@article{HollandMoritzGraupnerMoelleretal.2018,
  author    = {Holland-Moritz, Henry and Graupner, Julia and M{\"o}ller, Wolfhard and Pacholski, Claudia and Ronning, Carsten},
  title     = {Dynamics of nanoparticle morphology under low energy ion irradiation},
  series = {Nanotechnology},
  volume    = {29},
  journal   = {Nanotechnology},
  number    = {31},
  publisher = {IOP Publ. Ltd.},
  address   = {Bristol},
  issn      = {0957-4484},
  doi       = {10.1088/1361-6528/aac36c},
  pages     = {7},
  year      = {2018},
  abstract  = {If nanostructures are irradiated with energetic ions, the mechanism of sputtering becomes important when the ion range matches about the size of the nanoparticle. Gold nanoparticles with diameters of similar to 50 nm on top of silicon substrates with a native oxide layer were irradiated by gallium ions with energies ranging from 1 to 30 keV in a focused ion beam system. High resolution in situ scanning electron microscopy imaging permits detailed insights in the dynamics of the morphology change and sputter yield. Compared to bulk-like structures or thin films, a pronounced shaping and enhanced sputtering in the nanostructures occurs, which enables a specific shaping of these structures using ion beams. This effect depends on the ratio of nanoparticle size and ion energy. In the investigated energy regime, the sputter yield increases at increasing ion energy and shows a distinct dependence on the nanoparticle size. The experimental findings are directly compared to Monte Carlo simulations obtained from iradina and TRI3DYN, where the latter takes into account dynamic morphological and compositional changes of the target.},
  language  = {en}
}
@article{CvetkovićConradLie2021,
  author    = {Cvetković, Nada and Conrad, Tim and Lie, Han Cheng},
  title     = {A convergent discretization method for transition path theory for diffusion processes},
  series = {Multiscale modeling \& simulation : a SIAM interdisciplinary journal},
  volume    = {19},
  journal   = {Multiscale modeling \& simulation : a SIAM interdisciplinary journal},
  number    = {1},
  publisher = {Society for Industrial and Applied Mathematics},
  address   = {Philadelphia},
  issn      = {1540-3459},
  doi       = {10.1137/20M1329354},
  pages     = {242 -- 266},
  year      = {2021},
  abstract  = {Transition path theory (TPT) for diffusion processes is a framework for analyzing the transitions of multiscale ergodic diffusion processes between disjoint metastable subsets of state space. Most methods for applying TPT involve the construction of a Markov state model on a discretization of state space that approximates the underlying diffusion process. However, the assumption of Markovianity is difficult to verify in practice, and there are to date no known error bounds or convergence results for these methods. We propose a Monte Carlo method for approximating the forward committor, probability current, and streamlines from TPT for diffusion processes. Our method uses only sample trajectory data and partitions of state space based on Voronoi tessellations. It does not require the construction of a Markovian approximating process. We rigorously prove error bounds for the approximate TPT objects and use these bounds to show convergence to their exact counterparts in the limit of arbitrarily fine discretization. We illustrate some features of our method by application to a process that solves the Smoluchowski equation on a triple-well potential.},
  language  = {en}
}