Defect characterization of materials' surface using Python

Nowadays, technology flows at an extremely rapid rate in this technologically advancing world. As millions of products and devices these days hugely rely on IC chips, the demand for IC chips has immensely increased. As a result, the global chip shortage became a very transparent issue, especially...

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Main Author: Khine Mya Phyu Tun
Other Authors: Radhakrishnan K
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/157834
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1578342023-07-07T19:04:15Z Defect characterization of materials' surface using Python Khine Mya Phyu Tun Radhakrishnan K School of Electrical and Electronic Engineering ERADHA@ntu.edu.sg Engineering::Electrical and electronic engineering Nowadays, technology flows at an extremely rapid rate in this technologically advancing world. As millions of products and devices these days hugely rely on IC chips, the demand for IC chips has immensely increased. As a result, the global chip shortage became a very transparent issue, especially when Covid-19 started. Thus, the semiconductor engineering field plays a crucial role in this modern world. Surface defect analysis is vital to the semiconductor industry, R&D fields, and material science studies. As more and more new technologies are invented, there is a growing need for methods and software that can analyze, characterize, and visualize different types of materials’ surface defects quickly and accurately. In this final year project (FYP), the software that can rapidly detect the surface defects and count the number of defects on the AFM images will be implemented using a computer vision library in Python. In addition, the program will automatically calculate defect density based on the defect count obtained and then generate the defect density value of the AFM image Bachelor of Engineering (Electrical and Electronic Engineering) 2022-05-24T04:12:13Z 2022-05-24T04:12:13Z 2022 Final Year Project (FYP) Khine Mya Phyu Tun (2022). Defect characterization of materials' surface using Python. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157834 https://hdl.handle.net/10356/157834 en P2032-202 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::Electrical and electronic engineering
spellingShingle Engineering::Electrical and electronic engineering
Khine Mya Phyu Tun
Defect characterization of materials' surface using Python
description Nowadays, technology flows at an extremely rapid rate in this technologically advancing world. As millions of products and devices these days hugely rely on IC chips, the demand for IC chips has immensely increased. As a result, the global chip shortage became a very transparent issue, especially when Covid-19 started. Thus, the semiconductor engineering field plays a crucial role in this modern world. Surface defect analysis is vital to the semiconductor industry, R&D fields, and material science studies. As more and more new technologies are invented, there is a growing need for methods and software that can analyze, characterize, and visualize different types of materials’ surface defects quickly and accurately. In this final year project (FYP), the software that can rapidly detect the surface defects and count the number of defects on the AFM images will be implemented using a computer vision library in Python. In addition, the program will automatically calculate defect density based on the defect count obtained and then generate the defect density value of the AFM image
author2 Radhakrishnan K
author_facet Radhakrishnan K
Khine Mya Phyu Tun
format Final Year Project
author Khine Mya Phyu Tun
author_sort Khine Mya Phyu Tun
title Defect characterization of materials' surface using Python
title_short Defect characterization of materials' surface using Python
title_full Defect characterization of materials' surface using Python
title_fullStr Defect characterization of materials' surface using Python
title_full_unstemmed Defect characterization of materials' surface using Python
title_sort defect characterization of materials' surface using python
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/157834
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