化学物理

The construction of non-empirical density functional approximations is typically guided by the satisfaction of exact constraints. An important constraint is the recovery of the gradient expansion for slowly varying electron densities. In…

We present a theoretical investigation of ion-induced Coulomb explosion imaging (CEI) of pyridazine molecules driven by energetic C$^{5+}$ projectiles, using time-dependent density-functional theory (TDDFT) with Ehrenfest nuclear dynamics.…

Coarse-grained (CG) modeling enables molecular simulations to reach time and length scales inaccessible to fully atomistic methods. For classical CG models, the choice of mapping, that is, how atoms are grouped into CG sites, is a major…

Accurate prediction of liquid viscosity is essential for process design and simulation, yet remains challenging for novel molecules. Conventional group-contribution models struggle with isomer discrimination, large molecules, and parameter…

In the field of machine learning coarse-grained potentials in molecular dynamics, many propagators require that the effective Hamiltonian is quadratic in momentum, thus limiting the family of coarse-graining functions. In this paper, we…

We present a reusable, open-source software implementation of the second-order trust region algorithm in the new OpenTrustRegion library. We apply the implementation to the general-purpose optimization of molecular orbitals in various…

An economic modeling approach for cavity quantum electrodynamics is provided by mean-field dynamics, wherein the optical field is described classically while a self-consistent interaction with quantum emitters is incorporated through the…

A central pursuit in theoretical chemistry is the accurate simulation of photochemical reactions, which are governed by nonadiabatic transitions through conical intersections. Machine learning has emerged as a transformative tool for…

In this work, we explore the reuse of terms in the Jastrow factor between systems for use in the transcorrelated method, to reduce the number of optimisable parameters for a given system. In particular, we propose a workflow in which…

An accurate description of electron correlation energies in molecules requires either basis set extrapolation or the use of explicitly-correlated wave functions that address the deficiencies of standard determinantal expansions at short…

Accurately predicting protein-ligand binding free energies (BFEs) remains a central challenge in drug discovery, particularly because the most reliable methods, such as free energy perturbation (FEP), are computationally intensive and…

Experimental validation of chemical processes is slow and costly, limiting exploration in materials discovery. Machine learning can prioritize promising candidates, but existing data in patents and literature is heterogeneous and difficult…

The reported ''dissociation times'' for the Br$_{2}$ C ($^{1}\Pi_{u}$ $1_{u}$) state by various measurement methods differ widely across the literature (30 to 340 fs). We consider this issue by investigating attosecond extreme ultraviolet…

The simplest, algebraic quantum-electrodynamical corrections, due to the double-negative energy subspace and instantaneous interactions, are computed to the no-pair energy of two-spin-1/2-fermion systems. Numerical results are reported for…

Machine-Learned Interatomic Potentials (MLIPs) require vast amounts of atomic structure data to learn forces and energies, and their performance continues to improve with training set size. Meanwhile, the even greater quantities of…

In orbital-free density functional theory (OFDFT), an equation exists for $\psi = \sqrt n$, the square root of the ground state electron density $n$. We show that $\psi$ cannot be expanded as a linear combination of elements of a complete…

Nuclear quantum effects (NQEs) arising from the light mass of hydrogen can influence the structure and stability of hydrogen-bonded biomolecules, yet their role in determining peptide and protein folding remains unclear. Experiments show…

Ionic behaviors, including ion distributions and hydration characteristics at solid-liquid interfaces, are important research interests in many important applications, such as electric double-layer capacitors and water lubrication. Here, we…

Electroosmotic flow (EOF) through nanoporous membranes has broad applications in micro- and nanofluidic systems, particularly in biomedical diagnostics and chemical analysis. The use of short nanopores enables high fluid flux, and the…

With controlled ionic current rectification (ICR) achieved through a strategically designed non-uniform surface charge distribution, short unipolar nanopores exhibit promising applications in nanofluidic sensors, ionic circuits, and ion…