Multiscale Modeling Study Research Articles

Electro-reduction of organics on metal cathodes: A multiscale-modeling study of benzaldehyde on Au (111)

Abstract We present a multiscale modeling study on the electro-reduction of benzaldehyde (BZY) on Au(111) under realistic electrochemical conditions. To model the electrochemical cell, we adopt a capacitor model in which complex solvents are confined between a Au cathode and a carbon anode. Classical molecular dynamics simulations reveal that electrode charge density and the presence of alcohol show strong effects on the density, adsorption geometry and dynamics of benzaldehyde on the Au electrode. Under charging conditions, the surface concentration of benzaldehyde on the Au electrode decreases, while the content of other species increases. Finally, we proposed a scheme that correlates the electric current running through the Au/solvent interface with the applied bias. This study provides a molecular level understanding of how solvent composition, in this case water/alcohol content, controls the activity of electrocatalytic hydrogenation

Graphene-reinforced thermoplastic polyurethane nanocomposites: A simulation and experimental study

Multiscale modelling and simulations, based on molecular dynamics (MD) and object-oriented finite element method (OOFEM), are two important simulation tools to predict property enhancement of polymer nanocomposites for designing armor-type components in requisite applications. In this study, MD simulation software (Materials Studio) is used to develop 0.5%, 1%, 2%, 3%, and 4% (by weight) single-layer graphene (SLGR)-reinforced thermoplastic polyurethane (TPU) nanocomposites to find out their mechanical properties (mainly elastic moduli and Poisson’s ratio) using constant strain method. OOFEM simulation software (OOF2) is used for mechanical characterization of 0.5%, 3%, and 4% (by weight) SLGR-reinforced TPU nanocomposites from scanning electron microscopy–generated microstructures. Properties obtained from both the simulations are compared with experimental results to know the nanoreinforcement effect in atomic level as well as in microlevel in the nanocomposites. It is observed that the results based on OOF2 simulation are closer to the experimental results compared with the results obtained from MD simulation in this multiscale modelling and simulation study.

Multiscale analysis of the effect of surface charge pattern on a nanopore's rectification and selectivity properties: From all-atom model to Poisson-Nernst-Planck.

We report a multiscale modeling study for charged cylindrical nanopores using three modeling levels that include (1) an all-atom explicit-water model studied with molecular dynamics, and reduced models with implicit water containing (2) hard-sphere ions studied with the Local Equilibrium Monte Carlo simulation method (computing ionic correlations accurately), and (3) point ions studied with Poisson-Nernst-Planck theory (mean-field approximation). We show that reduced models are able to reproduce device functions (rectification and selectivity) for a wide variety of charge patterns, that is, reduced models are useful in understanding the mesoscale physics of the device (i.e., how the current is produced). We also analyze the relationship of the reduced implicit-water models with the explicit-water model and show that diffusion coefficients in the reduced models can be used as adjustable parameters with which the results of the explicit- and implicit-water models can be related. We find that the values of the diffusion coefficients are sensitive to the net charge of the pore but are relatively transferable to different voltages and charge patterns with the same total charge.

나노세컨드 펄스 DBD 플라즈마의 멀티스케일 모델링을 위한 비평형 플라즈마 유동 해석 및 검증

In a nanosecond pulse discharge, the computational cost is high because of the characteristic time difference between the plasma and the flow. In order to reduce the computational cost, multi-scale modeling study of nanosecond pulse discharge plasma is needed. In this study, we developed and verified a non-equilibrium plasma solver for nanosecond-pulse Dielectric Barrier Discharge(NS-DBD) multi-scale modeling study. To simulate the non-equilibrium phenomena, 17 chemical species / 54 chemistry reaction models were used. The governing equations included chemical species continuity equations, a electrical potential equation, and Navier-Stokes equations. Numerical results show that streamer velocity and micro shock wave speed are comparable to those of other experimental results. This study is expected to contribute to the future study of NS-DBD multi-scale modeling.

Synthesis, biological activity and multiscale molecular modeling studies of bis-coumarins as selective carbonic anhydrase IX and XII inhibitors with effective cytotoxicity against hepatocellular carcinoma

A series of novel bis-coumarin derivatives containing triazole moiety as a linker between the alkyl chains was synthesized and their inhibitory activity against the human carbonic anhydrase (hCA) isoforms I, II, IX and XII were evaluated. In addition, cytotoxic effects of the synthesized compounds on renal adenocarcinoma (769P), hepatocellular carcinoma (HepG2) and breast adeno carcinoma (MDA-MB-231) cell lines were examined. While the hCA I and II isoforms were inhibited in the micromolar range, the tumor-associated isoform hCA IX and XII were inhibited in the high nanomolar range. 4-methyl-7-((1-(12-((2-oxo-2H-chromen-7-yl)oxy)dodecyl)-1H-1,2,3-triazol-4-yl)methoxy)-2H-chromen-2-one (5p) showed the strongest inhibitory activity against hCA IX with the Ki of 144.6 nM and 4-methyl-7-((1-(10-((2-oxo-2H-chromen-7-yl)oxy)decyl)-1H-1,2,3-triazol-4-yl)methoxy)-2H-chromen-2-one (5n) exhibited the highest hCA XII inhibition with the Ki of 71.5 nM. In order to better understand the inhibitory profiles of studied molecules, multiscale molecular modelling approaches were applied. Low energy docking poses of studied molecules at the binding sites of targets have been predicted. In addition, electrostatic potential surfaces (ESP) for binding sites were also generated to understand interactions between proteins and active ligands.

Photothermal effects induced by surface plasmon resonance at graphene/gold nanointerfaces: A multiscale modeling study

Surface plasmon resonance (SPR) biosensors have enormous potential in biological recognitions and biomolecular interactions, especially for the real time measurement of disease diagnosis and drug screening. Extensive efforts have been invested to ameliorate the sensing performances, while the photothermal effects, which are induced by the plasmon resonance, have an obvious impact. However, due to the limitations of experimental approaches, the theoretical mechanisms and specific influences of the SPR sensors with photothermal effects are few researched. Here, a multiscale simulation method is developed to investigate the photothermal effects at graphene/gold (Au) nanointerfaces, and to calculate the quantitative contribution of the photothermal effects towards high reliability SPR sensors in order to elucidate their influence on the sensing performances by means of first-principle calculations and molecular dynamics simulations. Our results indicate that the sensitivity and detection accuracy of graphene/Au SPR sensors can be tailored from 0 K to 600 K, due to the tunable dielectric constants of Au and graphene films through temperature variation. By controlling the its material thickness, interfacial combination and lattice strain, an optimized graphene/Au SPR sensor with higher sensitivity, detection accuracy, and reliability to the temperature rising has been achieved. Such multiscale simulation method, which is capable of seeking both the role and the underlying mechanism of the interfacial phenomena, can serve as an excellent guideline for the performance optimization and commercialized application of SPR sensors in the analytical chemistry and biomedical fields.

Linking cross-bridge cycling kinetics to response to cardiac resynchronization therapy: a multiscale modelling study.

Cardiac resynchronization therapy (CRT) is currently the most widely used treatment for heart failure patients with left bundle branch block (LBBB). In recent years, the presence of septal rebound stretch (SRS) has been found to be a positive indicator for CRT response although the mechanism is unknown. In an attempt to understand the relation between cellular mechanics and global pump function in CRT patients, we utilize the CircAdapt closed-loop cardiovascular system model in combination with the MechChem model of cardiac sarcomere contraction. Left bundle branch block has been simulated with increasing delay in left ventricular free wall and septal wall activation. In addition to the electrical dyssynchrony, myocardial mechanical function was diminished by decreasing the cross-bridge cycling rate. Our results have shown that a decrease in the cross-bridge cycling rate in addition to LBBB resulted in a decrease in SRS with a concomitant decreased response to resynchronization. The results of our multiscale modelling study suggest that, while greater SRS during systole clearly indicates electrical dyssynchrony, it also predicts mechanical viability and healthy cross-bridge cycling rates in the myocardium. Hence, SRS positively indicates response to CRT.

Integrated Particle- and Reactor-Scale Simulation of Pine Pyrolysis in a Fluidized Bed

We report results from a multiscale computational modeling study of biomass fast pyrolysis in an experimental laboratory reactor that combined the hydrodynamics predicted by a two-fluid model (TFM)...

Stimulation Effect of Inter-subject Variability in tDCS-Multi-scale Modeling Study.

Transcranial direct current stimulation (tDCS) is an emerging non-invasive neuromodulation method that is convenient and popular in clinical use. However, there is a practical issue in applying tDCS; it is difficult to optimize the montage for each individual because of inherent inter-subject variability. Thus, the stimulation effect of such individual anatomical head variation has been investigated using anatomically realistic models. In this work, we developed a multi-scale computational model, which combined head models based on magnetic resonance imaging (MRI) and multi-compartmental neuronal models of pyramidal neurons (PNs), to investigate both the macroscopic and microscopic effects oftDCS. We constructed three different head models and compared the stimulation effects of tDCS in the primary cortex area (Brodmann area 4) with respect to the electric fields induced and steady-state membrane polarizations. We observed that the electric field behavior and induced somatic polarizations varied across subjects in accordance with the thicknesses of cerebrospinal fluid (CSF) and skull measured in each model. Thus, we concluded that variations in the CSF and skull might be correlated with the effects of tDCS.

Melt transport and mantle assimilation at Atlantis Massif (IODP Site U1309): Constraints from geochemical modeling

Olivine-rich troctolites (>70% olivine) reveal that extensive melt impregnation of pre-existing olivine-rich lithologies participate to the building of slow spread oceanic crust. To constrain their origin and their impact on the structure and geochemistry of oceanic crust, we realized a multi-scale petro-structural, geochemical, and numerical modeling study of olivine-rich troctolites drilled at IODP Hole U1309D (Atlantis Massif, Mid-Atlantic Ridge 30°N). Discrete intervals of olivine-rich troctolites display sharp to diffuse contacts with neighboring troctolites or gabbros. Their texture is characterized by plastically deformed (high temperature imprint), corroded coarse-grained to undeformed fine-grained olivine embayed in poikilitic clinopyroxene and plagioclase. Olivine crystallographic preferred orientations show weak [001] clusters. Olivine has variable major and minor element compositions, but similar fractionated REE (DyN/YbN = 0.04–0.11). We distinguished three types of olivine-rich troctolites based on microstructure, texture and mineral composition. Olivine-rich troctolites 1 and 2 display sharp contacts with adjacent lithologies. Type 1 has modal olivine <75%, occurring mainly as single rounded grains with primitive compositions (Mg# = 85–86), and associated with high Mg# clinopyroxene. Type 2 has higher olivine modes (>75%), dominantly forming aggregates, showing more evolved compositions (Mg# = 83–84) and associated with slightly lower Mg# clinopyroxene. These variations of olivine modes and compositions are in contrast to common trends of magmatic crystallization that predicts decreasing modal olivine with melt differentiation towards evolved compositions. Type 3 has diffuse contacts with gabbroic veins and modal olivine overlapping those of types 1 and 2. Chemical traverses along principal crystallographic axes of olivine are flat, suggesting local equilibrium between olivine and neighboring phases. Mineral modes and compositions, together with textures and microstructures, suggest that olivine-rich troctolites formed after melt-rock interactions in a reactive porous flow process. Their compositions are best modeled by percolation of primitive MORBs into Hole U1309D impregnated and compositionally heterogeneous harzburgites, triggering orthopyroxene dissolution, followed by olivine assimilation and concomitant crystallization of clinopyroxene and plagioclase. Modeling shows that Ni variations in olivine at constant Mg# are mantle inherited. Compositions of olivine-rich troctolite 1 are fitted assuming higher olivine assimilation (Ma = 0.06–0.13) in contrast to olivine-rich troctolites 2 and 3 (Ma = 0.01–0.02). Olivine-rich troctolite 3 was ‘buffered’ by crystallizing reacted melts, progressively more evolved as temperature decreased during a late stage process. We interpret olivine-rich troctolites from the Atlantis Massif as marking local assimilation of harzburgitic mantle into the gabbroic sequence during a period of enhanced magmatism at depth. Our study shows that the distribution and variable compositions of olivine-rich troctolites result from the incipient stages of this process when local spatial variations in mantle rock permeability, probably related to pyroxene distribution, controlled in turn melt transport and mantle-melt interactions.

A multiscale modeling study of particle size effects on the tissue penetration efficacy of drug-delivery nanoparticles

BackgroundParticle size is a key parameter for drug-delivery nanoparticle design. It is believed that the size of a nanoparticle may have important effects on its ability to overcome the transport barriers in biological tissues. Nonetheless, such effects remain poorly understood. Using a multiscale model, this work investigates particle size effects on the tissue distribution and penetration efficacy of drug-delivery nanoparticles.ResultsWe have developed a multiscale spatiotemporal model of nanoparticle transport in biological tissues. The model implements a time-adaptive Brownian Dynamics algorithm that links microscale particle-cell interactions and adhesion dynamics to tissue-scale particle dispersion and penetration. The model accounts for the advection, diffusion, and cellular uptakes of particles. Using the model, we have analyzed how particle size affects the intra-tissue dispersion and penetration of drug delivery nanoparticles. We focused on two published experimental works that investigated particle size effects in in vitro and in vivo tissue conditions. By analyzing experimental data reported in these two studies, we show that particle size effects may appear pronounced in an in vitro cell-free tissue system, such as collagen matrix. In an in vivo tissue system, the effects of particle size could be relatively modest. We provide a detailed analysis on how particle-cell interactions may determine distribution and penetration of nanoparticles in a biological tissue.ConclusionOur work suggests that the size of a nanoparticle may play a less significant role in its ability to overcome the intra-tissue transport barriers. We show that experiments involving cell-free tissue systems may yield misleading observations of particle size effects due to the absence of advective transport and particle-cell interactions.

Multi-Scale Computational Models for Electrical Brain Stimulation.

Electrical brain stimulation (EBS) is an appealing method to treat neurological disorders. To achieve optimal stimulation effects and a better understanding of the underlying brain mechanisms, neuroscientists have proposed computational modeling studies for a decade. Recently, multi-scale models that combine a volume conductor head model and multi-compartmental models of cortical neurons have been developed to predict stimulation effects on the macroscopic and microscopic levels more precisely. As the need for better computational models continues to increase, we overview here recent multi-scale modeling studies; we focused on approaches that coupled a simplified or high-resolution volume conductor head model and multi-compartmental models of cortical neurons, and constructed realistic fiber models using diffusion tensor imaging (DTI). Further implications for achieving better precision in estimating cellular responses are discussed.

Mesoscale Physicochemical Interactions in Lithium–Sulfur Batteries: Progress and Perspective

The shuttle effect and poor conductivity of the discharge products are among the primary impediments and scientific challenges for lithium–sulfur batteries. The lithium–sulfur battery is a complex energy storage system, which involves multistep electrochemical reactions, insoluble polysulfide precipitation in the cathode, soluble polysulfide transport, and self-discharge caused by chemical reactions between polysulfides and Li metal anode. These phenomena happen at different length and time-scales and are difficult to be entirely gauged by experimental techniques. In this paper, we reviewed the multiscale modeling studies on lithium–sulfur batteries: (1) the atomistic simulations were employed to seek alternative materials for mitigating the shuttle effect; (2) the growth kinetics of Li2S film and corresponding surface passivation were investigated by the interfacial model based on findings from atomistic simulations; (3) the nature of Li2S2, which is the only solid intermediate product, was revealed by the density functional theory simulation; and (4) macroscale models were developed to analyze the effect of reaction kinetics, sulfur loading, and transport properties on the cell performance. The challenge for the multiscale modeling approach is translating the microscopic information from atomistic simulations and interfacial model into the meso-/macroscale model for accurately predicting the cell performance.

Effects of protein properties on adsorption and transport in polymer‐grafted ion exchangers: A multiscale modeling study

We use multiscale modeling to study how the molecular properties of a protein affect its adsorption and transport in ion exchange chromatography matrices with either open pores or charged polymers grafted into the pore structure. Coarse‐grained molecular dynamics (MD) simulations of lysozyme, bovine serum albumin, and immunoglobulin show that higher protein net charge leads to greater partitioning into the polymer‐grafted pore space but slower diffusion there due to favorable electrostatic interactions, while larger size decreases both pore space partitioning and diffusion due to steric effects of the polymers. Mass transfer simulations based on the MD results show that the polymer‐grafted systems can enhance the adsorption kinetics if pore space partitioning and diffusion are both sufficiently high. The simulations illustrate that to achieve fast adsorption kinetics, there is a tradeoff between favorable binding and rapid diffusion which largely depends on the charge and size of the protein. © 2017 American Institute of Chemical Engineers AIChE J, 63: 4564–4575, 2017

The impact of simulated mesoscale convective systems on global precipitation: A multiscale modeling study.

The importance of precipitating mesoscale convective systems (MCSs) has been quantified from TRMM precipitation radar and microwave imager retrievals. MCSs generate more than 50% of the rainfall in most tropical regions. MCSs usually have horizontal scales of a few hundred kilometers (km); therefore, a large domain with several hundred km is required for realistic simulations of MCSs in cloud-resolving models (CRMs). Almost all traditional global and climate models do not have adequate parameterizations to represent MCSs. Typical multiscale modeling frameworks (MMFs) may also lack the resolution (4 km grid spacing) and domain size (128 km) to realistically simulate MCSs. The impact of MCSs on precipitation is examined by conducting model simulations using the Goddard Cumulus Ensemble (GCE, a CRM) model and Goddard MMF that uses the GCEs as its embedded CRMs. Both models can realistically simulate MCSs with more grid points (i.e., 128 and 256) and higher resolutions (1 or 2 km) compared to those simulations with fewer grid points (i.e., 32 and 64) and low resolution (4 km). The modeling results also show the strengths of the Hadley circulations, mean zonal and regional vertical velocities, surface evaporation, and amount of surface rainfall are weaker or reduced in the Goddard MMF when using more CRM grid points and higher CRM resolution. In addition, the results indicate that large-scale surface evaporation and wind feedback are key processes for determining the surface rainfall amount in the GMMF. A sensitivity test with reduced sea surface temperatures shows both reduced surface rainfall and evaporation.

Benchmarks and Tests of a Multidimensional Cluster Dynamics Model of Helium Implantation in Tungsten

We present a hierarchical multiscale modeling study of implanted helium (He) segregation near grain boundaries (GBs) of tungsten. We extend our spatially dependent cluster dynamics model to two spatial dimensions in order to take into account the biased drift of mobile He clusters toward the GBs observed in atomic-scale simulations. We are able to reproduce the results from large-scale molecular dynamics simulations near and away from the GBs at low fluence with the extended cluster dynamics model. We suggest and verify that the sink (surface and GB) strengths are attenuated by the increasing concentration of He clusters at high fluence. This cluster dynamics model continues to set the stage for development of fully atomistically informed, coarse-grained models for computationally efficient predictions of He retention and surface morphological evolution, advancing progress toward the goal of efficient and optimal design of plasma-facing components.

A multi-world agent-based model working at several spatial and temporal scales for simulating complex geographic systems

Interest in the modelling and simulation of complex systems with processes occurring at several spatial and temporal scales is increasing, particularly in biological, historical and geographic studies. In this multi-scale modelling study, we propose a generic model to account for processes operating at several scales. In this approach, a ‘world’ corresponds to a complete and self-sufficient submodel with its own places, agents, spatial resolution and temporal scale. Represented worlds can be nested: a world (with new scales) may have a greater level of detail than the model at the next level up, making it possible to study phenomena with greater precision. This process can be reiterated, to create additional scales, with no formal limit. Worlds’ simulations can be triggered simultaneously or in cascade. Within a world, agents can choose destinations in other worlds, to which they can travel using routes and inter-world ‘gates’. Once they arrive in a destination world, the agents ‘fit’ the new scale. An agent in a given world can also perceive and interact with other agents, regardless of the world to which they belong, provided they are encompassed by its perception disc. We present and discuss an application of this model to the issue of the spread of black rats by means of commercial transportation in Senegal (West Africa).

Cigarette Smoke-Induced Chronic Inflammation Leading to COPD and Lung Cancer: A Multiscale Modeling Study

Cigarette Smoke-Induced Chronic Inflammation Leading to COPD and Lung Cancer: A Multiscale Modeling Study

Synthesis, biological activity and multiscale molecular modeling studies for coumaryl-carboxamide derivatives as selective carbonic anhydrase IX inhibitors

New coumaryl-carboxamide derivatives with the thiourea moiety as a linker between the alkyl chains and/or the heterocycle nucleus were synthesized and their inhibitory activity against the human carbonic anhydrase (hCA) isoforms hCA I, II, VII and IX were evaluated. While the hCA I, II and VII isoforms were not inhibited by the investigated compounds, the tumour-associated isoform hCA IX was inhibited in the high nanomolar range. 2-Oxo-N-((2-(pyrrolidin-1-yl)ethyl)carbamothioyl)-2H-chromene-3-carboxamide (e11) exhibited a selective inhibitory action against hCA IX with the Ki of 107.9 nM. In order to better understand the inhibitory profiles of studied molecules, multiscale molecular modeling approaches were used. Different molecular docking algorithms were used to investigate binding poses and predicted binding energies of studied compounds at the active sites of the CA I, II, VII and IX isoforms.

Adsorption on a nanoporous organic polymer for clean energy applications: A multiscale modeling study using density functional tight binding approach

Adsorption of carbon dioxide, methane and hydrogen on the novel ferrocenyl-nanoporous organic polymer was studied from an approximate density-functional method. Geometric, energetic and electronic parameters are obtained using the self-consistent charge density functional tight binding (SCC-DFTB) spin polarized approach and prove a mechanism of adsorption governed by physisorption processes. In order to gain a deeper understanding of the effect of temperature on the adsorption-desorption process, an SCC-DFTB/MD simulation is implemented which enabled a satisfactory agreement with the experimental results reported in the literature.