Nowadays, academic research relies not only on sharing with the academic community the scientific results obtained by research groups while studying certain phenomena but also on sharing computer codes developed within the community. In the field of atomistic modeling, these were software packages for classical atomistic modeling, and later for quantum-mechanical modeling; currently, with the fast growth of the field of machine-learning potentials, the packages implement such potentials. In this paper, we present the MLIP-3 package for constructing moment tensor potentials and performing their active training. This package builds on the MLIP-2 package [Novikov et al., "The MLIP package: moment tensor potentials with MPI and active learning," Mach. Learn.: Sci. Technol., 2(2), 025002 (2020)], however, with a number of improvements, including active learning on atomic neighborhoods of a possibly large atomistic simulation.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1063/5.0155887 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Ab Initio Rotational and Vibrational Spectroscopy of CH Radicals at the Coupled Cluster Level.
J Phys Chem A
January 2025
Department of Chemistry, University of California, Davis, One Shields Ave., Davis, California 95616, United States.
Combustion and pyrolysis processes of allene and propyne are known to involve radicals with the structural formula CH, the most stable of which is the classic resonance-stabilized allyl radical. In addition to allyl, four other isomers of CH are possible: the propene derivatives -1-propenyl, -1-propenyl, and 2-propenyl, as well as the cyclopropane derivative cyclopropyl. Among these 5 species, the allyl radical has been extensively studied both theoretically and spectroscopically; however, little is known about the spectroscopy of the cyclopropyl radical, and virtually no experimental spectroscopic data are available for the remaining three.
View Article and Find Full Text PDFElectric dipole moment of excited octupolar molecules: Potential qubit implementation.
J Chem Phys
January 2025
Volgograd State University, University Avenue 100, Volgograd 400062, Russia.
The first excited state of conjugated donor-acceptor molecules of C3 symmetry (octupolar molecules) is doubly degenerate. Such a doublet is known to be isomorphic to a spin 1/2. It is shown that a large electric dipole moment is associated with this spin.
View Article and Find Full Text PDFEnd-divergent architecture diversifies within-muscle mechanical action in human gluteus maximus in vivo.
J Biomech
January 2025
Faculty of Health and Sports Science, Doshisha University, Kyoto, Japan; Human Performance Laboratory, Waseda University, Saitama, Japan.
A muscle's mechanical action is affected by its architecture. However, less is known about the architecture of muscles with broad attachments: "end-divergent" muscles. Potential regional variation of fascicle orientation in end-divergent muscles suggests that their mechanical action varies by region.
View Article and Find Full Text PDFUncovering the complexity of source mechanism in an anisotropic coal mine using sequential inversion.
Sci Rep
December 2024
Department of Geophysics, Graduate School of Science, Tohoku University, Sendai, 980-8578, Japan.
Accurate characterisation of seismic source mechanisms in mining environments is crucial for effective hazard mitigation, but it is complicated by the presence of anisotropic geological conditions. Neglecting anisotropic effects during moment tensor (MT) inversion introduces significant distortions in the retrieved source characteristics. In this study, we investigated the impact of ignoring anisotropy during MT inversion on the reliability of hazard assessment.
View Article and Find Full Text PDFOvercoming Inaccuracies in Machine Learning Interatomic Potential Implementation for Ionic Vacancy Simulations.
J Phys Chem Lett
January 2025
Department of Mechanical Engineering & Materials Science, University of Pittsburgh, Pittsburgh, Pennsylvania 15261, United States.
Machine learning interatomic potentials, particularly ones based on deep neural networks, have taken significant strides in accelerating first-principles simulations, expanding the length and time scales of the simulations with accuracies akin to first-principles simulations. Notwithstanding their success in accurately describing the physical properties of pristine ionic systems with multiple oxidation states, herein we show that an implementation of deep neural network potentials (DNPs) yield vacancy formation energies in MgO with a significant ∼3 eV error. In contrast, we show that moment tensor potentials can accurately describe all properties of the oxide, including vacancy formation energies.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!