Classical Field Methods Research Articles

Molecular relaxation by reverse diffusion with time step prediction

Abstract Molecular relaxation, finding the equilibrium state of a non-equilibrium structure, is an essential component of computational chemistry to understand reactivity. Classical force field (FF) methods often rely on insufficient local energy minimization, while neural network FF models require large labeled datasets encompassing both equilibrium and non-equilibrium structures. As a remedy, we propose MoreRed, molecular relaxation by reverse diffusion, a conceptually novel and purely statistical approach where non-equilibrium structures are treated as noisy instances of their corresponding equilibrium states. To enable the denoising of arbitrarily noisy inputs via a generative diffusion model, we further introduce a novel diffusion time step predictor. Notably, MoreRed learns a simpler pseudo potential energy surface (PES) instead of the complex physical PES. It is trained on a significantly smaller, and thus computationally cheaper, dataset consisting of solely unlabeled equilibrium structures, avoiding the computation of non-equilibrium structures altogether. We compare MoreRed to classical FFs, equivariant neural network FFs trained on a large dataset of equilibrium and non-equilibrium data, as well as a semi-empirical tight-binding model. To assess this quantitatively, we evaluate the root-mean-square deviation between the found equilibrium structures and the reference equilibrium structures as well as their energies.

Količine goriva u šumskoj prostirci sastojina hrasta crnike (Quercus ilex L.) i hrasta medunca (Quercus pubescens Willd.)

The application of newer remote sensing methods, such as aerial and terrestrial lidar scanning and the use of "Structure-from-motion" (SfM) photogrammetry, complemented field data collection and enabled 3D mapping of forest fuel layers, greatly simplifying and improving their characterization. However, these methods are not suitable for quantifying forest floor characteristics. For this purpose, it is still necessary to collect data using classical field methods, determining the presence of subhorizons and their depth, while the characteristics of the forest floor: bulk density, load, carbon concentration and carbon stock are determined in the laboratory. Therefore, it is still common practice to create regression equations that allow operatives to determine the amount of available forest floor fuel and the carbon stock it contains based on the depth of the forest floor, which is an easily measurable variable, or to determine forest floor loading by subhorizon and overall. Forest floor information is used in models for predicting forest fire behavior and spread, in fire effects models, in planning and monitoring mechanical fuel reduction, in quantifying fuel consumption and smoke emissions, in quantifying carbon stocks, in describing habitat and its productivity, and in planning for preparedness. As stands of holm oak (Quercus ilex L.) and pubescent oak (Quercus pubescens Willd.) are located in the Mediterranean part of Croatia, where the risk of forest fires is the highest, and the previously published data on the forest floor are not suitable for the models, the main objectives of the research were to determine the depth, bulk density and load of individual subhorizons of the forest floor and to create regression equations that allow estimating the amount of available fuel in the forest floor based on its depth. Sampling of forest floor in holm oak stands (60, 90 and 100 years old) was conducted on the islands of Lastovo and Mljet, while sampling in pubescent oak stands (53 and 90 years old) was conducted in Dugopolje and Biograd na Moru. The amount of forest floor and OC stock in old stands of holm oak and pubescent oak is twice as small as in old stands of Aleppo pine and Dalmatian black pine. This suggests that pine stands have a significantly greater amount of potentially available fuel in the forest floor and are therefore potentially more at risk from fire, but also that they store twice as much carbon in the forest floor. In this study, for the first time in Croatia, bulk densities of individual subhorizons of the forest floor were determined for holm oak and pubescent oak and regression equations were created that allow estimating the amount of available fuel in the forest floor based on its depth per subhorizon and overall. The results of this research have practical value in simpler quantification of forest floor fuel loading, which is important for operational use of models to predict forest fire behavior and spread, but they can also be used in other models mentioned earlier.

Covid-19 Containment Communication in Nigeria: Do Kari-Kasa Community Still Believe ‘the Media are of the Devil’?

The Covid-19 pandemic created an atmosphere of global uncertainty that challenged established assumptions and ways of life. Amid the uncertainty, most people turned to mass and social media for updates, direction and, especially during lockdowns, companionship. An earlier study of the Kari-kasa community shows their total disdain for modernity including the mass media: radio, television and newspaper. The question then arises: was the Kari-kasa able to sustain this disdain during a pandemic that turned most people to the media? To what extent did the community uphold its aversion to modernity in the face of a crippling pandemic? Employing classical ethnographic field methods of focus group discussion (FGD), observation, in-depth and key informant interviews, this study established a reasonable level of Covid-19 awareness among the Kari-kasa members, some of whom seemed to be modifying their belief system to conform to social pressure. They largely declined Covid-19 safety rules believing it was not obligatory. The nature of their information-seeking behavior breeds information disorder and infodemic within their micro-community. The Kari-kasa appeared to be left behind in government efforts on Covid-19 containment communication interventions. It is therefore recommended that specific behavior change communication intervention be targeted at conservative marginal and hidden communities such as Kari-kasa just like it is for the Amish. Also, since Kari-kasa members exhibit ideological belief rather than behavioral belief explained in theory, behavior change interventions targeted at such groups should pay attention to this influential factor for the intervention to be compatible with their belief.

Transmembrane Anion Transport Mediated by Halogen Bonds: Using Off-Center Charges.

Synthetic anion transporters are promising therapeutic agents designed to emulate the specialized role of certain transmembrane proteins that maintain the ion concentration in cells. In the last few years, besides hydrogen bonds and ion pairs, halogen bonds have also been explored to promote the association between the synthetic molecule and the anion and their subsequent transport. This interaction is due to an anisotropic charge distribution on the halogen, and therefore, modeling halogen bonds is not a trivial task using classical force field methods that typically rely on point-charge models.Herein, a computational protocol capable of dealing with halogen bonds is presented. This protocol takes advantage of the addition of anoff-center particle during the charge fitting procedure, and the resulting set of charges can be used along with the classical force field parameters from GAFF or GROMOS 54A7.

Density functional and classical simulations of liquid and glassy selenium

Molecular dynamics simulations of liquid and glassy selenium have been carried out using density functional (400--773 K, 600 atoms) and classical force field (290--500 K, 5488 atoms) methods. Structural features (structure factors, pair distribution functions, bond lengths, bond and dihedral angles, cavities) and dynamical properties (diffusion coefficients, power spectra, sound velocity, collective excitations, bond lifetimes) agree well with experimental data where available. The structures are predominantly chainlike, with a small fraction of rings with a range of sizes, and large cavity volumes lead to flexible chains. It is striking that the density functional simulations show very few ${\mathrm{Se}}_{8}$ rings at 600 K and below.

Socially-Aware Reactive Obstacle Avoidance Strategy Based on Limit Cycle

The letter proposes a combination of ideas to support navigation for a mobile robot across dynamic environments, cluttered with obstacles and populated by human beings. The combination of the classical potential field methods and limit cycle based approach with an innovative shape for the limit cycles, generates paths which are reasonably short, smooth and comfortable to follow (which can be very important for assistive robots), and it respects the safety and psychological comfort of the bystanders by staying clear of their private space.

Reproducing global potential energy surfaces with continuous-filter convolutional neural networks.

Neural networks fit to reproduce the potential energy surfaces of quantum chemistry methods offer a realization of analytic potential energy surfaces with the accuracy of ab initio methods at a computational cost similar to classical force field methods. One promising class of neural networks for this task is the SchNet architecture, which is based on the use of continuous-filter convolutional neural networks. Previous work has shown the ability of the SchNet architecture to reproduce density functional theory energies and forces for molecular configurations sampled during equilibrated molecular dynamics simulations. Due to the large change in energy when bonds are broken and formed, the fitting of global potential energy surfaces is normally a more difficult task than fitting the potential energy surface in the region of configurational space sampled during equilibrated molecular dynamics simulations. Herein, we demonstrate the ability of the SchNet architecture to reproduce the energies and forces of the potential energy surfaces of the H + H2 and Cl + H2 reactions and the OCHCO+ and H2CO/cis-HCOH/trans-HCOH systems. The SchNet models reproduce the potential energy surface of the reactions well with the best performing SchNet model having a test set root-mean-squared error of 0.52 meV and 2.01 meV for the energies of the H + H2 and Cl + H2 reactions, respectively, and a test set mean absolute error for the force of 0.44 meV/bohr for the H + H2 reaction. For the OCHCO+ and H2CO/cis-HCOH/trans-HCOH systems, the best performing SchNet model has a test set root-mean-squared error of 2.92 meV and 13.55 meV, respectively.

An efficient way to model complex magnetite: Assessment of SCC-DFTB against DFT.

Magnetite has attracted increasing attention in recent years due to its promising and diverse applications in biomedicine. Theoretical modelling can play an important role in understanding magnetite-based nanomaterials at the atomic scale for a deeper insight into the experimental observations. However, calculations based on density functional theory (DFT) are too costly for realistically large models of magnetite nanoparticles. Classical force field methods are very fast but lack of precision and of the description of electronic effects. Therefore, a cheap and efficient quantum mechanical simulation method with comparable accuracy to DFT is highly desired. Here, a less computationally demanding DFT-based method, i.e., self-consistent charge density functional tight-binding (SCC-DFTB), is adopted to investigate magnetite bulk and low-index (001) surfaces with newly proposed parameters for Fe-O interactions. We report that SCC-DFTB with on-site Coulomb correction provides results in quantitatively comparable agreement with those obtained by DFT + U and hybrid functional methods. Therefore, SCC-DFTB is valued as an efficient and reliable method for the description magnetite. This assessment will promote SCC-DFTB computational studies on magnetite-based nanostructures that attract increasing attention for medical applications.

Superballistic center-of-mass motion in one-dimensional attractive Bose gases: Decoherence-induced Gaussian random walks in velocity space

We show that the spreading of the center-of-mass density of ultracold attractively interacting bosons can become superballistic in the presence of decoherence, via single-, two- and/or three-body losses. In the limit of weak decoherence, we analytically solve the numerical model introduced in [Phys. Rev. A 91, 063616 (2015)]. The analytical predictions allow us to identify experimentally accessible parameter regimes for which we predict superballistic spreading of the center-of-mass density. Ultracold attractive Bose gases form weakly bound molecules; quantum matter-wave bright solitons. Our computer-simulations combine ideas from classical field methods ("truncated Wigner") and piecewise deterministic stochastic processes. While the truncated Wigner approach to use an average over classical paths as a substitute for a quantum superposition is often an uncontrolled approximation, here it predicts the exact root-mean-square width when modeling an expanding Gaussian wave packet. In the superballistic regime, the leading-order of the spreading of the center-of-mass density can thus be modeled as a quantum superposition of classical Gaussian random walks in velocity space.

Equilibration of a finite-temperature binary Bose gas formed by population transfer

We consider an equilibrium single-species homogeneous Bose gas from which a proportion of the atoms are instantaneously and coherently transferred to a second species, thereby forming a binary Bose gas in a non-equilibrium initial state. We study the ensuing evolution towards a new equilibrium, mapping the dynamics and final equilibrium state out as a function of the population transfer and the interspecies interactions by means of classical field methods. While in certain regimes, the condensate fractions are largely unaffected by the population transfer process, in others, particularly for immiscible interactions, one or both condensate fractions are vastly reduced to a new equilibrium value.

An Information Potential Approach to Integrated Sensor Path Planning and Control

This paper presents an information potential method for integrated path planning and control. The method is applicable to unicycle robotic sensors deployed to classify multiple targets in an obstacle-populated environment. A new navigation function, referred to as information potential, is generated from the target conditional mutual information, and used to design a closed-loop stable switched control law. The information potential is shown to obey the properties of potential navigation functions and to enable measurements that maximize the information value over time. The information potential is also used to construct a local roadmap for escaping local minima. The properties and computational complexity of the local roadmap algorithm are analyzed. Numerical simulation results show that the method outperforms other strategies, such as rapidly exploring random trees and classical potential field methods.

Adsorption of glucose, cellobiose, and cellotetraose onto cellulose model surfaces.

Reliable simulation of molecular adsorption onto cellulose surfaces is essential for the design of new cellulose nanocomposite materials. However, the applicability of classical force field methods to such systems remains relatively unexplored. In this study, we present the adsorption of glucose, cellobiose, and cellotetraose on model surfaces of crystalline cellulose Iα and Iβ. The adsorption of the two large carbohydrates was simulated with the GLYCAM06 force field. To validate this approach, quantum theoretical calculations for the adsorption of glucose were performed: Equilibrium geometries were studied with density functional theory (DFT) and dispersion-corrected DFT, whereas the adsorption energies were calculated with two standard density functional approximations and five dispersion-containing DFT approaches. We find that GLYCAM06 gives a good account of geometries and, in most cases, accurate adsorption energies when compared to dispersion-corrected DFT energies. Adsorption onto the (100) surface of cellulose Iα is, in general, stronger than onto the (100) surface of cellulose Iβ. Contrary to intuition, the adsorption energy is not directly correlated with the number of hydrogen bonds; rather, it is dominated by dispersion interactions. Especially for bigger adsorbates, a neglect of these interactions leads to a dramatic underestimation of adsorption energies.

Classical-field methods for atom-molecule systems

We extend classical-field methods [Blakie et al., Adv. Phys. 57, 363 (2008)] to provide a description of atom-molecule systems. We use a model of Bose-Einstein condensation of atoms close to a Feshbach resonance, in which the tunable scattering length of the atoms is described using a system of coupled atom and molecule fields [Holland et al., Phys. Rev. Lett. 86, 1915 (2001)]. We formulate the basic theoretical methods for a coupled atom-molecule system, including the determination of the phenomenological parameters in our system, the Thomas-Fermi description of Bose-Einstein condensate, the Bogoliubov--de Gennes equations, and the Bogoliubov excitation spectrum for a homogenous condensed system. We apply this formalism to the special case of Bragg scattering from a uniform condensate and find that for moderate and large scattering lengths, there is a dramatic difference in the shift of the peak of the Bragg spectra, compared to that based on a structureless atom model. The result is compatible with the experimental results of Papp et al. [Phys. Rev. Lett 101, 135301 (2008)] for Bragg scattering from a nonuniform condensate.

Long-term drought sensitivity of trees in second-growth forests in a humid region

Classical field methods of reconstructing drought using tree rings in humid, temperate regions typically target old trees from drought-prone sites. This approach limits investigators to a handful of species and excludes large amounts of data that might be useful, especially for coverage gaps in large-scale networks. By sampling in more “typical” forests, network density and species diversity would increase in ways that could potentially improve reconstructions. Ten nonclassical tree-ring chronologies derived from randomly selected trees, trees from logged forests, or both were compared to more classical chronologies and an independent regional drought reconstruction to determine their usefulness for dendrohydroclimatic research. We find that nonclassical chronologies are significantly correlated to classical chronologies and reconstructed drought over the last 2–3 centuries. While nonclassical chronologies have spectral properties similar to those from classical dendroclimatic collections, they do lack spectral power at lower frequencies that are present in the drought reconstruction. Importantly, our results show that tree growth is strongly dependent on moisture availability, even for small, randomly selected trees in cut forests. These results indicate that there could be more data available in areas with few current tree-ring collections for studying climate history and that drought plays an important role in humid forests.

Ab initiomethods for finite-temperature two-dimensional Bose gases

The stochastic Gross-Pitaevskii equation and modified Popov theory are shown to provide an ab initio description of finite temperature, weakly-interacting two-dimensional Bose gas experiments. Using modified Popov theory, a systematic approach is developed in which the momentum cut-off inherent to classical field methods is removed as a free parameter. This is shown to yield excellent agreement with the recent experiment of Hung et al. [Nature, 470, 236 (2011)], verifying that the stochastic Gross-Pitaevskii equation captures the observed universality and scale-invariance.

ChemInform Abstract: Large‐Scale Quantum Chemical Calculation for Drug Discovery

AbstractReview: 17 refs.

Large Scale Quantum Chemical Calculation for Drug Discovery

Due to the increase in computer power and the development of computational methods, it becomes possible to perform quantum mechanical calculations of very large molecules such as proteins that were previously exclusively treated with classical force field methods. We have developed the fragment molecular orbital (FMO) method aimed at biomolecular applications. One of the important applications of the method is in structure-based drug design because it provides accurate descriptions of various non-bonded interactions between a protein and its ligand. In this article, the FMO method will be described as well as its applications to the analysis of protein-ligand binding.

Impact of Chemical Impurities on the Crystalline Cement Clinker Phases Determined by Atomistic Simulations

The presence of chemical substitutions is believed to play a crucial role in the hydration reactions, structure, and elastic properties of cement clinker phases. Hence, substitutions are of great technological interest, as more efficient production of cement clinkers would result in a reduction of CO2 emissions, as well as possible economic benefits. Here we use a combination of classical and quantum mechanical simulation methods to study the detailed physicochemical changes of the clinker phases alite (Ca3SiO5) and belite (Ca2SiO4) when Mg2+, Al3+ and Fe3+ guest ions are incorporated into their structure. Using classical force field methods, we considered random substitutions among possible sites and different compositions in order to identify the preferential substitution sites on the crystalline structures. Then, the resulting structural changes that take place to accommodate the guest ions are investigated and discussed in detail. Using quantum mechanical density functional theory calculations the ele...

Molecular modeling studies of interactions between styrene–butadiene latex and sodium polyacrylate polymer surface

The interaction between two important paper coating ingredients, sodium polyacrylate polymer dispersing agent and styrene–butadiene latex binder, was studied using classical force field and quantum chemical methods. The objective was to understand the adsorption of styrene–butadiene latex on the sodium polyacrylate polymer model surfaces at 300 K using molecular dynamics simulations. A quantum mechanical ab initio Hartree–Fock method was also used to obtain detailed information about the above interactions. In addition, the effect of moisture was investigated. Calculations showed that the conformation and orientation of styrene–butadiene latex, the number of carboxylate groups in the latex, and the characteristics of different sodium polyacrylate polymer surfaces affected the interplay between the styrene–butadiene latex and the surfaces. The force field applied and water molecules also had an effect on the adsorption process. Electrostatic interactions were observed to be important in the systems containing styrene–butadiene latex and the model surfaces. In addition, Hartree–Fock calculations suggested that the aromatic ring of styrene–butadiene latex was able to coordinate to the carboxylate group of sodium polyacrylate polymer via the sodium atom.

Molecular simulations of metal adsorption to bacterial surfaces

The atomic-scale interactions that occur between cations and the metal-binding cell wall components common to many gram-positive bacteria were investigated using molecular simulations techniques. We examined the adsorption of Cd and Pb onto peptidoglycan and teichoic acid components of the bacterial cell wall using classical energy force field methods. Within the framework of molecular mechanics and the Cerius 2 modeling software, we used energy minimization, conformational analysis, and molecular dynamics to examine the different components of the cell wall and to determine relative binding energies and structural configurations of the cell wall components, both with and without the metals present. Electronic structure calculations of representative metal–organic complexes validate the more practical classical methods required in simulating the large number of atoms associated with the cell wall components. The classical force field simulations were conducted in both gas phase and solvated periodic cells. Force field-based simulation techniques can adequately describe the interactions of Cd with the cell wall, defining both metal ion coordinations and binding distances. However, the classical force field approach is inconsistent in describing the observed Pb–cell wall interactions due to possible limitations in the force field parameters, the propensity for Pb to form hydroxides at circumneutral pH, or the dominance of other adsorption mechanisms.