Molecular modeling of hydrogen bonding fluids: vapor-liquid coexistence and interfacial properties

Transcription

1 12 th HLRS Results and Review Workshop Molecular modeling of hydrogen bonding fluids: vapor-liquid coexistence and interfacial properties High Performance Computing Center Stuttgart (HLRS), October 8, 2009 M. HORSCH, M. HEITZIG, T. MERKER, T. SCHNABEL, Y.-L. HUANG, H. HASSE, J. VRABEC SFB 716

2 Technology Vision 2020: The US chemical industry New Chemical Engineering Science and Technology Supply Chain Management Information Systems Manufacturing & Operations Engineering Computational Technologies Computational Molecular Science Computational Fluid Dynamics Process Modeling & Simulation Operations Simulation & Optimization link between Engineering and Chemistry new processes, products, materials

3 Molecular modeling: Force fields Geometry Bond lengths and angles Electrostatics Position and magnitude of dipoles, quadrupoles and partial charges Dispersion and repulsion Parameters of Lennard-Jones potentials Numerous parameters

4 Modeling of hydrogen bonding fluids: Ammonia Vapor-liquid equilibrium Supercritical fluid density NH 3 model of Eckl et al. Other models Correlation of experimental data Excellent reliability for the extrapolation of thermophysical properties

5 Ammonia: Predicted transport properties Self-diffusion coefficient Shear viscosity 50 MPa experimental data simulation results

6 Molecular simulation of fluid mixtures Purely predictive electrostatics LJ parameters from combination rules A σ A, ε A A σ AB, ε AB B σ B, ε B B adjustment to a single experimental value p(t, x) or Δh v (T) 230 K 4650 kpa

7 MD simulation of a single droplet Vapor and liquid are equilibrated separately A small (n < 10000) droplet is inserted into the vapor If the droplet cannot evaporate completely, an equilibrium is established within a few nanoseconds truncated-shifted LJ fluid (r c = 2.5 σ)

8 Vapor-liquid coexistence: Cluster criteria

9 Comparison of cluster criteria 80 Supersaturated vapor, CO 2, T = 237 K size fluctuation in reduced units Stillinger TWF arithm. geom. Kible droplet size in molecules

10 Droplet interface properties δ in units of nm curvature 1/R σ in units of nm K 117 K Surface tension (Tolman): σ σ R R + simulation Tolman equation ---planar interface e e δ δ 110 K σ in units of g/s K For small droplets, the Tolman length δ = Re Rσ, i.e. a characteristic interface thickness, increases significantly. 97 K 110 K K droplet size in atoms

11 Contact angle: Simulation of a meniscus

12 Contact angle and fluid-wall dispersion distance from the wall in units of σ Methane meniscus (t. s. LJ fluid) between graphite walls T = 0.88 ε/k W = 0.07 W = 0.13 W = 0.1 W = z coordinate in units of σ contact angle in degrees T = 0.73 ε/k B T = 0.88 ε/k B T = 1 ε/k B reduced fluid-wall dispersive energy W ( T, E ΔW ) = cosθ( T, E ΔW ) cos θ +

13 High performance computing cacau XC 6000 SX8 100 ls1 Mardyn ms2 (small system sizes) speedup speedup processes cacau SX8 XC processes without load balancing static load balancing

14 Innovative HPC-Methoden und Einsatz für hochskalierbare Molekulare Simulation (IMEMO) Project scheduled from October 2008 to December 2011 Project associates: Industrial associates:

15 Conclusion Molecular simulation for process engineering is already applied in the industry raises high expectations is a common endeavor of engineers, natural scientists, and computer scientists relies on HPC: Hardware, software, and algorithms