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npj Computational Materials 2022年第1期8卷 1135-1145页

作者： Shuang Han Giovanni Barcaro Alessandro Fortunelli Steen Lysgaard tejs vegge Heine Anton Hansen Department of Energy Conversion and Storage Technical University of DenmarkFysikvej2800Kgs.LyngbyDenmark CNR-ICCOM&IPCF Consiglio Nazionale delle Ricerchevia G.Moruzzi 156124PisaItaly

The structural stability of nanoalloys is a challenging research subject due to the complexity of size,shape,composition,and chemical *** genetic algorithm is a popular global optimization method that can efficiently search for the ground-state nanoalloy ***,the algorithm suffers from three significant limitations:the efficiency and accuracy of the energy evaluator and the algorithm’s *** we describe the construction of a neural network potential intended for rapid and accurate energy predictions of Pt-Ni nanoalloys of various sizes,shapes,and *** further introduce a symmetry-constrained genetic algorithm that significantly improves the efficiency and viability of the algorithm for realistic size *** combination of the two allows us to explore the space of homotops and compositions of Pt-Ni nanoalloys consisting of up to 4033 atoms and quantitatively report the interplay of shape,size,and composition on the dominant chemical ordering patterns.

关键词： structure symmetry constrained

Rapid mapping of alloy surface phase diagrams via Bayesian evolutionary multitasking

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npj Computational Materials 2023年第1期9卷 905-918页

作者： Shuang Han Steen Lysgaard tejs vegge Heine Anton Hansen Department of Energy Conversion and Storage Technical University of DenmarkAnker EngelundsvejBuilding 3012800 Kgs.LyngbyDenmark

Surface phase diagrams(SPDs)are essential for understanding the dependence of surface chemistry on reaction *** multi-component systems such as metal alloys,the derivation of such diagrams often relies on separate first-principles global optimization tasks under different reaction *** we show that this can be significantly accelerated by leveraging the fact that all tasks essentially share a unified configurational search space,and only a single expensive electronic structure calculation is required to evaluate the stabilities of a surface structure under all considered reaction *** a general solution,we propose a Bayesian evolutionary multitasking(BEM)framework combining Bayesian statistics with evolutionary multitasking,which allows efficient mapping of SPDs even for very complex surface *** proofs of concept,we showcase the performance of our methods in deriving the alloy SPDs for two heterogeneous catalytic systems:the electrochemical oxygen reduction reaction(ORR)and the gas phase steam methane reforming(SMR)reaction.

关键词： alloy surface diagrams

Computational framework for a systematic investigation of anionic redox process in Li-rich compounds

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npj Computational Materials 2020年第1期6卷 1109-1117页

作者： Alexander Sougaard Tygesen Jin Hyun Chang tejs vegge Juan Maria García-Lastra Department of Energy Conversion and Storage Technical University of DenmarkDK-2800 Kgs.LyngbyDenmark

Anionic redox processes play a key role in determining the accessible capacity and cycle life of Li-rich cathode materials for *** present a framework for investigating the anionic redox processes based on data readily available from standard DFT *** recipe includes a method of classifying different anionic species,counting the number of species present in the structure and a preconditioning scheme to promote anionic redox.

关键词： redox anionic readily

Genetic algorithms for computational materials discovery accelerated by machine learning

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npj Computational Materials 2019年第1期5卷 746-751页

作者： Paul C.Jennings Steen Lysgaard Jens Strabo Hummelshøj tejs vegge Thomas Bligaard SUNCAT Center for Interface Science and Catalysis Department of Chemical EngineeringStanford UniversityStanfordCA 94305USA SLAC National Accelerator Laboratory 2575 Sand Hill RoadMenlo ParkCA 94025USA Department of Energy Conversion and Storage Technical University of DenmarkLyngbyDenmark Toyota Research Institute Los AltosCA 94022USA

Materials discovery is increasingly being impelled by machine learning methods that rely on pre-existing *** datasets are lacking,unbiased data generation can be achieved with genetic *** a machine learning model is trained on-the-fly as a computationally inexpensive energy predictor before analyzing how to augment convergence in genetic algorithm-based approaches by using the model as a *** leads to a machine learning accelerated genetic algorithm combining robust qualities of the genetic algorithm with rapid machine *** approach is used to search for stable,compositionally variant,geometrically similar nanoparticle alloys to illustrate its capability for accelerated materials discovery,e.g.,nanoalloy *** machine learning accelerated approach,in this case,yields a 50-fold reduction in the number of required energy calculations compared to a traditional“brute force”genetic *** makes searching through the space of all homotops and compositions of a binary alloy particle in a given structure feasible,using density functional theory calculations.

关键词： alloy alloys searching

Structural and chemical mechanisms governing stability of inorganic Janus nanotubes

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npj Computational Materials 2021年第1期7卷 380-387页

作者： Felix T.Bölle August E.G.Mikkelsen Kristian S.Thygesen tejs vegge Ivano E.Castelli Department of Energy Conversion and Storage Technical University of DenmarkKgs.LyngbyDenmark Department of Physics Technical University of DenmarkKgs.LyngbyDenmark

One-dimensional inorganic nanotubes hold promise for technological applications due to their distinct physical/chemical properties,but so far advancements have been hampered by difficulties in producing single-wall nanotubes with a well-defined *** this work we investigate,based on Density Functional Theory(DFT),the formation mechanism of 135 different inorganic nanotubes formed by the intrinsic self-rolling driving force found in asymmetric 2D Janus *** show that for isovalent Janus sheets,the lattice mismatch between inner and outer atomic layers is the driving force behind the nanotube formation,while in the non-isovalent case it is governed by the difference in chemical bond strength of the inner and outer layer leading to steric *** our pool of candidate structures we have identified more than 100 tubes with a preferred radius below 35Å,which we hypothesize can display distinctive properties compared to their parent 2D *** descriptors have been identified to accelerate the discovery of small-radius tubes and a Bayesian regression approach has been implemented to assess the uncertainty in our predictions on the radius.

关键词： inorganic chemical radius