Chemical Engineering @ChemengFiles.Com

Recent experiments showing reaction-driven propulsion at nanoscales have appeared as a possible mechanism for the transport of particles that may help us to not only understand chemo-mechanical transduction in biological systems, but also to create novel artificial motors that mimic living organisms and which can be harnessed to perform desired tasks. Reaction-driven propulsion consists of the generation of a localized potential gradient by an on-board surface chemical reaction. In this study, we propose and investigate a model for self-propulsion of a colloidal particle --- the osmotic motor --- immersed in a dispersion of ``bath" particles. The non-equilibrium concentration of bath particles induced by a surface chemical reaction creates an osmotic pressure imbalance on the motor causing it to move. The departure of the bath particle concentration distribution from equilibrium is governed by the Damköhler number Da --- the ratio of the speed of reaction to that of diffusion --- which is employed to calculate the driving force on the motor, and from which the self-induced osmotic velocity is determined via application of Stokes drag law. To illustrate the significant physics in osmotic propulsion, a first-order surface reaction on a portion of the motor's surface is assumed, for the most part, in this work. The implications of these features for different bath particle concentrations and motor sizes are discussed. Furthermore, we investigate the role played by the distribution of reactions on the motor's surface. Different responses are expected depending on the amount of reactive surface in the limiting behaviors of the reaction speed. Lastly, we consider a motor with constant production of particles on a hemisphere as a model that resembles actin-based motility of biological cells and organelles.

This research demonstrates that such an osmotic motor is possible and addresses such questions as: How fast can the motor move? How large of a force can it generate? What is the efficiency of such an osmotic motor? All motor behaviors discussed in this work are shown, after appropriate scaling, to be in good agreement with Brownian dynamics simulations

Recent experiments showing reaction-driven propulsion at nanoscales have appeared as a possible mechanism for the transport of particles that may help us to not only understand chemo-mechanical transduction in biological systems, but also to create novel artificial motors that mimic living organisms and which can be harnessed to perform desired tasks. Reaction-driven propulsion consists of the generation of a localized potential gradient by an on-board surface chemical reaction. In this study, we propose and investigate a model for self-propulsion of a colloidal particle --- the osmotic motor --- immersed in a dispersion of ``bath" particles. The non-equilibrium concentration of bath particles induced by a surface chemical reaction creates an osmotic pressure imbalance on the motor causing it to move. The departure of the bath particle concentration distribution from equilibrium is governed by the Damköhler number Da --- the ratio of the speed of reaction to that of diffusion --- which is employed to calculate the driving force on the motor, and from which the self-induced osmotic velocity is determined via application of Stokes drag law. To illustrate the significant physics in osmotic propulsion, a first-order surface reaction on a portion of the motor's surface is assumed, for the most part, in this work. The implications of these features for different bath particle concentrations and motor sizes are discussed. Furthermore, we investigate the role played by the distribution of reactions on the motor's surface. Different responses are expected depending on the amount of reactive surface in the limiting behaviors of the reaction speed. Lastly, we consider a motor with constant production of particles on a hemisphere as a model that resembles actin-based motility of biological cells and organelles.

This research demonstrates that such an osmotic motor is possible and addresses such questions as: How fast can the motor move? How large of a force can it generate? What is the efficiency of such an osmotic motor? All motor behaviors discussed in this work are shown, after appropriate scaling, to be in good agreement with Brownian dynamics simulations

Continuing the theme of separation processes, a more classic operations is distillation. The distillation tower design requires knowledge of thermodynamic data on the lequilibrium liquid vapor mixture to be separated.

There are many thermodynamic databases, some are restricted by subscription, but others are open to the public. The best are those that cite the original references, so that it can make a critical evaluation of information.

Continuing the theme of separation processes, a more classic operations is distillation. The distillation tower design requires knowledge of thermodynamic data on the lequilibrium liquid vapor mixture to be separated.

There are many thermodynamic databases, some are restricted by subscription, but others are open to the public. The best are those that cite the original references, so that it can make a critical evaluation of information.

According to an article in Physics Today a team of researchers from Stanford University, UCLA and other 9 universities, laboratories and medical schools have collaborated in the creation of a microfluidic chip that demonstrates the possibility of a multistep organic synthesis on a single chip microfluidics.

The device produces 2-deoxy-2-[18F] fluoro-D-glucose (FDG), a radiopharmaceutical tracer used in positron emission tomography.

According to an article in Physics Today a team of researchers from Stanford University, UCLA and other 9 universities, laboratories and medical schools have collaborated in the creation of a microfluidic chip that demonstrates the possibility of a multistep organic synthesis on a single chip microfluidics.

The device produces 2-deoxy-2-[18F] fluoro-D-glucose (FDG), a radiopharmaceutical tracer used in positron emission tomography.