High-throughput method–accelerated design of Ni-based superalloys
Ever-increasing demands for superior alloys with improved high-temperature service properties require accurate design of their composition. However, conventional approaches to screen the properties of alloys such as creep resistance and microstructural stability cost a lot of time and resources. Thi...
| Main Authors: | , , , , , , , , , , , , , , , , , |
|---|---|
| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2022
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/162051 |
| _version_ | 1811694710732881920 |
|---|---|
| author | Liu, Feng Wang, Zexin Wang, Zi Zhong, Jing Zhao, Lei Jiang, Liang Zhou, Runhua Liu, Yong Huang, Lan Tan, Liming Tian, Yujia Zheng, Han Fang, Qihong Zhang, Lijun Zhang, Lina Wu, Hong Bai, Lichun Zhou, Kun |
| author2 | School of Mechanical and Aerospace Engineering |
| author_facet | School of Mechanical and Aerospace Engineering Liu, Feng Wang, Zexin Wang, Zi Zhong, Jing Zhao, Lei Jiang, Liang Zhou, Runhua Liu, Yong Huang, Lan Tan, Liming Tian, Yujia Zheng, Han Fang, Qihong Zhang, Lijun Zhang, Lina Wu, Hong Bai, Lichun Zhou, Kun |
| author_sort | Liu, Feng |
| collection | NTU |
| description | Ever-increasing demands for superior alloys with improved high-temperature service properties require accurate design of their composition. However, conventional approaches to screen the properties of alloys such as creep resistance and microstructural stability cost a lot of time and resources. This work therefore proposes a novel high throughput–based design strategy for high-temperature alloys to accelerate their composition selections, by taking Ni-based superalloys as an example. A numerical inverse method is used to massively calculate the multielement diffusion coefficients based on an accurate atomic mobility database. These coefficients are subsequently employed to refine the physical models for tuning the creep rates and structural stability of alloys, followed by unsupervised machine learning to categorize their composition and determine the range of the composition with optimal performance. By using a strict screening criterion, two sets of composition with comprehensively optimal properties are selected, which is then validated by experiments. Compared with recent data-driven methods for materials design, this strategy exhibits high accuracy and efficiency attributed to the high-throughput multicomponent diffusion couples, self-developed atomic mobility database, and refined physical models. Since this strategy is independent of the alloy composition, it can efficiently accelerate the development of multicomponent high-performance alloys and tackle challenges in discovering novel materials. |
| first_indexed | 2024-10-01T07:11:54Z |
| format | Journal Article |
| id | ntu-10356/162051 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:11:54Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | ntu-10356/1620512022-10-03T02:42:06Z High-throughput method–accelerated design of Ni-based superalloys Liu, Feng Wang, Zexin Wang, Zi Zhong, Jing Zhao, Lei Jiang, Liang Zhou, Runhua Liu, Yong Huang, Lan Tan, Liming Tian, Yujia Zheng, Han Fang, Qihong Zhang, Lijun Zhang, Lina Wu, Hong Bai, Lichun Zhou, Kun School of Mechanical and Aerospace Engineering Engineering::Materials Alloy Design Creep Resistance Ever-increasing demands for superior alloys with improved high-temperature service properties require accurate design of their composition. However, conventional approaches to screen the properties of alloys such as creep resistance and microstructural stability cost a lot of time and resources. This work therefore proposes a novel high throughput–based design strategy for high-temperature alloys to accelerate their composition selections, by taking Ni-based superalloys as an example. A numerical inverse method is used to massively calculate the multielement diffusion coefficients based on an accurate atomic mobility database. These coefficients are subsequently employed to refine the physical models for tuning the creep rates and structural stability of alloys, followed by unsupervised machine learning to categorize their composition and determine the range of the composition with optimal performance. By using a strict screening criterion, two sets of composition with comprehensively optimal properties are selected, which is then validated by experiments. Compared with recent data-driven methods for materials design, this strategy exhibits high accuracy and efficiency attributed to the high-throughput multicomponent diffusion couples, self-developed atomic mobility database, and refined physical models. Since this strategy is independent of the alloy composition, it can efficiently accelerate the development of multicomponent high-performance alloys and tackle challenges in discovering novel materials. National Research Foundation (NRF) This work was funded by the National Key Research and Development Program of China (No. 2016YFB0701404), the Natural Science Foundation of China (Nos. 91860105 and 52074366), the China Postdoctoral Science Foundation (No. 2019M662799), the Youth Talent Project of Innovation-driven Plan at Central South University (Grant No. 2019XZ027), the Shandong Major Scientific and Technological Innovation Program of China (No. 2019JZZY010325), the Changsha Municipal Natural Science Foundation (No. kq2014126), and the Project Supported by State Key Laboratory of Powder Metallurgy, Central South University, Changsha, China. K.Z. acknowledges the support from the National Research Foundation, Prime Minister's Office, Singapore, under its Medium-Sized Center funding scheme through the Marine and Offshore Program. 2022-10-03T02:42:06Z 2022-10-03T02:42:06Z 2022 Journal Article Liu, F., Wang, Z., Wang, Z., Zhong, J., Zhao, L., Jiang, L., Zhou, R., Liu, Y., Huang, L., Tan, L., Tian, Y., Zheng, H., Fang, Q., Zhang, L., Zhang, L., Wu, H., Bai, L. & Zhou, K. (2022). High-throughput method–accelerated design of Ni-based superalloys. Advanced Functional Materials, 32(28), 2109367-. https://dx.doi.org/10.1002/adfm.202109367 1616-301X https://hdl.handle.net/10356/162051 10.1002/adfm.202109367 2-s2.0-85129331796 28 32 2109367 en Advanced Functional Materials © 2022 Wiley-VCH GmbH. All rights reserved. |
| spellingShingle | Engineering::Materials Alloy Design Creep Resistance Liu, Feng Wang, Zexin Wang, Zi Zhong, Jing Zhao, Lei Jiang, Liang Zhou, Runhua Liu, Yong Huang, Lan Tan, Liming Tian, Yujia Zheng, Han Fang, Qihong Zhang, Lijun Zhang, Lina Wu, Hong Bai, Lichun Zhou, Kun High-throughput method–accelerated design of Ni-based superalloys |
| title | High-throughput method–accelerated design of Ni-based superalloys |
| title_full | High-throughput method–accelerated design of Ni-based superalloys |
| title_fullStr | High-throughput method–accelerated design of Ni-based superalloys |
| title_full_unstemmed | High-throughput method–accelerated design of Ni-based superalloys |
| title_short | High-throughput method–accelerated design of Ni-based superalloys |
| title_sort | high throughput method accelerated design of ni based superalloys |
| topic | Engineering::Materials Alloy Design Creep Resistance |
| url | https://hdl.handle.net/10356/162051 |
| work_keys_str_mv | AT liufeng highthroughputmethodaccelerateddesignofnibasedsuperalloys AT wangzexin highthroughputmethodaccelerateddesignofnibasedsuperalloys AT wangzi highthroughputmethodaccelerateddesignofnibasedsuperalloys AT zhongjing highthroughputmethodaccelerateddesignofnibasedsuperalloys AT zhaolei highthroughputmethodaccelerateddesignofnibasedsuperalloys AT jiangliang highthroughputmethodaccelerateddesignofnibasedsuperalloys AT zhourunhua highthroughputmethodaccelerateddesignofnibasedsuperalloys AT liuyong highthroughputmethodaccelerateddesignofnibasedsuperalloys AT huanglan highthroughputmethodaccelerateddesignofnibasedsuperalloys AT tanliming highthroughputmethodaccelerateddesignofnibasedsuperalloys AT tianyujia highthroughputmethodaccelerateddesignofnibasedsuperalloys AT zhenghan highthroughputmethodaccelerateddesignofnibasedsuperalloys AT fangqihong highthroughputmethodaccelerateddesignofnibasedsuperalloys AT zhanglijun highthroughputmethodaccelerateddesignofnibasedsuperalloys AT zhanglina highthroughputmethodaccelerateddesignofnibasedsuperalloys AT wuhong highthroughputmethodaccelerateddesignofnibasedsuperalloys AT bailichun highthroughputmethodaccelerateddesignofnibasedsuperalloys AT zhoukun highthroughputmethodaccelerateddesignofnibasedsuperalloys |