Development of United-Atom Force Fields for Monomeric and Oligomeric Ionic Liquids through Regression-Guided Optimization of Electronic Continuum Correction Parameters
Ionic liquids are salts that exist in the liquid state at room temperature and exhibit high viscosity because of their strong electrostatic interactions. It was difficult to reproduce their viscosity by molecular dynamics simulations with conventional nonpolarizable force fields; however, recent development of force fields implementing electronic continuum correction (ECC), which accounts for polarizability, has enabled accurate predictions. Here, we present a regression-guided strategy to optimize scaling factors for ECC charges and Lennard-Jones parameters for monomeric (BMIM+, MOEMIM+) and oligomeric (IL22+, IL44+) imidazolium-based cations paired with TFSI– with united-atom models. The scaling factors were optimized to simultaneously reproduce experimental density and viscosity. To validate the strategy, we calculated the temperature dependence of density, diffusion coefficient, conductivity, and viscosity of BMIM–TFSI, achieving good agreements with experiments. Moreover, scaling factors optimized for MOEMIM+, which shares similar chemical structure and elemental compositions with IL22+ and IL44+, were found to be transferable to these compounds. Thus, this work not only provides a practical regression-guided workflow for selecting ECC-based united-atom force-field parameters but also suggests their transferability across chemically related ionic liquids.
Accurate prediction of solubility is crucial in various fields, including pharmaceuticals, environmental chemistry, and materials science. In this study, we demonstrate the application of Adaptive Force Matching (AFM) to predict the solubility of molecular liquids in water. By developing high-quality force fields using AFM, we accurately compute the free energy of vaporization and hydration, which are essential components for predicting solubility. Our results show that AFM models can reliably predict the solvation free energy of selected small molecules, exhibiting a deviation of <1.3 kJ/mol from experimental references for cyclohexene, isopentane, and n-butanol. Although a slightly larger error is observed for n-octanol, which was developed by borrowing AFM parameters from other molecules, the deviation remains comparable to commonly accepted chemical accuracy. This study highlights the potential of AFM as a powerful tool for predicting solubility, enabling the design and development of new materials and molecules with tailored properties.
Unknown authors· Journal of Chemical Physics· 0 citations
The performance of batteries is heavily influenced by the properties of their solvents, which play a crucial role in ion solvation, conductivity, and electrochemical stability. However, traditional force field models often fall short in accurately predicting these properties. This study investigates the potential of adaptive force matching (AFM) to predict a range of solvent-related properties using only electronic structure theory. To demonstrate this approach, we developed AFM models based on B3LYP-D3(BJ) for three common molecules present in battery solvents: dimethylamine (DMA), dimethyl carbonate (DMC), and tetrahydrofuran (THF). Our results reveal that AFM models significantly outperform traditional force fields, including OPLS-AA (CM1A), GAFF2, and GROMOS 54A7, in predicting key properties such as density, heat of vaporization, viscosity, diffusion constant, boiling temperature, and free energy of vaporization. Notably, the average percentage error of AFM models is approximately 13%, substantially lower than that of traditional force fields (21% for GAFF2, the best-performing empirical model). These findings underscore the promise of AFM in predicting physical properties of battery solvents, with far-reaching implications for chemistry, materials science, and related fields where accurate predictions are essential for understanding complex phenomena and designing innovative materials and systems.
Yang Wei, Raymond Weldon, Feng Wang· Journal of Chemical Theory a...· 0 citations
We propose an improved model, termed the gradient-corrected PCM (GCPCM), for improving the energy accuracy of the polarizable continuum model (PCM). Our previous study revealed deficiencies of PCM in describing the reaction field, i.e., the electrostatic potential generated by the solvent. These deficiencies can be partially alleviated by introducing an empirical correction to the solvent charges. As a result, solute-solvent interactions are improved at the self-consistent field level, leading to enhanced energy accuracy. The performance of GCPCM was evaluated through single-point calculations and geometry optimizations of phenol and phenolate, calculations of the free energy profile for proton transfer in glycine, and analysis of solvent responses of the HOMO and LUMO orbital energies of Brooker's merocyanine. The results demonstrate that the characteristic destabilization of charged solutes observed in conventional PCM is effectively resolved. Furthermore, despite having a computational cost comparable to that of PCM, GCPCM shows the potential to achieve an energy accuracy similar to that of 3D-RISM-SCF. The development of GCPCM enables more convenient and accurate treatment of solvation effects, which is expected to allow researchers to focus on other important challenges, such as the accurate description of electronic states.
Y. Kanamaru, Norio Yoshida, Toru Matsui· Journal of Chemical Theory a...· 0 citations
Classical molecular dynamics is a theoretical method useful for investigating noncovalent intermolecular interactions and conformational flexibility, enabling the simulation of processes such as aggregation/dissolution and adsorption. Molecular dynamics and quantum chemistry are increasingly introduced in chemistry curricula, yet students may encounter difficulties when translating theoretical concepts into robust simulation protocols, particularly outside biomolecular systems. Here, we present a tutorial designed to guide students through the preparation, execution, and analysis of the simulations of small organic molecules in nonaqueous solvents, followed by the calculation of ultraviolet–visible (UV–vis) absorption spectra using time-dependent density functional theory. This tutorial focuses on several practical issues: obtaining force-field parameters, building simulation cells, selecting ensembles, and interpreting critical simulation parameters. Custom solvent models are validated against reference density and radial distribution functions, demonstrating how selected observables can be used to assess simulation reliability. We illustrate the usefulness of molecular dynamics by showing that molecular flexibility and solvent interactions broaden the UV–vis absorption band of indigo in chloroform. This contribution is intended as a hands-on educational resource for upper-level undergraduate and graduate students enrolled in physical chemistry and computational chemistry courses, as well as for Ph.D. students working in chemistry, physics, or material science, who are approaching molecular simulations. To support dissemination, we have released a ready-to-use package on GitHub that includes solvent boxes and all the necessary files and data for incorporating new molecules into GROMACS simulations: https://github.com/cippee/SolventSafari-for-GROMACS.
Unknown authors· Journal of Chemical Educatio...· 0 citations
All-atom simulations with explicit solvent provide the most detailed and accurate description of dynamics and mechanisms in intrinsically disordered proteins and their condensates. However, interactions involving charged residues and ions remain a persistent source of systematic error. Here we introduce an osmometry-guided optimization strategy that directly targets residue–residue, residue–ion and ion–ion interactions. Osmotic pressure provides key experimental information on molecular interactions and can be calculated directly and rapidly from simulations, enabling efficient iterative force-field optimization. The resulting parameters improve agreement of all-atom simulations with a range of experimental data: single-molecule FRET measurements for 16 monomeric intrinsically disordered regions; NMR relaxation data for a complex between an IDP and a folded protein domain; and mean FRET efficiencies and chain reconfiguration times of IDPs in biomolecular condensates of highly charged proteins. For such condensates, simulations with an osmometry-calibrated force field provide the missing link for predicting condensate dynamics across length and time scales. The presented optimization strategy is broadly extensible to other interaction classes, including those governing protein–DNA and protein–RNA assemblies.
Miloš T. Ivanović, Valentin von Roten, Benjamin Schuler et al.· bioRxiv· 0 citations
Accurate modeling of nonbonded interactions remains challenging because conventional force fields often provide inadequate descriptions of polarization and charge transfer. Here, we introduce a polarizable split-charge equilibration (PSQ) framework that combines localized charge flow with dipolar polarization, thereby mitigating the unphysical long-range charge delocalization associated with polarizable charge-equilibration models. To enable practical large-scale simulations, we develop an efficient PSQ implementation through algorithmic optimization and parallelization, achieving performance comparable to conventional approaches despite the model’s greater formal complexity. We combine PSQ with the universal nonbond potential for van der Waals interactions and an explicit four-body hydrogen-bond term to form the PUxH framework. PUxH achieves near-chemical accuracy in predicting small-molecular pair interactions and accurately reproduces the bulk properties of water, ammonia, and benzene. Overall, PUxH provides a transferable, physically grounded, and computationally efficient framework for modeling nonbonded interactions in molecular and condensed-phase systems.
Taehwan Jang, Minho M. Kim, Hoon Ryu et al.· Journal of Physical Chemistr...· 0 citations
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