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Accurate electron densities from quantum Monte Carlo calculations using real-space grids
We provide accurate energies and electronic densities for Li2, C, and N2 from the diffusion Monte Carlo (DMC) method in the fixed node approximation based on orbitals from a real-space grid approach. With relatively simple single-determinant trial wave functions, we demonstrate the benefits of an all-electron approach in conjunction with a highly accurate grid method for calculating the orbitals that build the determinant. Our DMC ground state energies match with those of more elaborate single-reference quantum Monte Carlo (QMC) methods based on orbital basis sets. The binning technique is revisited to calculate the electronic density on a spatial grid. We examine the dependence of the resulting mixed estimator and extrapolated density on the trial wave function, specifically on the density functional generating the orbitals, by employing two distinctly different functionals, namely, the local density approximation and the exact-exchange functional. Residual statistical artifacts in the QMC densities are readily corrected by using a regularization method, resulting in smooth densities. As an example for the insight that can be gained from an accurate density, we verify that in the carbon atom, the density along one specific direction can have an asymptotic decay that differs from the decay found in all other directions. We relate this observation to previously published work, which discussed the implications that such a nodal feature may have for the exact Kohn–Sham potential.
Moment-based parameter inference with error guarantees for stochastic reaction networks
Inferring parameters of biochemical kinetic models from single-cell data remains challenging because of the uncertainty arising from the intractability of the likelihood function of stochastic reaction networks. Such uncertainty falls beyond current error quantification measures, which focus on the effects of finite sample size and identifiability but lack theoretical guarantees when likelihood approximations are needed. Here, we propose a method for the inference of parameters of stochastic reaction networks that works for both steady-state and time-resolved data and is applicable to networks with non-linear and rational propensities. Our approach provides bounds on the parameters via convex optimization over sets constrained by moment equations and moment matrices by taking observations to form moment intervals, which are then used to constrain parameters through convex sets. The bounds on the parameters contain the true parameters under the condition that the moment intervals contain the true moments, thus providing uncertainty quantification and error guarantees. Our approach does not need to predict moments and distributions for given parameters (i.e., it avoids solving or simulating the forward problem) and hence circumvents intractable likelihood computations or computationally expensive simulations. We demonstrate its use for uncertainty quantification, data integration, and prediction of latent species statistics through synthetic data from common non-linear biochemical models including the Schlögl model and the toggle switch, a model of post-transcriptional regulation at steady state, and a birth-death model with time-dependent data.
Martini 3 coarse-grained model of enzymes: Framework with validation by all-atom simulations and x-ray diffraction measurements
Recent experiments have shown that complexation with a stabilizing compound can preserve enzyme activity in harsh environments. Such complexation is believed to be driven by noncovalent interactions at the enzyme surface, including hydrophobicity and electrostatics. Molecular modeling of these interactions is costly at the all-atom scale due to the long time scales and large particle counts needed to characterize binding. Protein structure at the scale of amino acid residues is parsimoniously represented by a coarse-grained model in which one particle represents several atoms, significantly reducing the cost of simulation. Coarse-grained models may then be used to generate reduced surface descriptions to underlie detailed theories of surface adhesion. In this study, we present two coarse-grained enzyme models—lipase and dehalogenase—that have been prepared using the Martini 3 top-down modeling framework. We simulate each enzyme in aqueous solution and calculate the statistics of protein surface features and shape descriptors. The values from the coarse-grained data are compared with the same calculations performed on all-atom reference systems, revealing key similarities of surface chemistry at the two scales. Structural measures are calculated from the all-atom reference systems and compared with estimates from small-angle x-ray scattering experiments, with good agreement between the two. The described procedures of modeling and analysis comprise a framework for the development of coarse-grained models of protein surfaces with validation to experiment.
Richardson–Gaudin states of non-zero seniority: Matrix elements
Seniority-zero wave functions describe bond-breaking processes qualitatively. As eigenvectors of a model Hamiltonian, Richardson–Gaudin states provide a clear physical picture and allow for systematic improvement via standard single reference approaches. Until now, this treatment has been performed in the seniority-zero sector. In this paper, the corresponding states with higher seniorities are identified, and their couplings through the Coulomb Hamiltonian are computed. In every case, the couplings between the states are computed from the cofactors of their effective overlap matrix. Proof-of-principle calculations demonstrate that a single reference configuration interaction is comparable to seniority-based configuration interaction computations at a substantially reduced cost. The next paper in this series will identify the corresponding Slater–Condon rules and make the computations feasible.
Application of Nosé–Hoover dynamics for coarse-graining molecular systems: An evaluation of reproducibility in Lennard-Jones systems
This study proposes an application of Nosé–Hoover (NH) dynamics as a coarse-graining (CG) method for molecular simulations, offering an alternative to traditional Langevin-based approaches. The NH dynamics, known for its deterministic temperature control without stochastic forces, is adapted here to model a monoatomic Lennard-Jones system at different coarse-grained levels. The CG particle’s equation of motion is derived from atomic-level dynamics, linking NH thermostat terms with system properties obtained from molecular dynamics (MD) simulations. Key parameters, including the thermostat coefficient and thermal inertia, are calibrated using the MD data to assess their impact on the dynamic and structural reproducibility of the CG model. The calibration results suggest the potential application of NH dynamics as a coarse-graining method. The effectiveness of the proposed method is then evaluated through a set of CG simulations. The CG results show stable energy regulation and promising accuracy in reproducing system properties, particularly for mass diffusion, with opportunities for further refinement in representing structural reproducibility and momentum diffusion.
Anomalous propagators and the particle–particle channel: Bethe–Salpeter equation
The Bethe–Salpeter equation has been extensively employed to compute the two-body electron–hole propagator and its poles, which correspond to the neutral excitation energies of the system. Through a different time-ordering, the two-body Green’s function can also describe the propagation of two electrons or two holes. The corresponding poles are the double ionization potentials and double electron affinities of the system. In this work, a Bethe–Salpeter equation for the two-body particle–particle propagator is derived within the linear-response formalism using a pairing field and anomalous propagators. This framework allows us to compute kernels corresponding to different self-energy approximations (GW, T-matrix, and second-Born) as in the usual electron–hole case. The performance of these various kernels is gauged for singlet and triplet valence double ionization potentials using a set of 23 small molecules. The description of double core hole states is also analyzed.
An operational perspective on the Magnus–Fer conundrum in time-dependent quantum mechanics
The development of analytic methods for studying quantum systems driven by periodic Hamiltonians has remained an active pursuit for gaining insights into physical phenomena in spectroscopy and other related areas in chemical physics. From a theoretical perspective, the success of a given analytic method relies on the operational aspects as well as its exactness in replicating (known) experimental results. While analytic methods built around the Magnus expansion (ME) scheme have been preferred in time-evolution studies, the splitting of the time-propagator into a product of exponential operators in the Fer expansion (FE) scheme has gained wider attention in recent years. To this end, the operational advantages of one scheme over the other have always remained contentious and form the basis for the present report. Employing periodic Hamiltonians as examples, the operational aspects and the relative merits/demerits of the two methods are analyzed, and their long-term/short-term behavior is discussed through analytic expressions in experimentally verifiable systems.
MView: A pre- and post-processing tool for quantum chemistry calculation
A user-friendly graphical interface software named MView has been developed for molecular data processing. Featuring an intuitive graphical user interface design, MView enables analysis and visualization of quantum chemistry results, including molecular dimensions, thermochemical parameters, vibrational spectra (infrared/Raman), UV–Vis spectra, and automated generation of scan task input files. The software simplifies the workflow by directly analyzing output from mainstream computational packages (Gaussian, ORCA, DMol3, CP2K, xtb, etc.) and provides interfaces for visualization tools (Jmol, Avogadro, GaussView, VESTA, etc.) to facilitate one-click visualization of molecular structures.
Signature of interfacial water structure at the air–drug–polymer aqueous interface studied by sum frequency generation vibrational spectroscopy
The selection of polymers suitable for the formulation of supersaturating drug-delivery systems is imperative to improve the solubility, thermodynamic stability, precipitation inhibition ability, and bioavailability of drugs in vivo. However, a detailed molecular-level understanding of finding the right drug–polymer combination in the aqueous medium is still ambiguous and often selected based on the trial procedure. Here, we have employed sum frequency generation vibrational spectroscopy (SFG-VS) to probe the impact of drug–polymer interactions on the interfacial water structure at the model biorelevant medium (BM) interface to extract better insights into the molecular system. We investigated two different polymers, Eudragit EPO (E-EPO) and polyvinylpyrrolidone K30 (P-K30), resulting in a considerable difference in the supersaturation limits of the atorvastatin calcium (ATC), the model drug molecule in the BM solution. The solubility study suggests an ∼42 times enhancement in the solubility of ATC drug with the presence of E-EPO polymer and merely an ∼2.6 times enhancement for polymer P-K30. Interestingly, SFG spectroscopic studies showed that E-EPO supports a substantial orientational ordering of the interfacial water molecules with the signature of strongly hydrogen (H)-bonded water molecules. An opposite trend is witnessed for the P-K30 polymer with less preferential ordering and weakly H-bonded water molecules at the air–BM interface. The microscopic insights from the SFG spectroscopy, in correlation with the observations on drug solubility, present a new potential approach for probing drug–polymer interactions. The implementation of SFG vibrational spectroscopy can be beneficial in selecting suitable polymers to adopt better strategies for bioavailability enhancement in drug formulation development.
Nonlinear optical signatures of spin relaxation in 2D perovskites
Spin–orbit coupling splits the exciton resonances of two-dimensional organic–inorganic hybrid perovskites (2D-OIHPs) into an optically active fine structure. Although circularly polarized light can induce macroscopic spin polarizations in ensembles of quantum wells, the orientations of the angular momentum vectors associated with individual excitons generally randomize on sub-picosecond timescales in 2D-OIHPs with single lead-iodide layers. In the present work, we investigate the nonlinear optical signatures of spin depolarization in 2D-OIHP materials with various organic layer thicknesses and polaron binding energies. Transient absorption experiments conducted using circularly polarized laser pulses establish time constants for spin equilibration ranging from 65 to 110 fs in the targeted systems. In addition, with inspiration from time-resolved Faraday rotation spectroscopies, we introduce a transient grating method in which spin relaxation promotes an elliptical-to-linear transformation of the signal field polarization. Spectroscopic signatures for all experiments are simulated with a common third-order perturbative model that incorporates orientationally averaged transition dipoles and the polarizations of the laser pulses. Spectroscopic line broadening parameters obtained for the 2D-OIHP systems are considered in the context of a rate formula for spin relaxation, wherein the spin–orbit coupling is combined with a cumulant expansion for fluctuations of the energy levels. Our analysis suggests that the insensitivity of the measured spin relaxation rates to the polaron binding energies of 2D-OIHPs reflects the suppression of an activation energy barrier due to motional narrowing. Model calculations conducted with empirical parameters indicate that motional narrowing of the spin relaxation processes originates in correlated thermal fluctuations of the energy levels comprising the exciton fine structure.
Slower nucleation kinetics with stirring in a supercooled Zr80Pt20 liquid—Terrestrial and microgravity experiments on the International Space Station
Under terrestrial conditions, liquids are stirred by Marangoni and gravity-induced flows. A nucleation model that couples the stochastic fluxes of long-range diffusion and interfacial attachment [the Coupled-Flux Model (CFM)] predicts that the nucleation kinetics in metallic liquids should be faster with increased stirring for cases where long-range diffusion is required for nucleation due to an additional mechanism for the transportation of atoms to the nucleating cluster. Unfortunately, few experimental studies of stirring effects exist for metallic liquids. Here, the effect of stirring on hundreds of nucleation cycles is presented for a Zr80Pt20 eutectic liquid using the quiescent environment of ground-based electrostatic levitation and the controlled stirred environment of the electromagnetic levitation facility on the International Space Station. While the Zr80Pt20 liquid should solidify to a eutectic phase mixture, ground-based synchrotron x-ray studies of the crystallizing liquid presented here show that primary nucleation is to an icosahedral phase (i-phase). Approximately 5 s later, the i-phase/liquid transforms into the equilibrium eutectic phase mixture. Since Zr80Pt20 is the eutectic composition, little effect of stirring is expected since diffusion only occurs over short distances during crystallization. Stirring should also have little effect on the nucleation of the i-phase, which has a similar composition to that of the liquid. In contrast, the experimental results show that stirring slows down the nucleation kinetics of the i-phase. However, why the nucleation is heterogeneous, not homogeneous, is yet unknown; a few plausible explanations are suggested for this and the mechanism for the decrease in the nucleation kinetics with stirring.
Freezing in flat monolayers of soft spherocylinders
Lamellar or smectic phases often have an intricate intralamellar structure that remains scarcely understood from a microscopic viewpoint. In this work, we use molecular dynamics simulations to study the effect of volume exclusion on the phase transitions of a flat membrane of soft repulsive spherocylinders. With increasing rod packing, we identify liquid crystal and crystal phases and find that the disorder–order phase transition happens at a universal packing fraction (η ≈ 0.81), independent of the spherocylinder aspect ratio. We also confirm the existence of a small 2D hexatic region near the phase transition. The packing fraction associated with the phase transition is considerably higher than the well-known freezing transition of a hard disk fluid (η ≈ 0.7) to which one could naively map a system of near-parallel rods with co-planar mass centers. We attribute this difference to non-vanishing residual orientational entropy per rod. Our findings are corroborated by a simple theory based on a simple microscopic density functional theory of freezing of a two-dimensional rod fluid. The strength of the orientational fluctuations of the individual rods in our membranes exhibits a density scaling that differs from 3D bulk smectics. Our findings contribute to a qualitative understanding of liquid crystal phase stability in strong planar confinement and engage with recent experimental explorations involving nanorods on 2D substrates.
Planar tetracoordinate lithium in LiLi4F4+ cluster
Over the past 50 years, planar tetracoordinate carbons have attracted significant attention for challenging the classical tetrahedral bonding model proposed by van’t Hoff and Le Bel. While the planar framework has been extended to all other first-row elements beyond carbon, stable ptLi (lithium) compounds remain notably missing. Here, we conducted extensive structural searches on the potential energy surfaces of A5Ha4+ (A = alkali metals; Ha = halogens) to explore planar tetracoordinate alkali metals. Our results show that while A5Ha4+ species exhibit grid-like, square-planar A-centered ptA structures (A©A4Ha4+) in closed-shell states, most are transition states. Notably, we identified a rare, stable ptLi species, Li©Li4F4+. In this structure, strong charge transfer from Li to F atoms, forming a Li+©[Li+]4[F−]4 complex, provides strong electrostatic interactions. In addition, donor–acceptor covalent interactions Li4F4 → ptLi offer significant electronic stabilization, contributing to the overall stability of the intriguing ptLi structure.
Achieving designed texture and flows in bulk active nematics using optimal control theory
Being intrinsically nonequilibrium, active materials can potentially perform functions that would be thermodynamically forbidden in passive materials. However, active systems have diverse local attractors that correspond to distinct dynamical states, many of which exhibit chaotic turbulent-like dynamics and thus cannot perform work or useful functions. Designing such a system to choose a specific dynamical state is a formidable challenge. Motivated by recent advances enabling optogenetic control of experimental active materials, we describe an optimal control theory framework that identifies a spatiotemporal sequence of light-generated activity that drives an active nematic system toward a prescribed dynamical steady state. Active nematics are unstable to spontaneous defect proliferation and chaotic streaming dynamics in the absence of control. We demonstrate that optimal control theory can compute activity fields that redirect the dynamics into a variety of alternative dynamical programs and functions. This includes dynamically reconfiguring between states, selecting and stabilizing emergent behaviors that do not correspond to attractors, and are hence unstable in the uncontrolled system. Our results provide a roadmap to leverage optical control methods to rationally design structure, dynamics, and function in a wide variety of active materials.
Fatty acid methyl ester ethoxylate additive for enhancing high-temperature aqueous zinc-ion battery performance
Aqueous zinc-ion batteries (AZIBs) have attracted significant attention due to their high theoretical capacity, low cost, and excellent safety. Nevertheless, their practical applications are hindered by challenges such as electrolyte decomposition, Zn corrosion/passivation, and dendrite growth, which become more severe under high-temperature conditions. To address these issues, innovative electrolyte design has become a key strategy. In this study, we propose a simple and effective electrolyte modification strategy by introducing fatty acid methyl ester ethoxylate (FMEE) as an additive. FMEE functions as both a solvation structure regulator and a water cluster stabilizer, effectively suppressing side reactions and promoting the formation of a robust solid electrolyte interphase enriched with ZnS and ZnF2. This significantly improves the interfacial chemical stability of the Zn anode. As a result, the Zn anode achieves an extended cycling lifespan of up to 3000 h at 1 mA cm−2 and 1 mAh cm−2. Furthermore, the Zn–V2O5 full cell using the FMEE-modified electrolyte exhibits an excellent rate performance and long-term cycling stability. Notably, the cell maintains a superior electrochemical performance even at 60 °C, demonstrating remarkable thermal stability. This study offers a new strategy for developing high-performance, temperature-tolerant AZIBs.
Surface strain hampers dissociation and induces curious rotational-alignment effect for HCl on the Au/Cu(111) alloy surface
We present the first six-dimensional quantum dynamics study of HCl on a strained pseudomorphic monolayer of Au deposited on a Cu(111) substrate, utilizing a newly developed machine learning-based potential energy surface. The strain in the surface lattice, resulting from a 12.62% compression of the Au monolayer, induces a significant high barrier height (1.81 eV) and a tight saddle point. These effects lead to a marked suppression of the reactivity of ground-state HCl (v = 0) on Au/Cu(111), while the dissociation probability of vibrationally excited (v = 1) HCl increases substantially. As a result, the vibrational efficiency is notably higher compared to those for HCl on pure Au(111) and alloyed Au/Ag(111) surfaces. In addition, the surface strain induces a distinctive rotational alignment effect in the title reaction, where for HCl in the (v = 0, j) states, dissociation is most favorable when an HCl molecule collides with its rotation perpendicular to the Au/Cu(111) surface (the cartwheel alignment). In contrast, for HCl in the (v = 1, j) states, the opposite (helicopter) alignment is preferred. This leads to a pronounced difference in the effects of rotational excitation, depending on whether HCl is initially in the ground or excited vibrational state.
Long-term memory in lipid assemblies: Rate-independent hysteresis in the ripple-to-liquid-disordered transition of sphingomyelin bilayers
Sphingomyelin (SM) is the most abundant sphingolipid in mammalian cells. It contains a phosphorylcholine headgroup, which makes SM an analog of the (glycerol-containing) phosphatidylcholines. Palmitoyl (C16:0) SM bilayers in excess water exhibit a thermotropic transition from the ripple to the fluid phase centered at ≈41 °C. In phosphatidylcholines, as in most phospholipids, the ripple-to-fluid transition is fully reversible and virtually free of hysteresis. In this paper, however, the corresponding transition was assessed in aqueous SM by infrared (IR) spectroscopy, a technique detecting molecular vibrations. Vibrational spectra as a function of temperature revealed thermotropic phase transitions. When the samples were successively heated up and cooled down, a clear hysteresis was detected. The cooling transition started at the same temperature as the heating one, but the end-point, in terms of IR band position, was clearly different. Hysteresis was particularly visible in the shift of the IR Amide I band, associated with the lipid polar headgroup, and it was rate-independent, within a wide range of heating/cooling rates (from 5.5 °C/min to less than 0.05 °C/min). Atomistic computer simulations of the molecular dynamics provided information consistent with the IR data. In addition, it showed that the in-plane arrangement of SM bilayers displays a significant amount of hexatic order, and that the hexatic order parameter, reflecting primarily polar headgroup ordering, exhibited the same kind of hysteresis described by IR. Rate-independent hysteresis allows the development of durable memories; therefore, the observations in this paper could lead to novel applications of lipid assemblies.
The standard coil or globule phases cannot describe the denatured state of structured proteins and intrinsically disordered proteins
The concepts of globule and random coil were developed to describe the phases of homopolymers and then used to characterize the denatured state of structured cytosolic proteins and intrinsically disordered proteins. Using multi-scale molecular dynamics simulations, we were able to explore the conformational space of the disordered conformations of both types of protein under biological conditions in an affordable amount of computational time. By studying the size of the protein and the density correlations in space, we conclude that the standard phases of homopolymers and the tools to detect them cannot be applied straightforwardly to proteins.
Kinetic phase diagram for two-step nucleation in colloid–polymer mixtures
Two-step crystallization via a metastable intermediate phase is often regarded as a non-classical process that lies beyond the framework of classical nucleation theory (CNT). In this work, we investigate two-step crystallization in colloid–polymer mixtures via an intermediate liquid phase. Using CNT-based seeding simulations, we construct a kinetic phase diagram that identifies regions of phase space where the critical nucleus is either liquid or crystalline. These predictions are validated using transition path sampling simulations at nine different relevant state points. When the critical nucleus is liquid, crystallization occurs stochastically during the growth phase, whereas for a crystalline critical nucleus, the crystallization process happens pre-critically at a fixed nucleus size. We conclude that CNT-based kinetic phase diagrams are a powerful tool for understanding and predicting “non-classical” crystal nucleation mechanisms.
Exploring superconductivity under strong coupling with the vacuum electromagnetic field
Strong light–matter interactions have generated considerable interest as a means to manipulate material properties. Here, we explore this possibility with the molecular superconductor Rb3C60 under vibrational strong coupling (VSC) to surface plasmon polaritons. By placing the superconductor-surface plasmon system in a SQUID magnetometer, we find that the superconducting transition temperature (Tc) increases from 30 to 45 K at normal pressures under VSC, displaying a well-defined Meissner effect. A simple theoretical framework is provided to understand these results based on an enhancement of the electron–phonon coupling. This proof-of-principle study opens a new tool box to not only modify superconducting materials but also to understand the mechanistic details of different superconductors.