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  • On the growth of Si nanoparticles in non-thermal plasma: physisorption to chemisorption conversion

    work
    Creator:
    Shi, Xuetao, Elvati, Paolo, and Violi, Angela
    Description:
    Non-thermal plasma systems offer unique opportunities in the fields of bio-imaging, drug delivery, photovoltaics, microelectronics manufacturing. Such interests are largely inspired by the fact that hot plasma electrons coexist with neutral species and ions close to room-temperature under non-thermal plasma conditions. Modeling of these systems requires a deep understanding of the atomistic processes underlying the rich chemistry of the various radicals and ions with the nascent nanoparticle surface. A key parameter for determining the contribution of a certain radical/ion species to the nanoparticle surface growth, called sticking coefficient, is computed as a weighted sum from the simulated sticking outcomes with different collision velocities drawn from a Maxwell-Boltzmann distribution at certain temperatures. In this work, the collisions of SiHx (x=1-4) fragments and silicon cluster (Si4, Si2H6, and Si29H36) surfaces, responsible for the sticking coefficients, are simulated by molecular dynamics (MD) with a reactive force field. The dependence of sticking coefficients on temperature, H coverage of both silane fragments and cluster surfaces, and the size of the cluster, are systematically examined. And the mechanism underlying the sticking events, specifically the conversion of physical aggregation to chemisorption is investigated to better understand the complex interplay between factors influencing the surface growth. The detailed and multi-parameter model of sticking coefficients, accompanied by the mechanism study of physisorption to chemisorption conversion, provides a more accurate and robust approximation of surface growth rate using sticking coefficients, and a deeper understanding of surface growth processes, for the wider non-thermal plasma simulation community.
    Keyword:
    Sticking coefficients, Silanes, Molecular Dynamics, Non-equilibrium, and Aggregation mechanisms
    Citation to related publication:
    Shi, X., Elvati, P., Violi, A. (2021). On the growth of Si nanoparticles in non-thermal plasma: physisorption to chemisorption conversion. J. Phys. D. Submitted.
    Discipline:
    Science

  • Simulation Parameters used in the Study titled "Efficient Estimation of Binding Free Energies between Peptides and an MHC Class II Molecule Using Coarse-Grained Molecular Dynamics Simulations with a Weighted Histogram Analysis Method"

    work
    Creator:
    Larson, Ronald G., Wen, Fei, Huang, Wenjun, and Huang, Ming
    Description:
    We provide the parameters used in Umbrella Sampling simulations reported in our study "Efficient Estimation of Binding Free Energies between Peptides and an MHC Class II Molecule Using Coarse-Grained Molecular Dynamics Simulations with a Weighted Histogram Analysis Method", namely the set positions and spring constants for each window in simulations. Two tables are provided. Table 1 lists the names of the peptides and their corresponding sequences. Table 2 lists the parameters. The abstract of our work is the following: We estimate the binding free energy between peptides and an MHC class II molecule using molecular dynamics (MD) simulations with Weighted Histogram Analysis Method (WHAM). We show that, owing to its more thorough sampling in the available computational time, the binding free energy obtained by pulling the whole peptide using a coarse-grained (CG) force field (MARTINI) is less prone to significant error induced by biased-sampling than using an atomistic force field (AMBER). We further demonstrate that using CG MD to pull 3-4 residue peptide segments while leaving the remain-ing peptide segments in the binding groove and adding up the binding free energies of all peptide segments gives robust binding free energy estimations, which are in good agreement with the experimentally measured binding affinities for the peptide sequences studied. Our approach thus provides a promising and computationally efficient way to rapidly and relia-bly estimate the binding free energy between an arbitrary peptide and an MHC class II molecule.
    Keyword:
    Molecular Dynamics, Binding Free Energy, Protein, MHC, and Coarse-Grained
    Discipline:
    Science and Engineering