Equilibrium Simulations Research Articles

Optimized reaction coordinates for analysis of enhanced sampling.

Atomistic simulations of biological processes offer insights at a high level of spatial and temporal resolution, but accelerated sampling is often required for probing timescales of biologically relevant processes. The resulting data need to be statistically reweighted and condensed in a concise yet faithful manner to facilitate interpretation. Here, we provide evidence that a recently proposed approach for the unsupervised determination of optimized reaction coordinate (RC) can be used for both analysis and reweighting of such data. We first show that for a peptide interconverting between helical and collapsed configurations, the optimal RC permits efficient reconstruction of equilibrium properties from enhanced sampling trajectories. Upon RC-reweighting, kinetic rate constants and free energy profiles are in good agreement with values obtained from equilibrium simulations. In a more challenging test, we apply the method to enhanced sampling simulations of the unbinding of an acetylated lysine-containing tripeptide from the bromodomain of ATAD2. The complexity of this system allows us to investigate the strengths and limitations of these RCs. Overall, the findings presented here underline the potential of the unsupervised determination of reaction coordinates and the synergy with orthogonal analysis methods, such as Markov state models and SAPPHIRE analysis.

Development of an automated reliable method to compute transport properties from DPD equilibrium simulations: Application to simple fluids

Dissipative particle dynamics (DPD) is a promising candidate technique for modeling rheological properties of soft matter systems. However, several methodological issues inhibit its exploitation as a computational rheology tool. In this work, we focus on the development of an automated method to compute transport properties from equilibrium simulation with particular attention to the assessment of the Green-Kubo approach reliability and computational feasibility for a large set of simple DPD systems with increasing Schmidt number. Furthermore, we investigate the time step size dependency of dynamic properties and the role of different time integration schemes. In particular, we assess the performance of the Shardlow-splitting algorithm against the most popular modified velocity-Verlet algorithm. We consider, for the first time, application of the Shardlow-splitting algorithm to the transverse DPD thermostat in different friction regimes relying on systematic numerical experiments. In addition, we make use of these findings to perform a multi-parametric study aiming to investigate the Schmidt number relationship with the effective friction coefficient.

Crustal remelting origin of highly silicic magmatism on the Moon

Orbital observations of non-mare, highly silicic volcanic constructs on the Moon challenge the conventional view of the formation of silicic crusts in the presence of water and plate tectonics—the former the Moon has in very short supply and the latter it likely never ever had. Revealing the silica-rich magma origin may reshape our understanding of early planetary crust formation. However, the cause of lunar silicic magmatism remains enigmatic. Here we conduct phase equilibrium simulations for potential lunar igneous lithologies that demonstrate that the compositions of silicic volcanic constructs can be produced by partial melting of KREEP (potassium, rare earth elements, and phosphorus) basalts. Either internal radiogenic heating or external impact bombardment can provide the heat needed for KREEP basalt melting. Combined with silica-rich materials identified on other rocky planets, we suggest that highly evolved crusts might be more prevalent in the early solar system than anticipated as they can originate from crustal remelting in the absence of water and plate tectonics.

Collateral damage? Welfare effects of the Ukraine war on Pakistan

The 2022 Ukraine conflict has contributed to a major spike in international commodity prices. In this study, we conduct a top-down, macro-micro simulation analysis by combining Computable General Equilibrium simulations with data from the 2018–19 Pakistan Household Integrated Economic Survey to analyze the impact of global price shock to four major commodities, namely wheat, vegetable oil, petroleum, and fertilizers. We come up with evidence for a significant, non-negligible negative impact of the price shock, both at the aggregate and the household level: Real GDP shrinks and real household consumption and income decrease. The drop in consumption and income is more visible among farm households, with the two falling by 5% and 3.48% respectively. The consumption and income of the above-median income households fall more steeply, and income inequality decreases. The USD3.2 headcount poverty rate at the 2018 purchasing power parity increases by 1.15%. Urban households show the worst decline in food security, both in incidence and intensity. The role of petrol prices in driving poverty among rural farm households and that of food stuff (wheat and vegetable oil prices) in aggravating urban food security is particularly evident. These findings highlight the poverty and food security-worsening dimension of the Russo-Ukrainian conflict.

A New Approach for Estimating the Free Energy Differences among Multiple Thermodynamic States in Statistical Simulations.

In this letter, a new approach to compute free energy differences (FEDs) between multiple thermodynamics states is introduced. The method directly uses energy probability densities, which can be extracted with high accuracy from equilibrium simulations to obtain FEDs. Methods in current use, such as Bennett acceptance ratio (BAR), its multistate generalization (MBAR), or the weighted histogram analysis method (WHAM), require iterative solution of nonlinear equations which are known to be slowly convergent. The equations providing MBAR FEDs are identical to those derived earlier by Souaille and Roux in a method that has become known informally as "binless WHAM". In contrast, we obtain FEDs by solution of linear equations. For the classic two-state problem, the statistical error of our method, solving linear equations, is shown analytically to match that of BAR under common conditions.

Phase equilibrium and evaporation process simulation for the lithium recovery from NaCl-LiCl-H2O system with high presence of organic NMP

In the production process of polyphenylene sulfide (PPS), there is a waste liquid with the main composition of NaCl-LiCl-NMP-H2O. For the recovery of LiCl, the phase equilibrium data of the NaCl-LiCl-H2O system at a temperature of 333.15 K and 348.15 K with the highest presence of 24 % NMP in the solvent was experimentally measured. The results show that the phase diagram has one invariant point, two univariant curves and two single-salt crystallization regions corresponding to NaCl and LiCl·H2O, respectively. Neither double salt nor solid solution is found in the system. Meanwhile, the Electrolyte NRTL model was successfully developed to reproduce the phase equilibrium of the systems. Finally, the evaporation crystallization process was developed for the lithium enrichment and sodium separation. The different process operations of multi-effect evaporation (MEE), mechanical vapor recompression (MVR), and hierarchical compression MVR were compared with the focus on the energy consumption. The results show that compared with the other two processes, for this high boiling point rise system, the total annual cost and exergy loss can be reduced by 53.57 % and 64.81 % to the maximum extent by using the hierarchical compression MVR system.

Stochastic Simulations of Casual Groups

Free-forming or casual groups are groups in which individuals are in face-to-face interactions and are free to maintain or terminate contact with one another, such as clusters of people at a cocktail party, play groups in a children’s playground or shopping groups in a mall. Stochastic models of casual groups assume that group sizes are the products of natural processes by which groups acquire and lose members. The size distributions predicted by these models have been the object of controversy since their derivation in the 1960s because of the neglect of fluctuations around the mean values of random variables that characterize a collection of groups. Here, we check the validity of these mean-field approximations using an exact stochastic simulation algorithm to study the processes of the acquisition and loss of group members. In addition, we consider the situation where the appeal of a group of size i to isolates is proportional to iα. We find that, for α≤1, the mean-field approximation fits the equilibrium simulation results very well, even for a relatively small population size N. However, for α>1, this approximation scheme fails to provide a coherent description of the distribution of group sizes. We find a discontinuous phase transition at αc>1 that separates the regime where the variance of the group size does not depend on N from the regime where it grows linearly with N. In the latter regime, the system is composed of a single large group that coexists with a large number of isolates. Hence, the same underlying acquisition-and-loss process can explain the existence of small, temporary casual groups and of large, stable social groups.

Arctic Sea Ice Loss Weakens Northern Hemisphere Summertime Storminess but Not Until the Late 21st Century

AbstractObservations show Arctic sea ice has declined and midlatitude storminess has weakened during Northern Hemisphere (NH) summertime. It is currently unclear whether Arctic sea ice loss impacts summertime storminess because most previous work focuses on other seasons. Here we quantify the impact of Arctic sea ice loss on NH summertime storminess using equilibrium and transient climate model simulations. The equilibrium simulations show mid‐to‐late 21st century Arctic sea ice loss weakens summertime storminess, but only in the presence of ocean coupling. With ocean coupling, the equator‐to‐pole temperature and atmospheric energy gradients significantly weaken due to increased surface turbulent flux in the polar region following Arctic sea ice loss. The transient simulations show Arctic sea ice loss does not significantly weaken summertime storminess until the late 21st century. Furthermore, Arctic Amplification, which is dominated by Arctic sea ice loss in the present day, does not significantly impact the present‐day weakening of summertime storminess.

The Sensitivity of Convective Cloud Ensemble Statistics to Horizontal Grid Spacing in Idealized RCE Simulations

Abstract In this work, cloud ensemble statistics are extracted from idealized radiative–convective equilibrium simulations performed at horizontal grid spacings Δ ranging from 2 km to 125 m. At the coarsest resolution, convection remains randomly distributed in space such that the equilibrium statistical mechanics theory proposed by Craig and Cohen in 2006 (CC06; assumes Poisson distributed clouds and exponential mass flux distributions) remains valid. Using classical organization metrics, clustering is already observed at Δ = 1 km, but substantial deviations between the simulated cloud ensemble statistics and CC06 are only observed for grid spacings Δ < 500 m. At these resolutions, the cloud mass flux distributions exhibit heavy tails and cloud counts become overdispersed (higher variance than a Poisson distribution). These changes in ensemble statistics are accompanied by a shift in subcloud organization patterns as well as with the fact that individual cloudy updrafts start to be resolved. Consequently, a horizontal grid spacing no larger than 250 m is recommended, not only to properly resolve the dynamics of individual convective clouds, but also to capture the mesoscale organization of the cloud ensemble. Finally, it is shown that the CC06 theory and our high-resolution results including mesoscale organization may be reconciled if one considers 1) areas smaller than approximately 2 km in size, corresponding roughly to the narrow bands along which clouds develop almost randomly; and 2) individual cloud cores instead of cloud objects, core mass fluxes being shown to generally follow exponential distributions.

Non-Equilibrium Modeling of Concentration-Driven processes with Constant Chemical Potential Molecular Dynamics Simulations.

ConspectusConcentration-driven processes in solution, i.e., phenomena that are sustained by persistent concentration gradients, such as crystallization and surface adsorption, are fundamental chemical processes. Understanding such phenomena is crucial for countless applications, from pharmaceuticals to biotechnology. Molecular dynamics (MD), both in- and out-of-equilibrium, plays an essential role in the current understanding of concentration-driven processes. Computational costs, however, impose drastic limitations on the accessible scale of simulated systems, hampering the effective study of such phenomena. In particular, due to these size limitations, closed system MD of concentration-driven processes is affected by solution depletion/enrichment that unavoidably impacts the dynamics of the chemical phenomena under study. As a notable example, in simulations of crystallization from solution, the transfer of monomers between the liquid and crystal phases results in a gradual depletion/enrichment of solution concentration, altering the driving force for phase transition. In contrast, this effect is negligible in experiments, given the macroscopic size of the solution volume. Because of these limitations, accurate MD characterization of concentration-driven phenomena has proven to be a long-standing simulation challenge. While disparate equilibrium and nonequilibrium simulation strategies have been proposed to address the study of such processes, the methodologies are in continuous development.In this context, a novel simulation technique named constant chemical potential molecular dynamics (CμMD) was recently proposed. CμMD employs properly designed, concentration-dependent external forces that regulate the flux of solute species between selected subregions of the simulation volume. This enables simulations of systems under a constant chemical drive in an efficient and straightforward way. The CμMD scheme was originally applied to the case of crystal growth from solution and then extended to the simulation of various physicochemical processes, resulting in new variants of the method. This Account illustrates the CμMD method and the key advances enabled by it in the framework of in silico chemistry. We review results obtained in crystallization studies, where CμMD allows growth rate calculations and equilibrium shape predictions, and in adsorption studies, where adsorption thermodynamics on porous or solid surfaces was correctly characterized via CμMD. Furthermore, we will discuss the application of CμMD variants to simulate permeation through porous materials, solution separation, and nucleation upon fixed concentration gradients. While presenting the numerous applications of the method, we provide an original and comprehensive assessment of concentration-driven simulations using CμMD. To this end, we also shed light on the theoretical and technical foundations of CμMD, underlining the novelty and specificity of the method with respect to existing techniques while stressing its current limitations. Overall, the application of CμMD to a diverse range of fields provides new insight into many physicochemical processes, the in silico study of which has been hitherto limited by finite-size effects. In this context, CμMD stands out as a general-purpose method that promises to be an invaluable simulation tool for studying molecular-scale concentration-driven phenomena.

The effect of changing the molecular structure of the surfactant on the dissolution of lamellar phases

Dissolution processes of surfactants, especially when in the lamellar phase, into water are important for product formulation. Understanding this process at a molecular level will help to enhance product design and control surfactant processes. The main goal of this study is to examine the effect of different lengths of surfactants and the hydrophobic to hydrophilic ratio on the dissolution process of surfactants. To achieve this goal dissipative particle dynamic (DPD) simulations were used. Lamellar equilibrium simulations were carried out for different surfactant chain lengths at 80 vol% with water. The surfactant chains were each run in a simulation box of dimensions 20 × 20 × 20 until equilibrium was reached. The lamellar phase formed for all different surfactant chain lengths and, after the initial equilibrium the surfactant systems were then simulated with a water box for dissolution. The dissolution process was tracked by visual analysis, local concentration analysis, micelle size, and a zonal model to calculate the diffusion parameter.Results show that as the surfactant chain length increased by adding more of the hydrophobic beads, the dissolution process slowed down. Increasing the hydrophilic part of the surfactant speeds up the dissolution process, but the effect of adding more of the hydrophobic part is greater than the effect of adding more of the hydrophilic part on the dissolution process.

Shafranov shift correction to the Furth–Yoshikawa scaling of tokamak adiabatic compression

In 1970, Furth and Yoshikawa (1970 Phys. Fluids 13 2593–6) introduced the scalings of adiabatic plasma compression. Basically, if the shape of the external plasma boundary and the aspect ratio are preserved during the compression, then the density, kinetic pressure, beta and current scale respectively as , , , , , where C is the linear compression ratio, that is, the ratio between initial and final major radii. In this work, we show analytically, by expanding the Grad–Shafranov equation in terms of C, that the deviation to the Furth–Yoshikawa scaling is related to the Shafranov shift that arises when beta increases at large compression ratios. There is an obvious effect of the Shafranov shift because the axis is moved to a region with larger volume element, and an indirect effect, associated to the relation between flux and radius. The latter effect adds to the first, and is of the same order of magnitude. The result is that the pressure increases less than the C 5 scaling, which can have a significant impact on the fusion power achieved at maximum compression. The analytical results are backed up by equilibrium simulations carried out with the CHEASE code. Equilibria are obtained for different values of C, with conservation of the total fluxes, q profile, and entropy of the plasma. The agreement of the theory and simulations is very good when the boundary of the plasma is circular and the aspect ratio small. When the aspect ratio is close to 1, and/or the boundary not circular, the analytical result gives the gist of the reduction of compression. Finally, a pressure anisotropy approximately equal to the increase in normalized Shafranov shift is predicted.

Local equilibrium in liquid phase shock waves.

We have assessed the assumption of local thermodynamic equilibrium in a shock wave by comparing local thermodynamic data generated with nonequilibrium molecular dynamics (NEMD) simulations with results from corresponding equilibrium simulations. The shock had a Mach number approximately equal to 2 in a Lennard-Jones spline liquid. We found that the local equilibrium assumption holds perfectly well behind the wave front, and is a very good approximation in the front itself. This was supported by calculations of the excess entropy production in the shock front with four different methods that use the local equilibrium assumption in different ways. Two of the methods assume local equilibrium between excess thermodynamic variables by treating the shock as an interface in Gibbs's sense. The other two methods are based on the local equilibrium assumption in a continuous description of the shock front. We show for the shock studied in this work that all four methods give excess entropy productions that are in excellent agreement, with an average variance of 3.5% for the nonequilibrium molecular dynamics (NEMD) simulations. In addition, we solved the Navier-Stokes (N-S) equationsnumerically for the same shock wave using an equilibrium equationof state (EoS) based on a recently developed perturbation theory. The results for the density, pressure, and temperature profiles agree well with the profiles from the NEMD simulations. For instance, the shock waves generated in the two simulations travel with almost the same speed; the average absolute Mach-number deviation of the N-S simulations relative to NEMD is 2.6% in the investigated time interval.

Gene Association Analysis of Quantitative Trait Based on Functional Linear Regression Model with Local Sparse Estimator.

Functional linear regression models have been widely used in the gene association analysis of complex traits. These models retain all the genetic information in the data and take full advantage of spatial information in genetic variation data, which leads to brilliant detection power. However, the significant association signals identified by the high-power methods are not all the real causal SNPs, because it is easy to regard noise information as significant association signals, leading to a false association. In this paper, a method based on the sparse functional data association test (SFDAT) of gene region association analysis is developed based on a functional linear regression model with local sparse estimation. The evaluation indicators CSR and DL are defined to evaluate the feasibility and performance of the proposed method with other indicators. Simulation studies show that: (1) SFDAT performs well under both linkage equilibrium and linkage disequilibrium simulation; (2) SFDAT performs successfully for gene regions (including common variants, low-frequency variants, rare variants and mix variants); (3) With power and type I error rates comparable to OLS and Smooth, SFDAT has a better ability to handle the zero regions. The Oryza sativa data set is analyzed by SFDAT. It is shown that SFDAT can better perform gene association analysis and eliminate the false positive of gene localization. This study showed that SFDAT can lower the interference caused by noise while maintaining high power. SFDAT provides a new method for the association analysis between gene regions and phenotypic quantitative traits.

Determining vulnerable households and food groups sensitive to price and income increase from the perspective of food security: Evidence from Iran

Concerns about household food security of developing countries has been greatly intensified with rising food prices derives from various causes, such as market failure, climate change, political instability, the presence of poor financial institutions, and emerging challenges. It is very important, the development and evaluation of required policy responses such as income compensation policy to cope with foodstuff price increases. It is necessary to pay attention to different household groups regarding income, occupation, and urban/rural conditions in order to evaluate the effects of shocks and policies according to the different responses of households. This paper employes a multimarket equilibrium simulation model and evaluates the effect of price hikes with/without households' nominal income compensation policy on the calorie intake of different household groups. To this end, Iranian households that have suffered from severe food inflation and their nominal income compensation policy has always been the focus of government officials were investigated. First, we noticed that poor rural households with government occupations bear the brunt of ensuing the price hike of foodstuffs. Second, we found that households food security is highly reliant on the price of livestock products compared to other foodstuffs. Finally, we concluded that income compensation policy plays the role of a threat to food security for some households and a driver for others. Therefore, based on the different responses of households to foodstuff price and income increase, we recommended the design of more precise interventions in the market of foodstuff in a more targeted and efficient manner.

Insights into substrate transport and water permeation in the mycobacterial transporter MmpL3

Mycobacteria, such as Mycobacterium tuberculosis, are characterized by a uniquely thick and waxy cell envelope that consists of two membranes, with a variety of mycolates comprising their outer membrane (OM). The protein Mycobacterial membrane protein Large 3 (MmpL3) is responsible for the transport of a primary OM component, trehalose monomycolate (TMM), from the inner (cytoplasmic) membrane (IM) to the periplasmic space, a process driven by the proton gradient. Although multiple structures of MmpL3 with bound substrates have been solved, the exact pathway(s) for TMM or proton transport remains elusive. Here, employing molecular dynamics simulations we investigate putative pathways for either transport species. We hypothesized that MmpL3 will cycle through similar conformational states as the related transporter AcrB, which we used as targets for modeling the conformation of MmpL3. A continuous water pathway through the transmembrane region was found in one of these states, illustrating a putative pathway for protons. Additional equilibrium simulations revealed that TMM can diffuse from the membrane into a binding pocket in MmpL3 spontaneously. We also found that acetylation of TMM, which is required for transport, makes it more stable within MmpL3’s periplasmic cavity compared with the unacetylated form.

Charge Transport in Water-NaCl Electrolytes with Molecular Dynamics Simulations.

A systematic description of microscopic mechanisms is necessary to understand mass transport in solid and liquid electrolytes. From Molecular Dynamics (MD) simulations, transport properties can be computed and provide a detailed view of the molecular and ionic motions. In this work, ionic conductivity and transport numbers in electrolyte systems are computed from equilibrium and nonequilibrium MD simulations. Results from the two methods are compared with experimental results, and we discuss the significance of the frame of reference when determining and comparing transport numbers. Two ways of computing ionic conductivity from equilibrium simulations are presented: the Nernst-Einstein approximation or the Onsager coefficients. The Onsager coefficients take ionic correlations into account and are found to be more suitable for concentrated electrolytes. Main features and differences between equilibrium and nonequilibrium simulations are discussed, and some potential anomalies and critical pitfalls of using nonequilibrium molecular dynamics to determine transport properties are highlighted.

Nanotopographic micro-nano forces finely tune the conformation of macrophage mechanosensitive membrane protein integrin β2 to manipulate inflammatory responses.

Supplementary material (primer sequences of target genes in RT-qPCR assay; the results of solvent accessible surface area during equilibrium simulation, the ligplut results of hydrogen bonds, and hydrophobic interactions; the density of different nanotopographic structures; interaction analysis of the downregulated leading genes of "focal adhesion" signaling pathway in nanohemispheres and nanorods groups; and the GSEA results of "Rap 1 signaling pathway" and "regulation of actin cytoskeleton" in different groups) is available in the online version of this article at 10.1007/s12274-023-5550-0.

MgO/Molten salt interfacial thermal transport and its consequences on thermophysical property enhancement: A molecular dynamics study

The solid-liquid interface between molten salt and solid oxides is ubiquitous in the molten salt nanocomposite with enhanced heat storage and transfer properties for concentrating solar power (CSP) systems. Understanding the microscopic mechanisms of interfacial thermal transport on this solid-liquid interface have great significance for evaluating the effective thermal properties of nanocomposites. This study combines equilibrium and non-equilibrium molecular dynamics simulations to explore the thermal transport and its connection with interfacial microstructure at the solid MgO-molten Hitec salt interface. Simulation results indicate that the enhancement of thermal transport can be ascribed primarily to the highly ordered adsorption structure of molten salt ions formed at the MgO surface, and the effect medium model incorporated with the simulated interfacial thermal resistance can reproduce the thermal conductivity of nanocomposite accurately. Further investigation indicates that the stronger adsorption at the MgO (110) surface leads to smaller interfacial thermal resistance than the MgO (100) surface, while the heat transfer parallel to the slab does not show much difference in both surfaces. These findings have illustrated the enrichment of molten salt ions at the solid surface does have a strong enhancement effect on their heat transfer properties and it is also necessary to incorporate the contribution from this interfacial thermal transport enhancement when predicting the thermophysical properties of molten salt nanocomposite materials.

Genetic mechanisms and a stability evaluation of large landslides in Zhangjiawan, Qinghai Province

It is important to study the instability law of typical landslides to understand the evolution of regional landslides and for disaster prevention. This study uses the Zhangjiawan landslide in Xining City, Qinghai Province, as an example. Through field surveys and an analysis of the geological environmental conditions, the formation and evolution mechanisms of the Zhangjiawan landslide are summarized. The stability of the Zhangjiawan landslide was evaluated using limit equilibrium and numerical simulation methods to provide theoretical support for the susceptibility of the Zhangjiawan landslide. The results show that the main reasons for the occurrence of multi-grade landslides are the steep and gentle terrain changes, the poor permeability of the mudstone lithology, the excavation of the front anti-slide section, and rainfall. The whole deformation and failure mechanism of the landslide is the “unloading rebound-tension deformation-creep deformation.” The results of the numerical simulation and the limit equilibrium methods are nearly the same, and the difference in the stability coefficients is small. Under rainstorm conditions, the displacement and the maximum shear strain increments are mainly concentrated on the rear edge of the landslide mass, and the front edge is pushed, which is a typical push-type landslide.