Philipp Marquetand

Philipp Marquetand

Universität Wien

H-index: 40

Europe-Austria

About Philipp Marquetand

Philipp Marquetand, With an exceptional h-index of 40 and a recent h-index of 32 (since 2020), a distinguished researcher at Universität Wien, specializes in the field of theoretical chemistry, ab initio molecular dynamics, machine learning, quantum dynamics, computational chemistry.

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

Transferability of atomic energies from alchemical decomposition

Photodynamics With Neural Networks and Kernel Ridge Regression

Long Lived Electronic Coherences in Molecular Wave Packets Probed with Pulse Shape Spectroscopy

Long Lived Electronic Coherences in Molecules Studied with Pulse Shape Spectroscopy

CASNet: Learning Complete Active Space Orbitals using Message Passing Neural Networks

Learning excited-state properties

The OpenMolcas Web: A Community-Driven Approach to Advancing Computational Chemistry

Nonadiabatic forward flux sampling for excited-state rare events

Philipp Marquetand Information

University

Position

Institute of Theoretical Chemistry Vienna Austria

Citations(all)

7308

Citations(since 2020)

4872

Cited By

4147

hIndex(all)

40

hIndex(since 2020)

32

i10Index(all)

82

i10Index(since 2020)

66

Email

University Profile Page

Universität Wien

Google Scholar

View Google Scholar Profile

Philipp Marquetand Skills & Research Interests

theoretical chemistry

ab initio molecular dynamics

machine learning

quantum dynamics

computational chemistry

Top articles of Philipp Marquetand

Title

Journal

Author(s)

Publication Date

Transferability of atomic energies from alchemical decomposition

The Journal of Chemical Physics

Michael J Sahre

Guido Falk von Rudorff

Philipp Marquetand

O Anatole von Lilienfeld

2024/2/7

Photodynamics With Neural Networks and Kernel Ridge Regression

Philipp Marquetand

2023/1/1

Long Lived Electronic Coherences in Molecular Wave Packets Probed with Pulse Shape Spectroscopy

arXiv preprint arXiv:2311.10598

Brian Kaufman

Philipp Marquetand

Tamas Rozgonyi

Thomas Weinacht

2023/11/17

Long Lived Electronic Coherences in Molecules Studied with Pulse Shape Spectroscopy

APS Division of Atomic, Molecular and Optical Physics Meeting Abstracts

Brian Kaufman

Philipp Marquetand

Tamás Rozgonyi

Thomas Weinacht

2023

CASNet: Learning Complete Active Space Orbitals using Message Passing Neural Networks

Ruard van Workum

Joao Malhado

Philipp Marquetand

2023/6/28

Learning excited-state properties

Julia Westermayr

Pavlo O Dral

Philipp Marquetand

2023/1/1

The OpenMolcas Web: A Community-Driven Approach to Advancing Computational Chemistry

Journal of Chemical Theory and Computation

Giovanni Li Manni

Ignacio Fdez. Galván

Ali Alavi

Flavia Aleotti

Francesco Aquilante

...

2023/5/22

Nonadiabatic forward flux sampling for excited-state rare events

Journal of Chemical Theory and Computation

Madlen Maria Reiner

Brigitta Bachmair

Maximilian Xaver Tiefenbacher

Sebastian Mai

Leticia González

...

2023/3/1

Long-Lived Electronic Coherences in Molecules

Physical Review Letters

Brian Kaufman

Philipp Marquetand

Tamás Rozgonyi

Thomas Weinacht

2023/12/26

Coherent control of coupled field-nuclei-electron dynamics in strong field molecular ionization

APS Division of Atomic, Molecular and Optical Physics Meeting Abstracts

Brian Kaufman

Tamás Rozgonyi

Philipp Marquetand

Thomas Weinacht

2022

Luminescent Iridium Complexes with a Sulfurated Bipyridine Ligand: PCET Thermochemistry of the Disulfide Unit and Photophysical Properties

Inorganic Chemistry

Manuel Oelschlegel

Shao-An Hua

Lucius Schmid

Philipp Marquetand

Anna Bäck

...

2022/8/24

Deep learning study of tyrosine reveals that roaming can lead to photodamage

Nature Chemistry

Julia Westermayr

Michael Gastegger

Dóra Vörös

Lisa Panzenboeck

Florian Joerg

...

2022/8

Numerical calculations of multiphoton molecular absorption

Physical Review A

Brian Kaufman

Philipp Marquetand

Thomas Weinacht

Tamás Rozgonyi

2022/7/19

Recent advances in machine learning for electronic excited state molecular dynamics simulations

Brigitta Bachmair

Madlen Maria Reiner

Maximilian Xaver Tiefenbacher

Philipp Marquetand

2022/12/19

Solving the electronic Schrödinger equation for multiple nuclear geometries with weight-sharing deep neural networks

Nature Computational Science

Michael Scherbela

Rafael Reisenhofer

Leon Gerard

Philipp Marquetand

Philipp Grohs

2022/5

Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need?

Advances in Neural Information Processing Systems

Leon Gerard

Michael Scherbela

Philipp Marquetand

Philipp Grohs

2022/12/6

BuRNN: Buffer region neural network approach for polarizable-embedding neural network/molecular mechanics simulations

The Journal of Physical Chemistry Letters

Bettina Lier

Peter Poliak

Philipp Marquetand

Julia Westermayr

Chris Oostenbrink

2022/4/25

Trendbericht Theoretische Chemie 2022: Maschinelles Lernen für elektronisch angeregte Zustände

Philipp Marquetand

2022/10

A force field for a manganese-vanadium water oxidation catalyst: redox potentials in solution as showcase

Catalysts

Gustavo Cárdenas

Philipp Marquetand

Sebastian Mai

Leticia González

2021/4/13

Competition between dynamic resonance and internal conversion in strong-field molecular ionization with chirped ultrafast laser pulses

Physical Review A

Brian Kaufman

Tamás Rozgonyi

Philipp Marquetand

Thomas Weinacht

2021/2/15

See List of Professors in Philipp Marquetand University(Universität Wien)

Co-Authors

H-index: 63
Leticia Gonzalez

Leticia Gonzalez

Universität Wien

H-index: 62
Albert Stolow

Albert Stolow

University of Ottawa

H-index: 60
Jörg Behler

Jörg Behler

Georg-August-Universität Göttingen

H-index: 44
Felix Plasser

Felix Plasser

Loughborough University

H-index: 42
Carlos E. Crespo-Hernández

Carlos E. Crespo-Hernández

Case Western Reserve University

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