MCCCS Towhee: a tool for Monte Carlo molecular simulation

REFERENCES

• SiepmannJI, FrenkelD. Configurational bias Monte Carlo: a new sampling scheme for flexible chains. Mol Phys. 1992;75:59–70.
   Web of Science ®Google Scholar
• SiepmannJI, McDonaldIR. Monte Carlo simulations of the mechanical relaxation of a self-assembled monolayer. Phys Rev Lett. 1993;70:453–456.
   PubMed Web of Science ®Google Scholar
• SiepmannJI. A method for the direct calculation of chemical potentials for dense chain systems. Mol Phys. 1990;70:1145–1158.
   Web of Science ®Google Scholar
• SiepmannJI, McDonaldIR. Monte Carlo simulations of mixed monolayers. Mol Phys. 1992;75:255–259.
   Web of Science ®Google Scholar
• SiepmannJI, SprikM. Folding of model heteropolymer by configurational-bias Monte Carlo. Chem Phys Lett. 1992;199:220–224.
   Web of Science ®Google Scholar
• SmitB, De SmedtPh, FrenkelD. Computer simulations in the Gibbs ensemble. Mol. Phys. 1989;68:931–950.
   Web of Science ®Google Scholar
• PanagiotopoulosAZ. Direct determination of phase coexistence properties of fluids by Monte Carlo simulation in a new ensemble. Mol Phys. 1987;61:813–826.
   Web of Science ®Google Scholar
• PanagiotopoulosAZ, QuirkeN, StapletonM, TildesleyDJ. Phase equilibria by simulation in the Gibbs ensemble. Alternative derivation, generalization and application to mixture and membrane equilibria. Mol Phys. 1988;63:527–545.
   Web of Science ®Google Scholar
• MooijGCAM, FrenkelD, SmitB. Direct simulation of phase equilibria of chain molecules. J Phys Condens Matter. 1992;4:L255–L259.
   Web of Science ®Google Scholar
• SiepmannJI, KaraborniS, SmitB. Simulating the critical behaviour of complex fluids. Nature. 1993;365:330–332.
   Web of Science ®Google Scholar
• SmitB, SiepmannJI. Simulating the adsorption of alkanes in zeolites. Science. 1994;264:1118–1120.
   PubMed Web of Science ®Google Scholar
• MartinMG, SiepmannJI. Novel configurational-bias Monte Carlo method for branched molecules. Transferable potentials for phase equilibria. 2. United-atom description of branched alkanes. J Phys Chem B. 1999;103:4508–4517.
   Web of Science ®Google Scholar
• MartinMG, SiepmannJI. Transferable potentials for phase equilibria. 1. United-atom description of n-alkanes. J Phys Chem B. 1998;102:2569–2577.
   Web of Science ®Google Scholar
• ThompsonTB, editor. Chemical Industry of the Future Technology Roadmap for Computational Chemistry; 1999. Available from: http://www1.eere.energy.gov/manufacturing/resources/chemicals/pdfs/compchemistry_roadmap.pdf.
   Google Scholar
• MCCCS Towhee. Available from: http://towhee.sourceforge.net.
   Google Scholar
• SunH. COMPASS: an ab initio force-field optimized for condensed-phase applications – overview with details on alkane and benzene compounds. J Phys Chem B. 1998;102:7338–7364.
   Web of Science ®Google Scholar
• MetropolisN, RosenbluthAW, RosenbluthMN, TellerAH, TellerE. Equation of state calculations by fast computing machines. J Chem Phys. 1953;21:1087–1092.
   Web of Science ®Google Scholar
• McDonaldIR. NpT-ensemble Monte Carlo calculations for binary liquid mixtures. Mol Phys. 1972;23:41–58.
   Web of Science ®Google Scholar
• NormanGE, FilinovVS. Investigations of phase transitions by a Monte-Carlo method. High Temp. 1969;7:216–222.
   Web of Science ®Google Scholar
• ChenB, SiepmannJI. A novel Monte Carlo algorithm for simulating strongly associating fluids: applications to water, hydrogen fluoride, and acetic acid. J Phys Chem B. 2000;104:8725–8734.
   Web of Science ®Google Scholar
• ChenB, SiepmannJI. Improving the efficiency of the aggregation-volume-bias Monte Carlo algorithm. J Phys Chem B. 2001;105:11275–11282.
   Web of Science ®Google Scholar
• MartinMG, FrischknechtAL. Using arbitrary trial distributions to improve intramolecular sampling in configurational-bias Monte Carlo. Mol Phys. 2006;104:2439–2456.
   Web of Science ®Google Scholar
• VlugtTJH, MartinMG, SmitB, SiepmannJI, KrishnaR. Improving the efficiency of the configurational-bias Monte Carlo algorithm. Mol Phys. 1998;94:727–733.
   Web of Science ®Google Scholar
• EwaldPP. Die Berchnung optischer und elektrostatischer Gitterpotentiale. Ann Phys. 1921;64:253–287.
   Web of Science ®Google Scholar
• SangsterMJL, DixonM. Interionic potentials in alkali halides and their use in simulations of the molten salts. Adv Phys. 1976;25:247–343.
   Web of Science ®Google Scholar
• WidomB. Some topics in the theory of fluids. J Chem Phys. 1963;39:2808–2812.
   Web of Science ®Google Scholar
• WidomB. Potential-distribution theory and the statistical mechanics of fluids. J Phys Chem. 1982;86:869–872.
   Web of Science ®Google Scholar
• ShahJK, MaginnEJ. A general and efficient Monte Carlo method for sampling intramolecular degrees of freedom of branched and cyclic molecules. J Chem Phys. 2001;135:134121.
   Web of Science ®Google Scholar
• Cortéz MoralesAD, EconomouIG, PetersCJ, SiepmannJI. Influence of simulation protocols on the efficiency of Gibbs ensemble Monte Carlo simulations. Mol. Simul. this issue.
   Google Scholar
• CaseF, ChakaA, FriendDG, FruripD, GolabJ, JohnsonR, MooreJ, MountainRD, OlsonJ, SchillerM, StorerJ. The first industrial fluid properties simulation challenge. Fluid Phase Equilib. 2004;217:1–10.
   Web of Science ®Google Scholar
• CaseFH, BrennanJ, ChakaA, DobbsKD, FriendDG, FruripD, GordonPA, MooreJ, MountainRD, OlsonJ, RossRB, SchillerM, ShenVK. The third industrial fluid properties simulation challenge. Fluid Phase Equilib. 2007;260:153–163.
   Web of Science ®Google Scholar
• CaseFH, BrennanJ, ChakaA, DobbsKD, FriendDG, GordonPA, MooreJD, MountainRD, OlsonJD, RossRB, SchillerM, ShenVK, StahlbergEA. The fourth industrial fluid properties simulation challenge. Fluid Phase Equilib. 2008;274:2–9.
   Web of Science ®Google Scholar
• O'ConnellJP, GaniR, MathiasPM, MaurerG, OlsonJD, CraftsPA. Thermodynamic property modeling for chemical process and product engineering: some perspectives. Ind Eng Chem Res. 2009;48:4619–4637.
   Web of Science ®Google Scholar
• MaginnEJ. From discovery to data: what must happen for molecular simulation to become a mainstream chemical engineering tool. AIChE J. 2009;55:1304–1310.
   Web of Science ®Google Scholar
• HeffelfingerGS, MartinoA, GorinA, XuY, RintoulMDIII, GeistA, Al-HashimiHM, DavidsonGS, FaulonJL, FrinkLJ, HaalandDM, HartWE, JakobssonE, LaneT, LiM, LocascioP, OlkenF, OlmanV, PalenikB, PlimptonSJ, RoeDC, SamatovaNF, ShahM, ShoshoniA, StraussCEM, ThomasEV, TimlinJA, XuD. Carbon sequestration in Synechococcus Sp.: from molecular machines to hierarchical modeling. OMICS: J Integr Biol. 2002;6:305–330.
   PubMedGoogle Scholar
• VitalisA, PappuRV. Chapter 3 methods for Monte Carlo simulations of biomacromolecules. Ann Rep Comput Chem. 2009;5:49–76.
   PubMedGoogle Scholar
• BrennanJK, LisalM. CECAM workshop: ‘dissipative particle dynamics: addressing deficiencies and establishing new frontiers’ (1618 July 2008, Lausanne, Switzerland) report. Mol Simul. 2009;35:766–769.
   Web of Science ®Google Scholar
• EnginC, VrabecJ, HasseH. On the difference between a point multipole and an equivalent linear arrangement of point charges in force field models for vapour-liquid equilibria; partial charge based models for 59 real fluids. Mol Phys. 2011;109:1975–1982.
   Web of Science ®Google Scholar
• SunL, SiepmannJI, SchureMR. Conformation and solvation structure for an isolated n-octadecane chain in water, methanol, and their mixtures. J Phys Chem B. 2006;110:10519–10525.
   PubMed Web of Science ®Google Scholar
• MerkerT, EnginC, VrabecJ, HasseH. Molecular model for carbon dioxide optimized to vapor-liquid equilibria. J Chem Phys. 2010;132:234512.
   PubMed Web of Science ®Google Scholar
• KamathG, KetkoM, BakerGA, PotoffJJ. Monte Carlo predictions of phase equilibria and structure for dimethyl ether+sulfur dioxide and dimethyl ether+carbon dioxide. J Chem Phys. 2012;136:044514.
   PubMed Web of Science ®Google Scholar
• KetkoMH, RaffertyJ, SiepmannJI, PotoffJJ. Development of the TraPPE-UA force field for ethylene oxide. Fluid Phase Equilib. 2008;274:44–49.
   Web of Science ®Google Scholar
• van der StraatenT, KathawalaG, RavaioliU. BioMOCA: a transport Monte Carlo model for ion channels. J Comput Electron. 2003;2:231–237.
   Google Scholar
• TafipolskyM, AmirjalayerS, SchmidR. Atomistic theoretical models for nanoporous hybrid materials. Micropor Mesopor Mater. 2010;129:304–318.
   Web of Science ®Google Scholar
• FeldtJ, MataRA, DieterichJM. Atomdroid: a computational chemistry tool for mobile platforms. J Chem Inf. Model. 2012;52:1072–1078.
   PubMed Web of Science ®Google Scholar
• RamanjaneyuluM, SilambujanakiP, KumarMS. Novel drug design for glaucoma and non insulin dependent diabetes mellitus: a better lead design by binding free energy calculations. J Comput Method Mol Des. 2011;1:73–87.
   Google Scholar
• ZhangL, GreenfieldML. Relaxation time, diffusion, and viscosity analysis of model asphalt systems using molecular simulation. J Chem Phys. 2007;127:194502.
   PubMed Web of Science ®Google Scholar
• ZhangL, GreenfieldMichaelL. Effects of polymer modification on properties and microstructure of model asphalt systems. Energy Fuels. 2008;22:3363–3375.
   Web of Science ®Google Scholar
• TsigeM, GrestGS. Surface tension and surface orientation of perfluorinated alkanes. J Phys Chem C. 2008;112:5029–5035.
   Web of Science ®Google Scholar
• FrischknechtAL, MartinMG. Simulation of the adsorption of nucleotide monophosphates on carbon nanotubes in aqueous solution. J Phys Chem C. 2008;112:6271–6278.
   Web of Science ®Google Scholar
• LorenzCD, FaraudoJ, TravessetA. Hydrogen bonding and binding of polybasic residues with negatively charged mixed lipid monolayers. Langmuir. 2008;24:1654–1658.
   PubMed Web of Science ®Google Scholar
• SpearotDE, SudibjoA, UllalV, HuangA. Molecular dynamics simulations of diffusion of O2 and N2 penetrants in polydimethylsiloxane-based nanocomposites. J Eng Mater Technol. 2012;134:021013.
   Web of Science ®Google Scholar
• LiuY, LiX, WangL, SunH. Prediction of partition coefficients and infinite dilution activity coefficients of 1-ethylpropylamine and 3-methyl-1-pentanol using force field methods. Fluid Phase Equilib. 2009;285:19–23.
   Web of Science ®Google Scholar
• ZhangL, GreenfieldML. Molecular orientation in model asphalts using molecular simulation. Energy Fuels. 2007;21:1102–1111.
   Web of Science ®Google Scholar
• IsmailAE, TsigeM, Veld In'tPJ, GrestGS. Surface tension of normal and branched alkanes. Mol Phys. 2007;105:3155–3163.
   Web of Science ®Google Scholar
• ZhangL, GreenfieldML. Rotational relaxation times of individual compounds within simulations of molecular asphalt models. J Chem Phys. 2010;132:184502.
   Web of Science ®Google Scholar
• ZhaoL, WangX, WangL, SunH. Prediction of shear viscosities using periodic perturbation method and OPLS force field. Fluid Phase Equilib. 2007;260:212–217.
   Web of Science ®Google Scholar
• MilischukAA, LadanyiBM. Structure and dynamics of water confined in silica nanopores. J Chem Phys. 2011;135:174709.
   PubMed Web of Science ®Google Scholar
• LaageD, ThompsonWH. Reorientation dynamics of nanoconfined water: Power-law decay, hydrogen-bond jumps, and test of a two-state model. J Chem Phys. 2012;136:044513.
   Web of Science ®Google Scholar
• MilischukAA, KrewaldV, LadanyiBM. Water dynamics in silica nanopores: The self-intermediate scattering functions. J Chem Phys. 2012;136:224704.
   PubMed Web of Science ®Google Scholar
• PlimptonS. Fast parallel algorithms for short-range molecular dynamics. J Comput Phys. 1995;117:1–19.
   Web of Science ®Google Scholar
• BerendsenHJC, van der SpoelD, van DrunenR. GROMACS: A message-passing parallel molecular dynamics implementation. Comput Phys Commun. 1995;91:43–56.
   Web of Science ®Google Scholar
• TodorovIT, SmithW, TrachenkoK, DoveMT. DL_POLY_3: new dimensions in molecular dynamics simulations via massive parallelism. J Mater Chem. 2006;16:1911–1918.
   Web of Science ®Google Scholar
• LarsenGS, LinP, HartKE, ColinaCM. Molecular simulations of PIM-1-like polymers of intrinsic microporosity. Macromolecules. 2011;44:6944–6951.
   Web of Science ®Google Scholar
• GuptaA, ChempathS, SanbornMJ, ClarkLA, SnurrRQ. Object-oriented programming paradigms for molecular modeling. Mol Simul. 2003;29:29–46.
   Web of Science ®Google Scholar
• YazaydinAO, ThompsonRW. Molecular simulation of the adsorption of MTBE in silicalite, mordenite, and zeolite beta. J Phys Chem B. 2006;110:14458–14462.
   PubMed Web of Science ®Google Scholar
• Palace CarvalhoA, Prates RamalhoJP, VilliérasF. Simulation study of argon adsorption on (0 0 1) faces of phyllosilicates. Appl Surface Sci. 2007;253:5628–5632.
   Web of Science ®Google Scholar
• RakhmatkarievGU, Palace CarvalhoAJ, Prates RamalhoJP. Adsorption of normal pentane on the surface of rutile. Experimental results and simulations. Langmuir. 2007;23:7555–7561.
   PubMed Web of Science ®Google Scholar
• RakhmatkarievGU, Palace CarvalhoAJ, Prates RamalhoJP. Experimental and simulation study of n-heptane adsorption on rutile. Adsorpt Sci Technol. 2007;25:517–530.
   Google Scholar
• KondratyukP, WangY, LiuJ, JohnsonJK, YatesJT, Jr. Inter- and intratube self-diffusion in n-heptane adsorbed on carbon nanotubes. J Phys Chem C. 2007;111:4578–4584.
   Web of Science ®Google Scholar
• KotdawalaRR, YazaydinAO, KazantzisN, ThompsonRW. A molecular simulation approach to the study of adsorption of hydrogen cyanide and methyl ethyl ketone in silicalite, mordenite and zeolite beta structures, Mol Simul. 2007;33:843–850.
   Google Scholar
• LiuL, FuJ, SunH. Prediction of adsorption of small molecules in porous materials based on ab initio force field method. Sci China Ser B Chem. 2008;51:760–767.
   Google Scholar
• GreathouseJA, KinnibrughTL, AllendorfMD. Adsorption and separation of noble gases by IRMOF-1: grand canonical Monte Carlo simulations. Ind Eng Chem Res. 2009;48:3425–3431.
   Web of Science ®Google Scholar
• FuJ, SunH. An ab initio force field for predicting hydrogen storage in IRMOF materials. J Phys Chem C. 2009;113:21815–21824.
   Web of Science ®Google Scholar
• NarasimhanL, BouletP, KuchtaB, SchaefO, DenoyelR, BrunetP. Molecular simulations of water and paracresol in MFI Zeolite – a Monte Carlo atudy. Langmuir. 2009;25:11598–11607.
   PubMed Web of Science ®Google Scholar
• LiuL, ZhaoL, SunH. Simulation of NH3 temperature-programmed desorption curves using an ab initio force field. J Phys Chem C. 2009;113:16051–16057.
   Web of Science ®Google Scholar
• BouletP, NarasimhanL, Bergõe-LefrancD, KuchtaB, SchäfO, DenoyelR. Adsorption into the MFI zeolite of aromatic molecule of biological relevance. Investigations by Monte Carlo simulations. J Mol Model. 2009;15:573–579.
   PubMed Web of Science ®Google Scholar
• RankinRB, LiuJ, KulkarniAD, JohnsonJK. Adsorption and diffusion of light gases in ZIF-68 and ZIF-70: a simulation study. J Phys Chem C. 2009;113:16906–16914.
   Web of Science ®Google Scholar
• GulmenTS, ThompsonWH. Grand canonical Monte Carlo simulations of acetonitrile filling of silica pores of varying hydrophilicity/hydrophobicity. Langmuir. 2009;25:1103–1111.
   PubMed Web of Science ®Google Scholar
• BüttnerM, XiaoL, MandeltortL, EdingtonS, JohnsonJK, YatesJT, Jr. Enhancement of adsorption inside single-walled carbon nanotubes: Li doping effect on n-heptane van der Waals bonding. J Phys Chem C. 2009;113:4829–4838.
   Web of Science ®Google Scholar
• NarasimhanL, BouletP, KuchtaB, VagnerC, SchäfO, DenoyelR. Adsorption of paracresol in silicalite-1 and pure silica faujasite. A comparison study using molecular simulation, Appl Surface Sci. 2010;256:5470–5474.
   Web of Science ®Google Scholar
• MorrisW, LeungB, FurukawaH, YaghiOK, HeN, HayashiH, HoundonougboY, AstaM, LairdBB, YaghiOM. A combined experimental-computational investigation of carbon dioxide capture in a series of isoreticular zeolitic imidazolate frameworks. J Am Chem Soc. 2010;132:11006–11008.
   PubMed Web of Science ®Google Scholar
• LarsenGS, LinP, SipersteinFR, ColinaCM. Methane adsorption in PIM-1. Adsorption. 2011;17:21–26.
   Web of Science ®Google Scholar
• WangL, SunY, SunH. Incorporating magnesium and calcium cations in porous organic frameworks for high-capacity hydrogen storage. Faraday Discuss. 2011;151:143–156.
   PubMed Web of Science ®Google Scholar
• KondratS, GeorgiN, FedorovMV, KornyshevAA. A superionic state in nano-porous double-layer capacitors: insights from Monte Carlo simulations. Phys Chem Chem Phys. 2011;13:11359–11366.
   PubMed Web of Science ®Google Scholar
• RobinsonAL, StavilaV, ZeitlerTR, WhiteMI, ThornbergSM, GreathouseJA, AllendorfMD. Ultrasensitive humidity detection using metal-organic framework-coated microsensors. Anal Chem. 2012;84:7043–7051.
   PubMed Web of Science ®Google Scholar
• GomezDA, CombarizaAF, SastreG. Confinement effects in the hydrogen adsorption on paddle wheel containing metal-organic frameworks. Phys Chem Chem Phys. 2012;14:2508–2517.
   PubMed Web of Science ®Google Scholar
• MeekST, Teich-McGoldrickSL, PerryJJIV, GreathouseJA, AllendorfMD. Effects of polarizability on the adsorption of noble gases at low pressures in monohalogenated isoreticular metalorganic frameworks. J Phys Chem C. 2012;116:19765–19772.
   Web of Science ®Google Scholar
• ChakrabortySN, GelbLD. A Monte Carlo simulation study of methane clathrate hydrates confined in slit-shaped pores. J Phys Chem B. 2012;116:2183–2197.
   PubMed Web of Science ®Google Scholar
• ZeitlerTR, AllendorfMD, GreathouseJA. Grand canonical Monte Carlo simulation of low-pressure methane adsorption in nanoporous framework materials for sensing applications. J Phys Chem C. 2012;116:3492–3502.
   Web of Science ®Google Scholar
• MorrisW, HeN, RayKG, KlonowskiP, FurukawaH, DanielsIN, HoundonougboYA, AstaM, YaghiOM, LairdBB. A combined experimental-computational study on the effect of topology on carbon dioxide adsorption in zeolitic imidazolate frameworks. J Phys Chem C. 2012;116:24084–24090.
   Web of Science ®Google Scholar
• ChempathS, DurenT, SarkisovL, SnurrRQ. Experiences with the publicly available multipurpose simulation code. Music, Mol Simul. this issue.
   Google Scholar
• ChandrossM, WebbEBIII, GrestGS, MartinMG, ThompsonAP, RothMW. Dynamics of exchange at gas-zeolite interfaces I: pure component n-butane and isobutane. J Phys Chem B. 2001;105:5700–5712.
   Web of Science ®Google Scholar
• JaramilloE, ChandrossM. Adsorption of small molecules in LTA zeolites. 1. NH3, CO2, and H2O in zeolite 4A. J Phys Chem B. 2004;108:20155–20159.
   Web of Science ®Google Scholar
• Palace CarvalhoAJ, Prates RamalhoJP. Molecular simulation of C60 adsorption onto a TiO2 rutile (1 1 0) surface. Appl Surface Sci. 2010;256:5365–5369.
   Web of Science ®Google Scholar
• YazaydinAÖ, ThompsonRobertW. Computing adsorbate/adsorbent binding energies and Henryõs law constants from molecular simulations. Environ Eng Sci. 2009;26:297–303.
   Web of Science ®Google Scholar
• LiX, LiF, ShiY, ChenaQ, SunH. Predicting water uptake in poly(perfluorosulfonic acids) using force field simulation methods. Phys Chem Chem Phys. 2010;12:14543–14552.
   PubMed Web of Science ®Google Scholar
• MartinMG, ThompsonAP, NenoffTM. Effect of pressure, membrane thickness, and placement of control volumes on the flux of methane through thin silicalite membranes: a dual control volume grand canonical molecular dynamics study. J Chem Phys. 2001;114:7174–7181.
   Web of Science ®Google Scholar
• KamathG, CaoF, PotoffJJ. An improved force field for the prediction of the vapor-liquid equilibria for carboxylic acids. J Phys Chem B. 2004;108:14130–14136.
   Web of Science ®Google Scholar
• MartinMG, BiddyMJ. Monte Carlo molecular simulation predictions for the heat of vaporization of acetone and butyramide. Fluid Phase Equilib. 2005;236:53–57.
   Web of Science ®Google Scholar
• MartinMG. Comparison of the AMBER, CHARMM, COMPASS, GROMOS, OPLS, TraPPE and UFF force fields for prediction of vapor-liquid coexistence curves and liquid densities. Fluid Phase Equilib. 2006;248:50–55.
   Web of Science ®Google Scholar
• GordonPA. Development of intermolecular potentials for predicting transport properties of hydrocarbons. J Chem Phys. 2006;125:014504.
   PubMed Web of Science ®Google Scholar
• CliffordS, BoltonK, RamjugernathD. Monte Carlo simulation of carboxylic acid phase equilibria. J Phys Chem B. 2006;110:21938–21943.
   PubMed Web of Science ®Google Scholar
• HoundonougboY, JinH, RajagopalanB, WongK, KuczeraK, SubramaniamB, LairdB. Phase equilibria in carbon dioxide expanded solvents: experiments and molecular simulations. J Phys Chem B. 2006;110:13195–13202.
   PubMed Web of Science ®Google Scholar
• HoundonougboY, GuoJ-X, LushingtonGH, LairdB. Monte Carlo simulations of CO2-expanded acetonitrile. Mol Phys. 2006;104:2955–2960.
   Web of Science ®Google Scholar
• YazaydinAO, ThompsonW. Simulating the vapour-liquid equilibria of 1,4-dioxane. Mol Simul. 2006;32:657–662.
   Web of Science ®Google Scholar
• YazaydõnAO, MartinMG. Bubble point pressure estimates from Gibbs ensemble simulations. Fluid Phase Equilib. 2007;260:195–198.
   Web of Science ®Google Scholar
• HansenN, AgborFAB, KeilFJ. New force fields for nitrous oxide and oxygen and their application to phase equilibria simulations. Fluid Phase Equilib. 2007;259:180–188.
   Web of Science ®Google Scholar
• RaabeG, SadusRJ. Influence of bond flexibility on the vapor-liquid phase equilibria of water. J Chem Phys. 2007;126:044701.
   Web of Science ®Google Scholar
• ZhaoL, LiuL, SunH. Semi-ionic model for metal oxides and their interfaces with organic molecules. J Phys Chem C. 2007;111:10610–10617.
   Web of Science ®Google Scholar
• HoundonougboY, KuczerabK, SubramaniamB, LairdBB. Prediction of phase equilibria and transport properties in carbon-dioxide expanded solvents by molecular simulation. Mol Simul. 2007;33:861–869.
   Web of Science ®Google Scholar
• MüllerTJ, RoyS, ZhaoW, MaaA, ReithD. Economic simplex optimization for broad range property prediction: strengths and weaknesses of an automated approach for tailoring of parameters. Fluid Phase Equilib. 2008;274:27–35.
   Web of Science ®Google Scholar
• LiX, ZhaoL, ChengT, LiuL, SunH. One force field for predicting multiple thermodynamic properties of liquid and vapor ethylene oxide. Fluid Phase Equilib. 2008;274:36–43.
   Web of Science ®Google Scholar
• MerkerT, VrabecJ, HasseH. Comment on an optimized potential for carbon dioxide. J Chem Phys. 2008;129:087101 [J. Chem. Phys. 122, 214507 (2005)].
   Web of Science ®Google Scholar
• SaboD, VarmaS, MartinMG, RempeB. Studies of the thermodynamic properties of hydrogen gas in bulk water. J Phys Chem B. 2008;112:867–876.
   PubMed Web of Science ®Google Scholar
• AparicioS, AlcaldeaR. The green solvent ethyl lactate: an experimental and theoretical characterization. Green Chem. 2009;11:65–78.
   Web of Science ®Google Scholar
• LajovicA, TomšičM, Fritz-PopovskiG, VlčekL, JamnikA. Exploring the structural properties of simple aldehydes: a Monte Carlo and small-angle X-ray scattering study. J Phys Chem B. 2009;113:9429–9435.
   PubMed Web of Science ®Google Scholar
• GutowskiKE, GurkanB, MaginnEJ. Force field for the atomistic simulation of the properties of hydrazine, organic hydrazine derivatives, and energetic hydrazinium ionic liquids. Pure Appl Chem. 2009;81:1799–1828.
   Web of Science ®Google Scholar
• DellisD, SamiosJ. Molecular force field investigation for sulfur hexafluoride: a computer simulation study. Fluid Phase Equilib. 2010;291:81–89.
   Web of Science ®Google Scholar
• MoodleyS, BoltonK, RamjugernathD. Monte Carlo simulations of vapor-liquid-liquid equilibrium of some ternary petrochemical mixtures. Fluid Phase Equilib. 2010;299:24–31.
   Web of Science ®Google Scholar
• PaulechkaE, KazakovA, FrenkelM. Monte Carlo simulation of vapor-liquid equilibria for perfluoropropane (R-218) and 2,3,3,3-tetrafluoropropene (R-1234yf). Int J Thermophys. 2010;31:462–474.
   Web of Science ®Google Scholar
• DellisD, SkarmoutsosI, SamiosJ. Molecular simulations of benzene and hexafluorobenzene using new optimized effective potential models: investigation of the liquid, vapor-liquid coexistence and supercritical fluid phases. J Mol Liquids. 2010;153:25–30.
   Web of Science ®Google Scholar
• XuW, YangJ. A computer simulation study on self- and cross-aggregation of multiple polar species in supercritical carbon dioxide. J Phys Chem A. 2010;114:5414–5428.
   PubMed Web of Science ®Google Scholar
• XuW, YangJ. Computer simulations on aggregation of acetic acid in the gas phase, liquid phase, and supercritical carbon dioxide. J Phys Chem A. 2010;114:5377–5388.
   PubMed Web of Science ®Google Scholar
• RaabeG, MaginnEJ. A force field for 3,3,3-fluoro-1-propenes, including HFO-1234yf. J Phys Chem B. 2010;114:10133–10142.
   PubMed Web of Science ®Google Scholar
• VyalovI, KiselevM, TassaingT, SoetensJC, IdrissiA. Investigation of the local structure in sub and supercritical ammonia using the nearest neighbor approach: a molecular dynamics analysis. J Phys Chem B. 2010;114:15003–15010.
   PubMed Web of Science ®Google Scholar
• RaabeG, MaginnEJ. Molecular modeling of the vapor-liquid equilibrium properties of the alternative refrigerant 2,3,3,3-tetrafluoro-1-propene (HFO-1234yf). J Phys Chem Lett. 2010;1:93–96.
   Web of Science ®Google Scholar
• MaaßA, NikitinaL, CleesT, KirschnerKN, ReithD. Multi-objective optimisation on the basis of random models for ethylene oxide. Mol Simul. 2010;36:1208–1218.
   Web of Science ®Google Scholar
• MoodleyS, JohanssonE, BoltonK, RamjugernathD. Gibbs ensemble Monte Carlo simulations of binary vapour-liquid-liquid equilibrium: application to n-hexane-water and ethane-ethanol systems. Mol Simul. 2010;36:758–762.
   Web of Science ®Google Scholar
• DaiJ, WangL, SunY, WangL, SunH. Prediction of thermodynamic, transport and vapor-liquid equilibrium properties of binary mixtures of ethylene glycol and water. Fluid Phase Equilib. 2011;301:137–144.
   Web of Science ®Google Scholar
• VlcekL, ChialvoAA, ColeDR. Optimized unlike-pair interactions for water-carbon dioxide mixtures described by the SPC/E and EPM2 models. J Phys Chem B. 2011;115:8775–8784.
   PubMed Web of Science ®Google Scholar
• EnginC, MerkerT, VrabecJ, HasseH. Flexible or rigid molecular models? A study on vapour-liquid equilibrium properties of ammonia. Mol Phys. 2011;109:619–624.
   Web of Science ®Google Scholar
• PaulechkaE, KroenleinK, KazakovA, FrenkelM. A systematic approach for development of an OPLS-Like force field and its application to hydrofluorocarbons. J Phys Chem B. 2012;116:14389–14397.
   PubMed Web of Science ®Google Scholar
• RaabeG. Molecular modeling of fluoropropene refrigerants. J Phys Chem B. 2012;116:5744–5751.
   PubMed Web of Science ®Google Scholar
• MoodleyS, JohanssonE, BoltonK, RamjugernathD. Phase-dependent energy cross-parameters in a monatomic binary fluid system. Mol Simul. 2012;38:838–849.
   Web of Science ®Google Scholar
• SokkalingamN, KamathG, CoscioneM, PotoffJJ. Extension of the transferable potentials for phase equilibria force field to dimethylmethyl phosphonate, sarin, and soman. J Phys Chem B. 2009;113:10292–10297.
   PubMed Web of Science ®Google Scholar
• Bernard-BrunelDA, PotoffJJ. Effect of torsional potential on the predicted phase behavior of n-alkanes. Fluid Phase Equilib. 2009;279:100–104.
   Web of Science ®Google Scholar
• BoulougourisaGC, PeristerasLD, EconomouIG, TheodorouDN. Predicting fluid phase equilibrium via histogram reweighting with Gibbs ensemble Monte Carlo simulations. J Supercrit Fluids. 2010;55:503–509.
   Web of Science ®Google Scholar
• YuK, McDanielJG, SchmidtR. Physically motivated, robust, ab initio force fields for CO2 and N2. J Phys Chem B. 2011;115:10054–10063.
   PubMed Web of Science ®Google Scholar
• YuK, SchmidtJR. Many-body effects are essential in a physically motivated CO2 force field. J Chem Phys. 2012;136:034503.
   Web of Science ®Google Scholar
• MartinMG, ThompsonAP. Industrial property prediction using Towhee and LAMMPS. Fluid Phase Equilib. 2004;217:105–110.
   Web of Science ®Google Scholar
• ZhangL, GreenfieldML. Analyzing properties of model asphalts using molecular simulation. Energy Fuels. 2007;21:1712–1716.
   Web of Science ®Google Scholar
• Palace CarvalhoAJ, Prates RamalhoJP, MartinsLFG. Excess thermodynamics of mixtures involving xenon and light linear alkanes by computer simulation. J Phys Chem B. 2007;111:6437–6443.
   PubMed Web of Science ®Google Scholar
• BonifàcioRPMF, MartinsLFG, McCabeC, FilipeEJM. On the behavior of solutions of xenon in liquid n-alkanes: solubility of xenon in n-pentane and n-hexane. J Phys Chem B. 2010;114:15897–15904.
   PubMed Web of Science ®Google Scholar
• MartinsLFG, Palace CarvalhoAJ, Prates RamalhoJP, FilipeEJM. Excess thermodynamic properties of mixtures involving xenon and light alkanes: a study of their temperature dependence by computer simulation. J Phys Chem B. 2011;115:9745–9765.
   PubMed Web of Science ®Google Scholar
• LiDD, GreenfieldML. high internal energies of proposed asphaltene structures. Energy Fuels. 2011;25:3698–3705.
   Web of Science ®Google Scholar
• VrhovšekA, GerebenO, PothoczkiS, TomšičM, JamnikA, KoharaS, PusztaiL. An approach towards understanding the structure of complex molecular systems: the case of lower aliphatic alcohols. J Phys Condens Mater. 2010;22:404214.
   PubMed Web of Science ®Google Scholar
• BessiéresD, PiñeiroMM, De FerronG, PlantierF. Analysis of the orientational order effect on n-alkanes: evidences on experimental response functions and description using Monte Carlo molecular simulation. J Chem Phys. 2010;133:074507.
   Web of Science ®Google Scholar
• SaboD, RempeSB, GreathouseJA, MartinMG. Molecular studies of the structural properties of hydrogen gas in bulk water. Mol Simul. 2006;32:269–278.
   Web of Science ®Google Scholar
• ZhangX, HanX, XuW. A computer simulation study on Lewis acid-base interactions and cooperative C–H–O weak hydrogen bonding in various CO2 complexes. J Theor Comput Chem. 2011;10:483–508.
   Web of Science ®Google Scholar
• ZhuP, YouX, PrattLR, PapadopoulosKD. Generalizations of the Fuoss approximation for ion pairing. J Chem Phys. 2011;134:054502.
   Web of Science ®Google Scholar
• UlasS, DiwekarUM. Efficient molecular simulations for environmentally benign processes. Mol Simul. 2006;32:315–329.
   Web of Science ®Google Scholar
• PaluchAS, ShenVK, ErringtonJR. Comparing the use of Gibbs ensemble and grand-canonical transition-matrix Monte Carlo methods to determine phase equilibria. Ind Eng Chem Res. 2008;47:4533–4541.
   Web of Science ®Google Scholar
• WyczalkowskiMA, PappuRV. Satisfying the fluctuation theorem in free-energy calculations with Hamiltonian replica exchange. Phys Rev E. 2008;77:026104.
   Web of Science ®Google Scholar
• FrinkLJD, MartinM. A combined molecular simulation-molecular theory method applied to a polyatomic molecule in a dense solvent. Condens Matter Phys. 2005;8:271–280.
   Web of Science ®Google Scholar
• VrhovšekA, GerebenO, JamnikA, PusztaiL. Hydrogen bonding and molecular aggregates in liquid methanol, ethanol, and 1-propanol. J Phys Chem B. 2011;115:13473–13488.
   PubMed Web of Science ®Google Scholar
• LuciaA, BonkBM, WatermanRR, RoyA. A multi-scale framework for multi-phase equilibrium flash. Comput Chem Eng. 2012;36:79–98.
   Web of Science ®Google Scholar
• ShiW, MaginnEJ. Improvement in molecule exchange efficiency in Gibbs ensemble Monte Carlo: development and implementation of the continuous fractional component move. J. Comput. Chem. 2008;29:2520–2530.
   PubMed Web of Science ®Google Scholar
• GelbLD, ChakrabortySN. Boiling point determination using adiabatic Gibbs ensemble Monte Carlo simulations: application to metals described by embedded-atom potentials. J Chem Phys. 2011;135:224113.
   PubMed Web of Science ®Google Scholar
• EcklB, VrabecJ, HasseH. On the application of force fields for predicting a wide variety of properties: ethylene oxide as an example. Fluid Phase Equilib. 2008;274:16–26.
   Web of Science ®Google Scholar
• DeubleinS, EcklB, StollJ, LishchukSV, Guevara-CarrionG, GlassCW, MerkerT, BernreutherM, HasseH, VrabecJ. ms2: A molecular simulation tool for thermodynamic properties. Comput Phys Commun. 2011;182:2350–2367.
   Web of Science ®Google Scholar