Accurate first-principles-based prediction of the pressure-composition-temperature(PCT)relationships of metal hydrides can enable predictive optimization of hydrogen capacities and pressures.In this work,we introduce ...Accurate first-principles-based prediction of the pressure-composition-temperature(PCT)relationships of metal hydrides can enable predictive optimization of hydrogen capacities and pressures.In this work,we introduce a novel computational framework that integrates density functional theory(DFT)with a Python-based PCT Simulation Toolkit to predict PCT diagrams with high accuracy.By using only structural input data from the metallic phase,this toolkit automates the detection of interstitial voids,generates input files for DFT calculations,and constructs thermodynamic models based on para-equilibrium principles.We validate this approach across five major metal-hydride classes–BCC and FCC alloys,AB_(5),AB_(2),and AB compounds-and demonstrate that even with minimal computational effort,key hydrogen sorption characteristics can be reliably determined.Using the PBE functional without vibrational contribution,our results show that hydrogen capacity predictions achieve a mean accuracy of 95%,while sorption pressures are modeled within one order of magnitude of experimental values.Furthermore,our method can implicitly account for the phase transition in metal hydrides and can reliably model multicomponent alloys with representative alloys of lesser chemical complexity.This framework enables rapid and accurate exploration of metal hydrides to design alloys for new applications.展开更多
基金the ThermOSS and HYPHAD projects. Project HYPHAD was selected in the Joint Transnational Call 2023 of M-ERA.NET 3, which is an EU-funded network of about 49 funding organisations (Horizon 2020 grant agreement No 958174). The project is funded by the Korea Institute for Advancement of Technology, South Korea, the National Science Centre, Poland, and the Sächsisches Staatsministerium für Wissenschaft, Kultur und Tourismus, Germany. This project is co-financed with tax revenue on the basis of the budget adopted by the Saxon State Parliament. This research was financially supported by the Ministry of Trade, Industry and Energy (MOTIE) and Korea Institute for Advancement of Technology (KIAT) through the International Cooperative R&D program No. P0027799This research was partially funded by the National Science Centre, Poland, number: 2023/05/Y/ST3/00249 under the M-ERA.NET 3 Call 2023+1 种基金Project ThermOSS is funded by the European Union and is co-financed with tax revenue on the basis of the budget adopted by the Saxon State ParliamentG.G. acknowledges the support from the National Research Foundation of Korea, the Ministry of Science and ICT under award numbers (2021R1C1C2094407, RS-2024-00429941), and supercomputing resources from Korea Institute of Science and Technology Information (KISTI). The authors gratefully acknowledge the computing time made available to them on the high-performance computer at the NHR Center of TU Dresden. This center is jointly supported by the Federal Ministry of Education and Research (BMBF) and the state governments participating in the NHR.
文摘Accurate first-principles-based prediction of the pressure-composition-temperature(PCT)relationships of metal hydrides can enable predictive optimization of hydrogen capacities and pressures.In this work,we introduce a novel computational framework that integrates density functional theory(DFT)with a Python-based PCT Simulation Toolkit to predict PCT diagrams with high accuracy.By using only structural input data from the metallic phase,this toolkit automates the detection of interstitial voids,generates input files for DFT calculations,and constructs thermodynamic models based on para-equilibrium principles.We validate this approach across five major metal-hydride classes–BCC and FCC alloys,AB_(5),AB_(2),and AB compounds-and demonstrate that even with minimal computational effort,key hydrogen sorption characteristics can be reliably determined.Using the PBE functional without vibrational contribution,our results show that hydrogen capacity predictions achieve a mean accuracy of 95%,while sorption pressures are modeled within one order of magnitude of experimental values.Furthermore,our method can implicitly account for the phase transition in metal hydrides and can reliably model multicomponent alloys with representative alloys of lesser chemical complexity.This framework enables rapid and accurate exploration of metal hydrides to design alloys for new applications.
