Advanced Membrane Based Water Treatment Technologies

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 SohailMurad, Chemical Engineering Department Prime Grant Support: US Department of Energy • 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 • 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 • 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.

2. Simulation and design of microfluidic lab-on-chip systems Investigator: Ludwig C. Nitsche, Chemical Engineering Department Prime Grant Support: USIA Fulbright Commission • 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. Surface wetting Wavelet compression Of hydrodynamic Information for fast summations Hydrodynamic Interaction kernel • “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.