Accelerated viscosity measurements of polymer solutions using high throughput experimentation and machine learning
In this study, machine learning is used in conjunction with a proxy experiment to relate to high fidelity empirical data to measure and predict viscosity of materials in a rapid, and high throughput fashion. This paper details both the proxy and high-fidelity experiments focusing only on viscometry...
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2021
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sg-ntu-dr.10356-1476852023-03-04T15:45:02Z Accelerated viscosity measurements of polymer solutions using high throughput experimentation and machine learning Chua, Zhong Zhe Kedar Hippalgaonkar School of Materials Science and Engineering kedar@ntu.edu.sg Engineering::Materials::Testing of materials In this study, machine learning is used in conjunction with a proxy experiment to relate to high fidelity empirical data to measure and predict viscosity of materials in a rapid, and high throughput fashion. This paper details both the proxy and high-fidelity experiments focusing only on viscometry and how computation is used to find a relationship between the proxy and high-fidelity experiments. This method is time efficient and economical in the long run, only requiring initial efforts to setup a base standard for future predictive work. Bachelor of Engineering (Materials Engineering) 2021-04-11T12:42:55Z 2021-04-11T12:42:55Z 2021 Final Year Project (FYP) Chua, Z. Z. (2021). Accelerated viscosity measurements of polymer solutions using high throughput experimentation and machine learning. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/147685 https://hdl.handle.net/10356/147685 en application/pdf Nanyang Technological University |
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Engineering::Materials::Testing of materials Chua, Zhong Zhe Accelerated viscosity measurements of polymer solutions using high throughput experimentation and machine learning |
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In this study, machine learning is used in conjunction with a proxy experiment to relate to high fidelity empirical data to measure and predict viscosity of materials in a rapid, and high throughput fashion. This paper details both the proxy and high-fidelity experiments focusing only on viscometry and how computation is used to find a relationship between the proxy and high-fidelity experiments. This method is time efficient and economical in the long run, only requiring initial efforts to setup a base standard for future predictive work. |
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Kedar Hippalgaonkar |
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Kedar Hippalgaonkar Chua, Zhong Zhe |
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Final Year Project |
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Chua, Zhong Zhe |
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Chua, Zhong Zhe |
title |
Accelerated viscosity measurements of polymer solutions using high throughput experimentation and machine learning |
title_short |
Accelerated viscosity measurements of polymer solutions using high throughput experimentation and machine learning |
title_full |
Accelerated viscosity measurements of polymer solutions using high throughput experimentation and machine learning |
title_fullStr |
Accelerated viscosity measurements of polymer solutions using high throughput experimentation and machine learning |
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Accelerated viscosity measurements of polymer solutions using high throughput experimentation and machine learning |
title_sort |
accelerated viscosity measurements of polymer solutions using high throughput experimentation and machine learning |
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Nanyang Technological University |
publishDate |
2021 |
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https://hdl.handle.net/10356/147685 |
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1759853134659715072 |