Christopher J. Mundy

We report an implementation of projection-based quantum embedding that combines periodic density functional theory in the CP2K code with correlated wavefunction calculations in the Q-Chem program. Using this interface, correlated wavefunction methods can be applied to a subset of molecular orbitals, selected in an automated manner based on a user-defined list of nuclei, with an embedding potential that provides electronic coupling to the remaining orbitals that comprise the environment. Our implementation uses exact projection, without the need for any level-shift operator, and is “pseudoperiodic” in the sense that periodic boundary effects are implicit in the orbitals used in the (non-periodic) wavefunction calculation. Convergence tests demonstrate that computed properties are faithful to the corresponding periodic quantities, provided that the high-level subsystem is spatially localized and small, relative to the periodic simulation cell. Spectroscopic examples for aqueous chromophores demonstrate converged results using a very limited subset of water molecules in the simulation cell, decoupling the choice of excited-state method and basis set from the functional that is used to propagate ground-state ab initio molecular dynamics. Solvatochromic shifts for aqueous uracil are converged using equation-of-motion coupled-cluster theory, without the need for solvent molecules in the wavefunction calculation, and the embedded calculation captures solvent effects that are absent in gas-phase “microhydration” studies. Additional applications include adsorption of CO on a slab model of Si(100) and bond dissociation in a one-dimensional periodic polymer. In both of the latter cases, the system/environment partition crosses a covalent bond; these applications demonstrate that pseudoperiodic embedding can be applied to realistic systems in materials science.

Most chemical and biochemical reactions occur in solution; however, many details of the thermodynamics of solvation are not well understood, especially with regard to the role of energy and entropy in the solvation process. Currently, a prevailing view in the field is that the solvation free energy is fully determined by solute–solvent interactions acting through both energetic and entropic contributions. This rests on the claim, presented by Yu and Karplus [J. Chem. Phys. 89, 2366 (1988)], that the solvent–solvent energetic and entropic contributions to the solvation free energy exactly cancel. Here, we show that this result is not correct but rather arises from an erroneous assignment of the solvent–solvent and solute–solvent entropic contributions. Namely, we demonstrate that the solvent–solvent and solute–solvent energetic contributions to the free energy, which have an unambiguous assignment, are not compatible with the Yu–Karplus decomposition of the solvation entropy. This indicates that, contrary to a now commonly held view, rearrangements of the solvent upon introduction of a solute may contribute both energetically and entropically to the solvation free energy.

The structure of the aqueous electron, e–(aq), has been the focus of intense scrutiny from both theory and experiment. The temperature dependence of its g-factor, measured via electron paramagnetic resonance and shifted significantly from the free-electron value, has been suggested to be inconsistent with the conventional picture of an electron localized in a solvent void or “cavity”. Here, we use ab initio molecular dynamics simulations and quantum chemistry calculations to compute the ensemble-averaged, isotropic g-factor for e–(aq) over the entire temperature range of liquid water. A temperature-dependent shift is obtained, in reasonable agreement with experiment, without any qualitative change in either the localized structure of e–(aq) or its average coordination number. Far from being inconsistent with g-factor measurements, persistence of the cavity motif actually supports the rather mild temperature dependence of the g-factor because the amount of spin density hosted in oxygen orbitals is remarkably insensitive to temperature. These results support a cavity-localized picture of e–(aq) from 0–100 °C at atmospheric pressure. The simulations are also broadly consistent with spectroscopic measurements demonstrating that the molar extinction coefficient is insensitive to temperature and that there are no abrupt temperature-induced changes in the absorption spectrum, even into the supercooled and supercritical water regimes. This analysis further entrenches the cavity-centric picture of e–(aq).

Silica nanoparticles are expected to remain stable at alkaline pH because deprotonated silanol groups lead to a strong electrostatic interparticle repulsion. Here, we show that this mean-field expectation fails for ultrasmall silica nanoparticles. Electron microscopy, dynamic light scattering, and small-angle X-ray scattering (SAXS) show that 9 nm silica nanoparticles form finite equilibrium clusters at pH 8.7, whereas larger particles remain dispersed under identical conditions. Analysis of SAXS profiles demonstrate that interactions between smaller nanoparticles cannot be described by typical screened electrostatics alone and require an additional short-range attractive contribution. Surface-sensitive measurements show that decreasing particle size increases hydroxylated silanol groups, alters interfacial charge density, and enhances the contribution of higher-pK_a proton-active sites. The cluster size reaches a maximum when pH approaches the higher-pK_a, identifying surface protonation state as a key descriptor. These results show that molecular surface chemistry drives pH-dependent attractions in ultrasmall silica nanoparticles beyond mean-field electrostatics.

We introduce the MixPI software to implement path integral molecular dynamics (PIMD) simulations for the study of condensed phase systems where nuclear quantum effects (NQEs) are important. In contrast to existing PIMD simulation software, MixPI enables the implementation of mixed quantum–classical path integral simulations where only a subset of system degrees of freedom (dofs) are treated quantum mechanically in an extended phase space while the remaining dofs are described classically. We expect this software to be particularly useful for simulations of electron and proton transfer in condensed phase systems, as well as for the study of biological and material systems where only a handful of dofs contribute significantly to the observed NQEs. We demonstrate the use of MixPI in two different systems. The first is a simple water model where we implement a set of mixed quantum–classical simulations to compute average energy and radial distribution functions. We use these simulations to benchmark the effectiveness of MixPI and to demonstrate how it enables systematic investigation into the origin of observed NQEs. We then compute radial distribution functions for a system where MixPI is essential: a solvated metal (M2+) cation described using an explicit quantized electron localized on an M3+ ion in water.

The era of protein design has enabled the creation of hybrid protein-inorganic interfaces, leading to both surface-directed self-assembly of de novo protein architectures and protein-directed formation of inorganic materials. However, the resulting patterns of protein assembly are often unexpected, implying that essential interactions are not accounted for in current design platforms. Here, we use high-speed atomic force microscopy (AFM) analyzed through machine learning to follow the assembly of protein nanorods in aqueous electrolytes on two types of mica exhibiting disparate symmetry elements, which are imprinted on the overlying hydration structure. Using Monte Carlo simulations, we reproduce the observed phases and show that an observed smectic phase, previously thought to be unstable for non-interacting rods in two dimensions, emerges when crystal symmetry introduces a directional bias. The findings demonstrate the importance of incorporating solvent forces as modulated by the hydration structure inherent to interfacial systems when designing protein assemblies at liquid-crystal interfaces. Coupling physics-based simulations that can account for these factors to de novo protein design algorithms can lead to improved design platforms for bio-inspired, hybrid materials.

While FD31–CaCO ₃ interactions were confirmed in regions of the protein predicted in the model, discrepancies between the model and our NMR data include µsec dynamics for Glu side chain carbonyls at the surface and a FD31–CaCO ₃ distance of ∼5.1 Å.

The photochemistry of UV-irradiated liquid water underlies many physical, chemical, and biological processes, with the formation of the hydrated electron as a central event. Despite extensive experimental and theoretical efforts, its microscopic origin remains incompletely understood. Using excited state molecular dynamics simulations of photoexcited liquid water, we resolve the sequence of chemical events leading to hydrated electron formation on the excited state. The excitation localizes on specific hydrogen-bond network defects, followed by two competing pathways. The first produces a hydrogen atom and undergoes ultrafast non-radiative decay to the ground state within 100 femtoseconds. The other proceeds via proton-coupled electron transfer, generating hydronium ions, hydroxyl radicals, and an excited state hydrated electron. This mechanism is driven by ultrafast coupled rotational and translational motions of water molecules, forming water-mediated ion-radical pairs that persist on picosecond timescales and influence visible emission. These results provide a unified framework for interpreting time-resolved spectroscopic observations and guide future experimental and theoretical investigations.

Understanding the contact dynamics of nonspherical particles is crucial for accurately modeling colloidal and granular systems where shape anisotropy dictates structural organization and transport properties. We here introduce an energy-conserving contact dynamics framework for arbitrary convex rigid-body particles by implementing vertex–boundary interactions in 2D and vertex–surface and edge–edge detection in 3D. The established formulation enables continuous force evaluation and prevents particle overlap while conserving total energy during translational and rotational motion. We demonstrate the framework’s stability and its utility to capture packing behavior, anisotropic diffusion, and equations of state of polygonal and polyhedral particles as examples. The framework establishes a robust and extensible foundation for investigating nonequilibrium dynamics of complex nonspherical particulate systems, enabling enhanced understanding of phenomena across spatiotemporal scales in self- and directed-assembly, granular flows, and hydrodynamics, potentially coupled with interactions that represent underlying physical mechanisms.