Long-range Potential Research Articles

Early time wetting kinetics in surface-directed spinodal decomposition for off-critical quenches: A molecular dynamics study.

We present results from the molecular dynamics simulation of surface-directed spinodal decomposition in binary fluid mixtures (A + B) with off-critical compositions. The aim is to elucidate the role of composition ratio in the early time wetting kinetics under the influence of long-range surface potential. In our simulations, the attractive part of surface potential varies as V(z) = -ϵa/zn, with ϵa being the surface-potential strength. The surface prefers the "A" species to form the wetting layer. Its thickness [R1(t)] for the majority wetting (number of A-type particles [NA] > number of B-type particles [NB]) grows as a power-law with an exponent of 1/(n + 2). This is consistent with the early time kinetics in the form of potential-dependent growth present in the Puri-Binder model. However, for minority wetting (NA < NB), the growth exponent in R1(t) is less than 1/(n + 2). Furthermore, on decreasing the field strength ϵa, we recover 1/(n + 2) for a minority wetting case. We provide phenomenological arguments to explain the early time wetting kinetics for both cases.

Engineering band structures of two-dimensional materials with remote moiré ferroelectricity.

The stacking order and twist angle provide abundant opportunities for engineering band structures of two-dimensional materials, including the formation of moiré bands, flat bands, and topologically nontrivial bands. The inversion symmetry breaking in rhombohedral-stacked transitional metal dichalcogenides endows them with an interfacial ferroelectricity associated with an out-of-plane electric polarization. By utilizing twist angle as a knob to construct rhombohedral-stacked transitional metal dichalcogenides, antiferroelectric domain networks with alternating out-of-plane polarization can be generated. Here, we demonstrate that such spatially periodic ferroelectric polarizations in parallel-stacked twisted WSe2 can imprint their moiré potential onto a remote bilayer graphene. This remote moiré potential gives rise to pronounced satellite resistance peaks besides the charge-neutrality point in graphene, which are tunable by the twist angle of WSe2. Our observations of ferroelectric hysteresis at finite displacement fields suggest the moiré is delivered by a long-range electrostatic potential. The constructed superlattices by moiré ferroelectricity represent a highly flexible approach, as they involve the separation of the moiré construction layer from the electronic transport layer. This remote moiré is identified as a weak potential and can coexist with conventional moiré. Our results offer a comprehensive strategy for engineering band structures and properties of two-dimensional materials by utilizing moiré ferroelectricity.

Range Separation of the Interaction Potential in Intermolecular and Intramolecular Symmetry-Adapted Perturbation Theory.

Symmetry-adapted perturbation theory (SAPT) is a popular and versatile tool to compute and decompose noncovalent interaction energies between molecules. The intramolecular SAPT (ISAPT) variant provides a similar energy decomposition between two nonbonded fragments of the same molecule, covalently connected by a third fragment. In this work, we explore an alternative approach where the noncovalent interaction is singled out by a range separation of the Coulomb potential. We investigate two common splittings of the 1/r potential into long-range and short-range parts based on the Gaussian and error functions, and approximate either the entire intermolecular/interfragment interaction or only its attractive terms by the long-range contribution. These range separation schemes are tested for a number of intermolecular and intramolecular complexes. We find that the energy corrections from range-separated SAPT or ISAPT are in reasonable agreement with complete SAPT/ISAPT data. This result should be contrasted with the inability of the long-range multipole expansion to describe crucial short-range charge penetration and exchange effects; it shows that the long-range interaction potential does not just recover the asymptotic interaction energy but also provides a useful account of short-range terms. The best consistency is attained for the error-function separation applied to all interaction terms, both attractive and repulsive. This study is the first step toward a fragmentation-free decomposition of intramolecular nonbonded energy.

Molecular dynamics of liquid-electrode interface by integrating Coulomb interaction into universal neural network potential.

Computational understanding of the liquid-electrode interface faces challenges in efficiently incorporating reactive force fields and electrostatic potentials within reasonable computational costs. Although universal neural network potentials (UNNPs), representing pretrained machine learning interatomic potentials, are emerging, current UNNP models lack explicit treatment of Coulomb potentials, and methods for integrating additional charges on the electrode remain to be established. We propose a method to analyze liquid-electrode interfaces by integrating a UNNP, known as the preferred potential, with Coulomb potentials using the ONIOM method. This approach extends the applicability of UNNPs to electrode-liquid interface systems. Through molecular dynamics simulations of graphene-water and graphene oxide (GO)-water interfaces, we demonstrate the effectiveness of our method. Our findings emphasize the necessity of incorporating long-range Coulomb potentials into the water potential to accurately describe water polarization at the interface. Furthermore, we observe that functional groups on the GO electrode influence both polarization and capacitance.

Tibetan lake sediment records reveal historical emission and long-range atmospheric transport of chlorinated paraffins

The Tibetan Plateau, a recognized global sink for Persistent Organic Pollutants (POPs), lies adjacent to two major emitting regions, inland China and India. This unique geographical setting makes it a pivotal site for examining the presence and compositional evolution of POPs following their long-range atmospheric transport (LRAT). This study focuses on the current predominant POPs, chlorinated paraffins (CPs). We comprehensively screened 675 homologues of the very short- (vSCCPs), short- (SCCPs), medium- (MCCPs), and long-chain CPs (LCCPs) in six dated sediment cores across the extensive Tibetan area. The findings unveiled pronounced temporal disparities in CP concentrations and compositions between Tibet's southern and eastern sectors, reflecting divergent usage and emission chronicles of inland China and India. Notably, a market shift in China from regulated SCCPs to the in-use MCCPs and LCCPs was observed in the 21st century, contrasting with India's unregulated production of SCCPs. The Organization for Economic Cooperation and Development (OECD) Screening Tool, developed to assess the overall persistence (POV) and long-range transport potential (LRTP) of organic chemicals, elucidated the erosion of CP source signatures induced by fractionation, a process that intensifies with transport distance from the source regions. This study enhances our understanding of the emission inventories and LRAT behavior of these transitional regulatory contaminants, highlighting the Tibetan Plateau's crucial role as an environmental sentinel in global pollution dynamics.

Self-Assembly of Model Three- and Four-Patch Colloidal Particles in Two Dimensions.

A coarse-grained effective solvent model of two-patch particles is extended to study the self-assembly of three- and four-patch particles to two-dimensional honeycomb and square lattices, respectively. Employing this model, grand canonical ensemble simulations are done to calculate vapor-liquid equilibria and the critical temperatures for patchy particles of various patch widths. The range of stability of the liquid, although very limited compared to isotropic particles, which interact through a longer-range potential, depends on the patch width and on the number of patches. Biased sampling and unbiased simulations are also done to investigate the mechanism of nucleation and crystal growth for honeycomb and square lattices, self-assembled from three- and four-patch particles, respectively. A two-step mechanism governs the nucleation of both lattices. In the first step, the particles form a dense amorphous network, and in the second step, the particles inside the amorphous network reorient to form crystalline nuclei. Barrier heights for the nucleation of honeycomb and square lattices are 7.8 kBT and 7.4 kBT, which are close to the reported values for the nucleation of the kagome lattice. In agreement with confocal microscopy experiments, the self-assembly in a honeycomb lattice involves the formation of 5- to 7-membered rings. The 5- and 7-membered rings hamper the nucleation of the honeycomb lattice, through defect formation and rotation of the symmetry planes of crystals that form at their surfaces. With the progress of self-assembly, a substantial amount of restructuring of the defects and crystals in their vicinity is needed to heal the defects.

Suspect and non-target screening of chemicals of emerging Arctic concern in biota, air and human serum

Contaminants of emerging concern receive increasing attention in the Arctic environment. The aim of this study was to screen for chemicals of emerging Arctic concern (CEACs) in different types of Arctic samples including biota, air and human serum. We used a combination of gas chromatography (GC) and liquid chromatography (LC) with high resolution mass spectrometry (HRMS) for suspect and non-target screening (NTS). Suspect screening of 25 CEACs was based on published in-silico approaches for the identification of CEACs and revealed tetrabromophthalic anhydride (TBPA) in pilot whale and air, albeit with low detection frequencies (17 and 33%, respectively). An NTS workflow detected 49, 42, 31 and 30 compounds in pilot whale, ringed seal, air, and human serum, respectively, at confidence level 2 and 3. Although legacy POPs still dominated the samples, 64 CEACs were tentatively identified and further assessed for persistence (P), bioaccumulation (B), mobility (M), toxicity (T), and long-range transport potential (LRTP). While four PBT compounds were identified, 37 PMT substances dominated among these 64 compounds. Our study indicated that many chemicals of potential risk might be present in Arctic samples and would benefit from confirmation and further studies of their transport to and accumulation in the Arctic environment.

Fast, approximation-free molecular simulation of the SPC/Fw water model using non-reversible Markov chains

In a world made of atoms, computer simulations of molecular systems such as proteins in water play an enormous role in science. Software packages for molecular simulation have been developed for decades. They all discretize Hamilton’s equations of motion and treat long-range potentials through cutoffs or discretization of reciprocal space. This introduces severe approximations and artifacts that must be controlled algorithmically. Here, we bring to fruition a paradigm for molecular simulation that relies on modern concepts in statistics to explore the thermodynamic equilibrium with an exact and efficient non-reversible Markov process. It is free of all discretizations, approximations, and cutoffs. We explicitly demonstrate that this approach reaches a break-even point with traditional molecular simulation performed at high precision, but without any of its approximations. We stress the potential of our paradigm for crucial applications in biophysics and other fields, and as a practical approach to molecular simulation. We set out a strategy to reach our goal of rigorous molecular simulation.

Developing a Differentiable Long-Range Force Field for Proteins with E(3) Neural Network-Predicted Asymptotic Parameters.

Accurately describing long-range interactions is a significant challenge in molecular dynamics (MD) simulations of proteins. High-quality long-range potential is also an important component of the range-separated machine learning force field. This study introduces a comprehensive asymptotic parameter database encompassing atomic multipole moments, polarizabilities, and dispersion coefficients. Leveraging active learning, our database comprehensively represents protein fragments with up to 8 heavy atoms, capturing their conformational diversity with merely 78,000 data points. Additionally, the E(3) neural network (E3NN) is employed to predict the asymptotic parameters directly from the local geometry. The E3NN models demonstrate exceptional accuracy and transferability across all asymptotic parameters, achieving an R2 of 0.999 for both protein fragments and 20 amino acid dipeptide test sets. The long-range electrostatic and dispersion energies can be obtained using the E3NN-predicted parameters, with an error of 0.07 and 0.02 kcal/mol, respectively, when compared to symmetry-adapted perturbation theory (SAPT). Therefore, our force fields demonstrate the capability to accurately describe long-range interactions in proteins, paving the way for next-generation protein force fields.

Efficient circular Dyson Brownian motion algorithm

Circular Dyson Brownian motion describes the Brownian dynamics of particles on a circle (periodic boundary conditions), interacting through a logarithmic, long-range two-body potential. Within the log-gas picture of random matrix theory, it describes the level dynamics of unitary (“circular”) matrices. A common scenario is that one wants to know about an initial configuration evolved over a certain interval of time, without being interested in the intermediate dynamics. Numerical evaluation of this is computationally expensive as the time-evolution algorithm is accurate only on short time intervals because of an underlying perturbative approximation. This work proposes an efficient and easy-to-implement improved circular Dyson Brownian motion algorithm for the unitary class (Dyson index β=2, physically corresponding to broken time-reversal symmetry). The algorithm allows one to study time evolution over arbitrarily large intervals of time at a fixed computational cost, with no approximations being involved. Published by the American Physical Society 2024

Limiting absorption principle and radiation conditions for Schrödinger operators with long-range potentials

We show Rellich's theorem, the limiting absorption principle, and a Sommerfeld uniqueness result for a wide class of one-body Schrödinger operators with long-range potentials, extending and refining previously known results. Our general method is based on elementary commutator estimates, largely following the scheme developed recently by Ito and Skibsted.

Pressure of Coulomb systems with volume-dependent long-range potentials

In this work, we consider the pressure of Coulomb systems, in which particles interact via a volume-dependent potential (in particular, the Ewald potential and its angular-averaged version (Demyanov and Levashov 2022 J. Phys. A: Math. Theor. 55 385202)). We confirm that the expression for the virial pressure should be corrected in this case. We show that the corrected virial pressure coincides with the formula obtained by differentiation of free energy if the potential energy is a homogeneous function of particle coordinates and a cell length. As a consequence, we find out that the expression for the pressure in the recent paper by Liang et al (2022 J. Chem. Phys. 157 144102) is incorrect.

Predicting fundamental gaps accurately from density functional theory with non-empirical local range separation.

We present an exchange-correlation approximation in which the Coulomb interaction is split into long- and short-range components and the range separation is determined by a non-empirical density functional. The functional respects important constraints, such as the homogeneous and slowly varying density limits, leads to the correct long-range potential, and eliminates one-electron self-interaction. Our approach is designed for spectroscopic purposes and closely approximates the piecewise linearity of the energy as a function of the particle number. The functional's accuracy for predicting the fundamental gap in generalized Kohn-Sham theory is demonstrated for a large number of systems, including organic semiconductors with a notoriously difficult electronic structure.

Spectral properties of Schrödinger operators with locally $H^{-1}$ potentials

We study half-line Schrödinger operators with locally H^{-1} potentials. In the first part, we focus on a general spectral theoretic framework for such operators, including a Last–Simon-type description of the absolutely continuous spectrum and sufficient conditions for different spectral types. In the second part, we focus on potentials which are decaying in a local H^{-1} sense; we establish a spectral transition between short-range and long-range potentials and an \ell^{2} spectral transition for sparse singular potentials. The regularization procedure used to handle distributional potentials is also well suited for controlling rapid oscillations in the potential; thus, even within the class of smooth potentials, our results apply in situations which would not classically be considered decaying or even bounded.

Electron scattering beyond the independent atom model: Quantum fluctuation of the Coulomb potential.

In the past century, electron scattering has mostly served as a powerful tool to measure the microscopic structure of gases, liquids, and solids in either a static or time-resolved manner. One common basis for these works is the independent atom model, which directly relates electron scattering signals to the atomic structure of matter. In this perspective, we explore the information content of electron scattering that goes beyond the independent atom model. We show that the small-angle limit of the electron scattering signal encodes the quantum mechanical fluctuation of the long-range Coulomb potential. This quantum fluctuation, described by the second moment of the dipole operator, is the root cause of the intermolecular van der Waals forces.

Construction of Multiscale Dissipative Particle Dynamics (DPD) Models from Other Coarse-Grained Models.

We present a general scheme for converting coarse-grained models into Dissipative Particle Dynamics (DPD) models. We build the corresponding DPD models by analogy with the de novo DPD coarse-graining scheme suggested by Groot and Warren (J. Chem. Phys., 1997). Electrostatic interactions between charged DPD particles are represented though the addition of a long-range Slater Coulomb potential as suggested by González-Melchor et al. (J. Chem. Phys., 2006). The construction is illustrated by converting MARTINI models for various proteins into a DPD representation, but it not restricted to the usual potential form in the MARTINI model-viz., Lennard-Jones potentials. We further extended the DPD scheme away from the typical use of homogeneous particle sizes, therefore faithfully representing the variations in the particle sizes seen in the underlying MARTINI model. The accuracy of the resulting construction of our generalized DPD models with respect to several structural observables has been benchmarked favorably against all-atom and MARTINI models for a selected set of peptides and proteins, and variations in the scales of the coarse-graining of the water solvent.

Virtual and bound states in low-energy positron scattering by atoms and molecules via modified effective range theory

Modified effective range theory is applied as a tool to determine bound and virtual state energies in low-energy positron elastic scattering by atoms and molecules. This is achieved by the S-matrix continuation into the complex momentum plane, allowing to identify poles related to shallow energy states. The influence of the long-range polarization potential (∼r −4) on the bound and virtual-state pole positions is analyzed for noble gases and nonpolar molecules such as H2, N2, and CH4. The quantitative relations between the S-matrix poles and the s-wave scattering length accounting for dipole polarization are introduced.

Sediment-seawater partitioning, bioaccumulation, and biomagnification of perfluorobutane sulfonamide in marine environment

Environmental occurrence of perfluorobutane sulfonamide (PFBSA) has only been recently discovered. The current knowledge regarding the occurrence and environmental behaviors of PFBSA in the marine environment is still relatively limited. In this study, PFBSA and other 37 poly- and perfluoroalkyl substances were analyzed in seawater (n = 43), sediment (n = 43), and marine fish (n = 176) samples collected from East China Sea and Antarctic Ocean. PFBSA was detected in > 90% of seawater from East China Sea and Antarctic Ocean, with the concentrations of 1.0 − 19 ng/L and < LOD−228 pg/L, respectively. The field-based mean log-transformed sediment-seawater partitioning coefficients of PFBSA were 1.6 ± 0.19 L/kg dw and 1.1 ± 0.19 L/kg dw in East China Sea and Antarctic Ocean, respectively, which are lower than that of perfluorooctanoate and perfluorooctane sulfonate. This indicates its long-range transport potential in global oceans with ocean currents. The mean log-transformed bioaccumulation factor values of PFBSA determined in the multiple species of whole-body marine fishes from East China Sea and Antarctic Ocean were 2.3 L/kg ww and 2.4 L/kg ww, respectively, which are comparable to that of perfluoroheptanoate (2.3 L/kg ww) in marine fishes from East China Sea. We did not observe an obvious biomagnification or biodilution of PFBSA along the marine food chain in East China Sea or Antarctic Ocean. This study provides the first data on the environmental behaviors of PFBSA in the marine environment.

Global trade-driven transfer of atmospheric polycyclic aromatic hydrocarbon emissions and associated human inhalation exposure risk

Polycyclic aromatic hydrocarbons (PAHs) are of significant public concern because of their toxicity and long-range transport potential. Extensive studies have been conducted to explore the source-receptor relationships of PAHs via atmospheric transport. However, the transfer of trade-driven regional and global PAHs is poorly understood. This study estimated the virtual PAHs emission transfer embodied in global trade from 2004 to 2014 and simulated the impact of international trade on global contamination and associated human inhalation exposure risk of PAHs. Results show that trade-driven PAHs flowed primarily from developed to less-developed regions, particularly in those regions with intensive heavy industries and transportation. As the result, international trade resulted in an increasing risk of lung cancer induced by exposure to PAHs (27.8% in China, 14.7% in India, and 11.3% in Southeast Asia). In contrast, we found decreasing risks of PAHs-induced lung cancer in Western Europe (63.2%) and the United States (45.9%) in 2004. Our findings indicate that final demand and emission intensity are the key driving factors contributing to rising and falling consumption-based PAHs emissions and related health risk respectively. The results could provide a useful reference for global collaboration in the reduction of PAHs pollution and related health risks.

Quantum-classical rate coefficient datasets of vibrational energy transfer in carbon monoxide based on highly accurate potential energy surface.

A merged potential energy surface (PES) is introduced for CO + CO collisions by combining a recent full-dimensional abinitio PES [Chen et al. J. Chem. Phys. 153, 054310 (2020)] and analytical long-range multipolar interactions. This merged PES offers a double advantage: it retains the precision of the abinitio PES in describing the van der Waals well and repulsive short range while providing an accurate physical description of long-range interaction; it significantly reduces the computational time required for trajectory integration since the long-range portion of the abinitio PES (involving numerous neural network fitting parameters) is now replaced by the analytical model potential. Based on the present merged PES, mixed Quantum-Classical (MQC) calculations, which capture quantum effects related to vibrational motion, align with a range of experimental data, including transport properties, vibrational energy transfer between CO and its isotoplogues, as well as rate coefficients for V-V and V-T/R processes. Notably, the original abinitio PES yields V-T/R rate coefficients at low temperatures that are significantly higher than the experimental data due to the artificial contribution of its unphysical long-range potential. In addition to conducting extensive MQC calculations to obtain raw data for V-V and V-T/R rate coefficients, we employ Gaussian process regression to predict processes lacking computed MQC data, thereby completing the considered V-V and V-T/R datasets. These extensive rate coefficient datasets, particularly for V-T/R processes, are unprecedented and reveal the significant role played by V-T/R processes at high temperatures, emphasizing the necessity of incorporating both V-V and V-T/R processes in the applications.