operating circuit. In contrast, Self-powered photodetector can operate without requiring an external energy source, offering significantly benefit emerging technologies like the Internet of Things (IoT), autonomous systems, and wearable devices. Therefore, the development of self-powered photodetector is crucial for reducing power consumption in devices, and it shows promise as a tool that can drive economic and technical growth and improve human lives
author2 Kim Munho
author_facet Kim Munho
Low, Kelly Khe Li
format Final Year Project
author Low, Kelly Khe Li
author_sort Low, Kelly Khe Li
title Self-powered graphene-silicon photodetectors with hBN passivation
title_short Self-powered graphene-silicon photodetectors with hBN passivation
title_full Self-powered graphene-silicon photodetectors with hBN passivation
title_fullStr Self-powered graphene-silicon photodetectors with hBN passivation
title_full_unstemmed Self-powered graphene-silicon photodetectors with hBN passivation
title_sort self-powered graphene-silicon photodetectors with hbn passivation
publisher Nanyang Technological University
publishDate 2024
url https://hdl.handle.net/10356/181748
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