Valentin Vassilev-Galindo
University of Luxembourg
10 Papers
59 Citations
Valentin Vassilev-Galindo is an academic researcher from University of Luxembourg. The author has contributed to research in topics: van der Waals force & Computer science. The author has an hindex of 5, co-authored 10 publications. Previous affiliations of Valentin Vassilev-Galindo include Universidad Veracruzana.
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Papers
Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems.
John A. Keith,Valentin Vassilev-Galindo,Bingqing Cheng,Stefan Chmiela,Michael Gastegger,Klaus-Robert Müller,Alexandre Tkatchenko +6 more
TL;DR: A critical review of noteworthy applications that demonstrate how computational chemistry and machine learning can be used together to provide insightful predictions in molecular and materials modeling, retrosyntheses, catalysis, and drug design are reviewed.
334
Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems.
John A. Keith,Valentin Vassilev-Galindo,Bingqing Cheng,Stefan Chmiela,Michael Gastegger,Klaus-Robert Müller,Alexandre Tkatchenko +6 more
TL;DR: In this paper, the authors provide a review of the applications of computational chemistry and machine learning in molecular and materials modeling, retrosyntheses, catalysis, and drug design.
308
Planar pentacoordinate carbons
Valentin Vassilev-Galindo,Sudip Pan,Kelling J. Donald,Gabriel Merino +3 more
- 07 Feb 2018
TL;DR: In this article, the D5h-symmetric planar pentacoordinate carbon (ppC) species CAl5+ was reported, followed by a series of predicted ppC species that could be obtained by substituting the Al centres for other heteroatoms.
147
Planar pentacoordinate carbon atoms embedded in a metallocene framework.
Zhong-hua Cui,Valentin Vassilev-Galindo,José Luis Cabellos,Edison Osorio,Mesías Orozco,Sudip Pan,Yi-hong Ding,Gabriel Merino +7 more
TL;DR: The fulfillment of the 18 electron rule and electron delocalization is found to be crucial for the stabilization of these ppC arrangements.
66
Dynamical strengthening of covalent and non-covalent molecular interactions by nuclear quantum effects at finite temperature
Huziel E. Sauceda,Huziel E. Sauceda,Valentin Vassilev-Galindo,Stefan Chmiela,Klaus-Robert Müller,Alexandre Tkatchenko +5 more
TL;DR: In this paper, the authors use machine learned force fields trained on coupled cluster reference data to show the dynamical strengthening of covalent and non-covalent molecular interactions induced by NQE.