Relevant bibliographies by topics / Brownian dynamics simulations (BDS)

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Brownian dynamics simulations (BDS)'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Brownian dynamics simulations (BDS)"

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GUPTA, V. K. "BROWNIAN DYNAMICS SIMULATION OF CATCH TO SLIP TRANSITION OVER A MODEL ENERGY LANDSCAPE." Journal of Biological Systems 24, no. 02n03 (June 2016): 275–93. http://dx.doi.org/10.1142/s0218339016500145.

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We perform Brownian dynamics simulation (BDS) of catch to slip transition over a model energy landscape. Through our BDS we demonstrate that for forces below the critical force the bond rupture occurs mostly through the catch pathway while for forces above the critical force the bond rupture occurs mostly through the slip pathway. We also demonstrate that the shoulder in the bond rupture force distribution switches to peak as the loading rate increases progressively and the bond lifetime is maximized at the model dependent critical force. The force dependent bond lifetime obtained via transforming the bond rupture force distribution at a given loading rate is in excellent agreement with that obtained from our BDS at constant forces. An alternative to the current mechanism of catch to slip transition is presented and validated through BDS.
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Geyer, T., C. Gorba, and V. Helms. "Interfacing Brownian dynamics simulations." Journal of Chemical Physics 120, no. 10 (March 8, 2004): 4573–80. http://dx.doi.org/10.1063/1.1647522.

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Oettinger, Hans Christian. "Variance Reduced Brownian Dynamics Simulations." Macromolecules 27, no. 12 (June 1994): 3415–23. http://dx.doi.org/10.1021/ma00090a041.

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Huber, Gary A., and J. Andrew McCammon. "Brownian Dynamics Simulations of Biological Molecules." Trends in Chemistry 1, no. 8 (November 2019): 727–38. http://dx.doi.org/10.1016/j.trechm.2019.07.008.

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He, Siqian, and Harold A. Scheraga. "Brownian dynamics simulations of protein folding." Journal of Chemical Physics 108, no. 1 (January 1998): 287–300. http://dx.doi.org/10.1063/1.475379.

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Erban, Radek. "From molecular dynamics to Brownian dynamics." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 470, no. 2167 (July 8, 2014): 20140036. http://dx.doi.org/10.1098/rspa.2014.0036.

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Three coarse-grained molecular dynamics (MD) models are investigated with the aim of developing and analysing multi-scale methods which use MD simulations in parts of the computational domain and (less detailed) Brownian dynamics (BD) simulations in the remainder of the domain. The first MD model is formulated in one spatial dimension. It is based on elastic collisions of heavy molecules (e.g. proteins) with light point particles (e.g. water molecules). Two three-dimensional MD models are then investigated. The obtained results are applied to a simplified model of protein binding to receptors on the cellular membrane. It is shown that modern BD simulators of intracellular processes can be used in the bulk and accurately coupled with a (more detailed) MD model of protein binding which is used close to the membrane.
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Wade, R. C. "Brownian dynamics simulations of enzyme-substrate encounter." Biochemical Society Transactions 24, no. 1 (February 1, 1996): 254–59. http://dx.doi.org/10.1042/bst0240254.

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Li, Lei, Ronald G. Larson, and Tam Sridhar. "Brownian dynamics simulations of dilute polystyrene solutions." Journal of Rheology 44, no. 2 (March 2000): 291–322. http://dx.doi.org/10.1122/1.551087.

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Meng, Xuan-Yu, Yu Xu, Hong-Xing Zhang, Mihaly Mezei, and Meng Cui. "Predicting Protein Interactions by Brownian Dynamics Simulations." Journal of Biomedicine and Biotechnology 2012 (2012): 1–11. http://dx.doi.org/10.1155/2012/121034.

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We present a newly adapted Brownian-Dynamics (BD)-based protein docking method for predicting native protein complexes. The approach includes global BD conformational sampling, compact complex selection, and local energy minimization. In order to reduce the computational costs for energy evaluations, a shell-based grid force field was developed to represent the receptor protein and solvation effects. The performance of this BD protein docking approach has been evaluated on a test set of 24 crystal protein complexes. Reproduction of experimental structures in the test set indicates the adequate conformational sampling and accurate scoring of this BD protein docking approach. Furthermore, we have developed an approach to account for the flexibility of proteins, which has been successfully applied to reproduce the experimental complex structure from the structure of two unbounded proteins. These results indicate that this adapted BD protein docking approach can be useful for the prediction of protein-protein interactions.
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BRAŃKA, ARKADIUSZ C. "ON ALGORITHMS FOR BROWNIAN DYNAMICS COMPUTER SIMULATIONS." Computational Methods in Science and Technology 4, no. 1 (1998): 35–42. http://dx.doi.org/10.12921/cmst.1998.04.01.35-42.

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Dissertations / Theses on the topic "Brownian dynamics simulations (BDS)"

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Tran-Canh, Dung. "Simulating the flow of some non-Newtonian fluids with neural-like networks and stochastic processes." University of Southern Queensland, Faculty of Engineering and Surveying, 2004. http://eprints.usq.edu.au/archive/00001518/.

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The thesis reports a contribution to the development of neural-like network- based element-free methods for the numerical simulation of some non-Newtonian fluid flow problems. The numerical approximation of functions and solution of the governing partial differential equations are mainly based on radial basis function networks. The resultant micro-macroscopic approaches do not require any element-based discretisation and only rely on a set of unstructured collocation points and hence are truly meshless or element-free. The development of the present methods begins with the use of the multi-layer perceptron networks (MLPNs) and radial basis function networks (RBFNs) to effectively eliminate the volume integrals in the integral formulation of fluid flow problems. An adaptive velocity gradient domain decomposition (AVGDD) scheme is incorporated into the computational algorithm. As a result, an improved feed forward neural network boundary-element-only method (FFNN- BEM) is created and verified. The present FFNN-BEM successfully simulates the flow of several Generalised Newtonian Fluids (GNFs), including the Carreau, Power-law and Cross models. To the best of the author's knowledge, the present FFNN-BEM is the first to achieve convergence for difficult flow situations when the power-law indices are very small (as small as 0.2). Although some elements are still used to discretise the governing equations, but only on the boundary of the analysis domain, the experience gained in the development of element-free approximation in the domain provides valuable skills for the progress towards an element-free approach. A least squares collocation RBFN-based mesh-free method is then developed for solving the governing PDEs. This method is coupled with the stochastic simulation technique (SST), forming the mesoscopic approach for analyzing viscoelastic flid flows. The velocity field is computed from the RBFN-based mesh-free method (macroscopic component) and the stress is determined by the SST (microscopic component). Thus the SST removes a limitation in traditional macroscopic approaches since closed form constitutive equations are not necessary in the SST. In this mesh-free method, each of the unknowns in the conservation equations is represented by a linear combination of weighted radial basis functions and hence the unknowns are converted from physical variables (e.g. velocity, stresses, etc) into network weights through the application of the general linear least squares principle and point collocation procedure. Depending on the type of RBFs used, a number of parameters will influence the performance of the method. These parameters include the centres in the case of thin plate spline RBFNs (TPS-RBFNs), and the centres and the widths in the case of multi-quadric RBFNs (MQ-RBFNs). A further improvement of the approach is achieved when the Eulerian SST is formulated via Brownian configuration fields (BCF) in place of the Lagrangian SST. The SST is made more efficient with the inclusion of the control variate variance reduction scheme, which allows for a reduction of the number of dumbbells used to model the fluid. A highly parallelised algorithm, at both macro and micro levels, incorporating a domain decomposition technique, is implemented to handle larger problems. The approach is verified and used to simulate the flow of several model dilute polymeric fluids (the Hookean, FENE and FENE-P models) in simple as well as non-trivial geometries, including shear flows (transient Couette, Poiseuille flows)), elongational flows (4:1 and 10:1 abrupt contraction flows) and lid-driven cavity flows.
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Lappala, Anna. "Molecular dynamics simulations : from Brownian ratchets to polymers." Thesis, University of Cambridge, 2015. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.709251.

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Burmenko, Irina. "Brownian dynamics simulations of fine-scale molecular models." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/32330.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2005.
Includes bibliographical references (leaves 105-111).
One of the biggest challenges in non-Newtonian fluid mechanics is calculating the polymer contribution to the stress tensor, which is needed to calculate velocity and pressure fields as well as other quantities of interest. In the case of a Newtonian fluid, the stress tensor is linearly proportional to the velocity gradient and is given by the Newton's law of viscosity, but no such unique constitutive equation exists for non-Newtonian fluids. In order to predict accurately a polymer's rheological properties, it is important to have a good understanding of the molecular configurations in various flow situations. To obtain this information about molecular configurations and orientations, a micromechanical representation of a polymer molecule must be proposed. A micromechanical model may be fine scale, such as the Kramers chain model, which accurately predicts a real polymer's heological properties, but at the same time possesses too many degrees of freedom to be used in complex flow simulations, or it may be a coarse-grained model, such as the Hookean or the FENE dumbbell models, which can be used in complex flow analysis, but have too few degrees of freedom to adequately describe the rheology. The Adaptive Length Scale (ALS) model proposed by Ghosh et al. is only marginally more complicated than the FENE dumbbell model, yet it is able to capture the rapid stress growth in the start-up of uniaxial elongational flow, which is not predicted correctly by the simple dumbbell models. The ALS model is optimized in order to have its simulation time as close as possible to that of the FENE dumbbell.
(cont.) Subsequently, the ALS model is simulated in the start-up of the uniaxial elongational and shear flows as well as in steady extensional and shear flows, and the results are compared to those obtained with other competing rheological models such as the Kramers chain, FENE chain, and FENE dumbbell. While a 5-spring FENE chain predicts results that are in very good agreement with the Kramers chain, the required simulation time clearly makes it impossible to use this model in complex flow simulations. The ALS model agrees better with the Kramers chain than does the FENE dumbbell in the start-up of shear and elongational flows. However, the ALS model takes too long to achieve steady state, which is something that needs to be explored further before the model is used in complex flow calculations. Understanding of this phenomena may explain why the stress-birefringence hysteresis loop predicted by the ALS model is unexpectedly small. In general, if polymer stress is to be calculated using Brownian dynamics simulations, a large number of stochastic trajectories must be simulated in order to predict accurately the macroscopic quantities of interest, which makes the problem computationally expensive. However, recent technological advances as well as a new simulation algorithm called Brownian configuration fields make such problems much more tractable. The operation count in order to assess the feasibility of using the ALS model in complex flow situations yields very promising results if parallel computing is used to calculate polymer contribution to stress. In an attempt to capture polydispersity of real polymer solutions, the use of multi-mode models is explored.
(cont.) The model is fit to the linear viscoelastic spectrum to obtain relaxation times and individual modes' contributions to polymer viscosity. Then, data-fitting to the dimensionless extensional viscosity in the startup of the uniaxial elongational flow is performed for the ALS and the FENE dumbbell models to obtain the molecule's contour length, bmax. It is found that the results from the single-mode and the four-mode ALS models agree much better with the experimental data than do the corresponding single-mode and four-mode FENE dumbbell models. However, all four models resulted in a poor fit to the steady shear data, which may be explained by the fact that the zero-shear-rate viscosity obtained via a fit to the dynamic data by Rothstein and McKinley and used in present simulations, tends to be somewhat lower than the steady-state shear viscosity at very low shear rates, which may have caused a mismatch between the value of ... used in the simulation and the true ... of the polymer solution. As a motivation for using the ALS model in complex flow calculations, the results by Phillips, who simulated the closed-form version of the model in the benchmark 4:1:4 contraction- expansion problem are presented and compared to the experimental results by Rothstein and McKinley [49]. While the experimental observations show that there exists a large extra pres- sure drop, which increases monotonically with increasing De above the value observed for a Newtonian fluid subjected to the same flow conditions, the simulation results with a closed-form version of the FENE dumbbell model, called FENE-CR, exhibit the opposite trend.
(cont.) The ALS-C model, on the other hand, is able to predict the trend correctly. The use of the ALS-C model in another benchmark problem, namely the flow around an array of cylinders confined between two parallel plates, also shows very promising results, which are in much better agreement with experimental data by Liu as compared to the Oldroyd-B model. The simulation results for the ALS-C and the Oldroyd-B models are due to Joo, et al. [28] and Smith et al. [50], respectively. Overall, it is concluded that the ALS model is superior to the commonly used FENE dumb- bell model, although more work is needed to understand why it takes significantly longer than the FENE dumbbell to achieve steady state in uniaxial elongational flows, and why the stress birefringence hysteresis loop predicted by the ALS model is much smaller than that of the other rheological models.
by Irina Burmenko.
S.M.
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Evensen, Tom Richard, Stine Nalum Naess, and Arnljot Elgsaeter. "Transport properties of nanoparticles studied by Brownian dynamics simulations." Universitätsbibliothek Leipzig, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-192972.

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Evensen, Tom Richard, Stine Nalum Naess, and Arnljot Elgsaeter. "Transport properties of nanoparticles studied by Brownian dynamics simulations." Diffusion fundamentals 7 (2007) 2, S. 1-2, 2007. https://ul.qucosa.de/id/qucosa%3A14158.

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Murrow, Matthew Alan. "Kinesin model for Brownian dynamics simulations of stepping efficiency." University of Akron / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=akron156441669721832.

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Lodge, J. Felicity M. "Phase separation in model colloidal liquids by Brownian dynamics simulations." Thesis, University of Surrey, 1997. http://epubs.surrey.ac.uk/844592/.

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The technique of Brownian Dynamics simulation has been used to follow the evolution of model colloidal systems during phase separation in the liquid-vapour and solid-vapour regions of the phase diagram. Systems of monodisperse spherical particles interacting via LJ m:n type potentials were quenched in temperature from the one-phase region into the two phase region. Various structural and rheological properties were followed as the systems evolved, including the radial distribution functions, the small angle scattering peak of the structure factor, the interaction energy and the linear response rheology. The scaling behaviour of these quantities was found to be similar to that observed in light scattering experiments following the phase separation of colloidal systems. The aggregate structure could not be represented well by a single fractal dimension. Some evidence of fractal structure was found early in the phase separation, however the reversibility of the interactions allowed for a high degree of restructuring which led to a collapse of the initially tenuous structure into dense aggregates. The local structure was sensitive to the range of the interaction potential - as the potential became more short-ranged, increasing evidence of crystallisation of the denser phase was apparent from the form of g(f). Particles with 12:6 interactions formed structures displaying the rheological strength associated with an elastic gel. However restructuring was continual, resulting in a dense compact structure. The short-range 36:18 potential retained a tenuous gel-like structure and displayed an arrest of phase separation on long lengthscales. However, the particles did not have the interaction strength necessary to give significant rigidity to the system. This suggests that to form an arrested state with elastic gel-like rheology it would be necessary to have a more permanent form of interaction, in addition to the short-range reversible interactions used in this work.
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Carlsson, Tobias. "Brownian Dynamics Simulations of Macromolecules : Algorithm Development and Polymers under Confinement." Doctoral thesis, Uppsala universitet, Fysikalisk kemi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-173435.

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In this thesis I have used computer simulations to study the structure and dynamics of grafted polymers during confinement. These systems are of importance for understanding e.g. colloidal stability and surface coatings. We have used Brownian dynamics simulations with the polymers modeled as discrete wormlike chains allowing for a variable persistence length as well as different non-bonded interactions. The size and shape of the chains are characterized by the radius of gyration and the degree of oblateness/prolateness, and the entanglement is followed by calculating the mean overcrossing number. Starting in the dilute regime with a single polymer mushroom we have investigated how the rate of compression and solvent quality effects the behaviour of a compressed chain. In the brush regime, we investigated how the surface coverage effects the behaviour during compression. For low coverages the chains have the possibilty to increase their lateral extension during confinement but in general, the chains have a low inter-entanglement, as they strive to keep their integrity during the confinement process. To go from a polymer brush to the construction of a connected network, we have developed a method to construct a closed network without using periodic boundary conditions by building the network on a sphere in R4. In this way we avoid the restrictions of periodicity at the cell boundaries. We finally also show how to develop the idea of using spherical boundary conditions, by presenting a novel algorithm for simulating diffusion on a spherical surface. The method is more stable and allows for larger time steps, compared to commonly used methods in computer simulations.
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Hu, Xin. "Simulations of single molecular dynamics in hydrodynamic and electrokinetic flows." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1148579763.

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Fritschi, Sebastian [Verfasser]. "Event-driven Brownian dynamics simulations of two-dimensional fluids far from equilibrium / Sebastian Fritschi." Konstanz : Bibliothek der Universität Konstanz, 2018. http://d-nb.info/1159880484/34.

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Book chapters on the topic "Brownian dynamics simulations (BDS)"

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Bossis, G., and J. F. Brady. "Brownian and Stokesian Dynamics." In Microscopic Simulations of Complex Hydrodynamic Phenomena, 255–70. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4899-2314-1_19.

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Friedman, Avner. "Brownian dynamics simulations of colloidal dispersion." In Mathematics in Industrial Problems, 155–68. New York, NY: Springer New York, 1992. http://dx.doi.org/10.1007/978-1-4615-7405-7_15.

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Doyle, Patrick S., and Patrick T. Underhill. "Brownian Dynamics Simulations of Polymers and Soft Matter." In Handbook of Materials Modeling, 2619–30. Dordrecht: Springer Netherlands, 2005. http://dx.doi.org/10.1007/978-1-4020-3286-8_140.

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Bhattacharya, D. K., and E. Clementi. "Brownian Dynamics Simulations of a Complex Fluid System." In Modern Techniques in Computational Chemistry: MOTECC™-90, 919–34. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-2219-8_19.

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Doyle, Patrick S., and Patrick T. Underhill. "Brownian Dynamics Simulations of Polymers and Soft Matter." In Handbook of Materials Modeling, 2619–30. Dordrecht: Springer Netherlands, 2005. http://dx.doi.org/10.1007/1-4020-3286-2_140.

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Madura, Jeffry D., Malcolm E. Davist, Michael K. Gilson, Rebecca C. Wades, Brock A. Luty, and J. Andrew McCammon. "Biological Applications of Electrostatic Calculations and Brownian Dynamics Simulations." In Reviews in Computational Chemistry, 229–67. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2007. http://dx.doi.org/10.1002/9780470125823.ch4.

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Satoh, Akira. "Practice of Brownian Dynamics Simulations." In Introduction to Practice of Molecular Simulation, 173–86. Elsevier, 2011. http://dx.doi.org/10.1016/b978-0-12-385148-2.00005-7.

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Urbina-Villalba, G., J. Toro-Mendoza, A. Lozsán, and M. García-Sucre. "Brownian dynamics simulations of emulsion stability." In Interface Science and Technology, 677–719. Elsevier, 2004. http://dx.doi.org/10.1016/s1573-4285(04)80019-x.

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"Brownian Motion in an Inhomogeneous Medium Applied to Droplet Growth in the Transition Regime." In Rarefied Gas Dynamics: Theory and Simulations, 608–16. Washington DC: American Institute of Aeronautics and Astronautics, 1994. http://dx.doi.org/10.2514/5.9781600866319.0608.0616.

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Pastor, Richard W. "Determination of Chain Conformations in the Membrane Interior by Brownian Dynamics Simulations." In Molecular Description of Biological Membranes by Computer Aided Conformational Analysis, 171–202. CRC Press, 2019. http://dx.doi.org/10.1201/9780429291777-5.

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Conference papers on the topic "Brownian dynamics simulations (BDS)"

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Gallis, Michael, Daniel Rader, and John Torczynski. "DSMC Simulations of Brownian Dynamics of Particles." In 8th AIAA/ASME Joint Thermophysics and Heat Transfer Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2002. http://dx.doi.org/10.2514/6.2002-2760.

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Terada, Yayoi. "Brownian dynamics simulations on hard-sphere colloidal suspensions." In Third tohwa university international conference on statistical physics. AIP, 2000. http://dx.doi.org/10.1063/1.1291567.

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Tindjong, R. "Brownian dynamics simulations of ionic current through an open channel." In NOISE AND FLUCTUATIONS: 18th International Conference on Noise and Fluctuations - ICNF 2005. AIP, 2005. http://dx.doi.org/10.1063/1.2036815.

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Kumar, Satish. "Brownian Dynamics Simulations of Polymer Behavior in Nanofluidic and Microfluidic Systems." In ASME 2007 5th International Conference on Nanochannels, Microchannels, and Minichannels. ASMEDC, 2007. http://dx.doi.org/10.1115/icnmm2007-30162.

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Brownian dynamics (BD) is a stochastic simulation method that can quantitatively describe the non-equilibrium behavior of long polymers (∼1 micron contour length) over long time scales (∼1 s). With the increasing use of nanofluidic and microfluidic devices for the handling of biopolymers such as DNA, BD has the potential to be a powerful design tool for the separation and transport processes carried out in these devices. As a coarse-grained simulation method, BD also serves as a natural bridge between atomistic and continuum modeling. In this talk, an introduction to the Brownian dynamics simulation method will be given along with simulation results for some applications of current interest. The introduction will review basic molecular models for polymers (bead-rod, bead-spring) and the stochastic differential equations used to describe their dynamics. The applications will focus on polyelectrolyte adsorption and electrophoresis.
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Ikenna, Ivenso, and Todd D. Lillian. "The Dynamics of DNA Supercoiling: A Brownian Dynamics Study." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47444.

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Induced torsional stresses lead to an increase in the magnitude of torque sustained by double stranded DNA. There exists a critical magnitude of torque at which the DNA buckles signaling the beginning of the formation of a plectonemically supercoiled domain in the DNA. Further torsional deformation leads to an increase in the size of the supercoiled domain while the torque sustained by the DNA remains constant. The formation of the supercoiled domain also leads to a reduction in the end-to-end extension of the DNA starting with an abrupt reduction at the onset of buckling. Experiments have shown that this reduction in extension follows a linear trend. We investigate, by means of Brownian dynamics simulations, the extensional and torsional response of dsDNA to induced torsional stresses.
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Chirico, G., and J. Langowski. "Simulation of the Structure and Dynamics of Superhelical and Linear DNA by a Second-Order Brownian Dynamics Algorithm with Hydrodynamic Interactions." In Advances in biomolecular simulations. AIP, 1991. http://dx.doi.org/10.1063/1.41302.

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Ivenso, Ikenna D., and Todd D. Lillian. "Brownian Dynamics Simulation of the Dynamics of Stretched DNA." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-35487.

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DNA is a long flexible polymer and is involved in several fundamental cellular processes such as transcription, replication and chromosome packaging. These processes induce forces and torques in the DNA which deform it. These deformations in turn affect the structure and function of DNA. However, understanding of the dynamic response of DNA to the various forces that act on it is still far from complete. Several experiments have been carried out to study these responses most of which use a micron sized magnetic bead attached to the DNA molecule to both manipulate it and to observe its dynamics. One limitation of this approach is that the dynamics of the DNA molecule has mostly been characterized “indirectly” by observing the dynamics of the magnetic bead. It is also reasonable to expect that, because of the size of the bead relative to that of the DNA, the magnetic bead dynamics will obscure that of the DNA. We adapt existing coarse-grained Brownian dynamics models of DNA to develop a model capable of representing the dynamics of DNA without any of the artifacts inherent to the experiments. This model accounts for bending, torsion, extension, electrostatics, hydrodynamics and the random thermal forces acting on DNA in an electrolyte solution. We then carry out Brownian dynamics simulations with our model to benchmark with well established theoretical results of a stretched polymer in solution. Finally, we employ our model to predict the relaxation time scale for single molecule experiments which sets the framework for future studies in which we plan to further shed light on the dynamics of DNA over long length and time scales.
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Hayasaka, Ryo, and Akira Satoh. "Brownian Dynamics Simulations of Sedimentation Phenomena of Ferromagnetic Spherical Particles in a Colloidal Dispersion." In ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-67136.

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We have investigated sedimentation phenomena of a colloidal dispersion composed of ferromagnetic spherical particles in the gravity field, by means of Brownian dynamics simulations. In concrete, we have attempted to clarify the influences of the magnetic field strength, magnetic interactions between particles and volumetric fraction of particles on sedimentation phenomena of such magnetic particles. In order to discuss quantitatively the sedimentation process and the internal structures of particle aggregates after the sedimentation, we have concentrated our attention on the local radial distribution function of each layer. The main results obtained here are summarized as follows. For the case of a weak magnetic field and a weak magnetic force between particles, layered structures are formed. As the magnetic field increases, clusters are formed in upright formation along the gravity or the magnetic field direction. As magnetic particle-particle interactions increase, particles combine with each other to form aggregate in other directions, and new types of clusters are formed in the bottom area. In this situation, therefore, the upright-standing clusters come to disappear. For a dilute case, relatively small clusters are formed apart from each other in almost equal space. As the volumetric fraction increases from such a situation, clusters with voids in the center area of the clusters come to be observed, but such formation disappears and layered structures are formed with further increasing the volumetric fraction.
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Hoda, Nazish, Satish Kumar, Albert Co, Gary L. Leal, Ralph H. Colby, and A. Jeffrey Giacomin. "Polyelectrolyte Adsorption in Shear Flow with Hydrodynamic Interaction: Kinetic Theory and Brownian Dynamics Simulations." In THE XV INTERNATIONAL CONGRESS ON RHEOLOGY: The Society of Rheology 80th Annual Meeting. AIP, 2008. http://dx.doi.org/10.1063/1.2964910.

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Yaohang Li, M. Mascagni, and M. H. Peters. "Grid-based nonequilibrium multiple-time scale molecular dynamics/Brownian dynamics simulations of ligand-receptor interactions in structured protein systems." In CCGrid 2003. 3rd IEEE/ACM International Symposium on Cluster Computing and the Grid, 2003. Proceedings. IEEE, 2003. http://dx.doi.org/10.1109/ccgrid.2003.1199415.

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