Abstract
Grain boundary chemistry plays a critical role for the properties of metals and alloys, yet there is a lack of consistent datasets for alloy design and development. With the advent of artificial intelligence and machine learning in materials science, open materials models and datasets can be used to overcome such challenges. Here, we use a universal interatomic potential to compute a grain boundary segregation and embrittlement genome for the Σ5[001](210) grain boundary for FCC and BCC binary alloys. The grain boundary database calculated here serves as a design tool for the embrittlement of high-angle grain boundaries for alloys across 30 base metals of Ag, Al, Au, Ba, Ca, Ce, Co, Cr, Cs, Cu, Fe (both BCC and FCC), Ir, K, Li, Mo, Na, Nb, Ni, Pb, Pd, Pt, Rb, Rh, Sr, Ta, Ti, V, W, Yb, and Zr with 75 solute elements for each.
| Original language | English (US) |
|---|---|
| Article number | 171602 |
| Journal | Applied Physics Letters |
| Volume | 126 |
| Issue number | 17 |
| DOIs | |
| State | Published - Apr 28 2025 |
| Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Physics and Astronomy (miscellaneous)
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