arXiv subjects

Richard C. Remsing

Publications and source records attributed to Richard C. Remsing.

At least 19 recordsLinked to original sources

arXiv2026

Oxygen vacancies beyond the dilute limit in doped CaMnO3 perovskites and implications for screening materials in thermochemical applications

Thermochemical energy storage (TCES) in oxide perovskites relies on reversible oxygen vacancy formation, and computational high-throughput screening of candidate materials has predominantly used the single oxygen vacancy formation energy (OVFE) as the key descriptor. We demonstrate that the OVFE is insufficient for screening cubic CaMnO3 perovskites, because the stoichiometric compound is not the minimum energy reference state; vacancies are inherently present at operating temperatures. Materials with negative single OVFEs are routinely excluded from screening datasets as unsuitable, but this reflects a mischoice of reference state rather than a genuine materials limitation, and risks discarding promising TCES candidates. We address this by computing OVFEs as a function of vacancy concentration using ab initio density functional theory, establishing the equilibrium vacancy concentration as the correct reference point. OVFE curves referenced to this minimum align with experimentally measured reduction enthalpies, providing a framework directly comparable to experiments. We further show that A-site and B-site doping modify the vacancy formation landscape through distinct mechanisms. A-site dopants act primarily through strain relaxation and symmetry breaking, while B-site dopants reshape the local redox environment and introduce strong configurational dependence. Finally, we develop a thermodynamic model incorporating configurational entropy that accurately predicts equilibrium oxygen stoichiometry as a function of temperature and oxygen partial pressure and reveals that selective reduction of Mn4+ versus B-site dopant ions can tune the onset temperature for vacancy formation. These results establish a screening framework for perovskite TCES materials and provide practical guidance for extending high-throughput workflows beyond the single-vacancy paradigm.

cond-mat.mtrl-sci↗

arXiv2025

Electronic Fluctuations and Ionic Dynamics in Molten Silver Iodide

Molten salts are high-temperature ionic liquids whose unique combination of strong Coulombic interactions, large polarizabilities, and high ionic conductivities makes them central to energy storage, metallurgy, and nuclear technology. Understanding their delicate balance of Coulomb forces, short-range repulsion, and electronic polarization, particularly regarding the role that electronic fluctuations play in their structure and dynamics, is critical to predictively designing molten salts for applications of interest. We investigate the importance of electronic fluctuations in molten AgI using density functional theory, a universal machine learning model (Orb), and a classical, empirical pairwise model of interionic interactions. We find that directional polarization fluctuations of iodide ions enhance Ag+ diffusion, manifesting as enhanced force fluctuations and structure in the time-dependent friction experienced by the cations. The coupling between iodide polarization fluctuations and silver diffusion creates a dynamic asymmetry; Ag+ motion is tightly linked to the instantaneous polarization of neighboring I-, whereas I- dynamics are relatively unperturbed by electronic fluctuations. For all structural and dynamic quantities investigated, the Orb model is in excellent agreement with density functional theory-based simulations, highlighting the ability of this universal neural network potential to capture many-body polarization effects. In contrast, the empirical force field fails to reproduce key structural and dynamic quantities involving cations, ultimately because it neglects dynamic electronic fluctuations. Our findings connect liquid=state ionic dynamics with the "electronic paddle-wheel" mechanism of ionic diffusion in superionic solids and motivate further exploration of polarization fluctuation effects in complex electrolytes and ionic liquids.

physics.chem-ph↗

arXiv2025

Octahedral tilting and B-site off-centering in halide perovskites are not coupled

Metal halide perovskites show exceptional potential for solar energy, thermoelectrics, catalysis, and other photochemical technologies, with performance rooted in electronic structure-driven properties. In ABX3 halide perovskites, localized and often aspherical local electron densities from B-site lone pairs or polarizable X- anions can distort the lattice. However, the links among electronic structure fluctuations and distortions like tilting of the BX6 octahedra and off-centering of the B-site from the center of its octahedron are not fully understood. Using group theory and ab initio molecular dynamics, we quantify how lone pairs, halide polarization, off-centering, and octahedral tilting interact in the cubic phase CsBBr3, with B = Pb, Sn, and Ge. We find that lone pair-induced off-centering and octahedral tilting are symmetry-decoupled. Instead, stereochemical lone pair expression of the B-site ion is correlated to octahedral tilting through the propensity of the B-site to form a transient, partial covalent bond with the surrounding halide ions that stiffens octahedral tilting modes. These results link local electronic asymmetry to structural fluctuations and suggest that dynamic modulation of electronic symmetry offers a pathway to control functional properties in halide perovskites.

cond-mat.mtrl-sci↗

arXiv2025

Response Theory for Static and Dynamic Solvation of Ionic and Dipolar Solutes in Water

The response of polar solvents to ions and polar molecules dictates many fundamental molecular processes. To understand such electrostatically-driven solvation processes, one ideally would probe the dielectric response of a solvent to an idealized point test charge or dipole solute, as envisioned in classic continuum treatments of the problem. However, this is difficult in simulations using standard atomically-detailed solvent models with embedded point charges due to possible overlap with the test charge that lead to singular interaction energies. This problem is traditionally avoided for a realistic charged solute by introducing an excluded volume core that shields its embedded point charge or dipole from the charges in the solvent. However, this core introduces additional molecular-scale perturbations of the solvent density that complicate the interpretation of solvent dielectric response. In this work, we avoid these complications through the use of Gaussian-smoothed test charges and dipoles. Gaussian charges and dipoles can be readily inserted anywhere into an atomistic solvent model without encountering infinite energies. If the Gaussian-smoothing is on the scale of molecular correlations in the solvent, both the thermodynamic and dynamic solvation response is linear. Using this observation, we construct accurate predictive theories for solvation free energies and solvation dynamics for insertion of Gaussian charges and dipoles in polar solvents and demonstrate the accuracy of the theories for a widely-used model of water. Our results suggest that Gaussian test charge distributions can be used as an informative probe of dielectric response in molecular models, and our theories can be used to analytically predict the largest component of solvation free energies of charged and polar solutes.

physics.chem-ph↗

arXiv2025

Electronic Paddlewheels Impact the Dynamics of Superionic Conduction in AgI

Solid-state ion conductors hold promise as next generation battery materials. To realize their full potential, an understanding of atomic-scale ion conduction mechanisms is needed, including ionic and electronic degrees of freedom. Molecular simulations can create such an understanding, however, including a description of electronic structure necessitates computationally expensive methods that limit their application to small scales. We examine an alternative approach, in which neural network models are used to efficiently sample ionic configurations and dynamics at ab initio accuracy. Then, these configurations are used to determine electronic properties in a post-processing step. We demonstrate this approach by modeling the superionic phase of AgI, in which cation diffusion is coupled to rotational motion of local electron density on the surrounding iodide ions, termed electronic paddlewheels. The neural network potential can capture the many-body effects of electronic paddlewheels on ionic dynamics, but classical force field models cannot. Through an analysis rooted the generalized Langevin equation framework, we find that electronic paddlewheels have a significant impact on the time-dependent friction experienced by a mobile cation. Our approach will enable investigations of electronic fluctuations in materials on large length and time scales, and ultimately the control of ion dynamics through electronic paddlewheels.

cond-mat.mtrl-sci↗

arXiv2024

Quantum Tunneling Could Enable Proton Transfer Reactions on Titan

The surface of Titan, Saturn's largest moon, is rich in organics and is often suggested to model early Earth environments. Titan's surface is cold, at a temperature of approximately 90 K, which prohibits most thermally activated chemical reactions. However, quantum effects become more important at low temperatures and reactions that are classically prohibited can often proceed through quantum mechanical pathways. Using path integral molecular dynamics simulations, we investigate nuclear quantum effects on the thermodynamics of model proton transfer reactions in liquid ethane. We find that proton transfer can occur at Titan surface conditions through quantum tunneling. Consequently, we estimate that nuclear quantum effects can enhance reaction rates by many orders of magnitude. Our results suggest that nuclear quantum effects could facilitate prebiotic chemistry on Titan, and quantum effects should be considered in future investigations.

physics.chem-ph↗

arXiv2024

Molecular Structure and Rotational Dynamics in the Acetonitrile:Acetylene (1:2) Plastic Co-Crystal at Titan Conditions

The surface of Saturn's moon Titan is coated with small molecule organic solids termed cryominerals. Cryominerals play an analogous role to minerals on Earth in Titan's surface geology and geochemistry. To develop a predictive understanding of Titan's surface geochemistry, we need to characterize the structure and dynamics of cryominerals at the molecular scale. We use ab initio molecular dynamics simulations to quantify the structure and dynamics of the acetonitrile:acetylene (1:2) co-crystal at Titan surface conditions. We suggest that acetonitrile:acetylene is in a plastic phase, in which acetonitrile molecules are dynamically disordered about the N-C-C axis on sub-picosecond timescales, and that this rotational, plastic disorder persists at least to temperatures of 30 K. We anticipate that many cryominerals may have plastic phases at or near Titan surface conditions, and understanding this disorder will be crucial to predicting chemistry on Titan's surface.

physics.chem-ph↗

arXiv2024

Dynamic Local Symmetry Fluctuations of Electron Density in Halide Perovskites

Metal halide perovskites have emerged as an exciting class of materials for applications in solar energy harvesting, optical devices, catalysis, and other photophysical applications. Many of the exciting properties of halide perovskites are tied to their soft, dynamic, and anharmonic lattice. In particular, the precise coupling between anharmonic lattice dynamics and electronic fluctuations is not completely understood. To build an understanding of this coupling, we use ab initio molecular dynamics simulations supplemented by the calculation of maximally localized Wannier functions to carry out a dynamic group theory analysis of local electron density fluctuations and how these fluctuations are coupled to lattice fluctuations in the model inorganic halide perovskite CsSnBr3. We detail symmetry-dependent couplings between vibrational modes, including octahedral tilting. Importantly, we suggest that the large anharmonicity of some of the vibrational modes in CsSnBr3 result from electron rotation--nuclear translation coupling, in analogy to rotation--translation coupling effects in molecular plastic crystals. We also identify electronic fluctuations in the Cs cation that couple to distortions in the surrounding Sn-Br cubic coordination environment. We anticipate that our approach and resulting insights into electronic fluctuations will aid in further understanding the role of the fluctuating lattice in determining important physical properties of halide perovskites and beyond.

cond-mat.mtrl-sci↗

arXiv2023

Nuclear Quantum Effects in the Acetylene:Ammonia Plastic Co-crystal

Organic molecular solids can exhibit rich phase diagrams. In addition to structurally unique phases, translational and rotational degrees of freedom can melt at different state points, giving rise to partially disordered solid phases. The structural and dynamic disorder in these materials can have a significant impact on the physical properties of the organic solid, necessitating a thorough understanding of disorder at the atomic scale. When these disordered phases form at low temperatures, especially in crystals with light nuclei, the prediction of materials properties can be complicated by the importance of nuclear quantum effects. As an example, we investigate nuclear quantum effects on the structure and dynamics of the orientationally-disordered, translationally-ordered plastic phase of the acetylene:ammonia (1:1) co-crystal that is expected to exist on the surface of Saturn's moon Titan. Titan's low surface temperature (~90 K) suggests that the quantum mechanical behavior of nuclei may be important in this and other molecular solids in these environments. By using neural network potentials combined with ring polymer molecular dynamics simulations, we show that nuclear quantum effects increase orientational disorder and rotational dynamics within the acetylene:ammonia (1:1) co-crystal by weakening hydrogen bonds. Our results suggest that nuclear quantum effects are important to accurately model molecular solids and their physical properties in low temperature environments.

physics.chem-ph↗

arXiv2023

Modeling Nuclear Quantum Effects on Long Range Electrostatics in Nonuniform Fluids

Nuclear quantum effects play critical roles in a variety of molecular processes, especially in systems that contain hydrogen and other light nuclei, such as water. For water at ambient conditions, nuclear quantum effects are often interpreted as local effects resulting from a smearing of the hydrogen atom distribution. However, the orientational structure of water at interfaces determines long range effects like electrostatics through the O-H bond ordering that is impacted by nuclear quantum effects. In this work, I examine nuclear quantum effects on long range electrostatics of water confined between hydrophobic walls using path integral simulations. To do so, I combine concepts from local molecular field (LMF) theory with path integral methods at varying levels of approximation to develop an efficient and physically intuitive approaches for describing long range electrostatics in nonuniform quantum systems. Using these approaches, I show that quantum water requires larger electrostatic forces to achieve the same level of interfacial screening as the corresponding classical system. This work highlights subtleties of electrostatics in nonuniform classical and quantum molecular systems, and the methods presented here are expected to be of use to efficiently model nuclear quantum effects in large systems.

physics.chem-ph↗

arXiv2023

Electronic paddle-wheels in a solid-state electrolyte

Solid-state superionic conductors (SSICs) are promising alternatives to liquid electrolytes in batteries and other energy storage technologies. The rational design of SSICs and ultimately their deployment in battery technologies is hindered by the lack of a thorough understanding of their ion conduction mechanisms. In SSICs containing molecular ions, rotational dynamics couple to translational diffusion to create a 'paddle-wheel' effect that facilitates conduction. The paddle-wheel mechanism explains many important features of molecular SSICs, but an explanation for ion conduction and anharmonic lattice dynamics in SSICs composed of monatomic ions is still needed. We predict that ion conduction in the classic SSIC AgI involves 'electronic paddle-wheels,' rotational motion of lone pairs that couple to and facilitate ion diffusion. The electronic paddle-wheel mechanism creates a universal perspective for understanding ion conductivity in both monatomic and molecular SSICs that will create design principles for engineering solid-state electrolytes from the electronic level up to the macroscale.

physics.chem-ph↗

arXiv2023

Dielectric Saturation in Water from a Long Range Machine Learning Model

Machine learning-based neural network potentials have the ability to provide ab initio-level predictions while reaching large length and time scales often limited to empirical force fields. Traditionally, neural network potentials rely on a local description of atomic environments to achieve this scalability. These local descriptions result in short range models that neglect long range interactions necessary for processes like dielectric screening in polar liquids. Several approaches to including long range electrostatic interactions within neural network models have appeared recently, and here we investigate the transferability of one such model, the self consistent neural network (SCFNN), which focuses on learning the physics associated with long range response. By learning the essential physics, one can expect that such a neural network model should exhibit at least partial transferability. We illustrate this transferability by modeling dielectric saturation in a SCFNN model of water. We show that the SCFNN model can predict non-linear response at high electric fields, including saturation of the dielectric constant, without training the model on these high field strengths and the resulting liquid configurations. We then use these simulations to examine the nuclear and electronic structure changes underlying dielectric saturation. Our results suggest that neural network models can exhibit transferability beyond the linear response regime and make genuine predictions when the relevant physics is properly learned.

physics.chem-ph↗

arXiv2022

Molecular Structure, Dynamics, and Vibrational Spectroscopy of the Acetylene:Ammonia (1:1) Plastic Co-Crystal at Titan Conditions

The Saturnian moon Titan has a thick, organic-rich atmosphere, and condensed phases of small organic molecules are anticipated to be stable on its surface. Of particular importance are crystalline phases of organics, known as cryominerals, which can play important roles in surface chemistry and geological processes on Titan. Many of these cryominerals could exhibit rich phase behavior, especially multicomponent cryominerals whose component molecules have multiple solid phases. One such cryomineral is the acetylene:ammonia (1:1) co-crystal, and here we use density functional theory-based ab initio molecular dynamics simulations to quantify its structure and dynamics at Titan conditions. We show that the acetylene:ammonia (1:1) co-crystal is a plastic co-crystal (or rotator phase) at Titan conditions because the ammonia molecules are orientationally disordered. Moreover, the ammonia molecules within this co-crystal rotate on picosecond timescales, and this rotation is accompanied by the breakage and reformation of hydrogen bonds between the ammonia hydrogens and the π-system of acetylene. The robustness of our predictions is supported by comparing the predictions of two density functional approximations at different levels of theory, as well as through the prediction of infrared and Raman spectra that agree well with experimental measurements. We anticipate that these results will aid in understanding geochemistry on the surface of Titan.

physics.chem-ph↗

arXiv2021

Self-Consistent Determination of Long-Range Electrostatics in Neural Network Potentials

Machine learning has the potential to revolutionize the field of molecular simulation through the development of efficient and accurate models of interatomic interactions. In particular, neural network models can describe interactions at the level of accuracy of quantum mechanics-based calculations, but with a fraction of the cost, enabling the simulation of large systems over long timescales with ab initio accuracy. However, implicit in the construction of neural network potentials is an assumption of locality, wherein atomic arrangements on the scale of about a nanometer are used to learn interatomic interactions. Because of this assumption, the resulting neural network models cannot describe long-range interactions that play critical roles in dielectric screening and chemical reactivity. To address this issue, we introduce the self-consistent field neural network (SCFNN) model -- a general approach for learning the long-range response of molecular systems in neural network potentials. The SCFNN model relies on a physically meaningful separation of the interatomic interactions into short- and long-range components, with a separate network to handle each component. We demonstrate the success of the SCFNN approach in modeling the dielectric properties of bulk liquid water, and show that the SCFNN model accurately predicts long-range polarization correlations and the response of water to applied electrostatic fields. Importantly, because of the separation of interactions inherent in our approach, the SCFNN model can be combined with many existing approaches for building neural network potentials. Therefore, we expect the SCFNN model to facilitate the proper description of long-range interactions in a wide-variety of machine learning-based force fields.

physics.chem-ph↗

arXiv2021

Distributed Charge Models of Liquid Methane and Ethane for Dielectric Effects and Solvation

Liquid hydrocarbons are often modeled with fixed, symmetric, atom-centered charge distributions and Lennard-Jones interaction potentials that reproduce many properties of the bulk liquid. While useful for a wide variety of applications, such models cannot capture dielectric effects important in solvation, self-assembly, and reactivity. The dielectric constants of hydrocarbons, such as methane and ethane, physically arise from electronic polarization fluctuations induced by the fluctuating liquid environment. In this work, we present non-polarizable, fixed-charge models of methane and ethane that break the charge symmetry of the molecule to create fixed molecular dipoles, the fluctuations of which reproduce the experimental dielectric constant. These models can be considered a mean-field-like approximation that can be used to include dielectric effects in large-scale molecular simulations of polar and charged molecules in liquid methane and ethane. We further demonstrate that solvation of model ionic solutes and a water molecule in these fixed-dipole models improve upon dipole-free models.

physics.chem-ph↗

arXiv2020

Liquid-liquid Phase transitions in silicon

We use computationally simple neutral pseudo-atom (`average atom') one-center density functional theory (DFT) and standard N-center DFT-Molecular Dynamics simulations to elucidate liquid-liquid phase transitions (LPTs) in supercooled liquid silicon at 1200K ,and also in silicon under warm-dense matter conditions up to 11604k (1 eV). An ionization-driven transition and three LPTs including the known LPT near 2.5 g/cm$^3$ are found. They are robust even to 1 eV. The pair distributions functions, pair potentials, electrical conductivities, and compressibilites are reported. The LPTs are elucidated within a Fermi liquid picture of electron scattering at the Fermi energy that complements the usual transient covalent bonding picture.

cond-mat.mtrl-sci↗

arXiv2020

Effective Mass Path Integral Simulations of Quasiparticles in Condensed Phases

The quantum many-body problem in condensed phases is often simplified using a quasiparticle description, such as effective mass theory for electron motion in a periodic solid. These approaches are often the basis for understanding many fundamental condensed phase processes, including the molecular mechanisms underlying solar energy harvesting and photocatalysis. Despite the importance of these effective particles, there is still a need for computational methods that can explore their behavior on chemically relevant length and time scales. This is especially true when the interactions between the particles and their environment are important. We introduce an approach for studying quasiparticles in condensed phases by combining effective mass theory with the path integral treatment of quantum particles. This framework incorporates the generally anisotropic electronic band structure of materials into path integral simulation schemes to enable modeling of quasiparticles in quantum confinement, for example. We demonstrate the utility of effective mass path integral simulations by modeling an exciton in solid potassium chloride and electron trapping by a sulfur vacancy in monolayer molybdenum disulfide.

cond-mat.stat-mech↗

arXiv2020

Molecular Simulation of Covalent Bond Dynamics in Liquid Silicon

Many atomic liquids can form transient covalent bonds reminiscent of those in the corresponding solid states. These directional interactions dictate many important properties of the liquid state, necessitating a quantitative, atomic-scale understanding of bonding in these complex systems. A prototypical example is liquid silicon, wherein transient covalent bonds give rise to local tetrahedral order and consequent non-trivial effects on liquid state thermodynamics and dynamics. To further understand covalent bonding in liquid silicon, and similar liquids, we present an ab initio simulation-based approach for quantifying the structure and dynamics of covalent bonds in condensed phases. Through the examination of structural correlations among silicon nuclei and maximally localized Wannier function centers, we develop a geometric criterion for covalent bonds in liquid Si. We use this to monitor the dynamics of transient covalent bonding in the liquid state and estimate a covalent bond lifetime. We compare covalent bond dynamics to other processes in liquid Si and similar liquids and suggest experiments to measure the covalent bond lifetime.

physics.chem-ph↗