Hossein Tahmasbi

About Hossein Tahmasbi

Hossein Tahmasbi, With an exceptional h-index of 6 and a recent h-index of 6 (since 2020), a distinguished researcher at Universiteit Leiden, specializes in the field of Condensed matter physics, Structure prediction, Atomistic simulation, Machine Learning, Adsorption.

His recent articles reflect a diverse array of research interests and contributions to the field:

Machine learning-driven structure prediction for iron hydrides

Structure prediction of iron hydrides across pressure range with transferable machine-learned interatomic potential

Transferable Interatomic Potentials for Aluminum from Ambient Conditions to Warm Dense Matter

Machine learning-based quantum accurate interatomic potentials for warm dense matter

IR spectroscopic characterization of the co-adsorption of CO 2 and H 2 onto cationic Cu n+ clusters

Structure prediction of ionic materials using the Minima Hopping method and the CENT machine learning potential

An automated approach for developing neural network interatomic potentials with FLAME

Large-scale structure prediction of near-stoichiometric magnesium oxide based on a machine-learned interatomic potential: Crystalline phases and oxygen-vacancy ordering

Hossein Tahmasbi Information

University

Position

Theoretical Chemistry

Citations(all)

176

Citations(since 2020)

160

Cited By

80

hIndex(all)

6

hIndex(since 2020)

6

i10Index(all)

4

i10Index(since 2020)

4

Email

University Profile Page

Google Scholar

Hossein Tahmasbi Skills & Research Interests

Condensed matter physics

Structure prediction

Atomistic simulation

Machine Learning

Adsorption

Top articles of Hossein Tahmasbi

Machine learning-driven structure prediction for iron hydrides

Physical Review Materials

2024/3/21

Hossein Tahmasbi
Hossein Tahmasbi

H-Index: 3

Structure prediction of iron hydrides across pressure range with transferable machine-learned interatomic potential

Bulletin of the American Physical Society

2024/3/8

Hossein Tahmasbi
Hossein Tahmasbi

H-Index: 3

Transferable Interatomic Potentials for Aluminum from Ambient Conditions to Warm Dense Matter

Physical Review Research

2023/9/6

Sandeep Kumar
Sandeep Kumar

H-Index: 0

Hossein Tahmasbi
Hossein Tahmasbi

H-Index: 3

Machine learning-based quantum accurate interatomic potentials for warm dense matter

APS March Meeting Abstracts

2023

Sandeep Kumar
Sandeep Kumar

H-Index: 0

Hossein Tahmasbi
Hossein Tahmasbi

H-Index: 3

IR spectroscopic characterization of the co-adsorption of CO 2 and H 2 onto cationic Cu n+ clusters

Physical Chemistry Chemical Physics

2021

Hossein Tahmasbi
Hossein Tahmasbi

H-Index: 3

Structure prediction of ionic materials using the Minima Hopping method and the CENT machine learning potential

APS March Meeting Abstracts

2021

Hossein Tahmasbi
Hossein Tahmasbi

H-Index: 3

An automated approach for developing neural network interatomic potentials with FLAME

Computational Materials Science

2021/9/1

Hossein Mirhosseini
Hossein Mirhosseini

H-Index: 15

Hossein Tahmasbi
Hossein Tahmasbi

H-Index: 3

Large-scale structure prediction of near-stoichiometric magnesium oxide based on a machine-learned interatomic potential: Crystalline phases and oxygen-vacancy ordering

Phys. Rev. Materials

2021/8/30

IR Spectroscopic Characterization of H2 Adsorption on Cationic Cun+ (n = 4–7) Clusters

The Journal of Physical Chemistry A

2021/3/31

Hossein Tahmasbi
Hossein Tahmasbi

H-Index: 3

FLAME: a library of atomistic modeling environments

Computer Physics Communications

2020/6/2

Hossein Tahmasbi
Hossein Tahmasbi

H-Index: 3

Robabe Rasoulkhani
Robabe Rasoulkhani

H-Index: 4

See List of Professors in Hossein Tahmasbi University(Universiteit Leiden)

Co-Authors

academic-engine