D
Dennis C. Prieve
Researcher at Carnegie Mellon University
Publications - 107
Citations - 6297
Dennis C. Prieve is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Particle & van der Waals force. The author has an hindex of 45, co-authored 107 publications receiving 5914 citations. Previous affiliations of Dennis C. Prieve include University of Newcastle & University of California, Berkeley.
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Anomalous Migration of a Rigid Sphere in Torsional Flow of a Viscoelastic Fluid. II: Effect of Shear Rate
TL;DR: In this paper, a single particle is injected into a 0.1% w/w solution of polyisobutylene (Mv=1.5×106), dissolved in polybutene (Mn=800), held between a plate and a 21 cm disc.
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Force exerted by a laser beam on a microscopic sphere in water : designing for maximum axial force
TL;DR: In this article, the authors used ray optics to predict the force on a sphere (much larger than the wavelength of light) exerted by a laser beam of low divergence (in contrast with high divergence beams used to form optical traps) to determine if the magnitude of force attainable is large enough to dislodge microscopic particles adhered to surfaces.
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The effect of electrode kinetics on electrophoretic forces
TL;DR: Finite element analysis is employed to explore the effect of the current distribution beneath a particle on the net force acting on it, and previously established dimensionless kinetic parameters are used to scale between the two limiting cases.
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Small-Angle Rayleigh Scattering by Relatively Large Latex Particles
Robert Y. Ofoli,Dennis C. Prieve +1 more
TL;DR: In this paper, small-angle light scattering (SALS) was used as a tool for studying the kinetics of flocculation of model latexes, where the conformation of elemental particles in any floc is unknown.
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Total Internal Reflection Microscopy: Distortion Caused by Additive Noise
Paul C. Odiachi,Dennis C. Prieve +1 more
TL;DR: In this paper, the potential energy (PE) profiles obtained from TIRM are distorted by corrupting clean data obtained by Brownian dynamics simulations with various levels of additive background noise, having a mean background intensity of Īb and a standard deviation of σb.