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Advanced Membrane Based Water Treatment Technologies Sohail Murad, Chemical Engineering Department

Semi-permeable Membranes. S O L U T I O N. S O L V E N T. S O L U T I O N. Recycling Regions. Advanced Membrane Based Water Treatment Technologies Sohail Murad, Chemical Engineering Department Prime Grant Support: US Department of Energy.

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Advanced Membrane Based Water Treatment Technologies Sohail Murad, Chemical Engineering Department

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  1. Semi-permeable Membranes S O L U T I O N S O L V E N T S O L U T I O N Recycling Regions Advanced Membrane Based Water Treatment Technologies Sohail Murad, Chemical Engineering Department Prime Grant Support: US Department of Energy Problem Statement and Motivation • Understand The Molecular Basis For Membrane Based Separations • Explain At The Fundamental Molecular Level Why Membranes Allow Certain Solvents To Permeate, While Others Are Stopped • Use This Information To Develop Strategies For Better Design Of Membrane Based Separation Processes For New Applications. Solvated Ion Clusters Prevent Ions from Permeating the Membrane Technical Approach Key Achievements and Future Goals • Explained The Molecular Basis Of Reverse Osmosis in a Desalination Process (Formation of Solvated Ionic Clusters). • Used This Improved Understanding To Predict The Zeolite Membranes Would Be Effective In Removing A Wide Range Of Impurities From Water. • This Prediction Was Recently Confirmed By Experimental Studies Carried Out In New Mexico. • Showed That Ion Exchange Is Energetically Driven Rather Than Entropic. Explains The More Efficient Exchange Between Ca And Na In Zeolites. • Determine The Key Parameters/Properties Of The Membrane That Influence The Separation Efficiency • Use Molecular Simulations To Model The Transport Of Solvents And Solutes Across The Membrane? • Focus All Design Efforts On These Key Specifications To Improve The Design Of Membranes. • Use Molecular Simulations As A Quick Screening Tool For Determining The Suitability Of A Membrane For A Proposed New Separation Problem

  2. Simulation and design of microfluidic lab-on-chip systemsInvestigator: Ludwig C. Nitsche, Chemical Engineering Department Prime Grant Support: USIA Fulbright Commission Problem Statement and Motivation Hydrodynamic interaction kernel • Develop fast, predictive computer modeling capability for droplet formation, motion, mixing and reaction in micro-channels and lab-on-chip systems. • Merge continuum hydrodynamic models with molecular dynamics for nano-fluidic applications. • Design and optimize m-unit-operations for sensors and chemical analysis. Wavelet compression of hydrodynamic information for fast summations Surface wetting Technical Approach Key Achievements and Future Goals • “Smart swarms” of particles automatically solve for low-Reynolds-number fluid dynamics and catastrophic evolutions of phase and surface geometry (surface wetting, coalescence, rupture, reaction). • Hydrodynamic interaction kernels and interfacial forces can be extended to include molecular effects. • Wavelet compression of summations vastly increases computational speed. • Developed novel cohesive chemical potential that models interfaces more simply than previous volumetric formulations and also includes diffusion. • Treated surface wetting and contact angles through suitable adhesive force laws. • Development of simulations of lab-on-chip assay and sensor reactions is underway.

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