Towards high throughput melting property calculations with ab initio accuracy 
aided by machine learning potential

Zhu, Li-Fang; Neugebauer, Jörg; Grabowski, Blazej

Local TagsRelease HistoryDetailsSummary

Towards high throughput melting property calculations with ab initio accuracy aided by machine learning potential

Zhu, L.-F., Neugebauer, J., & Grabowski, B. (2023). Towards high throughput melting property calculations with ab initio accuracy aided by machine learning potential. Talk presented at CALPHAD L Conference. Cambridge, MA, USA. 2023-06-25 - 2023-06-30.

Item is Released

show all hide all

Basic

show hide

Item Permalink: https://hdl.handle.net/21.11116/0000-000F-A9A3-A Version Permalink: https://hdl.handle.net/21.11116/0000-000F-A9AE-F

Genre: Talk

Files

show Files

Locators

show

Creators

show

hide

Creators:
Zhu, Li-Fang^{1, 2}, Author
Neugebauer, Jörg³, Author
Grabowski, Blazej^{4, 5}, Author

Affiliations:
1Ab Initio Thermodynamics, Computational Materials Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society, ou_1863338
2Institute of Materials Science, University of Stuttgart, Germany, ou_persistent22
3Computational Materials Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society, ou_1863337
4Institute of Materials Science, University of Stuttgart, Pfaffenwaldring 55, Stuttgart, 70569, Germany, ou_persistent22
5Computational Phase Studies, Computational Materials Design, Max-Planck-Institut für Eisenforschung GmbH, Max Planck Society, ou_1863341

Content

show

Details

show

hide

Language(s): eng - English

Dates: Created: 2023-06

Publication Status: Not specified

Pages: -

Publishing info: -

Table of Contents: -

Rev. Type: -

Identifiers: -

Degree: -

Event

show

hide

Title: CALPHAD L Conference

Place of Event: Cambridge, MA, USA

Start-/End Date: 2023-06-25 - 2023-06-30

Legal Case

show

Project information

show

Source

show