In plasma-source ion implantation a target is pulse biased to a high negative voltage, forming an expanding plasma sheath. A numerical simulation model for the evolution of the sheath has been developed and compared successfully. with experimental results. The model is one dimensional (planar, cylindrical, or spherical). The time-dependent, self-consistent potential profile is calculated from Poisson's equation coupled with collisionless fluid equations for the ions and a Boltzmann assumption for the electrons. In addition to the density and potential profile, the simulation yields the ion current to the surface and the energy spectrum of the ions hitting the surface.
Molecular mechanics (MM) potentials have long been a workhorse of computational chemistry. Leveraging accuracy and speed, these functional forms find use in a wide variety of applications in biomolecular modeling...
Dust particles immersed within a plasma environment, such as those found in planetary rings or cometary environments, will acquire an electric charge. If the ratio of interparticle potential energy to average kinetic energy is high enough the particles will form either a 'liquid' structure with short-range ordering or a crystalline structure with long-range ordering. Since their discovery in laboratory environments in 1994, such crystals have been the subject of a variety of experimental, theoretical, and numerical investigations. Laboratory experiments analyzing the behavior of dust grains in a plasma rely on optical diagnostics to provide data about the system in a nonperturbative manner. In the past, capturing, imaging, and analyzing crystalline structure in dusty plasmas has been a non-trivial problem. Utilizing digital imaging and analysis systems, data capture, image formatting, and analysis can be done quickly. Following data capture, image analysis is conducted using modified Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV) algorithms. The data extracted is then used to construct Voronoi diagrams, calculate particle density, inter-particle spacing, pair correlation functions, and thermal energy. From this data other dust plasma parameters can be inferred such as inter-particle forces and grain charges.
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