@Article{macau_mods_00005908,
  author = 	{Majumdar, Arnab
		and M{\"u}ller, Martin
		and Busch, Sebastian},
  title = 	{Computation of X-ray and Neutron Scattering Patterns to Benchmark Atomistic Simulations against Experiments},
  journal = 	{International journal of molecular sciences},
  year = 	{2024},
  publisher = 	{MDPI AG},
  address = 	{Basel},
  volume = 	{25},
  number = 	{3},
  keywords = 	{Radiography; Neutron Diffraction; X-Ray Diffraction; Neutrons; X-Rays; Scattering, Small Angle; Molecular Dynamics Simulation; X-ray scattering; Neutron Scattering; Small-angle Scattering; Quasielastic Neutron Scattering; Finite-size Effect; Sassena; Wide-angle Diffraction},
  abstract = 	{Molecular Dynamics simulations study material structure and dynamics at the atomic level. X-ray and neutron scattering experiments probe exactly the same time- and length scales as the simulations. In order to benchmark simulations against measured scattering data, a program is required that computes scattering patterns from simulations with good single-core performance and support for parallelization. In this work, the existing program Sassena is used as a potent solution to this requirement for a range of scattering methods, covering pico- to nanosecond dynamics, as well as the structure from some {\AA}ngstr{\"o}ms to hundreds of nanometers. In the case of nanometer-level structures, the finite size of the simulation box, which is referred to as the finite size effect, has to be factored into the computations for which a method is described and implemented into Sassena. Additionally, the single-core and parallelization performance of Sassena is investigated, and several improvements are introduced.},
  issn = 	{1422-0067},
  doi = 	{10.3390/ijms25031547},
  url = 	{https://macau.uni-kiel.de/receive/macau_mods_00005908},
  url = 	{https://doi.org/10.3390/ijms25031547},
  url = 	{http://www.ncbi.nlm.nih.gov/pubmed/38338829},
  file = 	{:https://macau.uni-kiel.de/servlets/MCRFileNodeServlet/macau_derivate_00007369/ijms-25-01547.pdf:PDF},
  language = 	{en}
}