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Ab initio phonon transport across grain boundaries in graphene using machine learning based on small dataset

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arXiv 2019年

作者： Hashemi, Amirreza Guo, Ruiqiang Esfarjani, Keivan Lee, Sangyeop Computational Modeling and Simulation Program University of Pittsburgh PittsburghPA15261 United States Department of Mechanical Engineering and Materials Science University of Pittsburgh PittsburghPA15261 United States Department of Mechanical and Aerospace Engineering University of Virginia CharlottesvilleVA22904 United States Department of Materials Science and Engineering University of Virginia CharlottesvilleVA22904 United States Department of Physics University of Virginia CharlottesvilleVA22904 United States Department of Physics and Astronomy University of Pittsburgh PittsburghPA15261 United States

Establishing the structure-property relationship for grain boundaries (GBs) is critical for developing next generation functional materials, but has been severely hampered due to its extremely large configurational space. Atomistic simulations with low computational cost and high predictive power are strongly desirable, but the conventional simulations using empirical interatomic potentials and density functional theory suffer from the lack of predictive power and high computational cost, respectively. A machine learning interatomic potential (MLIP) recently emerged but often requires an extensive size of the training dataset, making it a less feasible approach. Here we demonstrate that an MLIP trained with a rationally designed small training dataset can predict thermal transport across GBs in graphene with ab initio accuracy at an affordable computational cost. In particular, we employed a rational approach based on the structural unit model to find a small set of GBs that can represent the entire configurational space and thus can serve as a cost-effective training dataset for the MLIP. Only 5 GBs were found to be enough to represent the entire configurational space of graphene GBs. Using the atomistic Green's function approach and the MLIP, we revealed that the structure-thermal resistance relation in graphene does not follow the common understanding that large dislocation density causes larger thermal resistance. In fact, thermal resistance is nearly independent of dislocation density at room temperature and is higher when the dislocation density is small at sub-room temperature. We explain this intriguing behavior with the buckling near a GB causing a strong scattering of flexural phonon modes. Our work shows that a machine learning technique combined with conventional wisdom (e.g., structural unit model) can extend the recent success of ab initio thermal transport simulation, which has been mostly limited to single crystals, to complex yet practically importa

关键词： Grain boundaries

How to verify the precision of density-functional-theory implementations via reproducible and universal workflows

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arXiv 2023年

作者： Bosoni, Emanuele Beal, Louis Bercx, Marnik Blaha, Peter Blügel, Stefan Bröder, Jens Callsen, Martin Cottenier, Stefaan Degomme, Augustin Dikan, Vladimir Eimre, Kristjan Flage-Larsen, Espen Fornari, Marco Garcia, Alberto Genovese, Luigi Giantomassi, Matteo Huber, Sebastiaan P. Janssen, Henning Kastlunger, Georg Krack, Matthias Kresse, Georg Kühne, Thomas D. Lejaeghere, Kurt Madsen, Georg K.H. Marsman, Martijn Marzari, Nicola Michalicek, Gregor Mirhosseini, Hossein Müller, Tiziano M.A. Petretto, Guido Pickard, Chris J. Poncé, Samuel Rignanese, Gian-Marco Rubel, Oleg Ruh, Thomas Sluydts, Michael Vanpoucke, Danny E.P. Vijay, Sudarshan Wolloch, Michael Wortmann, Daniel Yakutovich, Aliaksandr V. Yu, Jusong Zadoks, Austin Zhu, Bonan Pizzi, Giovanni Institut de Ciència de Materials de Barcelona ICMAB-CSIC Campus UAB Bellaterra08193 Spain Univ. Grenoble-Alpes CEA IRIG-MEM-L Sim Grenoble38000 France LausanneCH-1015 Switzerland Institute for Materials Chemistry Technical University of Vienna Getreidemarkt 9/165-TC ViennaA-1060 Austria Peter Grünberg Institut Institute for Advanced Simulation Forschungszentrum Jülich JARA JülichD-52425 Germany Forschungszentrum Jülich JülichD-52425 Germany Department of Electromechanical Systems and Metal Engineering Ghent University Belgium Ghent University Belgium Institute of Atomic and Molecular Sciences Academia Sinica Taipei10617 Taiwan Norwegian EuroHPC Competence Center Sigma2 AS Norway SINTEF Industry Materials Physics Oslo Norway Department of Physics Science of Advanced Materials Program Central Michigan University Mount PleasantMI48859 United States Université catholique de Louvain Chemin des Étoiles 8 Louvain-la-Neuve1348 Belgium LausanneCH-1015 Switzerland Kongens Lyngby2800 Denmark VilligenCH-5232 Switzerland University of Vienna Faculty of Physics Center for Computational Materials Science Kolingasse 14-16 ViennaA-1090 Austria VASP Software GmbH Sensengasse 8 ViennaA-1090 Austria Helmholtz-Zentrum Dresden-Rossendorf GörlitzD-02826 Germany Center for Sustainable Systems Design University of Paderborn PaderbornD-33098 Germany OCAS NV ArcelorMittal Global R&D Gent Pres. J. F. Kennedylaan 3 ZelzateB-9060 Belgium Dynamics of Condensed Matter Theoretical Chemistry University of Paderborn PaderbornD-33098 Germany HPE HPC EMEA Research Lab BaselCH-4051 Switzerland Department of Materials Science & Metallurgy University of Cambridge 27 Charles Babbage Road CambridgeCB3 0FS United Kingdom Advanced Institute for Materials Research Tohoku University 2-1-1 Katahira Aoba Sendai980-8577 Japan Department of Materials Science and Engineering McMaster University 1280 Main Street West HamiltonONL8S 4L8 Canada ePot

In the past decades many density-functional theory methods and codes adopting periodic boundary conditions have been developed and are now extensively used in condensed matter physics and materials science research. Only in 2016, however, their precision (i.e., to which extent properties computed with different codes agree among each other) was systematically assessed on elemental crystals: a first crucial step to evaluate the reliability of such computations. We discuss here general recommendations for verification studies aiming at further testing precision and transferability of density-functional-theory computational approaches and codes. We illustrate such recommendations using a greatly expanded protocol covering the whole periodic table from Z=1 to 96 and characterizing 10 prototypical cubic compounds for each element: 4 unaries and 6 oxides, spanning a wide range of coordination numbers and oxidation states. The primary outcome is a reference dataset of 960 equations of state cross-checked between two all-electron codes, then used to verify and improve nine pseudopotential-based approaches. Such effort is facilitated by deploying AiiDA common workflows that perform automatic input parameter selection, provide identical input/output interfaces across codes, and ensure full reproducibility. Finally, we discuss the extent to which the current results for total energies can be reused for different goals (e.g., obtaining formation energies). © 2023, CC BY.

关键词： Density functional theory

End-to-end symmetry preserving inter-atomic potential energy model for finite and extended systems 32

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End-to-end symmetry preserving inter-atomic potential energy...

32nd Conference on Neural Information Processing Systems, NeurIPS 2018

作者： Zhang, Linfeng Han, Jiequn Wang, Han Saidi, Wissam A. Car, Roberto Weinan, E. Program in Applied and Computational Mathematics Princeton University United States Institute of Applied Physics and Computational Mathematics China CAEP Software Center for High Performance Numerical Simulation China Department of Mechanical Engineering and Materials Science University of Pittsburgh United States Department of Chemistry Department of Physics Princeton University United States Princeton Institute for the Science and Technology of Materials Princeton University United States Department of Mathematics Princeton University United States Beijing Institute of Big Data Research China

Machine learning models are changing the paradigm of molecular modeling, which is a fundamental tool for material science, chemistry, and computational biology. Of particular interest is the inter-atomic potential energy surface (PES). Here we develop Deep Potential - Smooth Edition (DeepPot-SE), an end-to-end machine learning-based PES model, which is able to efficiently represent the PES of a wide variety of systems with the accuracy of ab initio quantum mechanics models. By construction, DeepPot-SE is extensive and continuously differentiable, scales linearly with system size, and preserves all the natural symmetries of the system. Further, we show that DeepPot-SE describes finite and extended systems including organic molecules, metals, semiconductors, and insulators with high fidelity. © 2018 Curran Associates Inc..All rights reserved.

关键词： Potential energy

Critical mass effect in evolutionary games triggered by zealots

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arXiv 2019年

作者： Cardillo, Alessio Masuda, Naoki Department of Engineering Mathematics University of Bristol BristolBS8 1UB United Kingdom Department of Computer Science and Mathematics University Rovira i Virgili TarragonaE-43007 Spain University of Zaragoza ZaragozaE-50018 Spain Department of Mathematics University at Buffalo BuffaloNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York BuffaloNY14260-5030 United States

Tiny perturbations may trigger large responses in systems near criticality, shifting them across equilibria. Committed minorities are suggested to be responsible for the emergence of collective behaviors in many physical, social, and biological systems. Using evolutionary game theory, we address the question whether a finite fraction of zealots can drive the system to large-scale coordination. We find that a tipping point exists in coordination games, whereas the same phenomenon depends on the selection pressure, update rule, and network structure in other types of games. Our study paves the way to understand social systems driven by the individuals’ benefit in presence of zealots, such as human vaccination behavior or cooperative transports in animal groups. Copyright © 2019, The Authors. All rights reserved.

关键词： Game theory

Pretreatment Chemometrics in Holistic Biogas Life Cycle Assessment: Framing Case Study with Carica papaya

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Waste and Biomass Valorization 2018年 1-14页

作者： Jensen, Cory D. Olugbemide, A.D. Akpa, F.A.O. Oladipo, Ajayi College of Engineering and Computational Sciences Colorado School of Mines GoldenCO United States Division of Liberal Arts and International Studies Joint Policy Program with the University of Colorado Colorado School of Mines GoldenCO United States Auchi Polytechnic AuchiEdo State Nigeria Department of Basic Sciences Auchi Polytechnic AuchiEdo State Nigeria Department of Science Laboratory Technology Auchi Polytechnic AuchiEdo State Nigeria Department of Agricultural and Bio-Environmental Engineering Auchi Polytechnic AuchiEdo State Nigeria

This research explores synergistic pre-treatment parameters and chemometrics as applicable to systems level biogas related research frameworks (such as the sustainable development goals) for anaerobic digestion biomass processes-policy. Specifically, the hypothesis that simple feedstock pretreatment-digestion methods can be applied to rapidly evaluate biochemical-biogas potential of anaerobically digested Carica papaya petioles was tested. Pretreatment parameters explored include hydration, i.e. 1:4, 1:6, 1:8 and 1:10 substrate mass to water weight ratios and hydrochloric acid pretreatment chemistry, i.e. 1%—0.3 M, 3%—0.7 M, 5%—1.0 M, in batch digestions experiments with non-inoculated C. papaya petioles. Biomass feedstock was obtained from Edo State, Nigeria. Digestions were performed at ambient temperature, i.e. 27 °C, for 3 weeks. Pretreated C. papaya petiole samples were analyzed with Fourier transform infrared spectroscopy to characterize spectra with characteristic absorbance ratios indicative of physicochemical changes in biomass that include;cross-linked lignin ratio, the lateral order index, and hydrogen bond intensity. Cumulative gaseous yields from C. papaya petiole digestions were fit to the modified Gompertz form and optimized with non-linear regression in Matlab® to derive mathematical parameters, i.e. daily maximum production rate of biogas, a lag phase prior to biogas production, and biogas potential. An optimum C. papaya petiole pretreatment digestion scenario, i.e. 1:4 substrate-to-water ratio and 3%, i.e. 0.7 M, HCl pretreatment resulted in a 150% increase in yield, (10.9 mL gas/g VS) compared to non-pretreated C. papaya petiole digestion. Analysis with the modified Gompertz form also suggests rapid biogas potential assessment can be performed in a few days-time, i.e. approximately 10 days with distinct visual characterization of individual digestion performance. It was concluded that the applied digestion procedures with the use of C. papaya peti

关键词： Anaerobic digestion

Tegavivint triggers TECR-dependent nonapoptotic cancer cell death

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Nature chemical biology 2025年 2025 May 26页

作者： Logan Leak Ziwei Wang Alby J Joseph Brianna Johnson Alyssa A Chan Cassandra M Decosto Leslie Magtanong Pin-Joe Ko Weaverly Colleen Lee Joan Ritho Sophia Manukian Alec Millner Shweta Chitkara Jennifer J Salinas Rachid Skouta Matthew G Rees Melissa M Ronan Jennifer A Roth Chad L Myers Jason Moffat Charles Boone Steven J Bensinger David A Nathanson G Ekin Atilla-Gokcumen Everett J Moding Scott J Dixon Department of Biology Stanford University Stanford CA USA. Department of Radiation Oncology Stanford University School of Medicine Stanford CA USA. Department of Chemistry University at Buffalo The State University of New York Buffalo NY USA. Department of Molecular and Medical Pharmacology University of California Los Angeles Los Angeles CA USA. Department of Chemistry University of Massachusetts Amherst Amherst MA USA. Department of Biology University of Massachusetts Amherst Amherst MA USA. Broad Institute of MIT and Harvard Cambridge MA USA. Department of Computer Science and Engineering Bioinformatics and Computational Biology Graduate Program University of Minnesota-Twin Cities Minneapolis MN USA. Program in Genetics & Genome Biology The Hospital for Sick Children Toronto Ontario Canada. Department of Molecular Genetics University of Toronto Toronto Ontario Canada. Donnelly Centre University of Toronto Toronto Ontario Canada. RIKEN Center for Sustainable Resource Science Saitama Japan. Department of Microbiology Immunology and Molecular Genetics University of California Los Angeles Los Angeles CA USA. UCLA Lipidomics Laboratory University of California Los Angeles Los Angeles CA USA. Jonsson Comprehensive Cancer Center David Geffen School of Medicine University of California Los Angeles Los Angeles CA USA. Department of Biology Stanford University Stanford CA USA. sjdixon@stanford.edu.

Small molecules that induce nonapoptotic cell death are of fundamental mechanistic interest and may be useful to treat certain cancers. Here we report that tegavivint, a drug candidate undergoing human clinical trials, can activate a unique mechanism of nonapoptotic cell death in sarcomas and other cancer cells. This lethal mechanism is distinct from ferroptosis, necroptosis and pyroptosis and requires the lipid metabolic enzyme trans-2,3-enoyl-CoA reductase (TECR). TECR is canonically involved in the synthesis of very-long-chain fatty acids but appears to promote nonapoptotic cell death in response to CIL56 and tegavivint via the synthesis of the saturated long-chain fatty acid palmitate. These findings outline a lipid-dependent nonapoptotic cell death mechanism that can be induced by a drug candidate currently being tested in humans.

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High-Throughput computational Studies in Catalysis and Materials Research, and their Impact on Rational Design

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arXiv 2019年

作者： Afzal, Mohammad Atif Faiz Hachmann, Johannes Schrödinger Inc. PortlandOR97204 United States Department of Chemical and Biological Engineering University at Buffalo State University of New York BuffaloNY14260 United States Computational and Data-Enabled Science and Engineering Graduate Program University at Buffalo The State University of New York BuffaloNY14260 United States New York State Center of Excellence in Materials Informatics BuffaloNY14203 United States

End-to-end symmetry preserving inter-atomic potential energy model for finite and extended systems 18

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End-to-end symmetry preserving inter-atomic potential energy...

Proceedings of the 32nd International Conference on Neural Information Processing Systems

作者： Linfeng Zhang Jiequn Han Han Wang Wissam A. Saidi Roberto Car E. Weinan Program in Applied and Computational Mathematics Princeton University Institute of Applied Physics and Computational Mathematics China and CAEP Software Center for High Performance Numerical Simulation China Department of Mechanical Engineering and Materials Science University of Pittsburgh Program in Applied and Computational Mathematics Princeton University and Department of Chemistry and Department of Physics Princeton University and Princeton Institute for the Science and Technology of Materials Princeton University Program in Applied and Computational Mathematics Princeton University and Department of Mathematics Princeton University and Beijing Institute of Big Data Research China

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Postdoc Perspectives on Leadership and Matters of Equity and Inclusion in Polar science

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Perspectives of Earth and Space Scientists

Perspectives of Earth and Space Scientists 2024年第1期5卷

作者： Sophie Goliber Jason Coenen Heather Fair Angela R. Szesciorka Kirstin Schulz David J. Harning Benjamin Fernando Stanislav Saas Ksenofontov Astrid Pacini Marisol Juarez Rivera Radiance Calmer John A. Conroy Eva Lisa Doting Marie Bergelin Devon Dunmire Maria Luisa Sánchez Montes Alexandra M. Ravelo Anne Sledd Taylor R. Stinchcomb Emily J. Tibbett Mariama C. Dryák-Vallies The State University of New York at Buffalo Buffalo NY USA Department of Earth and Atmospheric Sciences University of Nebraska-Lincoln Lincoln NE USA Department of Plant and Microbial Biology University of Minnesota Saint Paul MN USA Marine Mammal Institute Hatfield Marine Science Center Oregon State University Newport OR USA Oden Institute for Computational Engineering and Sciences The University of Texas at Austin Austin TX USA Institute of Arctic and Alpine Research University of Colorado Boulder Boulder CO USA Johns Hopkins University Baltimore MD USA ARCTICenter University of Northern Iowa Cedar Falls IA USA Applied Physics Laboratory Polar Science Center University of Washington Seattle WA USA University of New Mexico Albuquerque NM USA Cooperative Institute for Research in Environmental Sciences University of Colorado Boulder CO USA Ocean Sciences Department University of California Santa Cruz Santa Cruz CA USA Department of Earth and Environmental Science University of Pennsylvania Philadelphia PA USA Berkeley Geochronology Center Berkeley CA USA Department of Earth and Environmental Sciences KU Leuven Heverlee Belgium International Arctic Research Center University of Alaska Fairbanks Fairbanks AK USA National Oceanic and Atmospheric Administration Physical Sciences Laboratory Boulder CO USA Wildlife Conservation Society Arctic-Beringia Program Fairbanks AK USA University of Massachusetts Amherst Amherst MA USA Polar Science Early Career Community Office University of Colorado Boulder Boulder CO USA

In 2023, the first Polar Postdoc Leadership Workshop convened to discuss present and future polar science issues and to develop leadership skills. The workshop discussions fostered a collective commitment to inclusive leadership within the polar science community among all participants. Here, we outline challenges encountered by underrepresented groups in polar sciences, while also noting that progress has been made to improve inclusivity in the field. Further, we highlight the inclusive leadership principles identified by workshop participants to bring to the polar community as we transition into leadership roles. Finally, insights and practical knowledge we gained from the workshop are shared, aiming to inform the community of our commitment to inclusive leadership and encourage the polar community to join us in pursuing action toward our shared vision for a more welcoming polar science future. As a small community of postdoctoral researchers, we outline the leadership skills envisioned for an inclusive future in polar sciences Our vision is to increase the success of underrepresented individuals as leaders by creating a welcoming and supportive career environment Group norms and leadership skills focused on emotional intelligence are critical to equity and inclusion in polar sciences

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