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 o...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.展开更多
Maximally-localized Wannier functions(MLWFs)are widely employed as an essential tool for calculating the physical properties of materials due to their localized nature and computational efficiency.Projectability-disen...Maximally-localized Wannier functions(MLWFs)are widely employed as an essential tool for calculating the physical properties of materials due to their localized nature and computational efficiency.Projectability-disentangled Wannier functions(PDWFs)have recently emerged as a reliable and efficient approach for automatically constructing MLWFs that span both occupied and lowest unoccupied bands.Here,we extend the applicability of PDWFs to magnetic systems and/or those including spin-orbit coupling,and implement such extensions in automated workflows.Furthermore,we enhance the robustness and reliability of constructing PDWFs by defining an extended protocol that automatically expands the projectors manifold,when required,by introducing additional appropriate hydrogenic atomic orbitals.We benchmark our extended protocol on a set of 200 chemically diverse materials,as well as on the 40 systems with the largest band distance obtained with the standard PDWF approach,showing that on our test set the present approach delivers a success rate of over 98%in obtaining accurate Wannier-function interpolations,defined as an average band distance below20 meV between the DFT and Wannier-interpolated bands,up to 2 eV above the Fermi level for metals or above the conduction band minimum for insulators(and a 100%success rate when including only bands up to 1 eV above these values).展开更多
基金supported by the Research Grants Council,Hong Kong SAR through the General Research Fund(17210723,17200424)the support of The University of Hong Kong via seed fund(2201100392)+2 种基金supported by the National Key R&D Program of China(Grant No.2022YFA1004300)the National Natural Science Foundation of China(Grant No.12122103)startup funding from Materials Innovation Institute for Life Sciences and Energy(MILES),HKU-SIRI in Shenzhen for support of this manuscript.
文摘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.
基金supported by the NCCR MARVEL,a National Center of Competence in Research,funded by the Swiss National Science Foundation(grant number 205602)YJ acknowledge support by the China Scholarship Council program+5 种基金JQ acknowledges support by the HORIZON-RIA 2D-PRINTABLE(proposal number:101135196)this work has received funding from the Swiss State Secretariat for Education,Research and Innovation(SERI)NP and GP acknowledge support by the Swiss National Science Foundation(SNSF)Project Funding(grant 200021E_206190 FISH4DIET)WZ acknowledge support by the National Key Research and Development Program of China(Grant No.2022YFB4400200)National Natural Science Foundation of China(Grant Nos.T2394474,T2394470)the Beijing Outstanding Young Scientist Program and Tencent Foundation through the XPLORER PRIZE.We acknowledge access to Piz Daint or Alps at the Swiss National Supercomputing Center,Switzerland under MARVEL's share with the project ID mr32.We acknowledge fruitful discussions with Edward Baxter Linscott and Miki Bonacci.
文摘Maximally-localized Wannier functions(MLWFs)are widely employed as an essential tool for calculating the physical properties of materials due to their localized nature and computational efficiency.Projectability-disentangled Wannier functions(PDWFs)have recently emerged as a reliable and efficient approach for automatically constructing MLWFs that span both occupied and lowest unoccupied bands.Here,we extend the applicability of PDWFs to magnetic systems and/or those including spin-orbit coupling,and implement such extensions in automated workflows.Furthermore,we enhance the robustness and reliability of constructing PDWFs by defining an extended protocol that automatically expands the projectors manifold,when required,by introducing additional appropriate hydrogenic atomic orbitals.We benchmark our extended protocol on a set of 200 chemically diverse materials,as well as on the 40 systems with the largest band distance obtained with the standard PDWF approach,showing that on our test set the present approach delivers a success rate of over 98%in obtaining accurate Wannier-function interpolations,defined as an average band distance below20 meV between the DFT and Wannier-interpolated bands,up to 2 eV above the Fermi level for metals or above the conduction band minimum for insulators(and a 100%success rate when including only bands up to 1 eV above these values).
