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  • Machine learning models for Si nanoparticle growth in nonthermal plasma

    work
    Creator:
    Raymond, Matt, Elvati, Paolo, Saldinger, Jacob C, Lin, Jonathan, Shi, Xuetao, and Violi, Angela
    Description:
    Nanoparticles (NPs) formed in nonthermal plasmas (NTPs) can have unique properties and applications. However, modeling their growth in these environments presents significant challenges due to the non-equilibrium nature of NTPs, making them computationally expensive to describe. In this work, we address the challenges associated with accelerating the estimation of parameters needed for these models. Specifically, we explore how different machine learning models can be tailored to improve prediction outcomes. We apply these methods to reactive classical molecular dynamics data, which capture the processes associated with colliding silane fragments in NTPs. These reactions exemplify processes where qualitative trends are clear, but their quantification is challenging, hard to generalize, and requires time-consuming simulations. Our results demonstrate that good prediction performance can be achieved when appropriate loss functions are implemented and correct invariances are imposed. While the diversity of molecules used in the training set is critical for accurate prediction, our findings indicate that only a fraction (15-25%) of the energy and temperature sampling is required to achieve high levels of accuracy. This suggests a substantial reduction in computational effort is possible for similar systems.
    Keyword:
    machine learning, molecular dynamics, nanoparticle, nonthermal plasma, silane, and sticking coefficient
    Citation to related publication:
    Raymond, M., Elvati, P., Saldinger, J. C., Lin, J., Shi, X., & Violi, A. (2025). Machine learning models for Si nanoparticle growth in nonthermal plasma. Plasma Sources Science and Technology.  https://doi.org/10.1088/1361-6595/adbae1 and  https://arxiv.org/abs/2501.00003
    Discipline:
    Science

  • 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: Appl. Phys. 54 365203, DOI: 10.1088/1361-6463/ac0b71
    Discipline:
    Science