Karsten Wedel Jacobsen

Professor

Danmarks Tekniske Universitet

Denmark

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About

Karsten Wedel Jacobsen is a Professor at Danmarks Tekniske Universitet in Denmark. His research encompasses various areas including electronic density-functional distributions, machine learning applications in atomic structure optimization, and chemisorption phenomena in transition-metal halides. His recent publications reflect a focus on innovative techniques in material science, including the activation of 2D materials and the optimization of their properties through advanced computational methods.

Articles (19)

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2025

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2024

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2022

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2022

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2021

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2021

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2021

Collaborators (8)

Jens Jørgen Mortensen

Technical University of Denmark

DENMARK

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Sami Kaappa

University of Tampere

FINLAND

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Thorbjørn Skovhus

Technical University of Denmark

DENMARK

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Thomas Olsen

Technical University of Denmark

DENMARK

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Jakob Schiøtz

Professor

Technical University of Denmark

DENMARK

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Luca M. Ghiringhelli

Professor of data-driven materials modeling

Friedrich-Alexander Universität Erlangen-Nürnberg

GERMANY

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Andrew Medford

Assistant Professor

Georgia Institute of Technology

UNITED STATES

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Kristian Sommer Thygesen

Technical University of Denmark

DENMARK

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Karsten Wedel Jacobsen

Research Interests

Contact this professor

About

Articles (19)

Uncertainty-aware electronic density-functional distributions

Global atomic structure optimization through machine-learning-enabled barrier circumvention in extra dimensions

Activating the Basal Plane of 2D Transition Metal Dichalcogenides via High-Entropy Alloying

GPAW: An open Python package for electronic structure calculations

Selenium and the role of defects for photovoltaic applications

Chemisorption of gas atoms on one-dimensional transition-metal halides

Moiré Patterns in Pt Overlayers on Gold: A Graph Neural Network Interatomic Potential Study

Bayesian optimization of atomic structures with prior probabilities from universal interatomic potentials

Two-dimensional ferroelectrics from high throughput computational screening

Machine-learning-enabled optimization of atomic structures using atoms with fractional existence

Hundreds of new, stable, one-dimensional materials from a generative machine learning model

A Career in Catalysis: Jens Kehlet Nørskov

Computational exfoliation of atomically thin one-dimensional materials with application to Majorana bound states

Numerical quality control for DFT-based materials databases

Structure and energetics of liquid water–hydroxyl layers on Pt(111)

Is the water/Pt(111) interface ordered at room temperature?

Atomic Structure Optimization with Machine-Learning Enabled Interpolation between Chemical Elements

Atomic Structure Optimization with Machine-Learning Enabled Interpolation between Chemical Elements

Assessing the role of quantum effects in two-dimensional heterophase MoTe2 field effect transistors

Collaborators (8)

Jens Jørgen Mortensen

Sami Kaappa

Thorbjørn Skovhus

Thomas Olsen

Jakob Schiøtz

Luca M. Ghiringhelli

Andrew Medford

Kristian Sommer Thygesen

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