Academic Journal
Q1Journal of Chemical Theory and Computation
About Journal of Chemical Theory and Computation
Journal of Chemical Theory and Computation is a scholarly journal published by American Chemical Society. SCImago 2025 lists it in Q1, with an SJR of 1.488 and H-index of 248.
Coverage: 2005-2026. Research categories: Computer Science Applications (Q1); Physical and Theoretical Chemistry (Q1).
Source-backed journal facts
Topics in published research
Advanced Chemical Physics Studies; Spectroscopy and Quantum Chemical Studies; Protein Structure and Dynamics; Machine Learning in Materials Science; Photochemistry and Electron Transfer Studies; Computational Drug Discovery Methods.
OpenAlex classifies topics from published works. These topics are not the publisher’s official aims and scope.
Reported open-access list prices
4,500.00 USD
APC list prices reported by OpenAlex, which obtains this information from DOAJ. Confirm current charges, taxes, waivers and eligibility with the publisher; this is not a fee quotation.
Source: OpenAlex source record. Retrieved 2026-10-03. Source record updated 2026-10-02. OpenAlex metrics are different from SCImago metrics and the Clarivate Journal Impact Factor.
Journal Metrics
Quartile, SJR and the listed SCImago H-index use the 2025 imported SCImago dataset. A quartile may vary by subject category. Values without a source or reporting year are unverified historical entries. Verify the current Journal Impact Factor with Clarivate or the publisher before using it.
Aims & Scope
The publisher’s official aims and scope have not yet been verified for this profile. Use the journal website to check subject fit and accepted article types before submitting.
Recent Research Articles
Latest publications matched automatically by ISSN.
First-Principles Simulation of Ionizing Radiation Damage in Molecular Systems over Short Time Scales
Pison Naija, Aurelio Alvarez Ibarra, Roberto Flores-Moreno, Dominique Guillaumont et al.
2026-10-07 · DOI: 10.1021/acs.jctc.6c01190Influence of Exchange–Correlation Functional on Machine-Learned Interatomic Potentials’ Accuracy: A Systematic Study of Borosilicate Glasses
Fengming Shi, Luca Brugnoli, François-Xavier Coudert
2026-10-07 · DOI: 10.1021/acs.jctc.6c01609A Thermodynamically Consistent Approach to Molecular Simulations of Adsorption-Induced Deformation and Structural Transitions in MOFs
Nicholas J. Corrente, Kaelyn Chang, Muhtasim Noor, Alexander V. Neimark et al.
2026-10-07 · DOI: 10.1021/acs.jctc.6c01243Electronically Nonadiabatic Dynamics of O2 + O Collisions on Sixteen New Machine-Learned 3 A ″ Global Potential Energy Surfaces
Qinghui Meng, Yinan Shu, Zoltan Varga, Donald G. Truhlar et al.
2026-10-07 · DOI: 10.1021/acs.jctc.6c01449Nuclear–Electronic Orbital Coupled Cluster Theory with the Nuclear Hartree Product Representation for Multiple Quantum Nuclei and Application to Geometric Isotope Effects
Rowan J. Goudy, Sharon Hammes-Schiffer
2026-10-07 · DOI: 10.1021/acs.jctc.6c01568Enhancing the Efficiency and Flexibility of AutoMeKin: Integrating ORCA and Machine-Learning Potentials
Omar Rodríguez-López, Emilio Martínez-Núñez, Berta Fernández, Saulo A. Vázquez et al.
2026-10-06 · DOI: 10.1021/acs.jctc.6c01565Dual Machine-Learning Prediction of Excited-State Energetics from Ground-State Descriptors and Its Implication on Intramolecular Singlet Fission in Dimeric Chromophores
Hongyang Wang, Wenjing Fan, Xiaoqing Zhang, Xiufang Song et al.
2026-10-06 · DOI: 10.1021/acs.jctc.6c01469Accessing Free-Energy Barriers from Unbiasing Dynamics: Delocalized Transition States in Heterogeneous Catalysis
Peipei Zhang, Chenxi Guo, P. Hu
2026-10-05 · DOI: 10.1021/acs.jctc.6c01132First-Principles Modeling of Charge Transfer Excitons in Organic Solar Cells
Vishal Jindal, Michael J. Janik, Scott T. Milner
2026-10-05 · DOI: 10.1021/acs.jctc.6c01456Unified Mesoscale Framework Bridging Equilibrium Thermodynamics and Transport Properties of Ionic Liquids and Their Mixtures
Young Jin Lee, Qin M. Qi
2026-10-04 · DOI: 10.1021/acs.jctc.6c01130Clifford Disentanglers for Entanglement Reduction in Molecular Electronic Structure Simulations
Longfei Chang, Zibo Wu, Yunzhi Li, Haiqi Liu et al.
2026-10-02 · DOI: 10.1021/acs.jctc.6c01170Convolutional Kernel-Embedded E (3)-Equivariant Networks (KEN): Overcoming Architectural Rigidity in Machine Learning Interatomic Potentials
Jha Gautam
2026-10-02 · DOI: 10.1021/acs.jctc.6c01109Beyond Multiscale: A Neural-Network-Unified Molecular Model for Asymmetry-Free Dynamics Simulation
Takuma Ikeda, Hiroshi C. Watanabe, Haruyuki Nakano
2026-10-02 · DOI: 10.1021/acs.jctc.6c01037Predicting the Radical Character of Open-Shell Nanographenes with the GVB-Based Block-Correlated Coupled Cluster Theory
Xiaochuan Ren, Jingxiang Zou, Jun Lin, Cong Sun et al.
2026-10-02 · DOI: 10.1021/acs.jctc.6c01707pGM5P-26: A Polarizable Gaussian Multipole Water Model with Transferable Temperature-Dependent Thermodynamics
Yongxian Wu, Piotr Cieplak, Yong Duan, Ray Luo et al.
2026-10-01 · DOI: 10.1021/acs.jctc.6c01267Bayesian Learning of Distance Metrics Beyond RMSD for Biomolecule Alignment, Clustering, and Domain Identification
Saumyak Mukherjee, Gerhard Hummer
2026-10-01 · DOI: 10.1021/acs.jctc.6c01395Efficient Tensorized Evaluation of Permutation Invariant Polynomials for Representing Potential Energy Surfaces
Junhong Li, Kaisheng Song, Hua Guo, Jun Li et al.
2026-09-30 · DOI: 10.1021/acs.jctc.6c01659Efficient and Transferable Machine Learning Potentials for Zn-Coordinated Zeolitic Imidazolate Frameworks Through Structural Diversity Sampling and Transfer Learning
Shang-Wei Lin, Yen-Yung Wu, Li-Chiang Lin
2026-09-30 · DOI: 10.1021/acs.jctc.6c01271Analytical and Separable Representation of Coulomb-like Potentials
Subhra K. Das, Annika Bande, Daniel Peláez
2026-09-30 · DOI: 10.1021/acs.jctc.6c00636Can Machine Learning Predict Solvation Effects on Energies and Geometries of Highly Charged Molecules?
Dario Baum, Lucas Visscher, Amber Pausch
2026-09-29 · DOI: 10.1021/acs.jctc.6c00804Reviews
Community Reviews
Version History
October 4, 2026 at 8:52 pm
September 25, 2026