Steen Lysgaard

Technical University of Denmark — Denmark

Materials Science · Physical Sciences

13h-index5.0kcitations37works0.02yr avg
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Research Topics

Machine Learning in Materials Science(14), Electrocatalysts for Energy Conversion(8), Ammonia Synthesis and Nitrogen Reduction(8), Advanced Battery Materials and Technologies(7), Computational Drug Discovery Methods(5)

Publications37 total

Rapid mapping of alloy surface phase diagrams via Bayesian evolutionary multitasking
npj Computational Materials·2023· 20 citedOpen Access
Unveiling the plating-stripping mechanism in aluminum batteries with imidazolium-based electrolytes: A hierarchical model based on experiments and ab initio simulations
Chemical Engineering Journal·2023· 7 citedOpen Access
Rapid mapping of alloy surface phase diagrams via Bayesian evolutionary multitasking
2023Open Access
Rapid mapping of alloy surface phase diagrams via Bayesian evolutionary multitasking
2023Open Access
Rapid and accurate mapping of reaction condition-dependent alloy phase diagrams via Bayesian evolutionary multitasking
2022Open Access
Rapid and accurate mapping of reaction condition-dependent alloy phase diagrams via Bayesian evolutionary multitasking
2022· 2 citedOpen Access
Unfolding the structural stability of nanoalloys via symmetry-constrained genetic algorithm and neural network potential
npj Computational Materials·2022· 39 citedOpen Access
Charge Transport in Al<sub>2</sub>S<sub>3</sub> and Its Relevance in Secondary Al–S Batteries
The Journal of Physical Chemistry C·2021· 8 citedOpen Access
Front Cover: Ab initio Molecular Dynamics Investigations of the Speciation and Reactivity of Deep Eutectic Electrolytes in Aluminum Batteries (ChemSusChem 9/2021)
ChemSusChem·2021Open Access
Ab initio Molecular Dynamics Investigations of the Speciation and Reactivity of Deep Eutectic Electrolytes in Aluminum Batteries
ChemSusChem·2021· 1 citedOpen Access
Ab Initio Molecular Dynamics Investigations of the Speciation and Reactivity of Deep Eutectic Electrolytes in Aluminum Batteries
2021Open Access
Ab initio Molecular Dynamics Investigations of the Speciation and Reactivity of Deep Eutectic Electrolytes in Aluminum Batteries
ChemSusChem·2021· 6 cited
Ab Initio Molecular Dynamics Investigations of the Speciation and Reactivity of Deep Eutectic Electrolytes in Aluminum Batteries
2021Open Access
Ab Initio Molecular Dynamics Investigations of the Speciation and Reactivity of Deep Eutectic Electrolytes in Aluminum Batteries
2021· 1 citedOpen Access
Genetic algorithms for computational materials discovery accelerated by machine learning
npj Computational Materials·2019· 248 citedOpen Access
Machine Learning Accelerated Genetic Algorithms for Computational Materials Search
2018· 1 citedOpen Access
Machine Learning Accelerated Genetic Algorithms for Computational Materials Search
2018· 2 citedOpen Access
Machine Learning Accelerated Genetic Algorithms for Computational Materials Search
2018Open Access
Combined DFT and Differential Electrochemical Mass Spectrometry Investigation of the Effect of Dopants in Secondary Zinc–Air Batteries
ChemSusChem·2018· 30 citedOpen Access
The atomic simulation environment—a Python library for working with atoms
Journal of Physics Condensed Matter·2017· 4.3k citedOpen Access
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Frequent Co-authors

Tejs Vegge(31), Heine Anton Hansen(10), J. M. García‐Lastra(9), Paul C. Jennings(7), Arghya Bhowmik(7), Jens S. Hummelshøj(6), Ulrich J. Quaade(6), David Carrasco‐Busturia(6), P. Jensen(5), Thomas Bligaard(5), Jón Steinar Garðarsson Mýrdal(4), Piotr Jankowski(4), Shuang Han(3), Shuang Han(3), Piotr Jankowski(3), Jón Bergmann Maronsson(2), Andreas L. Ammitzbøll(2), Poul Norby(2), Ask Hjorth Larsen(1), Jens Jørgen Mortensen(1)