Mie Andersen

Aarhus University — Denmark

Materials Science · Physical Sciences

27h-index4.3kcitations66works3.92yr avg
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Research Topics

Graphene research and applications(27), Machine Learning in Materials Science(17), Catalytic Processes in Materials Science(15), Advanced Chemical Physics Studies(13), Electrocatalysts for Energy Conversion(12)

Publications66 total

Breaking Scaling Relations with Inverse Catalysts: A Machine Learning Exploration of Trends in CO <sub>2</sub> -to-Formate Energy Barriers
ACS Catalysis·2025Open Access
Interpretable machine learned predictions of adsorption energies at the metal–oxide interface
The Journal of Chemical Physics·2025· 1 citedOpen Access
Transition States Energies from Machine Learning: An Application to Reverse Water–Gas Shift on Single-Atom Alloys
ACS Catalysis·2025· 2 cited
Breaking scaling relations with inverse catalysts: a machine learning exploration of trends in $\mathrm{CO_2}$ hydrogenation energy barriers
arXiv (Cornell University)·2025Open Access
Trends in Structure and IR Spectra of Mixed H<sub>2</sub>O/CO<sub>2</sub> Ices of Astrochemical Relevance
ACS Earth and Space Chemistry·2025· 1 cited
Inverse catalysts: tuning the composition and structure of oxide clusters through the metal support
npj Computational Materials·2025· 7 citedOpen Access
Unraveling the Effect of Dopants in Zirconia-Based Catalysts for CO<sub>2</sub> Hydrogenation to Methanol
ACS Catalysis·2024· 13 cited
Role of Cu Oxide and Cu Adatoms in the Reactivity of CO<sub>2</sub> on Cu(110)
Angewandte Chemie International Edition·2024· 11 citedOpen Access
Role of Cu Oxide and Cu Adatoms in the Reactivity of CO<sub>2</sub> on Cu(110)
Angewandte Chemie·2024Open Access
Machine learning speeds up search for surface structure
Nature Computational Science·2023· 3 cited
Descriptors for binding energies at clusters: The case of nanosilicates as models of interstellar dust grains
The Journal of Chemical Physics·2023· 4 citedOpen Access
Revelations of the d band
Nature Catalysis·2023· 71 cited
Atomic-Scale Site Characterization of Cu–Zn Exchange on Cu(111)
The Journal of Physical Chemistry C·2023· 6 cited
Synthesis, Structure and Mg2+ Ionic Conductivity of Isopropylamine Magnesium Borohydride
Inorganics·2022· 8 citedOpen Access
Graphene at Liquid Copper Catalysts: Atomic‐Scale Agreement of Experimental and First‐Principles Adsorption Height
Advanced Science·2022· 22 citedOpen Access
Graphene as an Adsorption Template for Studying Double Bond Activation in Catalysis
The Journal of Physical Chemistry C·2022· 1 citedOpen Access
Predicting binding motifs of complex adsorbates using machine learning with a physics-inspired graph representation
Nature Computational Science·2022· 46 citedOpen Access
Predicting binding energies of astrochemically relevant molecules via machine learning
Astronomy and Astrophysics·2022· 23 citedOpen Access
Graphene at Liquid Copper Catalysts: Atomic-Scale Agreement of Experimental and First-Principles Adsorption Height
2022· 3 citedOpen Access
(Invited) Bare and Modified Cu(111) Electrocatalysts: Interfacial Structure and Reactivity
ECS Meeting Abstracts·2022
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Frequent Co-authors

Karsten Reuter(22), Bjørk Hammer(16), Liv Hornekær(15), Richard Balog(8), Bjarke Jørgensen(5), Louis Nilsson(5), Philip Hofmann(4), Juan Santiago Cingolani(4), Silvano Lizzit(3), Željko Šljivančanin(3), Flemming Besenbacher(3), Albert Bruix(3), Jeppe V. Lauritsen(3), I. Stensgaard(3), Andrew J. Medford(3), Jens K. Nørskov(3), J. D. Thrower(3), Jan Knudsen(3), Maciej Jankowski(3), Mehdi Saedi(3)