Marius Juul Nielsen

most citedBreaking scaling relations with inverse catalysts: a machine learning exploration of trends in

C O_{2}

hydrogenation energy barriers

4 citations · 6 across the 2 of their papers we have counts for

collaborators

2 papers

cond-mat.mtrl-sci2025★ 2 cited

Interpretable machine learned predictions of adsorption energies at the metal--oxide interface

Marius Juul Nielsen, Luuk H. E. Kempen, Julie de Neergaard Ravn +2

The conversion of $C O_{2}$ to value-added compounds is an important part of the effort to store and reuse atmospheric $C O_{2}$ emissions. Here we focus on $\mathrm{CO…

cond-mat.mtrl-sci2025★ 4 cited

Breaking scaling relations with inverse catalysts: a machine learning exploration of trends in $C O_{2}$ hydrogenation energy barriers

Luuk H. E. Kempen, Marius Juul Nielsen, Mie Andersen

The conversion of $C O_{2}$ into useful products such as methanol is a key strategy for abating climate change and our dependence on fossil fuels. Developing new catalysts fo…

Interpretable machine learned predictions of adsorption energies at the metal--oxide interface

Breaking scaling relations with inverse catalysts: a machine learning exploration of trends in CO2​ hydrogenation energy barriers

Breaking scaling relations with inverse catalysts: a machine learning exploration of trends in $C O_{2}$ hydrogenation energy barriers