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Journal of Chemical Theory and Computation

The Journal of Chemical Theory and Computation is a leading scientific journal that publishes cutting-edge research in the field of theoretical and computational chemistry. It covers a wide range of topics, including molecular modeling, quantum chemistry, molecular dynamics simulations, and computational materials science. The journal provides a platform for scientists to share their innovative theories, computational methods, and computational studies, advancing our understanding of chemical systems and their properties.
Details
Abbr. J Chem Theory Comput
Publisher American Chemical Society
Start 2005
End Continuing
Frequency Monthly, 2009-
p-ISSN 1549-9618
e-ISSN 1549-9626
Country United States
Language English
Specialties Biochemistry
Chemistry
Metrics
h-index / Ranks: 525 222
SJR / Ranks: 2060 1457
CiteScore / Ranks: 1186 10.90
JIF / Ranks: 1321 5.5
Recent Articles
1.
Shadow Molecular Dynamics with a Machine Learned Flexible Charge Potential
Li C, Kaymak M, Kulichenko M, Lubbers N, Nebgen B, Tretiak S, et al.
J Chem Theory Comput . 2025 Mar; PMID: 40085742
We present an extended Lagrangian shadow molecular dynamics scheme with an interatomic Born-Oppenheimer potential determined by the relaxed atomic charges of a second-order charge equilibration model. To parametrize the charge...
2.
A General Formalism of Excitation-Dependent Luminescence Properties in Triplet-Triplet Annihilation Systems
Zeng W, Zhang Y, Chen H, Huang H, Peng Q
J Chem Theory Comput . 2025 Mar; PMID: 40085027
Triplet-triplet annihilation (TTA) has promising applications in optical functional devices and technologies due to its efficient exciton utilization and up-conversion. Traditionally, the change in the slope of the dual logarithmic...
3.
Fine-Tuning Graph Neural Networks via Active Learning: Unlocking the Potential of Graph Neural Networks Trained on Nonaqueous Systems for Aqueous CO Reduction
Jiao Z, Mao Y, Lu R, Liu Y, Guo L, Wang Z
J Chem Theory Comput . 2025 Mar; PMID: 40084714
Graph neural networks (GNNs) have revolutionized catalysis research with their efficiency and accuracy in modeling complex chemical interactions. However, adapting GNNs trained on nonaqueous data sets to aqueous systems poses...
4.
Investigating Data Hierarchies in Multifidelity Machine Learning for Excitation Energies
Vinod V, Zaspel P
J Chem Theory Comput . 2025 Mar; PMID: 40079624
Recent progress in machine learning (ML) has made high-accuracy quantum chemistry (QC) calculations more accessible. Of particular interest are multifidelity machine learning (MFML) methods, where training data from differing accuracies...
5.
Thermal Adaptation of Cytosolic Malate Dehydrogenase Revealed by Deep Learning and Coevolutionary Analysis
Shukla D, Martin J, Morcos F, Potoyan D
J Chem Theory Comput . 2025 Mar; PMID: 40079215
Protein evolution has shaped enzymes that maintain stability and function across diverse thermal environments. While sequence variation, thermal stability and conformational dynamics are known to influence an enzyme's thermal adaptation,...
6.
Role of Electron Correlation beyond the Active Space in Achieving Quantitative Predictions of Spin-Phonon Relaxation
Haldar S, Mariano L, Lunghi A, Gagliardi L
J Chem Theory Comput . 2025 Mar; PMID: 40074562
Single-molecule magnets (SMMs) are promising candidates for molecular-scale data storage and processing due to their strong magnetic anisotropy and long spin relaxation times. However, as the temperature rises, interactions between...
7.
Improved Free-Energy Estimates for the Permeation of Bulky Antibiotic Molecules through Porin Channels Using Temperature-Accelerated Sliced Sampling
Acharya A, Kleinekathofer U
J Chem Theory Comput . 2025 Mar; PMID: 40073220
The estimation of accurate free energies for antibiotic permeation via the bacterial outer-membrane porins has proven to be challenging. Atomistic simulations of the process suffer from sampling issues that are...
8.
A Phase-Space View of Vibrational Energies without the Born-Oppenheimer Framework
Bian X, Khan C, Duston T, Rawlinson J, Littlejohn R, Subotnik J
J Chem Theory Comput . 2025 Mar; PMID: 40072941
We show that following the standard mantra of quantum chemistry and diagonalizing the Born-Oppenheimer (BO) Hamiltonian () is not the optimal means to construct potential energy surfaces. A better approach...
9.
Fukui Function and Fukui Potential for Solid-State Chemistry: Application to Surface Reactivity
Barrera N, Cabezas-Escares J, Munoz F, Muriel W, Gomez T, Calatayud M, et al.
J Chem Theory Comput . 2025 Mar; PMID: 40069120
The Fukui function and its associated potential serve as essential descriptors of chemical reactivity within the framework of conceptual density functional theory (c-DFT). While c-DFT is well-established for molecular systems,...
10.
ABCG2: A Milestone Charge Model for Accurate Solvation Free Energy Calculation
He X, Man V, Yang W, Lee T, Wang J
J Chem Theory Comput . 2025 Mar; PMID: 40068154
In this report, we describe the development and validation of ABCG2, a new charge model with milestone free energy accuracy, while allowing instantaneous atomic charge assignment for arbitrary organic molecules....