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...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Final Year Project |
| Language: | English |
| Published: |
Nanyang Technological University
2021
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/147685 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | 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. |
|---|