Date of Graduation
5-2017
Document Type
Thesis
Degree Name
Master of Science in Computer Science (MS)
Degree Level
Graduate
Department
Computer Science & Computer Engineering
Advisor/Mentor
Patitz, Matthew J.
Committee Member
Beavers, M. Gordon
Second Committee Member
Hendricks, Jacob
Third Committee Member
Kim, Jin-Woo
Fourth Committee Member
Li, Qinghua
Keywords
Applied sciences; Dna nanotechnology; Graphical processing units; Molecular dynamics; Oxdna
Abstract
This thesis discusses massively parallel molecular dynamics simulations of nBLOCKs using graphical processing units. nBLOCKs are nanoscale building blocks composed of gold nanoparticles functionalized with single-stranded DNA molecules. To explore greater simulation time scales we implement our nBLOCK computational model as an extension to the coarse grain molecular simulator oxDNA. oxDNA is parameterized to match the thermodynamics of DNA strand hybridization as well as the mechanics of single stranded DNA and double stranded DNA. In addition to an in-depth review of our implementation details we also provide results of the model validation and performance tests. These validation and performance tests are comprised of over a hundred separate simulations spanning in simulation length from one thousand to ten million times steps and with simulation sizes ranging from 16 to 27832 particles. Together these tests show the ability of our implementation to handle the full range of basic nBLOCK topologies in a diverse set of conditions. A selection of the utilities developed during the course of this thesis are also discussed. We provide descriptions of the scripting utilities which support nBLOCK assembly generation, simulation, and analysis.
Citation
Fochtman, T. L. (2017). Molecular Dynamics Simulations of DNA-Functionalized Nanoparticle Building Blocks on GPUs. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/1926
Included in
Nanoscience and Nanotechnology Commons, Numerical Analysis and Scientific Computing Commons