化学物理
Molecular polaritons, hybrid light-matter states formed from the strong coupling of molecular transitions and discrete photonic modes, are a compelling platform for optical control of chemical reactivity. Despite the origins of the field of…
Free energies play a central role in characterising the behaviour of chemical systems and are among the most important quantities that can be calculated by molecular dynamics simulations. Solvation free energies in various organic solvents,…
Cooperative collective dynamics is a principal determinant of the ability of synthetic micromotors to perform specific functions. However, realizing controllable and predictable collective behavior in complex physiological environments…
Radial asymmetry in a quadrupole mass filter (QMF), introduced by symmetric displacement of a diagonally opposite rod pair, modifies the confinement potential and alters the ion stability characteristics. In this work, the influence of such…
A machine learning (ML) based equivariant neural network for constructing distributed charge models (DCMs) of arbitrary resolution, DCM-net, is presented. DCMs efficiently and accurately model the anisotropy of the molecular electrostatic…
Transition Metal Complexes (TMCs) have wide-ranging practical utility in chemistry, with possible applications that range from catalysis to medicinal chemistry. The study of TMCs and their properties is thus a field rich with potential, one…
Various representation learning methods for molecular structures have been devised to accelerate data-driven chemistry. However, the representation capabilities of existing methods are essentially limited to atom-level information, which is…
Electrostatic interactions fundamentally govern the structure and transport of electrolytes. In concentrated electrolytes, however, electrostatic and steric correlations, together with ion-solvent coupling, give rise to complex behavior,…
Molecular dynamics simulations are widely used to investigate nucleation in first-order phase transitions. Brute-force simulations, though popular, are limited to conditions of high metastability, where the critical cluster and the…
The Global Natural Orbital Functional (GNOF) provides a straightforward approach to capture most electron correlation effects without needing perturbative corrections or limited active spaces selection. In this work, we evaluate both the…
Simulating electrochemical interfaces using density functional theory (DFT) requires incorporating the effects of electrochemical potential. The electrochemical potential acts as a new degree of freedom that can effectively tune DFT results…
Precise characterization of the graphene/water interface has been hindered by experimental inconsistencies and limited molecular-level access to interfacial structures. In this work, we present a novel integrated computational approach that…
Weighted ensemble (WE) is an enhanced path-sampling method that is conceptually simple, widely applicable, and statistically exact. In a WE simulation, an ensemble of trajectories is periodically pruned or replicated to enhance sampling of…
Hydrocarbon pyrolysis is a complex chemical reaction system at extreme temperature and pressure conditions involving large numbers of chemical reactions and chemical species. Only two kinds of atoms are involved: carbons and hydrogens. Its…
Ion partitioning between different compartments (\emph{e.g.} a porous material and a bulk solution reservoir), known as Donnan equilibrium, plays a fundamental role in various contexts such as energy, environment, or water treatment. The…
The electrostatic interactions of phosphate groups and counter ions critically affect the structure, function and reactivity of DNA or RNA. We present a joint experimental-theoretical investigation of dimethyl phosphate (DMP-) in aqueous…
Nuclear quantum effects (NQEs) play an essential role in many atomistic systems, yet their explicit inclusion in molecular simulations remains challenging. Path-integral molecular dynamics (PIMD) provides a rigorous framework for…
Coupled cluster theory with a Kohn-Sham reference (KS-CC) can dramatically outperform its Hartree-Fock counterpart for strongly correlated systems, but the origin of these improvements has remained unclear. Here we demonstrate that these…
We present a distilled multi-time-step (DMTS) strategy to accelerate molecular dynamics simulations using foundation neural network models. DMTS uses a dual-level neural network where the target accurate potential is coupled to a simpler…
We present an optimized random phase approximation method (optRPA26) that significantly improves upon conventional RPA. The method employs an empirically constructed hybrid functional to generate DFT orbitals to evaluate the RPA correlation…