Multiband character revealed from weak antilocalization in platinum thin films

Strategic sampling with stochastic surface walking for machine learning force fields in iron's bcc–hcp phase transitions

“…The energy trajectories from bcc to hcp phase was shown in Fig. 6 , the phase transition from bcc to hcp needs to overcome a energy barrier of 0.12 eV, which is very close to the previous DFT calculation results (0.132 eV, 58 0.156 eV, 46 0.112 eV, 8 0.185 eV 59 ). We also calculated the energies of these intermediate configurations using DFT.…”

“…This is related to the lack of high-energy region data used in the fitting, although we use the SSW sampling method to avoid this problem. This phenomenon is not unique to our model; the PES calculated by Jana et al 46 used Dragoni's GAP potential 28 and Mendelev's EAM potential 60 also exhibit similar behavior. The low weight of transition state structures in the fitting process, owing to their small proportion in the dataset, contributes to the challenges in accurately capturing their energy during the fitting process.…”

“…At the time of our research, publicly available datasets specifically focused on the structures formed by the Fe element were not identified. However, subsequent to our research work, we came across a recent paper 46 that provides a dataset on iron clusters. Regrettably, there remains a lack of available data on the bulk structure, which is directly relevant to our work.…”

“…Therefore, in Fig. 6(b), we present a failed schematic representation of the 60 Dragoni's GAP potential 28 and the latest Jana's TurboGAP potential 46 with the same structures based on our MLFF PES. The dashed line represents the barrierless prediction using MLFF trained without SSW data.…”

“…Fig.6(a)IS, TS, FS structures and (b) reaction energy profile along the Fe bcc-to-hcp phase transition pathway the double-ended surface walking trajectories from bcc to hcp phase, calculated by our MLFF, DFT, Mendelev's EAM potential,60 Dragoni's GAP potential28 and the latest Jana's TurboGAP potential46 with the same structures based on our MLFF PES. The dashed line represents the barrierless prediction using MLFF trained without SSW data.…”