Daniel Ayoubi
7 Papers
Daniel Ayoubi is an academic researcher. The author has contributed to research in topics: Cluster (spacecraft) & Computer science. The author has an hindex of 1, co-authored 5 publications.
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Papers
Quantum chemical modeling of organic enhanced atmospheric nucleation: A critical review
Jonas Elm,Daniel Ayoubi,Morten Engsvang,Andreas B. Jensen,Yosef Knattrup,Jakub Kubečka,Conor J Bready,Vance R Fowler,Shannon E Harold,George C. Shields +9 more
TL;DR: In this paper , the authors comprehensively review the literature on atmospheric cluster formation involving organic compounds, and suggest a "cluster of functional groups" approach to identify the potential structure of organic compounds that are involved in atmospheric particle formation.
22
Clusteromics V: Organic Enhanced Atmospheric Cluster Formation
TL;DR: In this article , the role of Formic acid (FA) in organic enhanced nucleation was studied through the use of state-of-the-art quantum chemical methods on the cluster systems (acid)1−2(FA)1(base)1-2 with the acids being sulfuric acid, SA)/methanesulfonic acid (MSA), and the bases consisting of ammonia (A), methylamine (MA), dimethylamine, DMA, trimethyamine (TMA), and ethylenediamine (EDA).
17
Do you get what you see? The illicit doping market in Denmark - an analysis of performance and image enhancing drugs seized by the police over a one-year period.
Pia Johansson Heinsvig,Ask Vest Christiansen,Daniel Ayoubi,Laura Smedegaard Heisel,Christian Lindholst +4 more
TL;DR: In this article , the authors examined doping products seized by the police in three regional police districts in Denmark from December 2019 to December 2020 and found that many different companies supply performance and image-enhancing drugs to the Danish market and that counterfeit and substandard products are widespread.
5
Automatization of Atmospheric OH Radical Abstraction Reactions.
Daniel Ayoubi,Galib Hasan,Luís P Viegas,J. Kubečka,J. Elm +4 more
TL;DR: Researchers developed JKTS, an automated tool, to compute gas-phase reaction kinetics of atmospheric VOCs with OH radicals, achieving accurate rate constants within a factor of 2-3 of experimental data for various short-chain compounds and pinonaldehyde.
Clusterome: A Comprehensive Data Set of Atmospheric Molecular Clusters for Machine Learning Applications
TL;DR: In this article , a large database of ∼250k atmospheric relevant cluster structures is used to train the ML model kernel ridge regression (KRR) with the FCHL19 representation, which can extrapolate to larger sizes and transfer acid and base interactions with mean absolute errors below 1 kcal/mol.