Journal articles: 'Molecular simulation techniques'

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Gruenhut, S., M. Amini, D. R. Macfarlane, and P. Meakin. "Molecular Dynamics Glass Simulation and Equilibration Techniques." Molecular Simulation 19, no. 3 (June 1997): 139–60. http://dx.doi.org/10.1080/08927029708024147.

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Scheraga, Harold A., Mey Khalili, and Adam Liwo. "Protein-Folding Dynamics: Overview of Molecular Simulation Techniques." Annual Review of Physical Chemistry 58, no. 1 (May 2007): 57–83. http://dx.doi.org/10.1146/annurev.physchem.58.032806.104614.

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Smith, Andrea, Xin Dong, and Vijaya Raghavan. "An Overview of Molecular Dynamics Simulation for Food Products and Processes." Processes 10, no. 1 (January 7, 2022): 119. http://dx.doi.org/10.3390/pr10010119.

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Molecular dynamics (MD) simulation is a particularly useful technique in food processing. Normally, food processing techniques can be optimized to favor the creation of higher-quality, safer, more functional, and more nutritionally valuable food products. Modeling food processes through the application of MD simulations, namely, the Groningen Machine for Chemical Simulations (GROMACS) software package, is helpful in achieving a better understanding of the structural changes occurring at the molecular level to the biomolecules present in food products during processing. MD simulations can be applied to define the optimal processing conditions required for a given food product to achieve a desired function or state. This review presents the development history of MD simulations, provides an in-depth explanation of the concept and mechanisms employed through the running of a GROMACS simulation, and outlines certain recent applications of GROMACS MD simulations in the food industry for the modeling of proteins in food products, including peanuts, hazelnuts, cow’s milk, soybeans, egg whites, PSE chicken breast, and kiwifruit.

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McCluskey, Andrew R., James Grant, Adam R. Symington, Tim Snow, James Doutch, Benjamin J. Morgan, Stephen C. Parker, and Karen J. Edler. "An introduction to classical molecular dynamics simulation for experimental scattering users." Journal of Applied Crystallography 52, no. 3 (May 7, 2019): 665–68. http://dx.doi.org/10.1107/s1600576719004333.

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Classical molecular dynamics simulations are a common component of multi-modal analyses of scattering measurements, such as small-angle scattering and diffraction. Users of these experimental techniques often have no formal training in the theory and practice of molecular dynamics simulation, leading to the possibility of these simulations being treated as a `black box' analysis technique. This article describes an open educational resource (OER) designed to introduce classical molecular dynamics to users of scattering methods. This resource is available as a series of interactive web pages, which can be easily accessed by students, and as an open-source software repository, which can be freely copied, modified and redistributed by educators. The topics covered in this OER include classical atomistic modelling, parameterizing interatomic potentials, molecular dynamics simulations, typical sources of error and some of the approaches to using simulations in the analysis of scattering data.

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Londhe, Ashwini Machhindra, Changdev Gorakshnath Gadhe, Sang Min Lim, and Ae Nim Pae. "Investigation of Molecular Details of Keap1-Nrf2 Inhibitors Using Molecular Dynamics and Umbrella Sampling Techniques." Molecules 24, no. 22 (November 12, 2019): 4085. http://dx.doi.org/10.3390/molecules24224085.

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In this study, we investigate the atomistic details of Keap1-Nrf2 inhibitors by in-depth modeling techniques, including molecular dynamics (MD) simulations, and the path-based free energy method of umbrella sampling (US). The protein–protein interaction (PPI) of Keap1-Nrf2 is implicated in several neurodegenerative diseases like cancer, diabetes, and cardiomyopathy. A better understanding of the five sub-pocket binding sites for Nrf2 (ETGE and DLG motifs) inside the Kelch domain would expedite the inhibitor design process. We selected four protein–ligand complexes with distinct co-crystal ligands and binding occupancies inside the Nrf2 binding site. We performed 100 ns of MD simulation for each complex and analyzed the trajectories. From the results, it is evident that one ligand (1VV) has flipped inside the binding pocket, whereas the remaining three were stable. We found that Coulombic (Arg483, Arg415, Ser363, Ser508, and Ser602) and Lennard–Jones (Tyr525, Tyr334, and Tyr572) interactions played a significant role in complex stability. The obtained binding free energy values from US simulations were consistent with the potencies of simulated ligands. US simulation highlight the importance of basic and aromatic residues in the binding pocket. A detailed description of the dissociation process brings valuable insight into the interaction of the four selected protein–ligand complexes, which could help in the future to design more potent PPI inhibitors.

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Skipper, N. T. "Computer simulation of aqueous pore fluids in 2:1 clay minerals." Mineralogical Magazine 62, no. 5 (October 1998): 657–67. http://dx.doi.org/10.1180/002646198548043.

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AbstractMonte Carlo and molecular dynamics computer simulations are now able to provide detailed information concerning the structure, dynamics, and thermodynamics of pore fluids in 2:1 clays. This article will discuss interparticle interaction potentials currently available for atomistic simulations of clay-water systems, and will describe how computational techniques can be applied to modelling of clay systems. Some recent simulation studies of 2:1 clay hydration will then be reviewed. Comparison with experimental data promotes confidence in the molecular models and simulation techniques, and points to exciting future prospects.

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Stack, Andrew G., and Paul R. C. Kent. "Geochemical reaction mechanism discovery from molecular simulation." Environmental Chemistry 12, no. 1 (2015): 20. http://dx.doi.org/10.1071/en14045.

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Environmental context Computational simulations are providing an increasingly useful way to isolate specific geochemical and environmental reactions and to test how important they are to the overall rate. In this review, we summarise a few ways that one can simulate a reaction and discuss each technique’s overall strengths and weaknesses. Selected case studies illustrate how these techniques have helped to improve our understanding for geochemical and environmental problems. Abstract Methods to explore reactions using computer simulation are becoming increasingly quantitative, versatile and robust. In this review, a rationale for how molecular simulation can help build better geochemical kinetics models is first given. Some common methods are summarised that geochemists use to simulate reaction mechanisms, specifically classical molecular dynamics and quantum chemical methods and their strengths and weaknesses are also discussed. Useful tools such as umbrella sampling and metadynamics that enable one to explore reactions are discussed. Several case studies wherein geochemists have used these tools to understand reaction mechanisms are presented, including water exchange and sorption on aqueous species and mineral surfaces, surface charging, crystal growth and dissolution, and electron transfer. The effect that molecular simulation has had on our understanding of geochemical reactivity is highlighted in each case. In the future, it is anticipated that molecular simulation of geochemical reaction mechanisms will become more commonplace as a tool to validate and interpret experimental data, and provide a check on the plausibility of geochemical kinetic models.

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Baskes, Michael, Murray Daw, Brian Dodson, and Stephen Foiles. "Atomic-Scale Simulation in Materials Science." MRS Bulletin 13, no. 2 (February 1988): 28–35. http://dx.doi.org/10.1557/s0883769400066331.

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Realistic simulation of the atomic-scale properties of complex systems has long been a goal of scientists interested in the behavior of condensed matter. Until recently, the role of atomistic simulation techniques has been to address rather idealized problems in statistical mechanics. Treatment of more realistic materials has been uncommon not because suitable approaches toward simulating such materials were unknown, but rather because the computer power available was inadequate. Recently, major advances have occurred in the complexity of systems subject to atomistic simulation, primarily due to a dramatic increase in availability of computer power. These new capabilities have driven the development of atomic-scale descriptions of real materials accurate enough for atomistic simulation of a wide range of specific materials science problems.In this section, we will outline several of the techniques used to simulate the microscopic behavior of an atomistic system. The first method introduced for atomistic simulation was the molecular dynamics technique, in which Newton's equations of motion for the individual atoms are integrated numerically for given interatomic and external forces. One of the first uses of this technique was the study, by Fermi, Pasta, and Ulam, of randomization of vibrational energy in a one-dimensional chain of atoms. Although the results of this initial application were to some extent unsatisfactory, the molecular dynamics technique has since been applied to a wide range of problems in the statistical mechanics of condensed media.

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Kobayashi, Yasunori, Seiichi Takami, Momoji Kubo, and Akira Miyamoto. "Non-equilibrium molecular simulation studies on gas separation by microporous membranes using dual ensemble molecular simulation techniques." Fluid Phase Equilibria 194-197 (March 2002): 319–26. http://dx.doi.org/10.1016/s0378-3812(01)00690-2.

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BRENNAN, JOHN K., and BETSY M. RICE. "Efficient determination of Hugoniot states using classical molecular simulation techniques." Molecular Physics 101, no. 22 (November 20, 2003): 3309–22. http://dx.doi.org/10.1080/00268970310001636404.

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Rahmat, Meysam, and Pascal Hubert. "Molecular Dynamics Simulation of Single-Walled Carbon Nanotube – PMMA Interaction." Journal of Nano Research 18-19 (July 2012): 117–28. http://dx.doi.org/10.4028/www.scientific.net/jnanor.18-19.117.

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Mechanical performance of nanocomposites is strongly dependent on the interaction properties between the matrix and the reinforcement. Therefore, the aim of this work is to investigate the carbon nanotube – polymer interaction in nanocomposites. With the ever-increasing power of computers, and enormous advantage of parallel computing techniques, molecular dynamics is the favourite technique to simulate various atomic and molecular systems for this application. In order to simulate nanocomposites using molecular dynamics techniques, a stepwise approach was followed. First, a single-walled carbon nanotube was modelled as the reinforcing material. The validity of the model was examined by applying simple tension boundary conditions and comparing the results with the literature. Next, PMMA chains, with different geometries and molecular weights, were modelled employing the chemical potentials extracted from the literature. The last step included the modelling of the nanotubes surrounded by the matrix material and the investigation of the energy minimization for the system. Based on the results, the non-covalent interaction energy between a single-walled carbon nanotube and the PMMA matrix was obtained.

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Li, Jiu. "Multiscale Modeling Techniques Based on Molecular Structure and Elastic Properties." Applied Mechanics and Materials 312 (February 2013): 438–41. http://dx.doi.org/10.4028/www.scientific.net/amm.312.438.

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Based on the principle of using atomistic force field, and the use of ultra-flexible multi-scale modeling techniques to predict the polycarbonate and polyimide polymer molecular structure and the elastic properties of the system. The model combines molecular modeling and nonlinear continuum mechanics basic principles, to simulate and predict the behavior of the material properties of the polymer molecular structure. For the polymer structure and properties, using a plurality of force field simulation to predict the contrast, and binding experiments measured polymer performance value, using static and dynamic molecular simulation technology for molecular mechanics energy minimization to solve.

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Anderson, Ian, Ron Ghosh, and Emmanuel Farhi. "Simulation techniques discussed at SINS." Neutron News 11, no. 4 (January 2000): 3–4. http://dx.doi.org/10.1080/10448630008233752.

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Farhadian, Nafiseh. "A Mimetic Amorphous Active Carbon Model Using Molecular Dynamics Simulation." Advanced Materials Research 829 (November 2013): 199–203. http://dx.doi.org/10.4028/www.scientific.net/amr.829.199.

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Porous carbons are disordered materials with applications in many areas such as catalysis, molecular separation, and energy storage/conversion. Among porous materials, active carbons are the most popular materials in separation processes. They are non-crystalline materials with heterogeneous pore structures. This property does not permit accurate structural determinations by diffraction techniques. Thus only limited structural information can be extracted from experimental techniques. Consequently, a molecular model of nanoporous carbon can't be constructed that is based solely on experimental data. Computer simulation techniques provide an alternative way to tackle this problem. So, in this study, the synthesis process of an amorphous active carbon is investigated using molecular dynamics simulation. Simulations are carried out at constant temperature in the box containing specific numbers of pure carbon sheets. Two different types of ensembles have been used for simulation includingNPTandNVT. Calculated results show that the final structure of porous carbons is in agreement with SEM images of some commercial active carbons. Also, results indicate that the final structure is consisted of three different pore size (r) zones: r<2 nm which produces micro pores,250 nm which named macro pores. These observations are exactly the same as what is observed in experiments. These various pore sizes especially micro and meso pores are observed in radial distribution function curve, too. At last, the temperature effect on the pore size is investigated. Three different temperatures of 973K, 1073 K and 1173 K are applied for the simulation. Calculated results show that increasing the temperature does not have any significant effects on the pore size and structure.

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Walther, J. H., and P. Koumoutsakos. "Molecular Dynamics Simulation of Nanodroplet Evaporation." Journal of Heat Transfer 123, no. 4 (November 20, 2000): 741–48. http://dx.doi.org/10.1115/1.1370517.

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Molecular dynamics simulations are used to study the sub-critical evaporation of a nanometer-size droplet at 300 K and 3 MPa. Classical molecular dynamics techniques are combined with an adaptive tree data structure for the construction of the neighbor lists, allowing efficient simulations using hundreds of thousands of molecules. We present a systematic convergence study of the method demonstrating its convergence for heat conduction problems in submicron scales. These high resolution simulations compute values of the evaporation coefficient that are in excellent agreement with theoretical predictions.

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Burrage, K., J. Hancock, A. Leier, and D. V. Nicolau. "Modelling and simulation techniques for membrane biology." Briefings in Bioinformatics 8, no. 4 (March 29, 2007): 234–44. http://dx.doi.org/10.1093/bib/bbm033.

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CAO, Liao-Ran, Chun-Yu ZHANG, Ding-Lin ZHANG, Hui-Ying CHU, Yue-Bin ZHANG, and Guo-Hui LI. "Recent Developments in Using Molecular Dynamics Simulation Techniques to Study Biomolecules." Acta Physico-Chimica Sinica 33, no. 7 (2017): 1354–65. http://dx.doi.org/10.3866/pku.whxb201704144.

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MORITA, Hiroshi. "General Techniques of Coarse-grained Molecular Dynamics Simulation for Rubber Materials." NIPPON GOMU KYOKAISHI 89, no. 6 (2016): 157–63. http://dx.doi.org/10.2324/gomu.89.157.

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Fan, H. "Refinement of homology-based protein structures by molecular dynamics simulation techniques." Protein Science 13, no. 1 (January 1, 2004): 211–20. http://dx.doi.org/10.1110/ps.03381404.

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Chakraborti, Tamaghna, Anish Desouza, and Jhumpa Adhikari. "Prediction of Thermodynamic Properties of Levulinic Acid via Molecular Simulation Techniques." ACS Omega 3, no. 12 (December 31, 2018): 18877–84. http://dx.doi.org/10.1021/acsomega.8b02793.

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Schwichtenberg, H., G. Winter, and H. Wallmeier. "Acceleration of molecular mechanic simulation by parallelization and fast multipole techniques." Parallel Computing 25, no. 5 (May 1999): 535–46. http://dx.doi.org/10.1016/s0167-8191(99)00014-9.

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Sarkar, Daipayan, Martin Kulke, and Josh V. Vermaas. "LongBondEliminator: A Molecular Simulation Tool to Remove Ring Penetrations in Biomolecular Simulation Systems." Biomolecules 13, no. 1 (January 5, 2023): 107. http://dx.doi.org/10.3390/biom13010107.

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We develop a workflow, implemented as a plugin to the molecular visualization program VMD, that can fix ring penetrations with minimal user input. LongBondEliminator, detects ring piercing artifacts by the long, strained bonds that are the local minimum energy conformation during minimization for some assembled simulation system. The LongBondEliminator tool then automatically treats regions near these long bonds using multiple biases applied through NAMD. By combining biases implemented through the collective variables module, density-based forces, and alchemical techniques in NAMD, LongBondEliminator will iteratively alleviate long bonds found within molecular simulation systems. Through three concrete examples with increasing complexity, a lignin polymer, an viral capsid assembly, and a large, highly glycosylated protein aggrecan, we demonstrate the utility for this method in eliminating ring penetrations from classical MD simulation systems. The tool is available via gitlab as a VMD plugin, and has been developed to be generically useful across a variety of biomolecular simulations.

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Sofos, Filippos, and Theodoros E. Karakasidis. "Machine Learning Techniques for Fluid Flows at the Nanoscale." Fluids 6, no. 3 (March 1, 2021): 96. http://dx.doi.org/10.3390/fluids6030096.

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Simulations of fluid flows at the nanoscale feature massive data production and machine learning (ML) techniques have been developed during recent years to leverage them, presenting unique results. This work facilitates ML tools to provide an insight on properties among molecular dynamics (MD) simulations, covering missing data points and predicting states not previously located by the simulation. Taking the fluid flow of a simple Lennard-Jones liquid in nanoscale slits as a basis, ML regression-based algorithms are exploited to provide an alternative for the calculation of transport properties of fluids, e.g., the diffusion coefficient, shear viscosity and thermal conductivity and the average velocity across the nanochannels. Through appropriate training and testing, ML-predicted values can be extracted for various input variables, such as the geometrical characteristics of the slits, the interaction parameters between particles and the flow driving force. The proposed technique could act in parallel to simulation as a means of enriching the database of material properties, assisting in coupling between scales, and accelerating data-based scientific computations.

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Thompson, Scott, Corinne Stone, Brendan Howlin, and Ian Hamerton. "Exploring Structure–Property Relationships in Aromatic Polybenzoxazines Through Molecular Simulation." Polymers 10, no. 11 (November 12, 2018): 1250. http://dx.doi.org/10.3390/polym10111250.

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A series of commercial difunctional benzoxazine monomers are characterized using thermal and thermo-mechanical techniques before constructing representative polymer networks using molecular simulation techniques. Good agreement is obtained between replicate analyses and for the kinetic parameters obtained from differential scanning calorimetry data (and determined using the methods of Kissinger and Ozawa). Activation energies range from 85 to 108 kJ/mol (Kissinger) and 89 to 110 kJ/mol (Ozawa) for the uncatalyzed thermal polymerization reactions, which achieve conversions of between 85% and 97%. Glass transition temperatures determined from differential scanning calorimetry and dynamic mechanical thermal analysis are comparable, ranging from BA-a (151 °C, crosslink density 3.6 × 10−3 mol cm−3) containing the bisphenol A moiety to BP-a, based on a phenolphthalein bridge (239 to 256 °C, crosslink density 5.5 to 18.4 × 10−3 mol cm−3, depending on formulation). Molecular dynamics simulations of the polybenzoxazines generally agree well with empirical data, indicating that representative networks have been modelled.

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Kadupitiya, JCS, Geoffrey C. Fox, and Vikram Jadhao. "Machine learning for parameter auto-tuning in molecular dynamics simulations: Efficient dynamics of ions near polarizable nanoparticles." International Journal of High Performance Computing Applications 34, no. 3 (January 14, 2020): 357–74. http://dx.doi.org/10.1177/1094342019899457.

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Simulating the dynamics of ions near polarizable nanoparticles (NPs) using coarse-grained models is extremely challenging due to the need to solve the Poisson equation at every simulation timestep. Recently, a molecular dynamics (MD) method based on a dynamical optimization framework bypassed this obstacle by representing the polarization charge density as virtual dynamic variables and evolving them in parallel with the physical dynamics of ions. We highlight the computational gains accessible with the integration of machine learning (ML) methods for parameter prediction in MD simulations by demonstrating how they were realized in MD simulations of ions near polarizable NPs. An artificial neural network–based regression model was integrated with MD simulation and predicted the optimal simulation timestep and optimization parameters characterizing the virtual system with 94.3% success. The ML-enabled auto-tuning of parameters generated accurate dynamics of ions for ≈ 10 million steps while improving the stability of the simulation by over an order of magnitude. The integration of ML-enhanced framework with hybrid Open Multi-Processing / Message Passing Interface (OpenMP/MPI) parallelization techniques reduced the computational time of simulating systems with thousands of ions and induced charges from thousands of hours to tens of hours, yielding a maximum speedup of ≈ 3 from ML-only acceleration and a maximum speedup of ≈ 600 from the combination of ML and parallel computing methods. Extraction of ionic structure in concentrated electrolytes near oil–water emulsions demonstrates the success of the method. The approach can be generalized to select optimal parameters in other MD applications and energy minimization problems.

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Gong, Xiping, Yumeng Zhang, and Jianhan Chen. "Advanced Sampling Methods for Multiscale Simulation of Disordered Proteins and Dynamic Interactions." Biomolecules 11, no. 10 (September 28, 2021): 1416. http://dx.doi.org/10.3390/biom11101416.

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Intrinsically disordered proteins (IDPs) are highly prevalent and play important roles in biology and human diseases. It is now also recognized that many IDPs remain dynamic even in specific complexes and functional assemblies. Computer simulations are essential for deriving a molecular description of the disordered protein ensembles and dynamic interactions for a mechanistic understanding of IDPs in biology, diseases, and therapeutics. Here, we provide an in-depth review of recent advances in the multi-scale simulation of disordered protein states, with a particular emphasis on the development and application of advanced sampling techniques for studying IDPs. These techniques are critical for adequate sampling of the manifold functionally relevant conformational spaces of IDPs. Together with dramatically improved protein force fields, these advanced simulation approaches have achieved substantial success and demonstrated significant promise towards the quantitative and predictive modeling of IDPs and their dynamic interactions. We will also discuss important challenges remaining in the atomistic simulation of larger systems and how various coarse-grained approaches may help to bridge the remaining gaps in the accessible time- and length-scales of IDP simulations.

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BULUT, MEVLUT, and RENATO P. CAMATA. "A GENERALIZED CELL METHOD FOR HARD DISK MOLECULAR DYNAMICS SIMULATION OF POLYDISPERSE SYSTEMS." International Journal of Modern Physics C 18, no. 09 (September 2007): 1407–16. http://dx.doi.org/10.1142/s0129183107011418.

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Hard Disk Molecular Dynamics (HDMD) techniques often exhibit significant loss in calculation speed when applied to the simulation of highly polydisperse particle systems. The collision rate of the reported algorithms may be lower by as much as two orders of magnitude if compared to the collision rate of a monodisperse system of the same number of particles. This is mainly due to the fact that the rectangular cells in the simulation domain used in HDMD methods must meet a certain size criterion. In this paper, we introduce a cell technique that removes the requirement on the cell size enabling simulation of particles with sizes much larger than the cell size. This approach improves the collision rates in the simulation of tested polydisperse systems by factors ranging from 5.5 to 57 depending on the size distribution of the particle population simulated. This may enable the simulation of grand canonical systems in which the size and the number of particles can change throughout the simulation. The technique is compatible with the simulation of disk-like as well as irregularly shaped particles and can be extended to three dimensions.

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Procacci, Piero. "Does Hamiltonian Replica Exchange via Lambda-Hopping Enhance the Sampling in Alchemical Free Energy Calculations?" Molecules 27, no. 14 (July 11, 2022): 4426. http://dx.doi.org/10.3390/molecules27144426.

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In the context of computational drug design, we examine the effectiveness of the enhanced sampling techniques in state-of-the-art free energy calculations based on alchemical molecular dynamics simulations. In a paradigmatic molecule with competition between conformationally restrained E and Z isomers whose probability ratio is strongly affected by the coupling with the environment, we compare the so-called λ-hopping technique to the Hamiltonian replica exchange methods assessing their convergence behavior as a function of the enhanced sampling protocols (number of replicas, scaling factors, simulation times). We found that the pure λ-hopping, commonly used in solvation and binding free energy calculations via alchemical free energy perturbation techniques, is ineffective in enhancing the sampling of the isomeric states, exhibiting a pathological dependence on the initial conditions. Correct sampling can be restored in λ-hopping simulation by the addition of a “hot-zone” scaling factor to the λ-stratification (FEP+ approach), provided that the additive hot-zone scaling factors are tuned and optimized using preliminary ordinary replica-exchange simulation of the end-states.

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Zhao, Yungang, Meifen Li, and Yan Shao. "Effect of demineralization on Yimin lignite by experiments and molecular simulation techniques." Journal of Molecular Structure 1269 (December 2022): 133837. http://dx.doi.org/10.1016/j.molstruc.2022.133837.

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Smith, William R., Magda Francová, Marian Kowalski, and Ivo Nezbeda. "Refrigeration cycle design for refrigerant mixtures by molecular simulation." Collection of Czechoslovak Chemical Communications 75, no. 4 (2010): 383–91. http://dx.doi.org/10.1135/cccc2009544.

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We describe a molecular simulation methodology to calculate the properties of a vapor-compression refrigeration cycle and its Coefficient of Performance, in the case when the refrigerant is a mixture. The methodology requires only a molecular force-field model for each refrigerant pure component and, for improved accuracy, an expression for the vapor pressure of each pure component as a function of temperature. Both may be constructed by means of theoretical approaches in combination with minimal amounts of experimental data, and the latter may also be estimated by empirical formulae with reasonable accuracy. The approach involves a combination of several available molecular-level computer simulation techniques for the individual processes of the cycle. This work extends our earlier study to cases when the refrigerant is a pure fluid. The mixture refrigerant simulations entail the calculation of bubble- and dew-point curves for the refrigerant mixtures, and we propose a new approach for dew-point calculations via molecular simulation. We compare results for a test case with those obtained from the Equation-of-State model used in the standard REFPROP software and with experimental data for a commercially available refrigerant mixture of R32 (CH2F2) and R143a (CH2FCF3).

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Kadau, Kai, John L. Barber, Timothy C. Germann, Brad L. Holian, and Berni J. Alder. "Atomistic methods in fluid simulation." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 368, no. 1916 (April 13, 2010): 1547–60. http://dx.doi.org/10.1098/rsta.2009.0218.

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Atomistic methods, such as molecular dynamics and direct simulation Monte Carlo, constitute a powerful and growing set of techniques for fluid-dynamics simulation. The more fundamental nature of such methods, which exhibit nonlinear transport effects and small-scale fluctuations, extends their modelling accuracy to a significantly wider range of scales and regimes than the more traditional Navier–Stokes-based continuum fluid-simulation techniques. In this paper, we describe the current state of the art in atomistic fluid simulation, from both a theoretical and a computational standpoint, and outline the advantages and limitations of such methods. In addition, we present an overview of some recent atomistic-simulation results on fluid instabilities and on the physical scaling of atomistic techniques. Finally, we suggest possible avenues of future research in the field.

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Schuller, Ivan K. "Molecular Dynamics Simulation of Epitaxial Growth." MRS Bulletin 13, no. 11 (November 1988): 23–28. http://dx.doi.org/10.1557/s0883769400063880.

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The growth of thin films has been instrumental in the study of many areas of material science, physics, metallurgy, and chemistry and is an important ingredient in the development of many devices. Although experimental studies have been extensively pursued for many years, theoretical studies have only been performed using model calculations which rely on a number of unknown parameters a priori. Only recently have attempts been made to understand thin film growth using realtime numerical simulation. The main reason for the recent increase of such studies is the development of computers capable of tackling a problem of the magnitude required to understand thin film growth. The phenomena present in thin film growth occur for systems containing many particles (e.g., columnar growth) and long relaxation times, which strain the capabilities presently available in modern supercomputers. Further increases in computational power might bring a number of important problems within reach and improve our understanding of thin film growth at the microscopic level.I will present a number of epitaxial growth studies we have performed using molecular dynamics (MD) techniques. I will show that a number of properties predicted by these calculations are in good agreement with experimental observations. These include the microcrystalline and epitaxial growth of metal films, the growth of amorphous films in mixtures of metals, and the vapor phase growth of silicon. Finally, I will outline several important studies yet to be implemented.

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Cheng, Yaoshuang, and Shiling Yuan. "Emulsification of Surfactant on Oil Droplets by Molecular Dynamics Simulation." Molecules 25, no. 13 (June 30, 2020): 3008. http://dx.doi.org/10.3390/molecules25133008.

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Heavy oil in crude oil flooding is extremely difficult to extract due to its high viscosity and poor fluidity. In this paper, molecular dynamics simulation was used to study the emulsification behavior of sodium dodecyl sulfonate (SDSn) micelles on heavy oil droplets composed of asphaltenes (ASP) at the molecular level. Some analyzed techniques were used including root mean square displacement, hydrophile-hydrophobic area of an oil droplet, potential of mean force, and the number of hydrogen bonds between oil droplet and water phase. The simulated results showed that the asphaltene with carboxylate groups significantly enhances the hydration layer on the surface of oil droplets, and SDSn molecules can change the strength of the hydration layer around the surface of the oil droplets. The water bridge structure between both polar heads of the surfactant was commonly formed around the hydration layer of the emulsified oil droplet. During the emulsification of heavy oil, the ratio of hydrophilic hydrophobic surface area around an oil droplet is essential. Molecular dynamics method can be considered as a helpful tool for experimental techniques at the molecular level.

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Perches, Sara, M. Victoria Collados, and Jorge Ares. "Retinal Image Simulation of Subjective Refraction Techniques." PLOS ONE 11, no. 3 (March 3, 2016): e0150204. http://dx.doi.org/10.1371/journal.pone.0150204.

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Hashmi, Abdul Wahab, Harlal Singh Mali, Anoj Meena, Kuldeep K. Saxena, Ana Pilar Valerga Puerta, Chander Prakash, Dharam Buddhi, J. P. Davim, and Dalael Saad Abdul-Zahra. "Understanding the Mechanism of Abrasive-Based Finishing Processes Using Mathematical Modeling and Numerical Simulation." Metals 12, no. 8 (August 8, 2022): 1328. http://dx.doi.org/10.3390/met12081328.

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Recent advances in technology and refinement of available computational resources paved the way for the extensive use of computers to model and simulate complex real-world problems difficult to solve analytically. The appeal of simulations lies in the ability to predict the significance of a change to the system under study. The simulated results can be of great benefit in predicting various behaviors, such as the wind pattern in a particular region, the ability of a material to withstand a dynamic load, or even the behavior of a workpiece under a particular type of machining. This paper deals with the mathematical modeling and simulation techniques used in abrasive-based machining processes such as abrasive flow machining (AFM), magnetic-based finishing processes, i.e., magnetic abrasive finishing (MAF) process, magnetorheological finishing (MRF) process, and ball-end type magnetorheological finishing process (BEMRF). The paper also aims to highlight the advances and obstacles associated with these techniques and their applications in flow machining. This study contributes the better understanding by examining the available modeling and simulation techniques such as Molecular Dynamic Simulation (MDS), Computational Fluid Dynamics (CFD), Finite Element Method (FEM), Discrete Element Method (DEM), Multivariable Regression Analysis (MVRA), Artificial Neural Network (ANN), Response Surface Analysis (RSA), Stochastic Modeling and Simulation by Data Dependent System (DDS). Among these methods, CFD and FEM can be performed with the available commercial software, while DEM and MDS performed using the computer programming-based platform, i.e., “LAMMPS Molecular Dynamics Simulator,” or C, C++, or Python programming, and these methods seem more promising techniques for modeling and simulation of loose abrasive-based machining processes. The other four methods (MVRA, ANN, RSA, and DDS) are experimental and based on statistical approaches that can be used for mathematical modeling of loose abrasive-based machining processes. Additionally, it suggests areas for further investigation and offers a priceless bibliography of earlier studies on the modeling and simulation techniques for abrasive-based machining processes. Researchers studying mathematical modeling of various micro- and nanofinishing techniques for different applications may find this review article to be of great help.

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Todd, B. D. "Computer simulation of simple and complex atomistic fluids by nonequilibrium molecular dynamics techniques." Computer Physics Communications 142, no. 1-3 (December 2001): 14–21. http://dx.doi.org/10.1016/s0010-4655(01)00304-6.

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Preethi, B., V. Shanthi, and K. Ramanathan. "Investigation of Nalidixic Acid Resistance Mechanism in Salmonella enterica Using Molecular Simulation Techniques." Applied Biochemistry and Biotechnology 177, no. 2 (July 25, 2015): 528–40. http://dx.doi.org/10.1007/s12010-015-1760-6.

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Wilson, Mark R., Michael P. Allen, Mark A. Warren, Alain Sauron, and William Smith. "Replicated data and domain decomposition molecular dynamics techniques for simulation of anisotropic potentials." Journal of Computational Chemistry 18, no. 4 (March 1997): 478–88. http://dx.doi.org/10.1002/(sici)1096-987x(199703)18:4<478::aid-jcc3>3.0.co;2-q.

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van Gunsteren, W. F. "The role of computer simulation techniques in protein engineering." "Protein Engineering, Design and Selection" 2, no. 1 (1988): 5–13. http://dx.doi.org/10.1093/protein/2.1.5.

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PERKIN, JONATHAN. "ACORNE SIMULATION WORK." International Journal of Modern Physics A 21, supp01 (July 2006): 207–11. http://dx.doi.org/10.1142/s0217751x06033635.

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A summary of the simulation studies currently underway by the UK based Acoustic Cosmic Ray Neutrino Experiment (ACoRNE) collaboration is presented. Ideas for future development are also discussed. The work described here has been developed for simulations of large scale hydrophone arrays but many of the same considerations apply for other detection techniques.

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Mohammad R. Gharibzahedi, Sayyed, and Javad Karimi-Sabet. "Gas Separation in Nanoporous Graphene from Molecular Dynamics Simulation." Chemical Product and Process Modeling 11, no. 1 (March 1, 2016): 29–33. http://dx.doi.org/10.1515/cppm-2015-0059.

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Abstract Membrane separation processes are energetically efficient compared to the other techniques such as cryogenic distillation and gas adsorption techniques. It is well known that a membrane's permeance is inversely proportional to its thickness. Regard to its single atom thickness and its mechanical strength, nanoporous graphene has been proposed as a very promising candidate for highly efficient gas separation applications. In this work, using classical molecular dynamics, we report the separation performance of such membrane in a molecular-sieving process as a function of pore size and chemical functionalization of pore rim. To investigate the membrane separation capability, we have calculated the permeance of each gas molecule of the considered binary mixtures through the membranes and therefore the separation selectivity. We investigated the separation performance of nanoporous graphene for CO2/N2, H2/CH4 and He/CH4 with 50:50 proportions of each component and the separation selectivity has been calculated. We also calculated the potential of the mean force to characterize the energy profile for gas transmission. The separation selectivity reduced by increasing the pore size. However, presence of chemical functionally pores in the membrane increased the separation selectivity. Furthermore, the gas permeance through nanoporous graphene membranes is related not only to transport rate to the graphene surface as well as kinetic diameters but also to molecular adsorbed layer which is formed on the surface. The flux of molecules through the nanopores is also dependent on pore chemistry which is considered as gas-pore interactions in the molecular simulations and can be a sizable factor in simulation in contrast to experimental observations. This study suggests that nanoporous graphene could represent a suitable membrane for gas separation.

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Biagini, Tommaso, Francesco Petrizzelli, Mauro Truglio, Roberto Cespa, Alessandro Barbieri, Daniele Capocefalo, Stefano Castellana, Maria Florencia Tevy, Massimo Carella, and Tommaso Mazza. "Are Gaming-Enabled Graphic Processing Unit Cards Convenient for Molecular Dynamics Simulation?" Evolutionary Bioinformatics 15 (January 2019): 117693431985014. http://dx.doi.org/10.1177/1176934319850144.

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In several fields of research, molecular dynamics simulation techniques are exploited to evaluate the temporal motion of particles constituting water, ions, small molecules, macromolecules, or more complex systems over time. These techniques are considered difficult to setup, computationally demanding and require high specialization and scientific skills. Moreover, they need specialized computing infrastructures to run faster and make the simulation of big systems feasible. Here, we have simulated 3 systems of increasing sizes on scientific- and gaming-enabled graphic processing unit (GPU) cards with Amber, GROMACS, and NAMD and measured their performance accounting also for the market prices of the GPU cards where they were run on.

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Stavrogiannis, Christos, Filippos Sofos, Theodoros E. Karakasidis, and Denis Vavougios. "Investigation of water desalination/purification with molecular dynamics and machine learning techniques." AIMS Materials Science 9, no. 6 (2022): 919–38. http://dx.doi.org/10.3934/matersci.2022054.

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<abstract> <p>This paper incorporates a number of parameters, such as nanopore size, wall wettability, and electric field strength, to assess their effect on ion removal from nanochannels filled with water. Molecular dynamics simulations are incorporated to monitor the process and a numerical database is created with the results. We show that the movement of ions in water nanochannels under the effect of an electric field is multifactorial. Potential energy regions of various strength are formed inside the nanochannel, and ions are either drifted to the walls and rejected from the solution or form clusters that are trapped inside low potential energy regions. Further computational investigation is made with the incorporation of machine learning techniques that suggest an alternative path to predict the water/ion solution properties. Our test procedure here involves the calculation of diffusion coefficient values and the incorporation of four ML algorithms, for comparison reasons, which exploit MD calculated results and are trained to predict the diffusion coefficient values in cases where no simulation data exist. This two-fold computational approach constitutes a fast and accurate solution that could be adjusted to similar ion separation models for property extraction.</p> </abstract>

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Hosseini-Koupaei, Mansoore, Behzad Shareghi, Ali Akbar Saboury, and Fateme Davar. "Molecular investigation on the interaction of spermine with proteinase K by multispectroscopic techniques and molecular simulation studies." International Journal of Biological Macromolecules 94 (January 2017): 406–14. http://dx.doi.org/10.1016/j.ijbiomac.2016.10.038.

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Gillan, M. J., P. J. D. Lindan, L. N. Kantorovich, and S. P. Bates. "Molecular processes on oxide surfaces studied by first-principles calculations." Mineralogical Magazine 62, no. 5 (October 1998): 669–85. http://dx.doi.org/10.1180/002646198548052.

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AbstractFirst-principles quantum techniques based on density functional theory (DFT) have made important contributions to the understanding of oxide surfaces over the last four years. Important features of these calculations include: the use of periodic boundary conditions, which avoid the edge effects associated with the cluster approach; plane-wave basis sets, which make the calculation of ionic forces straightforward, so that both static relaxation and dynamical simulation can be done; and the approximate inclusion of electron correlation. A short introduction to DFT techniques is given, and recent work on the structure and energetics of a variety of oxide surfaces is presented. It is shown how the techniques can be used to study molecular and dissociative adsorption of molecules on oxide surfaces, with the emphasis on water and simple organic molecules. The growing importance of dynamical first-principles simulation in the study of surface chemical reactions is illustrated.

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Singal, Jack, J. Brian Langton, and Rafe Schindler. "Geant4 applications for modeling molecular transport in complex vacuum geometries." International Journal of Modeling, Simulation, and Scientific Computing 05, no. 02 (February 25, 2014): 1350025. http://dx.doi.org/10.1142/s1793962313500256.

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We discuss a novel use of the Geant4 simulation toolkit to model molecular transport in a vacuum environment, in the molecular flow regime. The Geant4 toolkit was originally developed by the high energy physics community to simulate the interactions of elementary particles within complex detector systems. Here its capabilities are utilized to model molecular vacuum transport in geometries where other techniques are impractical. The techniques are verified with an application representing a simple vacuum geometry that has been studied previously both analytically and by basic Monte Carlo simulation. We discuss the use of an application with a very complicated geometry, that of the Large Synoptic Survey Telescope camera cryostat, to determine probabilities of transport of contaminant molecules to optical surfaces where control of contamination is crucial.

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J Brennan, Michael, Andrew M Garvie, and Lesley J Kelly. "A Monte Carlo Investigation of E x B Discharges in Molecular Nitrogen." Australian Journal of Physics 43, no. 1 (1990): 27. http://dx.doi.org/10.1071/ph900027.

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A Monte Carlo simulation method has been developed and tested using the ramp model gas proposed by Reid (1979). This method is particularly useful for investigations in gases which must be modelled using many cross sections. This paper reports various phenomena associated with Townsend discharges in ExB fields in nitrogen. Of particular interest is the relative importance of terms in the density gradient expansion of the electron energy distribution function. Simulations are conducted to assist in the interpretation of data from experimental techniques, particularly the 'photon flux' method.

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Hinkle, Kevin, Xiaoyu Wang, Xuehong Gu, Cynthia Jameson, and Sohail Murad. "Computational Molecular Modeling of Transport Processes in Nanoporous Membranes." Processes 6, no. 8 (August 9, 2018): 124. http://dx.doi.org/10.3390/pr6080124.

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In this report we have discussed the important role of molecular modeling, especially the use of the molecular dynamics method, in investigating transport processes in nanoporous materials such as membranes. With the availability of high performance computers, molecular modeling can now be used to study rather complex systems at a fraction of the cost or time requirements of experimental studies. Molecular modeling techniques have the advantage of being able to access spatial and temporal resolution which are difficult to reach in experimental studies. For example, sub-Angstrom level spatial resolution is very accessible as is sub-femtosecond temporal resolution. Due to these advantages, simulation can play two important roles: Firstly because of the increased spatial and temporal resolution, it can help understand phenomena not well understood. As an example, we discuss the study of reverse osmosis processes. Before simulations were used it was thought the separation of water from salt was purely a coulombic phenomenon. However, by applying molecular simulation techniques, it was clearly demonstrated that the solvation of ions made the separation in effect a steric separation and it was the flux which was strongly affected by the coulombic interactions between water and the membrane surface. Additionally, because of their relatively low cost and quick turnaround (by using multiple processor systems now increasingly available) simulations can be a useful screening tool to identify membranes for a potential application. To this end, we have described our studies in determining the most suitable zeolite membrane for redox flow battery applications. As computing facilities become more widely available and new computational methods are developed, we believe molecular modeling will become a key tool in the study of transport processes in nanoporous materials.

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Chen, Fu, Shu-Shen Liu, Xin-Tian Duan, and Qian-Fen Xiao. "Predicting the mixture effects of three pesticides by integrating molecular simulation with concentration addition modeling." RSC Adv. 4, no. 61 (2014): 32256–62. http://dx.doi.org/10.1039/c4ra02698e.

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Burkhart, Craig W. "Structurally Realistic Modeling of Elastomers." Rubber Chemistry and Technology 71, no. 3 (July 1, 1998): 342–406. http://dx.doi.org/10.5254/1.3538489.

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Abstract This review covers the methods by which elastomers have been microscopically modeled and simulated since the mid-1960s. Of particular importance was the rotational isomeric state (RIS) methods of the Flory school in the 60s. His group was the first to attempt to use such statistical mechanical methods to determine observables such as the characteristic ratio, Cn. The early success of Flory's efforts were expanded in the early 1970s by members of his group in what appears to be the first true attempt to use molecular mechanics optimization techniques to obtain RIS statistical weighting matrices. Following these two pioneering breakthroughs, molecular mechanics techniques were refined and extended. Not much later, it became possible to perform temporal molecular dynamics simulations on flexible molecular liquids. Simulations of elastomer systems lagged somewhat; both single chains and elastomer amorphous liquids were not studied until the beginning of this decade. With the improvement in molecular forcefields and computational horsepower, it has become possible to perform simulations on relatively large-scale polymer systems. We track these developments, which include equation-of-state simulations and the simulation of oxygen diffusion in elastomers.

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Journal articles on the topic 'Molecular simulation techniques'

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