APEX: an automated cloud-native material property explorer
Abstract The ability to rapidly evaluate materials properties through atomistic simulation approaches is the foundation of many new artificial intelligence-based approaches to materials identification and design. This depends on the availability of accurate descriptions of atomic bonding and an effi...
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| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
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| Series: | npj Computational Materials |
| Online Access: | https://doi.org/10.1038/s41524-025-01580-y |
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| Summary: | Abstract The ability to rapidly evaluate materials properties through atomistic simulation approaches is the foundation of many new artificial intelligence-based approaches to materials identification and design. This depends on the availability of accurate descriptions of atomic bonding and an efficient means for determining materials properties. We present an efficient, robust platform for calculating materials properties from a wide-range of atomic bonding descriptions, i.e., APEX, the Alloy Property Explorer. APEX enables the rapid evolution of interatomic potential development and optimization, which is of particular importance in fine-tuning new classes of general AI-based foundation models for applications in materials science and engineering. APEX is an open-source, extendable, cloud-native platform for material property calculations using a range of atomistic simulation methodologies that effectively manages diverse computational resources and is built upon user-friendly features including automatic results visualization, a web-based platform and a NoSQL database client. It is designed for expert and non-specialist users, lowering the barrier to entry for interdisciplinary research within an “AI for Materials” framework. We describe the foundation and use of APEX, as well as provide two examples of its application to properties of titanium and 179 metals and alloys for a wide-range of bonding descriptions. |
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| ISSN: | 2057-3960 |