Delvin Wuu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Delvin Wuu has a total of 37 co-authors. Here are the top co-authors by number of shared publications:
- Pei Wang
Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
7 shared publications - Fengxia Wei
Institute of Materials Research and Engineering
5 shared publications - Chee Koon Ng
Institute of Materials Research and Engineering, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
4 shared publications Jing Jun Lee
4 shared publications- Yong-Wei Zhang
Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
4 shared publications Dennis Cheng Cheh Tan
3 shared publications
Latest Publications
- Open Access
- 9 April 2024
- Published by Elsevier in Materials & Design
- Vol. 241
Search for eutectic high entropy alloys by integrating high-throughput CALPHAD, machine learning and experiments
- 9 April 2024
- Published by Elsevier in Materials & Design
- Vol. 241
Open AccessSearch for eutectic high entropy alloys by integrating high-throughput CALPHAD, machine learning and experiments
- Open Access
- 25 November 2023
- Published by Elsevier in Materials & Design
- Vol. 236
Unexpected spinodal decomposition in as-cast eutectic high entropy alloy Al30Co10Cr30Fe15Ni15
- 25 November 2023
- Published by Elsevier in Materials & Design
- Vol. 236
Open AccessUnexpected spinodal decomposition in as-cast eutectic high entropy alloy Al30Co10Cr30Fe15Ni15
- 12 November 2022
- Published by Elsevier in Acta Materialia
- Vol. 243
Short-range ordering heredity in eutectic high entropy alloys: A new model based on pseudo-ternary eutectics
- 12 November 2022
- Published by Elsevier in Acta Materialia
- Vol. 243
Short-range ordering heredity in eutectic high entropy alloys: A new model based on pseudo-ternary eutectics
- Open Access
- 1 October 2022
- Published by AIP Publishing in APL Materials
- Vol. 10 (10) , 101104
Machine learning-based inverse design for single-phase high entropy alloys
In this work, we develop an inverse design framework to search for single-phase high entropy alloys (HEAs) subjected to specified phase targets and constraints. This framework is based on the fast grid search in the composition–temperature space, enabled by a highly accurate and efficient machine learning model trained by a huge amount of data. Using the framework, we search through the entire quaternary, quinary, and senary alloy systems, formed by Al, Co, Cr, Cu, Fe, Mn, Ni, and Ti, to identify three types of HEAs: (1) the single-phase FCC HEA with the highest Al content; (2) the single-phase FCC HEA with lower equilibrium temperatures; and (3) single-phase BCC HEAs with Al as the principal element. For the first time, we reveal that the highest Al content in single-phase FCC HEAs is 0.15 in mole fraction, which is higher than the Al contents in all reported single-phase FCC HEAs. The identified HEAs for the quaternary, quinary, and senary groups are Al0.15Co0.34Cr0.16Ni0.35, Al0.15Co0.35Cr0.1Fe0.05Ni0.35, and Al0.15Co0.36Cr0.06Fe0.06Mn0.01Ni0.36, respectively. All the designed HEAs are verified by the equilibrium calculations with Thermo-Calc software and the TCHEA3 database. We further conduct Scheil–Gulliver calculations and experimental fabrications and characterizations for the designed HEAs, to verify the formation of the targeted phases at non-equilibrium conditions. This work demonstrates a viable approach to design HEAs with specified phase targets and constraints.
- 1 October 2022
- Published by AIP Publishing in APL Materials
- Vol. 10 (10) , 101104
Open AccessMachine learning-based inverse design for single-phase high entropy alloys
In this work, we develop an inverse design framework to search for single-phase high entropy alloys (HEAs) subjected to specified phase targets and constraints. This framework is based on the fast grid search in the composition–temperature space, enabled by a highly accurate and efficient machine learning model trained by a huge amount of data. Using the framework, we search through the entire quaternary, quinary, and senary alloy systems, formed by Al, Co, Cr, Cu, Fe, Mn, Ni, and Ti, to identify three types of HEAs: (1) the single-phase FCC HEA with the highest Al content; (2) the single-phase FCC HEA with lower equilibrium temperatures; and (3) single-phase BCC HEAs with Al as the principal element. For the first time, we reveal that the highest Al content in single-phase FCC HEAs is 0.15 in mole fraction, which is higher than the Al contents in all reported single-phase FCC HEAs. The identified HEAs for the quaternary, quinary, and senary groups are Al0.15Co0.34Cr0.16Ni0.35, Al0.15Co0.35Cr0.1Fe0.05Ni0.35, and Al0.15Co0.36Cr0.06Fe0.06Mn0.01Ni0.36, respectively. All the designed HEAs are verified by the equilibrium calculations with Thermo-Calc software and the TCHEA3 database. We further conduct Scheil–Gulliver calculations and experimental fabrications and characterizations for the designed HEAs, to verify the formation of the targeted phases at non-equilibrium conditions. This work demonstrates a viable approach to design HEAs with specified phase targets and constraints.
- 22 February 2022
- Published by Elsevier in Journal of Alloys and Compounds
- Vol. 906, 164288
Additive manufacturing of high-strength and ductile high entropy alloy CoCrFeNiW0.2 composites via laser powder bed fusion and post-annealing
- 22 February 2022
- Published by Elsevier in Journal of Alloys and Compounds
- Vol. 906, 164288
Additive manufacturing of high-strength and ductile high entropy alloy CoCrFeNiW0.2 composites via laser powder bed fusion and post-annealing