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Molecular Simulation: Prediction and Design for the Future

Explore the world of molecular simulation and its applications in prediction and design, including adsorption in porous materials and solvation of pharmaceuticals. Discover the potential for synthesis of nanoporous materials and novel Metal-Organic Framework (MOF) materials.

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Molecular Simulation: Prediction and Design for the Future

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  1. MOLECULAR SIMULATION AS A PREDICTION AND DESIGN TOOL FOR THE FUTURE Miguel Jorge Laboratory of Separation and Reaction Engineering (LSRE) Associate Laboratory LSRE/LCM Department of Chemical Engineering, Faculty of Engineering, University of Porto (FEUP) Porto, Portugal

  2. Outline • What is Molecular Simulation? - Microstates and Macrostates. - Monte Carlo (MC) and molecular dynamics (MD). - Molecular Modelling. • Molecular Simulation for Prediction - Predicting adsorption in complex porous materials. - Predicting solvation of pharmaceuticals. • Molecular Simulation for Design - Synthesis of nanoporous materials. - Novel Metal-Organic Framework (MOF) materials. • Conclusions and Outlook 2

  3. Outline • What is Molecular Simulation? - Microstates and Macrostates. - Monte Carlo (MC) and molecular dynamics (MD). - Molecular Modelling. • Molecular Simulation for Prediction - Predicting adsorption in complex porous materials. - Predicting solvation of pharmaceuticals. • Molecular Simulation for Design - Synthesis of nanoporous materials. - Novel Metal-Organic Framework (MOF) materials. • Conclusions and Outlook 3

  4. Statistical Mechanics and Thermodynamics MACROSTATE MICROSTATE • Fluctuating microscopic properties (positions, velocities, etc.) • Fixed set of thermodynamic properties (Temperature, Pressure, etc.) • Each macrostate is consistent with a infinitely large number of possible microstates. • Macroscopic properties (as measured in a laboratory experiment) are an average over time and over a large number of microstates. • Statistical Mechanics connects microscopic to macroscopic properties. • In Molecular Simulation, we create many microstates on the computer, and calculate properties by averaging over time and/or over several microstates. COMPUTER EXPERIMENT 4

  5. Simulation Methods MOLECULAR DYNAMICS • Design a microscopic model of the system and study its evolution in time. • Solve Newton’s equations of motion for all atoms using a numerical integrator. • Average the properties over time, just like in a real experiment. • Allows for the calculation of both equilibrium and dynamical properties. MONTE CARLO • Create a large number of microstates (ensemble) consistent with a given macrostate. • System evolves along Markov chain through stochastic (unphysical) moves. • Properties are averaged over all the microstates in the ensemble. • In principle, may be used in any thermodynamic ensemble. • Allows only for the calculation of equilibrium properties. 5

  6. FORCE-FIELD MONTE CARLO MOLECULAR DYNAMICS PREDICTION DESIGN Molecular Modelling Gather information about the system. Develop molecular level model. Apply simulation methods. Refine the model. Analyse results. Compare with experimental data. SUCCESS !! 6

  7. Outline • What is Molecular Simulation? - Microstates and Macrostates. - Monte Carlo (MC) and molecular dynamics (MD). - Molecular Modelling. • Molecular Simulation for Prediction - Predicting adsorption in complex porous materials. - Predicting solvation of pharmaceuticals. • Molecular Simulation for Design - Synthesis of nanoporous materials. - Novel Metal-Organic Framework (MOF) materials. • Conclusions and Outlook 7

  8. w Predicting Adsorption in Complex Porous Materials ACTIVATED CARBON MOLECULAR MODEL CARBON PORES POLAR SITES WATER + POLLUTANTS PURIFIED WATER WATER • Complex structure and chemistry. • Stacked graphite plates with some polar sites. • Need to develop model to predict adsorption. ETHANE 8

  9. Predicting Adsorption in Complex Porous Materials Pure Ethane Pore size distribution Predict Ethane/Water adsorption Pure Water Active site distribution 9

  10. Predicting Solvation of Pharmaceuticals Biochemistry, Medicine and Pharmaceutical Industry Understanding molecular level interactions Understanding molecular level interactions Protein-Ligand Binding Affinities Solvation Gibbs Free Energy Molecular Docking & Scoring Testing Interaction Force Fields Testing Interaction Force Fields Drug Solubility Drug Solubility Drug Absorption Partition Coefficients Partition Coefficients 10

  11. Predicting Solvation of Pharmaceuticals Hydrocarbons Dissolved in Octanol Water/Octanol Partition Coefficients Hydrocarbons Dissolved in Water • Good predictions of individual solvation energies. • Excellent predictions of partition coefficients of both polar and non-polar molecules. 11

  12. Outline • What is Molecular Simulation? - Microstates and Macrostates. - Monte Carlo (MC) and molecular dynamics (MD). - Molecular Modelling. • Molecular Simulation for Prediction - Predicting adsorption in complex porous materials. - Predicting solvation of pharmaceuticals. • Molecular Simulation for Design - Synthesis of nanoporous materials. - Novel Metal-Organic Framework (MOF) materials. • Conclusions and Outlook 12

  13. Synthesis of Nanoporous Materials Molecular Dynamics simulation of mesoporous silica formation Addition of Silica Silica Condensation • Understand the synthesis process. • Identify factors that can control material structure and function. • Build molecular-level models to be used in adsorption simulations. 13

  14. Novel Hybrid MOF Materials ORGANIC LINKER METALLIC CENTRE Large Pores Small Pockets • Combination of Metallic Centres and Organic Linkers. • Allows for design of both pore structure and surface chemistry. • Show unusual properties (specific sites, “breathing”, ultra-large porosity). • Great potential for challenging separations (e.g., propane/propylene). 14

  15. Novel Hybrid MOF Materials PROPANE PROPYLENE PROPYLENE • Classical Model. • Good Predictions. • Classical Model. • Poor Predictions. • Model with open metal sites. • Good Predictions. 15

  16. Applications of Molecular Simulation • Fundamental Science - Probing complex systems in detail at the molecular level. - Easy to separate different physical effects (not possible experimentally). - Already routinely used for this purpose. • Property Predictions - Properties that are difficult and/or expensive to measure experimentally. - Based on physically realistic models => possible to extrapolate. - Possible for several properties, but not yet routinely used. • Design of Materials and Molecules - Understanding and controlling the synthesis process. - Identifying necessary characteristics for a given goal. - First efforts are currently underway => integrated strategies are required. 16

  17. Acknowledgements FUNDING: - FCT Project PTDC/EQU-EQU/099423/2008. - FCT Project PTDC/EQU-FTT/104195/2008. - HCP-Europa Programme. - Treaty of Windsor grant B-11/08. CO-WORKERS: - Alírio E. Rodrigues (LSRE/LCM) - António Queimada (LSRE/LCM) - Ioannis Economou (Petroleum Institute) - José Richard Gomes (CICECO) - Maria Eugénia Macedo (LSRE/LCM) - Miguel Ângelo Granato (LSRE/LCM) - Natália Cordeiro (REQUIMTE) - Nigel A. Seaton (University of Edinburgh) - Nuno Garrido (LSRE/LCM) Find out more at:http://lsre.fe.up.pt 17

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