Efficient Global Structure Optimization with a Machine-Learned Surrogate Model von Bisbo, Malthe K., Hammer, Bjork

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A genetic algorithm for first principles global structure optimization of supported nano structures von Vilhelmsen, Lasse B, Hammer, Bjørk

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Dimerization of dehydrogenated polycyclic aromatic hydrocarbons on graphene von Tang, Zeyuan, Hammer, Bjørk

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Global optimization of atomic structure enhanced by machine learning von Bisbo, Malthe K., Hammer, Bjørk

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An automated nudged elastic band method von Kolsbjerg, Esben L., Groves, Michael N., Hammer, Bjørk

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Accelerating structure search using atomistic graph-based classifiers von Slavensky, Andreas Møller, Hammer, Bjørk

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The mechanism of Mg2+ conduction in ammine magnesium borohydride promoted by a neutral molecule von Yan, Yigang, Dononelli, Wilke, Jorgensen, Mathias, Grinderslev, Jakob B., Lee, Young-Su, Cho, Young Whan, Cerny, Radovan, Hammer, Bjork, Jensen, Torben R.

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A machine learning potential for simulating infrared spectra of nanosilicate clusters von Tang, Zeyuan, Bromley, Stefan T., Hammer, Bjørk

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Atomistic global optimization X: A Python package for optimization of atomistic structures von Christiansen, Mads-Peter V., Rønne, Nikolaj, Hammer, Bjørk

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Systematic study of Au6 to Au12 gold clusters on MgO(100) F centers using density-functional theory von Vilhelmsen, Lasse B, Hammer, Bjørk

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Identification of the Catalytic Site at the Interface Perimeter of Au Clusters on Rutile TiO2(110) von Vilhelmsen, Lasse B, Hammer, Bjørk

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Cascading symmetry constraint during machine learning-enabled structural search for sulfur-induced Cu(111)-(43×43) surface reconstruction von Brix, Florian, Verner Christiansen, Mads-Peter, Hammer, Bjørk

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Atomic Energies from a Convolutional Neural Network von Chen, Xin, Jørgensen, Mathias S, Li, Jun, Hammer, Bjørk

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Machine learning enhanced global optimization by clustering local environments to enable bundled atomic energies von Meldgaard, Søren A., Kolsbjerg, Esben L., Hammer, Bjørk

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Generating candidates in global optimization algorithms using complementary energy landscapes von Slavensky, Andreas Møller, Christiansen, Mads-Peter V., Hammer, Bjørk

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Tight-Binding Approximation-Enhanced Global Optimization von Van den Bossche, Maxime, Grönbeck, Henrik, Hammer, Bjørk

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A Machine‐Learning‐Based Approach for Solving Atomic Structures of Nanomaterials Combining Pair Distribution Functions with Density Functional Theory von Kløve, Magnus, Sommer, Sanna, Iversen, Bo B., Hammer, Bjørk, Dononelli, Wilke

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Visualizing hydrogen-induced reshaping and edge activation in MoS2 and Co-promoted MoS2 catalyst clusters von Grønborg, Signe S., Salazar, Norberto, Bruix, Albert, Rodríguez-Fernández, Jonathan, Thomsen, Sean D., Hammer, Bjørk, Lauritsen, Jeppe V.

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Gaussian representation for image recognition and reinforcement learning of atomistic structure von Christiansen, Mads-Peter V., Mortensen, Henrik Lund, Meldgaard, Søren Ager, Hammer, Bjørk

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Exploration versus Exploitation in Global Atomistic Structure Optimization von Jørgensen, Mathias S., Larsen, Uffe F., Jacobsen, Karsten W., Hammer, Bjørk

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