Development of an ultrasonic technique for the non-invasive characterization of membrane morphology

Current techniques available for the characterization of membranes are destructive and/or off-line and include methods such as scanning electron microscopy (SEM), gas permeation measurements, mercury intrusion porosimetry and size exclusion of particles. An alternative technique that would allow easy non-invasive, real-time analysis of membrane morphology would be of significant value to the membrane industry. Ultrasonic time-domain reflectometry (UTDR) has been successfully employed by researchers at the MAST Center at CU to study a number of membrane-related phenomena including membrane formation, compaction and fouling. The present research focuses on adapting the UTDR technique for the study and characterization of membrane structure. The main aspects of the research involve the identification of a suitable ultrasonic system and the development of techniques for obtaining and analyzing acoustic signatures of internal membrane morphology. A high frequency pulse-echo immersion ultrasonic characterization system has been designed and fabricated. A three-axis motorized scanning system is used to raster the membrane based on a specified grid. Labview® programs have been developed to control and automate the scanning and data acquisition.; The velocity and amplitude of reflected ultrasonic waves are greatly altered by the presence of defects in the membrane structure. The UTDR technique has been evaluated for the ability to identify defects with a wide range of size-scales including pinholes (through-the-wall) and macrovoids (sub-surface) in polymeric membranes. Detection testing of defects commonly observed in commercial supported ultrafiltration membranes has shown excellent results.; The velocity and attenuation of the ultrasonic waves are dependent on the medium of propagation. Pores present in the membrane act as scatterers and result in attenuation. Also, the velocity of the ultrasonic waves depend upon the overall porosity. The UTDR technique employing a 90MHz ultrasonic transducer has been used successfully to obtain unique acoustic signatures from microporous polymeric membranes of three different sub-micron pore sizes. A phenomenological artificial neural network (ANN) model has been employed to correlate the acoustic signatures with the corresponding membranes.; A predictive model to relate the ultrasonic parameters, velocity and attenuation, to pore-size has been developed for stainless steel microfilters. A through-transmission ultrasonic characterization methodology has been employed to obtain the attenuation and velocity of ultrasonic waves through the stainless steel microfilters. Biot's theory for the propagation of elastic waves through fluid-saturated porous media has been used to relate the ultrasonic velocity through the microfilters to the overall porosity. Next, a multilayer neural network employing a backpropagation training algorithm has been used to combine the porosity values with measured attenuation values to predict membrane pore-size. Excellent correlation between network outputs and target values is observed.; SEM studies and gas-liquid porometry measurements have been made to independently determine mean pore-sizes and pore-size distributions for the polymeric membranes and metallic microfilters studied. Results of ultrasonic studies and inde pendent characterization are found to be in excellent agreement. It is concluded that the ultrasonic characterization technique can be successfully used to quantify membrane morphology and has significant potential as a non-invasive real-time membrane-structure monitoring tool.