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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Combining Quantum Mechanics and Machine-Learning Calculations for Anharmonic Corrections to Vibrational Frequencies
Julien Lam, Saleh Abdul-Al, A. Allouche
Journal of Chemical Theory and Computation (2020) Vol. 16, Iss. 3, pp. 1681-1689
Open Access | Times Cited: 20

Showing 20 citing articles:

Predicting Infrared Spectra with Message Passing Neural Networks
Charles J. McGill, Michael Forsuelo, Yanfei Guan, et al.
Journal of Chemical Information and Modeling (2021) Vol. 61, Iss. 6, pp. 2594-2609
Closed Access | Times Cited: 60
Efficient modelling of anharmonicity and quantum effects in PdCuH2 with machine learning potentials
Francesco Belli, Eva Zurek
npj Computational Materials (2025) Vol. 11, Iss. 1
Open Access | Times Cited: 1
Comprehensive Assessment of GFN Tight-Binding and Composite Density Functional Theory Methods for Calculating Gas-Phase Infrared Spectra
Philipp Pracht, David F. Grant, Stefan Grimme
Journal of Chemical Theory and Computation (2020) Vol. 16, Iss. 11, pp. 7044-7060
Open Access | Times Cited: 51
Roadmap on dynamics of molecules and clusters in the gas phase
Henning Zettergren, Alicja Domaracka, Thomas Schlathölter, et al.
The European Physical Journal D (2021) Vol. 75, Iss. 5
Open Access | Times Cited: 41
Infrared spectra prediction using attention-based graph neural networks
Naseem Saquer, Razib Iqbal, Joshua D. Ellis, et al.
Digital Discovery (2024) Vol. 3, Iss. 3, pp. 602-609
Open Access | Times Cited: 7
Graphormer-IR: Graph Transformers Predict Experimental IR Spectra Using Highly Specialized Attention
Cailum M. K. Stienstra, Liam Hebert, P. Thomas, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 12, pp. 4613-4629
Closed Access | Times Cited: 6
Machine learning, artificial intelligence, and chemistry: How smart algorithms are reshaping simulation and the laboratory
David Kuntz, Angela K. Wilson
Pure and Applied Chemistry (2022) Vol. 94, Iss. 8, pp. 1019-1054
Open Access | Times Cited: 25
Exploring the formation of gold/silver nanoalloys with gas-phase synthesis and machine-learning assisted simulations
Quentin Gromoff, Patrizio Benzo, Wissam A. Saidi, et al.
Nanoscale (2023) Vol. 16, Iss. 1, pp. 384-393
Open Access | Times Cited: 9
A machine learning potential for simulating infrared spectra of nanosilicate clusters
Zeyuan Tang, Stefan T. Bromley, Bjørk Hammer
The Journal of Chemical Physics (2023) Vol. 158, Iss. 22
Open Access | Times Cited: 7
The resolution-vs.-accuracy dilemma in machine learning modeling of electronic excitation spectra
Prakriti Kayastha, Sabyasachi Chakraborty, Raghunathan Ramakrishnan
Digital Discovery (2022) Vol. 1, Iss. 5, pp. 689-702
Open Access | Times Cited: 10
Computational Infrared Spectroscopy of 958 Phosphorus-Bearing Molecules
Juan C. Zapata Trujillo, Anna-Maree Syme, Keiran Rowell, et al.
Frontiers in Astronomy and Space Sciences (2021) Vol. 8
Open Access | Times Cited: 14
Infrared spectra of neutral polycyclic aromatic hydrocarbons based on machine learning potential energy surface and dipole mapping
Gaétan Laurens, Malalatiana Rabary, Julien Lam, et al.
Theoretical Chemistry Accounts (2021) Vol. 140, Iss. 6
Open Access | Times Cited: 13
The effect of machine learning predicted anharmonic frequencies on thermodynamic properties of fluid hydrogen fluoride
Jamoliddin Khanifaev, Tim Schrader, Eva Perlt
The Journal of Chemical Physics (2024) Vol. 160, Iss. 12
Closed Access | Times Cited: 1
Machine-learning to predict anharmonic frequencies: a study of models and transferability
Jamoliddin Khanifaev, Tim Schrader, Eva Perlt
Physical Chemistry Chemical Physics (2024) Vol. 26, Iss. 35, pp. 23495-23502
Open Access | Times Cited: 1
Prediction of the Infrared Absorbance Intensities and Frequencies of Hydrocarbons: A Message Passing Neural Network Approach
Maliheh Shaban Tameh, Veaceslav Coropceanu, Thomas A. R. Purcell, et al.
The Journal of Physical Chemistry A (2024) Vol. 128, Iss. 44, pp. 9695-9706
Open Access | Times Cited: 1
Infrared Spectroscopy of Chemically Diverse Carbon Clusters: A Data-Driven Approach
F. Calvo, Aude Simon, P. Parneix, et al.
The Journal of Physical Chemistry A (2021) Vol. 125, Iss. 25, pp. 5509-5518
Open Access | Times Cited: 6
Recent Advances toward Efficient Calculation of Higher Nuclear Derivatives in Quantum Chemistry
Selin Bac, Abhilash Patra, Kareesa J. Kron, et al.
The Journal of Physical Chemistry A (2022) Vol. 126, Iss. 43, pp. 7795-7805
Open Access | Times Cited: 4
Neural network approach for predicting infrared spectra from 3D molecular structure
Saleh Abdul Al, A. Allouche
Chemical Physics Letters (2024) Vol. 856, pp. 141603-141603
Open Access
Non long‐range corrected density functionals incorrectly describe the intensity of the CH stretching band in polycyclic aromatic hydrocarbons
Hugo Geindre, A. Allouche, Daniel Peláez
Journal of Computational Chemistry (2021) Vol. 42, Iss. 14, pp. 1018-1027
Closed Access | Times Cited: 3
Molecular Dynamics Simulations and Vibrational Spectroscopy
Andrea Amadei, Massimiliano Aschi
Elsevier eBooks (2023), pp. 821-834
Closed Access
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