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In a recent paper, Di Lisio et al. [J. Chem. Phys. 159, 064505 (2023)] analyzed a series of temperature down-jumps using the single-parameter aging (SPA) ansatz combined with a specific assumption about density scaling in the out-of-equilibrium system and did not find a good prediction for the largest down-jumps. In this paper, we show that SPA in its original form does work for all their data, including large jumps of ΔT > 20 K. Furthermore, we discuss different approaches to the extension of the density scaling concept to out-of-equilibrium systems. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the role of electron correlation in predicting the S1–S0 and T1–S0 excitation energies and, hence, the singlet–triplet gap (ΔEST) in a set of cyclazines, which act as templates for potential candidates for fifth generation organic light emitting diode materials. This issue has recently garnered much interest with the focus being on the inversion of the ΔEST, although experiments have indicated near degenerate levels with both positive and negative being within the experimental error bar [J. Am. Chem. Soc. 102, 6068 (1980), J. Am. Chem. Soc. 108, 17(1986)]. We have carried out a systematic and exhaustive study of various excited state electronic structure methodologies and identified the strengths and shortcomings of the various approaches and approximations in view of this challenging case. We have found that near degeneracy can be achieved either with a proper balance of static and dynamic correlation in multireference theories or with state-specific orbital corrections, including its coupling with correlation. The role of spin contamination is also discussed. Eventually, this paper seeks to produce benchmark numbers for establishing cost-effective theories, which can then be used for screening derivatives of these templates with desirable optical and structural properties. Additionally, we would like to point out that the use of domain-based local pair natural orbital-similarity transformed EOM-coupled cluster singles and doubles as the benchmark for ΔEST [as used in J. Phys. Chem. A 126(8), 1378 (2022), Chem. Phys. Lett. 779, 138827 (2021)] is not a suitable benchmark for these classes of molecules. [ABSTRACT FROM AUTHOR]

Thermal energy storage and utilization has been widely concerned due to the intermittency, renewability, and economy of renewable energy. In this paper, the potential energy function of binary Na2CO3–K2CO3 salt was first constructed using the Deep Potential GENerator (DPGEN) enhanced sampling method. Deep potential molecular dynamics simulations were performed to calculate the thermal properties and structural evolution of binary carbonates. The results show that as the temperature increases from 1073 to 1273 K, the viscosity and thermal conductivity decrease from 5.011 mPa s and 0.502 W/(m K) to 2.526 mPa s and 0.481 W/(m K), respectively. The decrease in viscosity is related to the distance and interaction between the molten salt ions. In addition, the diffusion coefficients, energy barriers, ionic radius, angular distribution function, and coordination number of molten salt were calculated and analyzed. The CO32− exhibits a stable planar triangular structure. The ionic radius of Na+ is smaller than that of K+, which makes Na+ suffer less spatial hindrance during motion and has a higher diffusion coefficient. The energy barriers that Na+ needs to overcome to escape the Coulomb force is greater than that of K+ ions, so molten salt containing Na+ may possess greater heat storage potential. We believe that the potential function constructed with DPGEN enhanced sampling strategy can provide more convincing results for predicting the thermal properties of molten salts. This paper aims to provide a technical route to develop the novel complex molten salt phase change material for thermal energy storage. [ABSTRACT FROM AUTHOR]

Diffusion in complex heterogeneous media, such as biological tissues or porous materials, typically involves constrained displacements in tortuous structures and sticky environments. Therefore, diffusing particles experience both entropic (excluded-volume) forces and the presence of complex energy landscapes. In this situation, one may describe transport through an effective diffusion coefficient. In this paper, we examine comb structures with finite-length 1D and finite-area 2D fingers, which act as purely diffusive traps. We find that there exists a critical width of 2D fingers, above which the effective diffusion along the backbone is faster than for an equivalent arrangement of 1D fingers. Moreover, we show that the effective diffusion coefficient is described by a general analytical form for both 1D and 2D fingers, provided the correct scaling variable is identified as a function of the structural parameters. Interestingly, this formula corresponds to the well-known general situation of diffusion in a medium with fast reversible adsorption. Finally, we show that the same formula describes diffusion in the presence of dilute potential energy traps, e.g., through a landscape of square wells. While diffusion is ultimately always the result of microscopic interactions (with particles in the fluid, other solutes, and the environment), effective representations are often of great practical use. The results reported in this paper help clarify the microscopic origins and the applicability of global, integrated descriptions of diffusion in complex media. [ABSTRACT FROM AUTHOR]

The Wigner phase space formulation of quantum mechanics is a complete framework for quantum dynamic calculations that elegantly highlights connections with classical dynamics. In this series of two articles, building upon previous efforts, we derive the full hierarchy of approximate semiclassical (SC) dynamic methods for adiabatic and non-adiabatic problems in Wigner phase space. In Paper I, focusing on adiabatic single surface processes, we derive the well-known double Herman–Kluk (DHK) approximation for real-time correlation functions in Wigner phase space and connect it to the linearized SC (LSC) approximation through a stationary phase approximation. We exploit this relationship to introduce a new hybrid SC method, termed Adiabatic Hybrid Wigner Dynamics (AHWD) that allows for a few important "system" degrees of freedom (dofs) to be treated at the DHK level, while treating the rest of the dofs (the "bath") at the LSC level. AHWD is shown to accurately capture quantum interference effects in models of coupled oscillators and the decoherence of vibrational probability density of a model I2 Morse oscillator coupled to an Ohmic thermal bath. We show that AHWD significantly mitigates the sign problem and employs reduced dimensional prefactors bringing calculations of complex system–bath problems within the reach of SC methods. Paper II focuses on extending this hybrid SC dynamics to nonadiabatic processes. [ABSTRACT FROM AUTHOR]

The Journal of Chemical Physics has released a special issue focused on software for atomistic machine learning. This issue aims to address the lack of journals dedicated to publishing scientific software papers. The collection of papers in this issue provides insight into the tools and goals of software implementations in the field of atomistic machine learning. The articles cover a range of topics, including machine-learning interatomic potentials, sampling, dataset repositories, workflows, and auxiliary tooling and analysis. The article concludes by emphasizing the importance of software implementations in the field and encourages further submissions on relevant topics. [Extracted from the article]

This paper is dedicated to the quantum chemical package Jaguar, which is commercial software developed and distributed by Schrödinger, Inc. We discuss Jaguar's scientific features that are relevant to chemical research as well as describe those aspects of the program that are pertinent to the user interface, the organization of the computer code, and its maintenance and testing. Among the scientific topics that feature prominently in this paper are the quantum chemical methods grounded in the pseudospectral approach. A number of multistep workflows dependent on Jaguar are covered: prediction of protonation equilibria in aqueous solutions (particularly calculations of tautomeric stability and pKa), reactivity predictions based on automated transition state search, assembly of Boltzmann-averaged spectra such as vibrational and electronic circular dichroism, as well as nuclear magnetic resonance. Discussed also are quantum chemical calculations that are oriented toward materials science applications, in particular, prediction of properties of optoelectronic materials and organic semiconductors, and molecular catalyst design. The topic of treatment of conformations inevitably comes up in real world research projects and is considered as part of all the workflows mentioned above. In addition, we examine the role of machine learning methods in quantum chemical calculations performed by Jaguar, from auxiliary functions that return the approximate calculation runtime in a user interface, to prediction of actual molecular properties. The current work is second in a series of reviews of Jaguar, the first having been published more than ten years ago. Thus, this paper serves as a rare milestone on the path that is being traversed by Jaguar's development in more than thirty years of its existence. [ABSTRACT FROM AUTHOR]

A preceding paper [M. Dhar, J. A. Dickinson, and M. A. Berg, J. Chem. Phys. 159, 054110 (2023)] shows how to remove additive noise from an experimental time series, allowing both the equilibrium distribution of the system and its Green's function to be recovered. The approach is based on nonlinear-correlation functions and is fully nonparametric: no initial model of the system or of the noise is needed. However, single-molecule spectroscopy often produces time series with either photon or photon-counting noise. Unlike additive noise, photon noise is signal-size correlated and quantized. Photon counting adds the potential for bias. This paper extends noise-corrected-correlation methods to these cases and tests them on synthetic datasets. Neither signal-size correlation nor quantization is a significant complication. Analysis of the sampling error yields guidelines for the data quality needed to recover the properties of a system with a given complexity. We show that bias in photon-counting data can be corrected, even at the high count rates needed to optimize the time resolution. Using all these results, we discuss the factors that limit the time resolution of single-molecule spectroscopy and the conditions that would be needed to push measurements into the submicrosecond region. [ABSTRACT FROM AUTHOR]

This article is a response to a comment made by Professor Liu regarding a previously published paper. The response addresses questions raised by Professor Liu and focuses on three key aspects of the validity of the paper. It explains the use of different contractions in the construction of the QED Hamiltonians and clarifies the commutation relations used in the calculations. The article also highlights that the formulation of the molecular orbital method described in the paper is independent of the ordering of the operators and can derive expressions for various perturbation theories. The response concludes by stating that alternative criteria for the QED Hamiltonians are not ruled out and could be explored in future research. [Extracted from the article]

This document is an erratum for a previous paper titled "Modified Fermi's golden rule rate expressions." The erratum corrects an error in equation (41) by adding a missing factor of 1/2. The correction does not change any major conclusions or implications of the paper, but it does require the correction of figures 1-4, which show results of model calculations. The corrected figures and their captions are provided in the erratum. [Extracted from the article]

The study and modeling of water exchange in complex media using different applications of diffusion and relaxation magnetic resonance (MR) have been of interest in recent years. Most models attempt to describe this process using a first order kinetics expression, which is appropriate to describe chemical exchange; however, it may not be suitable to describe diffusion-driven exchange since it has no direct relationship to diffusion dynamics of water molecules. In this paper, these limitations are addressed through a more general exchange expression that does consider such important properties. This exchange fraction expression features a multi-exponential recovery at short times and a mono-exponential decay at long times, both of which are not captured by the first order kinetics expression. Furthermore, simplified exchange expressions containing partial information of the analyzed system's diffusion and relaxation processes and geometry are proposed, which can potentially be employed in already established estimation protocols. Finally, exchange fractions estimated from simulated MR data and derived here were compared, showing qualitative similarities but quantitative differences, suggesting that the features of the derived exchange fraction in this paper can be partially recovered by employing an existing estimation framework. [ABSTRACT FROM AUTHOR]

Biased and accelerated molecular simulations (BAMS) are widely used tools to observe relevant molecular phenomena occurring on time scales inaccessible to standard molecular dynamics, but evaluation of the physical time scales involved in the processes is not directly possible from them. For this reason, the problem of recovering dynamics from such kinds of simulations is the object of very active research due to the relevant theoretical and practical implications of dynamics on the properties of both natural and synthetic molecular systems. In a recent paper [A. Rapallo et al., J. Comput. Chem. 42, 586–599 (2021)], it has been shown how the coupling of BAMS (which destroys the dynamics but allows to calculate average properties) with Extended Diffusion Theory (EDT) (which requires input appropriate equilibrium averages calculated over the BAMS trajectories) allows to effectively use the Smoluchowski equation to calculate the orientational time correlation function of the head–tail unit vector defined over a peptide in water solution. Orientational relaxation of this vector is the result of the coupling of internal molecular motions with overall molecular rotation, and it was very well described by correlation functions expressed in terms of weighted sums of suitable time-exponentially decaying functions, in agreement with a Brownian diffusive regime. However, situations occur where exponentially decaying functions are no longer appropriate to capture the actual dynamical behavior, which exhibits persistent long time correlations, compatible with the so called subdiffusive regimes. In this paper, a generalization of EDT will be given, exploiting a fractional Smoluchowski equation (FEDT) to capture the non-exponential character observed in the relaxation of intramolecular distances and molecular radius of gyration, whose dynamics depend on internal molecular motions only. The calculation methods, proper to EDT, are adapted to implement the generalization of the theory, and the resulting algorithm confirms FEDT as a tool of practical value in recovering dynamics from BAMS, to be used in general situations, involving both regular and anomalous diffusion regimes. [ABSTRACT FROM AUTHOR]

Despite the importance of rhodium complexes in catalysis, and the favorable 100% natural abundance of the spin-1/2 103Rh nucleus, there are few reports of 103Rh nuclear magnetic resonance (NMR) parameters in the literature. In part, this is the consequence of the very low gyromagnetic ratio of 103Rh and its dismal NMR sensitivity. In a previous paper [Harbor-Collins et al., J. Chem. Phys. 159, 104 307 (2023)], we demonstrated an NMR methodology for 1H-enhanced 103Rh NMR and demonstrated an application to the 103Rh NMR of the dirhodium formate paddlewheel complex. In this paper, we employ selective 18O labeling to break the magnetic equivalence of the 103Rh spin pair of dirhodium formate. This allows the estimation of the 103Rh–103Rh spin–spin coupling and provides access to the 103Rh singlet state. We present the first measurement of a 18O-induced 103Rh secondary isotope shift as well as the first instance of singlet order generated in a 103Rh spin pair. The field-dependence of 103Rh singlet relaxation is measured by field-cycling NMR experiments. [ABSTRACT FROM AUTHOR]

Spontaneous self-assembly of hard convex polyhedra is known to form orientationally disordered crystalline phases, where particle orientations do not follow the same pattern as the positional arrangement of the crystal. A distinct type of orientational phase with discrete rotational mobility has been reported in hard particle systems. In this paper, we present a new analysis method for characterizing the orientational phase of a crystal, which is based on algorithmic detection of unique orientations. Using this method, we collected complete statistics of discrete orientations along the Monte Carlo simulation trajectories and observed that particles were equally partitioned among them, with specific values of pairwise orientational differences. These features remained constant across the pressure range and did not depend on rotational mobility. The discrete mobility was characteristic of a distinct equilibrium thermodynamic phase, qualitatively different from the freely rotating plastic phase with continuous orientations. The high pressure behavior with frozen particle orientations was part of that same description and not a non-equilibrium arrested state. We introduced a precise notion of orientational order and demonstrated that the system was maximally disordered at the level of a unit cell, even though individual particles could only take a few discrete orientations. We report the existence of this phase in five polyhedral shapes and in systematically curated shape families constructed around two of them. The symmetry mismatch between the particle and the crystallographic point groups was found to be a predictive indicator for the occurrence of this phase. [ABSTRACT FROM AUTHOR]

When we place conducting bodies in electrolyte solutions, their surface potential Φs appears to be much smaller in magnitude than the applied one Φ0 and normally does not obey the classical electrostatic boundary condition of a constant potential expected for conductors. In this paper, we demonstrate that an explanation of these observations can be obtained by postulating that diffuse ions condense at the "wall" due to the reduced permittivity of a solvent. For small values of Φ0, the surface potential responds linearly. On increasing Φ0 further, Φs augments nonlinearly and then saturates to a constant value. Analytical approximations for Φs derived for these three distinct modes show that it always adjusts to salt concentration, which is equivalent to a violation of the constant potential condition. The latter would be appropriate for highly dilute solutions but only if Φ0 is small. Surprisingly, when the plateau with high Φs is reached, the conductor surface switches to a constant charge density condition normally expected for insulators. Our results are directly relevant for conducting electrodes, mercury drops, colloidal metallic particles, and more. [ABSTRACT FROM AUTHOR]

Proteins can form droplets via liquid–liquid phase separation (LLPS) in cells. Recent experiments demonstrate that LLPS is qualitatively different on two-dimensional (2D) surfaces compared to three-dimensional (3D) solutions. In this paper, we use mathematical modeling to investigate the causes of the discrepancies between LLPS in 2D and 3D. We model the number of proteins and droplets inducing LLPS by continuous-time Markov chains and use chemical reaction network theory to analyze the model. To reflect the influence of space dimension, droplet formation and dissociation rates are determined using the first hitting times of diffusing proteins. We first show that our stochastic model reproduces the appropriate phase diagram and is consistent with the relevant thermodynamic constraints. After further analyzing the model, we find that it predicts that the space dimension induces qualitatively different features of LLPS, which are consistent with recent experiments. While it has been claimed that the differences between 2D and 3D LLPS stem mainly from different diffusion coefficients, our analysis is independent of the diffusion coefficients of the proteins since we use the stationary model behavior. Our results thus give new hypotheses about how space dimension affects LLPS. [ABSTRACT FROM AUTHOR]

The introduction of machine learned potentials (MLPs) has greatly expanded the space available for studying Nuclear Quantum Effects computationally with ab initio path integral (PI) accuracy, with the MLPs' promise of an accuracy comparable to that of ab initio at a fraction of the cost. One of the challenges in development of MLPs is the need for a large and diverse training set calculated by ab initio methods. This dataset should ideally cover the entire phase space, while not searching this space using ab initio methods, as this would be counterproductive and generally intractable with respect to computational time. In this paper, we present the self-learning PI hybrid Monte Carlo Method using a mixed ab initio and ML potential (SL-PIHMC-MIX), where the mixed potential allows for the study of larger systems and the extension of the original SL-HMC method [Nagai et al., Phys. Rev. B 102, 041124 (2020)] to PI methods and larger systems. While the MLPs generated by this method can be directly applied to run long-time ML-PIMD simulations, we demonstrate that using PIHMC-MIX with the trained MLPs allows for an exact reproduction of the structure obtained from ab initio PIMD. Specifically, we find that the PIHMC-MIX simulations require only 5000 evaluations of the 32-bead structure, compared to the 100 000 evaluations needed for the ab initio PIMD result. [ABSTRACT FROM AUTHOR]

In this paper, we analyze the properties of the recently proposed real-time equation-of-motion coupled-cluster (RT-EOM-CC) cumulant Green's function approach [Rehr et al., J. Chem. Phys. 152, 174113 (2020)]. We specifically focus on identifying the limitations of the original time-dependent coupled cluster (TDCC) ansatz and propose an enhanced double TDCC ansatz, ensuring the exactness in the expansion limit. In addition, we introduce a practical cluster-analysis-based approach for characterizing the peaks in the computed spectral function from the RT-EOM-CC cumulant Green's function approach, which is particularly useful for the assignments of satellite peaks when many-body effects dominate the spectra. Our preliminary numerical tests focus on reproducing, approximating, and characterizing the exact impurity Green's function of the three-site and four-site single impurity Anderson models using the RT-EOM-CC cumulant Green's function approach. The numerical tests allow us to have a direct comparison between the RT-EOM-CC cumulant Green's function approach and other Green's function approaches in the numerical exact limit. [ABSTRACT FROM AUTHOR]

Singlet fission (SF) is a charge carrier multiplication process that has potential for improving the performance of (opto)electronic devices from the conversion of one singlet exciton S1 into two triplet excitons T1 via a spin-entangled triplet pair state 1(TT). This process depends highly on molecular packing and morphology, both for the generation and dissociation of 1(TT) states. Many benchmark SF materials, such as acenes, are also prone to photodegradation reactions, such as endoperoxide (EPO) formation and photodimerization, which inhibit realization of SF devices. In this paper, we compare functionalized tetracenes R–Tc with two packing motifs: "slip-stack" packing in R = TES, TMS, and tBu and "gamma" packing in R = TBDMS to determine the effects of morphology on SF as well as on photodegradation using a combination of temperature and magnetic field dependent spectroscopy, kinetic modeling, and time-dependent density functional theory. We find that both "slip-stack" and "gamma" packing support SF with high T1 yield at room temperature (up to 191% and 181%, respectively), but "slip-stack" is considerably more advantageous at low temperatures (< 150 K). In addition, each packing structure has a distinct emissive relaxation pathway competitive to SF, while the states involved in the SF itself are dark. The "gamma" packing has superior photostability, both in regards to EPO formation and photodimerization. The results indicate that the trade-off between SF efficiency and photostability can be overcome with material design, emphasize the importance of considering both photophysical and photochemical properties, and inform efforts to develop optimal SF materials for (opto)electronic applications. [ABSTRACT FROM AUTHOR]

We theoretically demonstrated that helical-photon-dressed states determine the rotational directions of the π-electrons of aromatic ring molecules formed by a circularly polarized or an elliptically polarized laser. This theory was verified using a minimal three-electronic-state model under the frozen nuclei condition. The model consists of the ground state and either a doubly degenerate electronic excited state or two quasi-degenerate excited states. Three helical-photon-dressed states were derived by solving the time-dependent Schrödinger equation within the semi-classical treatment of light–molecule interactions and rotating wave approximation. The angular momenta of the two helical-photon-dressed states represent the classical rotational direction, and that of the remaining state represents the opposite rotation, that is, non-classical rotation. Classical rotation means that π-electrons have the same rotational direction as that of a given helical electric field vector and obeys the classical equations of motion. Non-classical rotation indicates that the rotational direction is opposite to that of the helical electric field vector. Non-classical rotation is forbidden in an aromatic ring molecule with high symmetry formed by a circularly polarized laser but is allowed in a low symmetric aromatic ring molecule. The sum of the angular momenta of the three dressed states is zero. This is called the sum law for the angular momentum components in this paper. Benzene (D6h) and toluene (CS) were adopted as typical aromatic ring molecules of high and low symmetries, respectively. Finally, considering the effects of nuclear vibrations in the adiabatic approximation, an expression for the π-electron angular momentum was derived and applied to toluene. [ABSTRACT FROM AUTHOR]

Recent 15N R1ρ-relaxation studies have shown that proteins in the solid state undergo slow, low amplitude global motion in the sub-millisecond time range. This range is at the edge of the time window for R1ρ experiments and, therefore, the motional parameters obtained by this method are not precise or reliable. In this paper, we present a 2H stimulated echo study of this type of molecular dynamics. The 2H stimulated echo experiments on a static sample allow for direct measurement of the correlation function in the time range of 10−6–10−1 s, making them well suited to study this type of molecular mobility. We have conducted a detailed analytical and numerical comparison of the correlation functions obtained from the relaxation and stimulated echo experiments, which are generally different. We have identified conditions and algorithms that enable a direct comparison of the relaxation and stimulated echo experimental results. Using the protein GB1 in the form of a lyophilized powder, we have demonstrated that 15N R1ρ-relaxation and 2H stimulated echo experiments yield essentially the same slow-motion correlation function. Surprisingly, this type of motion is observed not only in the protein sample but also in the tripeptide and single amino acid solid samples. The comparison of data measured in these three samples at different temperatures led us to conclude that this slow motion is, in fact, ultrasonic phonons, which seem to be inherent to all rigid biological solids. [ABSTRACT FROM AUTHOR]

In a companion paper, we put forth a thermodynamic model for complex formation via a chemical reaction involving multiple macromolecular species, which may subsequently undergo liquid–liquid phase separation and a further transition into a gel-like state. In the present work, we formulate a thermodynamically consistent kinetic framework to study the interplay between phase separation, chemical reaction, and aging in spatially inhomogeneous macromolecular mixtures. A numerical algorithm is also proposed to simulate domain growth from collisions of liquid and gel domains via passive Brownian motion in both two and three spatial dimensions. Our results show that the coarsening behavior is significantly influenced by the degree of gelation and Brownian motion. The presence of a gel phase inside condensates strongly limits the diffusive transport processes, and Brownian motion coalescence controls the coarsening process in systems with high area/volume fractions of gel-like condensates, leading to the formation of interconnected domains with atypical domain growth rates controlled by size-dependent translational and rotational diffusivities. [ABSTRACT FROM AUTHOR]

Instanton theory relates the rate constant for tunneling through a barrier to the periodic classical trajectory on the upturned potential energy surface, whose period is τ = ℏ/(kBT). Unfortunately, the standard theory is only applicable below the "crossover temperature," where the periodic orbit first appears. This paper presents a rigorous semiclassical (ℏ → 0) theory for the rate that is valid at any temperature. The theory is derived by combining Bleistein's method for generating uniform asymptotic expansions with a real-time modification of Richardson's flux-correlation function derivation of instanton theory. The resulting theory smoothly connects the instanton result at low temperature to the parabolic correction to Eyring transition state theory at high-temperature. Although the derivation involves real time, the final theory only involves imaginary-time (thermal) properties, consistent with the standard version of instanton theory. Therefore, it is no more difficult to compute than the standard theory. The theory is illustrated with application to model systems, where it is shown to give excellent numerical results. Finally, the first-principles approach taken here results in a number of advantages over previous attempts to extend the imaginary free-energy formulation of instanton theory. In addition to producing a theory that is a smooth (continuously differentiable) function of temperature, the derivation also naturally incorporates hyperasymptotic (i.e., multi-orbit) terms and provides a framework for further extensions of the theory. [ABSTRACT FROM AUTHOR]

This paper presents a mean field theory of electrolyte solutions, extending the classical Debye–Hückel–Onsager theory to provide a detailed description of the electrical conductivity in strong electrolyte solutions. The theory systematically incorporates the effects of ion specificity, such as steric interactions, hydration of ions, and their spatial charge distributions, into the mean-field framework. This allows for the calculation of ion mobility and electrical conductivity, while accounting for relaxation and hydrodynamic phenomena. At low concentrations, the model reproduces the well-known Kohlrausch's limiting law. Using the exponential (Slater-type) charge distribution function for solvated ions, we demonstrate that experimental data on the electrical conductivity of aqueous 1:1, 2:1, and 3:1 electrolyte solutions can be approximated over a broad concentration range by adjusting a single free parameter representing the spatial scale of the nonlocal ion charge distribution. Using the fitted value of this parameter at 298.15 K, we obtain good agreement with the available experimental data when calculating electrical conductivity across different temperatures. We also analyze the effects of temperature and electrolyte concentration on the relaxation and electrophoretic contributions to total electrical conductivity, explaining the underlying physical mechanisms responsible for the observed behavior. [ABSTRACT FROM AUTHOR]

Aqueous interfaces containing organic/inorganic molecules are important in various biological, industrial, and atmospheric processes. So far, the study on the dynamics of interfacial molecules has been carried out with time-resolved vibrational sum-frequency generation (TR-VSFG) and time-resolved electronic sum-frequency generation (TR-ESFG) techniques. Although the ESFG probe is powerful for investigating interfacial photochemical dynamics of solute molecules by monitoring the electronic transition of transients or photoproducts at the interface, heterodyne detection is highly desirable for obtaining straightforward information, particularly in time-resolved measurements. So far, heterodyne detection has been realized only for TR-VSFG measurements but not for TR-ESFG measurements. In this paper, we report on femtosecond time-resolved heterodyne-detected ESFG (TR-HD-ESFG) spectroscopy for the first time. With TR-HD-ESFG developed, we measured the time-resolved electronic ΔImχ(2) spectra (pump-induced changes in the imaginary part of the second-order susceptibility) of a prototype dye, malachite green (MG), at the air/water interface. The obtained ΔImχ(2) spectra clearly show not only the ground-state bleach but also the excited-state band of MG at the air/water interface, demonstrating the high potential of TR-HD-ESFG as a new powerful tool to investigate ultrafast reaction dynamics at the interface. [ABSTRACT FROM AUTHOR]

Signaling in cells is full of noise and, hence, described with stochastic biochemical models. Thus, an efficient computation algorithm for these fluctuating reactions is much needed. Apart from the very popular Monte Carlo simulation, methods based on probability distributions are frequently desired due to their analytical tractability and possible numerical advantages in diverse circumstances, among which the variational approach is the most notable. In this paper, new basis functions are proposed to better depict possibly complex distribution profiles, and an extra regularization scheme is supplied to the variational equation to remove occasional degeneracy-induced singularities during the evolution. The new extension is applied to four typical biochemical reaction models and restores the Gillespie results accurately but with greatly reduced simulation time. This modified variational approach is expected to work in a wide range of cell signaling networks. [ABSTRACT FROM AUTHOR]

In 2012, the molecular structure of a new, broad class of ice-binding proteins, classified as "domain of unknown function" (DUF) 3494, was described for the first time. These proteins have a common tertiary structure and are characterized by a very wide spectrum of antifreeze activity (from weakly active to hyperactive). The ice-binding surface (IBS) region of these molecules differs significantly in its structure from the IBS of previously known antifreeze proteins (AFPs), showing a complete lack of regularity and high hydrophilicity. The presence of a regular, repeating structural motif in the IBS region of hitherto known AFP molecules, combined with the hydrophobic nature of this surface, promotes the formation of an ice-like ordering of the solvation water layer and, as a result, facilitates the process of transformation of this water layer into ice. It is, therefore, surprising that the newly discovered DUF3494 class of proteins clearly breaks out of this characteristic. In this paper, using molecular dynamics simulations, we analyze the solvation water structure of the IBS region of both DUF3494 family molecules and AFPs. As we show, although the IBS of DUF3494 molecules does not form an ice-like water structure in the solvation layer, this is compensated by the formation of the equivalent of "anchored clathrate water," in the form of a relatively large number of water molecules bound to the surface of the protein molecule and providing potential binding sites for it to the ice surface. [ABSTRACT FROM AUTHOR]

The generalized quantum master equation (GQME) approach provides a powerful general-purpose framework for simulating the inherently quantum mechanical dynamics of a subset of electronic reduced density matrix elements of interest in complex molecular systems. Previous studies have found that combining the GQME approach with quasiclassical mapping Hamiltonian (QC/MH) methods can dramatically improve the accuracy of electronic populations obtained via those methods. In this paper, we perform a complimentary study of the advantages offered by the GQME approach for simulating the dynamics of electronic coherences, which play a central role in optical spectroscopy, quantum information science, and quantum technology. To this end, we focus on cases where the electronic coherences predicted for the spin-boson benchmark model by direct application of various QC/MH methods are inaccurate. We find that similar to the case of electronic populations, combining the QC/MH methods with the GQME approach can dramatically improve the accuracy of the electronic coherences obtained via those methods. We also provide a comprehensive analysis of how the performance of GQMEs depends on the choice of projection operator and electronic basis and show that the accuracy and feasibility of the GQME approach can benefit from casting the GQME in terms of the eigen-basis of the observable of interest. [ABSTRACT FROM AUTHOR]

ipie is a Python-based auxiliary-field quantum Monte Carlo (AFQMC) package that has undergone substantial improvements since its initial release [Malone et al., J. Chem. Theory Comput. 19(1), 109–121 (2023)]. This paper outlines the improved modularity and new capabilities implemented in ipie. We highlight the ease of incorporating different trial and walker types and the seamless integration of ipie with external libraries. We enable distributed Hamiltonian simulations of large systems that otherwise would not fit on a single central processing unit node or graphics processing unit (GPU) card. This development enabled us to compute the interaction energy of a benzene dimer with 84 electrons and 1512 orbitals with multi-GPUs. Using CUDA and cupy for NVIDIA GPUs, ipie supports GPU-accelerated multi-slater determinant trial wavefunctions [Huang et al. arXiv:2406.08314 (2024)] to enable efficient and highly accurate simulations of large-scale systems. This allows for near-exact ground state energies of multi-reference clusters, [Cu2O2]2+ and [Fe2S2(SCH3)4]2−. We also describe implementations of free projection AFQMC, finite temperature AFQMC, AFQMC for electron–phonon systems, and automatic differentiation in AFQMC for calculating physical properties. These advancements position ipie as a leading platform for AFQMC research in quantum chemistry, facilitating more complex and ambitious computational method development and their applications. [ABSTRACT FROM AUTHOR]

Transport and dispersion of active particles in structured environments, such as corrugated channels and porous media, are important for the understanding of both natural and engineered active systems. Owing to their continuous self-propulsion, active particles exhibit rectified transport under spatially asymmetric confinement. While progress has been made in experiments and particle-based simulations, a theoretical understanding of the effective long-time transport dynamics in spatially periodic geometries remains less developed. In this paper, we apply generalized Taylor dispersion theory to analyze the long-time effective transport dynamics of active Brownian particles (ABPs) in periodic channels and fields. We show that the long-time transport behavior is governed by an effective advection–diffusion equation. The derived macrotransport equations allow us to characterize the average drift and effective dispersion coefficient. For the case of ABPs subject to a no-flux boundary condition at the channel wall, we show that regardless of activity, the average drift is given by the net diffusive flux along the channel. For ABPs, their activity is the driving mechanism that sustains a density gradient, which ultimately leads to rectified motion along the channel. Our continuum theory is validated against direct Brownian dynamics simulations of the Langevin equations governing the motion of each ABP. [ABSTRACT FROM AUTHOR]

The transformative impact of modern computational paradigms and technologies, such as high-performance computing (HPC), quantum computing, and cloud computing, has opened up profound new opportunities for scientific simulations. Scalable computational chemistry is one beneficiary of this technological progress. The main focus of this paper is on the performance of various quantum chemical formulations, ranging from low-order methods to high-accuracy approaches, implemented in different computational chemistry packages and libraries, such as NWChem, NWChemEx, Scalable Predictive Methods for Excitations and Correlated Phenomena, ExaChem, and Fermi–Löwdin orbital self-interaction correction on Azure Quantum Elements, Microsoft's cloud services platform for scientific discovery. We pay particular attention to the intricate workflows for performing complex chemistry simulations, associated data curation, and mechanisms for accuracy assessment, which is demonstrated with the Arrows automated workflow for high throughput simulations. Finally, we provide a perspective on the role of cloud computing in supporting the mission of leadership computational facilities. [ABSTRACT FROM AUTHOR]

A central paradigm of polymer physics states that chains in melts behave like random walks as intra- and interchain interactions effectively cancel each other out. Likewise, θ-chains, i.e., chains at the transition from a swollen coil to a globular phase, are also thought to behave like ideal chains, as attractive forces are counterbalanced by repulsive entropic contributions. While the simple mapping to an equivalent Kuhn chain works rather well in most scenarios with corrections to scaling, random walks do not accurately capture the topology and knots, particularly for flexible chains. In this paper, we demonstrate with Monte Carlo and molecular dynamics simulations that chains in polymer melts and θ-chains not only agree on a structural level for a range of stiffnesses but also topologically. They exhibit similar knotting probabilities and knot sizes, both of which are not captured by ideal chain representations. This discrepancy comes from the suppression of small knots in real chains, which is strongest for very flexible chains because excluded volume effects are still active locally and become weaker with increasing semiflexibility. Our findings suggest that corrections to ideal behavior are indeed similar for the two scenarios of real chains and that the structure and topology of a chain in a melt can be approximately reproduced by a corresponding θ-chain. [ABSTRACT FROM AUTHOR]

This paper investigates the dynamic behavior of EthylChlorophyllide A (EChlideA) molecules in a methanol solution confined within a 4 nm silica nanoslit, using molecular dynamics simulations over a duration of 1 ms. Three systems, containing 1, 2, and 4 solutes, were studied at 298 K. The results demonstrate that EChlideA molecules predominantly adsorb onto the silica surfaces, driven by specific interactions between chlorin ring's methyl group and the hydroxyl groups of the silica. This adsorption leads to stable binding, particularly in less crowded environments, as indicated by the potential of mean force analysis. Higher molecular concentrations, such as those with four EChlideA molecules, introduce variation in binding strength due to molecular aggregation and complex interactions. The orientation analysis reveals that the chlorin ring tends to align parallel to the surface, requiring rotational adjustments during surface diffusion. In addition, solvent coordination around the Mg ion remains consistent under bulk conditions, although with some variation in higher concentrations. This study also highlights a decrease in linear diffusion and an increase in rotational relaxation times for EChlideA molecules within the confined nanoslit, reflecting the influence of molecular concentration and arrangement on their dynamics. These findings provide valuable insights into the role of surface interactions, molecular orientation, and solvent coordination in confined environments, offering implications for the design of nanoscale systems. [ABSTRACT FROM AUTHOR]

An important class of methods for modeling dynamics in open quantum systems is based on the well-known influence functional (IF) approach to solving path-integral equations of motion. Within this paradigm, path-filtering schemes based on the removal of IF elements that fall below a certain threshold aim to reduce the effort needed to calculate and store the influence functional, making very challenging simulations possible. A filtering protocol of this type is considered acceptable as long as the simulation remains mathematically stable. This, however, does not guarantee that the approximated dynamics preserve the physics of the simulated process. In this paper, we explore the possibility of training Generative Flow Networks (GFlowNets) to produce filtering protocols while optimizing for mathematical stability and for physical accuracy. Trained using the trajectory balance objective, the model produces sets of paths to be added to a truncated initial set; it is rewarded if the combined set of paths gives rise to solutions in which the trace of the density matrix is conserved, the populations remain real, and the dynamics approach the exact reference. Using a simple two-level system coupled to a dissipative reservoir, we perform proof-of-concept simulations and demonstrate the elegant and surprising filtering solutions proposed by the GFlowNet. [ABSTRACT FROM AUTHOR]

Action spectroscopies use a readout created by the action of light on the molecules or material rather than optical absorption. Ultrafast 2D photocurrent and 2D fluorescence spectroscopies are two such action spectroscopies. Despite their utility, multidimensional action spectroscopies suffer from a background created by incoherent population mixing. These backgrounds appear when the action of one molecule impacts that of another, creating a signal that mimics a fourth-order population response but is really just the convolution of two linear responses. The background created by incoherent mixing is often much larger than the desired foreground signals. In this paper, we describe the physical mechanisms that give rise to the incoherent signals, drawing Feynman paths for each. There are three variations of incoherent signals, differing by their pulse ordering. They all have the same phase dependence as the desired fourth-order population signals and so cannot be removed by standard phase cycling, but they do differ in their polarization responses and dephasing times. We propose, and implement, a spectrometer design that eliminates the background signals for isotropically oriented samples, leaving only the desired fourth-order 2D action spectra. Our spectrometer utilizes a TWINS interferometer and a pulse shaper interferometer, each driven with a different white-light source so that the pulse pairs within each interferometer are phase stable, but not between the two. The lack of phase stability between the two interferometers eliminates two of the three incoherent responses. The third incoherent response is eliminated with the polarization scheme ⟨0, π/2, π/4, π/4⟩. Our spectrometer also enables both 2D photocurrent and 2D white-light spectra to be collected simultaneously, thereby enabling a direct comparison between action and optical detection under identical conditions and at the exact same position on the sample. Using this spectrometer and photovoltaic devices made from thin films of semiconducting carbon nanotubes, we demonstrate 2D photocurrent spectra free of incoherent background. [ABSTRACT FROM AUTHOR]

The first-principles quantum chemical computations often scale as Nk (N = basis sets; k = 1–4 for linear scaling, Hartree–Fock or density functional theory methods), which makes the development of accurate pseudopotentials and efficient basis sets necessary ingredients in modeling of heavy elements such as lanthanides and actinides. Recently, we have developed 4f-in-core norm-conserving pseudopotentials and associated basis sets for the trivalent lanthanides [Lu et al., J. Chem. Theory Comput. 19, 82–96 (2023)]. In the present paper, we present a unified approach to optimize high-quality Gaussian basis sets for modeling and simulations of condensed-phase systems. The newly generated basis sets not only capture the low total energy and fairly reasonable condition number of overlap matrix of lanthanide-containing systems, but also exhibit good transferability and reproducibility. These advantages ensure the accuracy of the basis sets while avoiding linear dependency concern of atom-centered basis sets. The performance of the basis sets is further illustrated in lanthanide molecular and condensed-phase systems by using Gaussian-plane wave density functional approach of CP2K. These new basis sets can be of particular interest to model structurally complicated lanthanide molecules, clusters, solutions, and solid systems. [ABSTRACT FROM AUTHOR]

The homogeneous electron gas is a system that has many applications in chemistry and physics. However, its infinite nature makes studies at the many-body level complicated due to long computational run times. Because it is size extensive, coupled cluster theory is capable of studying the homogeneous electron gas, but it still poses a large computational challenge as the time needed for precise calculations increases in a polynomial manner with the number of particles and single-particle states. Consequently, achieving convergence in energy calculations becomes challenging, if not prohibited, due to long computational run times and high computational resource requirements. This paper develops the sequential regression extrapolation (SRE) to predict the coupled cluster energies of the homogeneous electron gas in the complete basis limit using Bayesian ridge regression and many-body perturbation theory correlation energies to the second order to make predictions from calculations at truncated basis sizes. Using the SRE method, we were able to predict the coupled cluster double energies for the electron gas across a variety of values of N and rs, for a total of 70 predictions, with an average error of 5.20 × 10−4 hartree while saving 88.9 h of computational time. The SRE method can accurately extrapolate electron gas energies to the complete basis limit, saving both computational time and resources. Additionally, the SRE is a general method that can be applied to a variety of systems, many-body methods, and extrapolations. [ABSTRACT FROM AUTHOR]

The Atomic, Molecular, and Optical Science (AMOS) Gateway is a comprehensive cyberinfrastructure for research and educational activities in computational AMO science. The B-Spline atomic R-Matrix (BSR) suite of programs is one of several computer programs currently available on the gateway. It is an excellent example of the gateway's potential to increase the scientific productivity of AMOS users. While the suite is available to be used in batch mode, its complexity does not make it well-suited to the approach taken in the gateway's default setup. The complexity originates from the need to execute many different computations and to construct generally complex workflows, requiring numerous input files that must be used in a specific sequence. The BSR graphical user interface described in this paper was developed to considerably simplify employing the BSR codes on the gateway, making BSR available to a large group of researchers and students interested in AMO science. [ABSTRACT FROM AUTHOR]

In molecular physics, it is often necessary to average over the orientation of molecules when calculating observables, in particular when modeling experiments in the liquid or gas phase. Evaluated in terms of Euler angles, this is closely related to integration over two- or three-dimensional unit spheres, a common problem discussed in numerical analysis. The computational cost of the integration depends significantly on the quadrature method, making the selection of an appropriate method crucial for the feasibility of simulations. After reviewing several classes of spherical quadrature methods in terms of their efficiency and error distribution, we derive guidelines for choosing the best quadrature method for orientation averages and illustrate these with three examples from chiral molecule physics. While Gauss quadratures allow for achieving numerically exact integration for a wide range of applications, other methods offer advantages in specific circumstances. Our guidelines can also be applied to higher-dimensional spherical domains and other geometries. We also present a Python package providing a flexible interface to a variety of quadrature methods. [ABSTRACT FROM AUTHOR]

In a well-known paper, Jeremy England derived a bound on the free energy dissipated by a self-replicating system [J. L. England, "Statistical physics of self-replication," J. Chem. Phys. 139, 121923 (2013)]. This bound is usually interpreted as a universal relationship that connects thermodynamic dissipation to replicator per-capita decay and growth rates. We argue from basic thermodynamic principles against this interpretation. In fact, we suggest that such a relationship cannot exist in principle, because it is impossible for a thermodynamically consistent replicator to undergo both per-capita growth and per-capita decay back into reactants. Instead, replicator may decay into separate waste products, but in that case, replication and decay are two independent physical processes, and there is no universal relationship that connects their thermodynamic and dynamical properties. [ABSTRACT FROM AUTHOR]

Designing coatings and films that can protect surfaces is important in a wide variety of applications from corrosion prevention to anti-fouling. These systems are challenging from a modeling perspective because they are invariably multicomponent, which quickly leads to an expansive design space. At a minimum, the system has a substrate, a film (often composed of a polymeric material), a ubiquitous carrier solvent, which may be either a vapor or liquid phase, and one or more contaminants. Each component has an impact on the effectiveness of coating. This paper focuses on films that are used as a barrier to surface contamination, but the results also extend to surface coatings that are designed to extract a low density species from the fluid phase as in liquid chromatography. A coarse-grained model is developed using Yukawa potentials that encompasses both repulsive and attractive interactions among the species. Classical density functional theory calculations are presented to show how contaminant adsorption is controlled by the molecular forces in the system. Two specific vectors through the parameter space are considered to address likely experimental manipulations that change either the solvent or the polymer in a system. We find that all the adsorption results can be unified by considering an appropriate combination of molecular parameters. As a result, these calculations provide a link between molecular interactions and film performance and may serve to guide the rational design of films. [ABSTRACT FROM AUTHOR]

Heterojunction catalysts in the field of hydrogen evolution reaction (HER) from electrocatalytic water splitting have recently become a hot research topic. In this paper, we systematically calculated the HER catalytic performance of a MoS2/CoS2 heterojunction for the first time, considering the effect of edge sites regulation, strain and electric field. The results indicate that the MoS2/CoS2 heterojunction exhibits synergistic catalytic performance compared to MoS2 and CoS2, the HER catalytic activity of which can be improved by exposing more edge sites or regulating the S content on the edges, with an optimized ratio of 25%. Surprisingly, applying strain has a slight effect on the catalytic activity of the edge, however, an obvious effect on the basal plane. For example, applying 2% tensile strain on the MoS2/CoS2 heterojunction can improve the edge catalytic performance by 13%, and for the basal plane, this value can reach 92%. In this case, the catalytic performance of the basal plane is better than that of the edge with 2% and without strain. Since the basal plane accounts for the majority of the two-dimensional catalysts, the catalytic performance of the basal plane is generally much lower than that of the edge. This discovery is of great significance, which means by adjusting strain, the catalytic performance of the heterojunction catalyst is likely to be improved by orders of magnitude. Moreover, considering the actual experimental process, we also calculated the effect of the electric field and found that 0.7 V/Å electric field can enhance the HER catalytic activity of the MoS2/CoS2 heterojunction by 23%. [ABSTRACT FROM AUTHOR]

The calculation of molecular excited states is critically important to decipher a plethora of molecular properties. In this paper, we develop an equation of motion formalism on top of a bi-exponentially parameterized ground state wavefunction toward the determination of excited states. While the ground state bi-exponential parameterization ensures an accurate description of the wavefunction through the inclusion of high-rank correlation effects, the excited state is parameterized by a novel linear response operator with an effective excitation rank beyond two. To treat the ground and excited states in the same footings, in addition to the conventional one- and two-body response operators, we introduced certain two-body "generalized" response operators with an effective excitation rank of one. We introduce a projective formulation for determining the perturbed amplitudes for the set of "generalized" operators. Our formulation entails a significantly small number of unknown parameters and is shown to be highly accurate compared to allied methods for several difficult chemical systems. [ABSTRACT FROM AUTHOR]

Liquid–liquid phase transitions hold a unique and profound significance within condensed matter physics. These transitions, while conceptually intriguing, often pose formidable computational challenges. However, recent advances in neural network (NN) potentials offer a promising avenue to effectively address these challenges. In this paper, we delve into the structural transitions of liquid CdTe, CdS, and their alloy systems using molecular dynamics simulations, harnessing the power of an NN potential named LaspNN. Our investigations encompass both pressure and temperature effects. Through our simulations, we uncover three primary liquid structures around melting points that emerge as pressure increases: tetrahedral, rock salt, and close-packed structures, which greatly resemble those of solid states. In the high-temperature regime, we observe the formation of Te chains and S dimers, providing a deeper understanding of the liquid's atomic arrangements. When examining CdSxTe1−x alloys, our findings indicate that a small substitution of S by Te atoms for S-rich alloys (x > 0.5) exhibits a structural transition much different from CdS, while a large substitution of Te by S atoms for Te-rich alloys (x < 0.5) barely exhibits a structural transition similar to CdTe. We construct a schematic diagram for liquid alloys that considers both temperature and pressure, providing a comprehensive overview of the alloy system's behavior. The local aggregation of Te atoms demonstrates a linear relationship with alloy composition x, whereas that of S atoms exhibits a nonlinear one, shedding light on the composition-dependent structural changes. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the Feshbach resonances of high partial waves and the influence of spin–spin (S–S) interaction on ultracold scattering processes. Taking the N a 23 - R b 87 system as an example, we plot the variations of weakly bound state energy and elastic scattering cross section with magnetic field and with collision energy. We find that the number of splittings in high partial wave Feshbach resonances does not strictly conform to the expected l + 1 (l is rotational angular momentum), and the deviation is attributed to the influence of bound states in other channels coupled by S–S interaction. For different ml (the projection of l on the external magnetic field direction), the effects of S–S interaction lead to different scattering patterns in the incident channels. These results reveal the complex features of ultracold scattering processes in high partial waves caused by S–S interaction. [ABSTRACT FROM AUTHOR]

Strong light–matter coupling within an optical cavity leverages the collective interactions of molecules and confined electromagnetic fields, giving rise to the possibilities of modifying chemical reactivity and molecular properties. While collective optical responses, such as enhanced Rabi splitting, are often observed, the overall effect of the cavity on molecular systems remains ambiguous for a large number of molecules. In this paper, we investigate the non-adiabatic electron transfer process in electron donor–acceptor pairs influenced by collective excitation and local molecular dynamics. Using the timescale difference between reorganization and thermal fluctuations, we derive analytical formulas for the electron transfer rate constant and the polariton relaxation rate. These formulas apply to any number of molecules (N) and account for the collective effect as induced by cavity photon coupling. Our findings reveal a non-monotonic dependence of the rate constant on N, which can be understood by the interplay between electron transfer and polariton relaxation. As a result, the cavity-induced quantum yield increases linearly with N for small N (as predicted by a simple Dicke model) but shows a turnover and suppression for large N. We also interrelate the thermal bath frequency and the number of molecules, suggesting the optimal number for maximizing enhancement. The analysis provides an analytical insight for understanding the collective excitation of light and electron transfer, helping to predict the optimal condition for effective cavity-controlled chemical reactivity. [ABSTRACT FROM AUTHOR]

Understanding how external electric fields (EFs) impact the properties of aqueous molecules is crucial for various applications in chemistry, biology, and engineering. In this paper, we present a study utilizing molecular dynamics simulation to explore how direct-current (DC) and alternative-current (AC) EFs affect hydrophobic (n-triacontane) and hydrophilic (PEG-10) oligomer chains. Through a machine learning approach, we extract a 2-dimensional free energy (FE) landscape of these molecules, revealing that electric fields modulate the FE landscape to favor stretched configurations and enhance the alignment of the chain with the electric field. Our observations indicate that DC EFs have a more prominent impact on modulation compared to AC EFs and that EFs have a stronger effect on hydrophobic chains than on hydrophilic oligomers. We analyze the orientation of water dipole moments and hydrogen bonds, finding that EFs align water molecules and induce more directional hydrogen bond networks, forming 1D water structures. This favors the stretched configuration and alignment of the studied oligomers simultaneously, as it minimizes the disruption of 1D structures. This research deepens our understanding of the mechanisms by which electric fields modulate molecular properties and could guide the broader application of EFs to control other aqueous molecules, such as proteins or biomolecules. [ABSTRACT FROM AUTHOR]

This second paper in a series of two describes the chirped-pulse ice apparatus that permits the detection of buffer gas cooled molecules desorbed from an energetically processed ice using broadband mm-wave rotational spectroscopy. Here, we detail the lower ice stage developed to generate ices at 4 K, which can then undergo energetic processing via UV/VUV photons or high-energy electrons and which ultimately enter the gas phase via temperature-programmed desorption (TPD). Over the course of TPD, the lower ice stage is interfaced with a buffer gas cooling cell that allows for sensitive detection via chirped-pulse rotational spectroscopy in the 60–90 GHz regime. In addition to a detailed description of the ice component of this apparatus, we show proof-of-principle experiments demonstrating the detection of H2CO products formed through irradiation of neat methanol ices or 1:1 CO + CH4 mixed ices. [ABSTRACT FROM AUTHOR]

The high resolution Rydberg absorption spectrum of 2-butyne C4H6 recorded previously at the SOLEIL synchrotron facility has been interpreted using multichannel quantum defect theory (MQDT). The calculations are based on the continuum scattering calculations of Xu et al., J. Chem. Phys. 136, 154303 (2012) and of Jacovella et al., J. Phys. Chem. A 119, 12339 (2015) pertaining to the dipole-allowed excited state symmetries in absorption from the ground state. In contrast to the traditional approach of calculating low-lying electronic states first and then attempting to extend the calculations to ever higher energy, here the analysis proceeds through the extension of these detailed calculations of the electronic continuum scattering down into the discrete region of the spectrum. The continuum reaction matrices and dipole transition moments are adapted to the discrete Rydberg region via the use of an energy-modified formulation of MQDT theory and associated energy dependences of the quantum defects. The analysis reproduces more than 40 Rydberg states from n ≈ 10 down to the 3d and 4s levels with an rms error of better than 20 cm−1. These belong to five Rydberg series with three different molecular symmetries. While the approach predicts many additional series, most of these are calculated and observed to carry only little oscillator strength. The analysis shows that the Rydberg spectrum is dominated by the excitation of an e″ symmetry electron of fδ and gπ type, in line with what previous studies of the above-threshold shape resonance of 2-butyne have shown. The present study is intended to serve as an example showing how first principles continuum calculations may be useful for the interpretation of highly bound discrete states in a range that poses problems for the standard ab initio techniques. The quantitative treatment of the dipole absorption cross sections is deferred to a future paper. [ABSTRACT FROM AUTHOR]

Biphasic interfaces are complex but fascinating regimes that display a number of properties distinct from those of the bulk. The CO2–H2O interface, in particular, has been the subject of a number of studies on account of its importance for the carbon life cycle as well as carbon capture and sequestration schemes. Despite this attention, there remain a number of open questions on the nature of the CO2–H2O interface, particularly concerning the interfacial tension and phase behavior of CO2 at the interface. In this paper, we seek to address these ambiguities using ab initio-quality simulations. Harnessing the benefits of machine-learned potentials and enhanced statistical sampling methods, we present an ab initio-level description of the CO2–H2O interface. Interfacial tensions are predicted from 1 to 500 bars and found to be in close agreement with experiment at pressures for which experimental data are available. Structural analyses indicate the buildup of an adsorbed, saturated CO2 film forming at a low pressure (20 bars) with properties similar to those of the bulk liquid, but preferential perpendicular alignment with respect to the interface. The CO2 monolayer buildup coincides with a reduced structuring of water molecules close to the interface. This study highlights the predictive nature of machine-learned potentials for complex macroscopic properties of biphasic interfaces, and the mechanistic insight obtained into carbon dioxide aggregation at the water interface is of high relevance for geoscience, climate research, and materials science. [ABSTRACT FROM AUTHOR]