Jonas Elm

Aarhus University

Denmark

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Articles (20)

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2024

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2024

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2023

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2023

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2023

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2023

Collaborators (13)

Nina Sarnela

University of Helsinki

FINLAND

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Xu-Cheng He

University of Helsinki

FINLAND

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Jakub Kubečka

Aarhus University

DENMARK

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Andreas Buchgraitz Jensen

Aarhus University

DENMARK

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Yosef Knattrup

Aarhus University

DENMARK

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Robin Vinther Nielsen

Københavns Universitet

DENMARK

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Daniel McCluskey

University of Hertfordshire

UNITED KINGDOM

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Frank Jensen

Professor

Aarhus University

DENMARK

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Adam Kristensson

Lund University

SWEDEN

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Benjamin Murray

Lecturer/Reader/Professor

University of Leeds

UNITED KINGDOM

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Coty Jen

Assistant Professor

Carnegie Mellon University

UNITED STATES

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George C. Shields

Furman University

UNITED STATES

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Aurelien Dantan

Associate Professor

Aarhus University

DENMARK

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Jonas Elm

Research Interests

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Articles (20)

Chlorine Oxyacids Potentially Contribute to Arctic Aerosol Formation

A cluster-of-functional-groups approach for studying organic enhanced atmospheric cluster formation

Accurate modeling of the potential energy surface of atmospheric molecular clusters boosted by neural networks

Reparameterization of GFN1-xTB for atmospheric molecular clusters: applications to multi-acid–multi-base systems

A new setup for measurements of absolute saturation vapor pressures using a dynamical method: Experimental concept and validation

Natural Marine Precursors Boost Continental New Particle Formation and Production of Cloud Condensation Nuclei

Iodine Clusters in the Atmosphere I: Computational Benchmark and Dimer Formation of Oxyacids and Oxides

HIO3–HIO2-Driven Three-Component Nucleation: Screening Model and Cluster Formation Mechanism

Editorial: Aerosol Research – a new diamond open-access journal covering the breadth of aerosol science and technology

Nitric Acid and Organic Acids Suppress the Role of Methanesulfonic Acid in Atmospheric New Particle Formation

Clusterome: A Comprehensive Data Set of Atmospheric Molecular Clusters for Machine Learning Applications

Current and future machine learning approaches for modeling atmospheric cluster formation

Quantum chemical modeling of organic enhanced atmospheric nucleation: A critical review

Clusteromics V: Organic Enhanced Atmospheric Cluster Formation

Atmospheric Sulfuric Acid–Multi-Base New Particle Formation Revealed through Quantum Chemistry Enhanced by Machine Learning

Limited Role of Malonic Acid in Sulfuric Acid-Dimethylamine New Particle Formation

Toward Modeling the Growth of Large Atmospheric Sulfuric Acid–Ammonia Clusters

Enhancement of Atmospheric Nucleation Precursors on Iodic Acid-Induced Nucleation: Predictive Model and Mechanism

Computational Tools for Handling Molecular Clusters: Configurational Sampling, Storage, Analysis, and Machine Learning

Improved Configurational Sampling Protocol for Large Atmospheric Molecular Clusters

Collaborators (13)

Nina Sarnela

Xu-Cheng He

Jakub Kubečka

Andreas Buchgraitz Jensen

Yosef Knattrup

Robin Vinther Nielsen

Daniel McCluskey

Frank Jensen

Adam Kristensson

Benjamin Murray

Coty Jen

George C. Shields

Aurelien Dantan

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