480702 Screening Chemical Parameter Space of Self Assembling Monolayers

Monday, November 14, 2016
Grand Ballroom B (Hilton San Francisco Union Square)
Trevor J. Jones1, Christoph Klein1, János Sallai2, Peter T. Cummings1 and Clare McCabe1, (1)Chemical and Biomolecular Engineering, Vanderbilt University, Nashville, TN, (2)Institute for Software Integrated Systems, Vanderbilt University, Nashville, TN

Spurred by the Materials Genome Initiative (MGI), there has been substantial effort to harness the power of supercomputing to accelerate the development of novel materials. Both the MIT Materials Project [1] and Harvard Clean Energy Project [2] have successfully leveraged molecular simulation to begin developing databases for crystalline structures and candidate molecules for organic electronic materials. However, to harness the power of molecular simulation on a scale required by the MGI for soft materials requires a different approach due to the added requirement of sampling systems in configurational space. To use molecular dynamic (MD) simulations for the chemical parameter screening of self assembling monolayers (SAMs) a robust set of tools is required to manage the chemical systems and MD simulations.

Here, we present MoSDeF (Molecular Simulation and Design Framework) [3]: developed to create and parameterize such arbitrary systems and naively manage simulations enabling large scale parameter screening of soft materials. We demonstrate the efficiency of using MoSDeF by generating an ensemble of 36 SAM systems using crystalline and amorphous silica substrates; alkane, methyl capped polyethylene glycol, and hydroxyl capped polyethylene glycol polymers; and chain lengths of 7, 10, 13, 16, 19, and 22 in minutes on a conventional workstation. Seven shearing simulations were done on each of the 36 SAM systems at 300 K and a 10 m/s shear rate for normal loads of 300, 600, 900, 1200, 1500, 2100, and 2700 kJ/mol/Å for a total of 252 simulations. Shearing simulations of the SAM systems were performed using the GROMACS [4] simulation engine to explore frictional forces, perpendicular forces, nematic ordering, and the stick-slip phenomenon of the individual SAM systems and to establish chemical parameter trends. While crystalline alkane SAM systems may produce unreliable data because of the extreme order of the system, trends were observed for orther systems. Trends observed relate the frictional forces, perpendicular forces, nematic ordering, and the stick-slip phenomenon to the three different polymers and varying chain lengths. The workflow presented here serves as a stepping stone towards the automated screening of soft materials using molecular simulation.

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[2] J. Hachmann, R. Olivares-Amaya, S. Atahan-Evrenk, C. Amador-Bedolla, R. S. Sánchez-Carrera, A. Gold-Parker, L. Vogt, A. M. Brockway, and A. Aspuru-Guzik, "The Harvard Clean Energy Project: Large-Scale Computational Screening and Design of Organic Photovoltaics on the World Community Grid," J. Phys. Chem. Lett., 2 (17), 2241–2251. (2011)

[3] C. Klein, J. Sallai, T. J. Jones, C. R. Iacovella, C. McCabe, and P. T. Cummings, "mBuild: A Hierarchical, Component Based Molecule Builder," (2016)

[4] S. Pronk, S. Pall, R. Schulz, P. Larsson, P. Bjelkmar, R. Apostolov, M. R. Shirts, J. C. Smith, P. M. Kasson, D. Van Der Spoel, B. Hess, E. Lindahl, "GROMACS 4.5: A high-throughput and highly parallel open source molecular simulation toolkit." Bioinformatics 29, 845-854. (2013).


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