| About this Abstract |
| Meeting |
Materials Science & Technology 2020
|
| Symposium
|
Ceramics and Glasses Simulations and Machine Learning
|
| Presentation Title |
Data, Materials and Disorder |
| Author(s) |
Stefano Curtarolo |
| On-Site Speaker (Planned) |
Stefano Curtarolo |
| Abstract Scope |
Critical understanding of large amount of data exposes the unavoidability of disorder and leads to new descriptors for discovering entropic materials. The formalism, based on the energy distribution spectrum of randomized calculations, captures the accessibility of equally-sampled states near the ground state and quantifies configurational disorder capable of stabilizing high-entropy homogeneous phases. The combination of these descriptors and Machine Learning uncover scientific surprises. Research sponsored by DOD-ONR. |