NSF Award
1519057
This Small Business Innovation Research Phase I project will support the development of a novel approach, based on holographic video microscopy, to analyze the physical properties of colloidal dispersions. This technology will have immediate applications in industries as diverse as pharmaceuticals, cosmetics, personal care products, petrochemicals and food, all of which rely on the properties of colloidal dispersions and the microscopic particles from which they are composed. The worldwide market for particle characterization exceeded $5 billion per year in 2012. The present effort's holographic characterization technology extends the state-of-the-art in particle characterization by providing simultaneous information about both the size and the composition of individual particles in dispersion, and by building up a clear picture of the distribution of properties within a sample without relying on models or assumptions. Access to these new dimensions of information will be useful for product development, process control and quality assurance in all of the industrial sectors that rely on the properties of colloidal materials, thereby increasing opportunities for innovation, enhancing product performance, and decreasing manufacturing costs. In addition to capturing a share of the established market for particle characterization, this new product may also broaden the market by creating new application areas.<br/><br/>The intellectual merit of this project resides in transforming holographic video microscopy from an academic research tool to a powerful commercial instrument. Several innovations are required to make this revolutionary technology commercially viable. In its present incarnation, holographic characterization has been demonstrated with nearly ideal spheres, for which it yields the size to within a nanometer, the complex refractive index to within a part per thousand, and the time-resolved trajectory to within a nanometer in three dimensions. No other particle characterization technique offers such a wealth of particle-resolved information. This Phase I effort will demonstrate the feasibility of holographic particle characterization for a range of non-ideal industrial materials by applying state-of-the-art methods of machine learning to extend the technique's domain of applicability while simultaneously reducing the time per analysis from seconds to tens of milliseconds. This 100-fold acceleration, and the associated reduction in computational cost, will enable the technology to be deployed in large-volume and high-throughput applications. The resulting real-time insights into colloidal dispersions' compositions will improve manufacturing efficiency by identifying and helping to correct process deviations and failures. In so doing it will reduce product costs in all of the industrial sectors that develop and sell colloidal materials.
