NSF Award
1631815
This Small Business Innovation Research (SBIR) Phase II project will enable a commercial implementation of holographic video microscopy, a fast, precise and flexible technology for measuring the properties of individual colloidal particles suspended in fluid media. This disruptive technology solves critical manufacturing problems across industries that work with colloidal dispersions. Demonstrated applications include: 1) monitoring the growth of nanoparticle agglomerates in precision slurries used to polish semiconductor wafers where scratches due to slurry agglomerates are responsible for waste valued at $1 billion annually; 2) tracking concentrations of dangerous contaminants in wastewater streams; and 3) measuring the concentration of protein aggregates in biopharmaceuticals, a safety concern noted by the Food and Drug Administration (FDA) in this $250 billion industry. Holographic video microscopy is unique among particle-characterization technologies in providing comprehensive information about the size, shape and composition of individual particles in real time and in situ. Having access to this wealth of data facilitates product development, creates new opportunities for process control and provides a new tool for quality assurance across a broad spectrum of industries enabling safer, less expensive products for consumers while providing cost savings to manufacturers.<br/><br/>The technical objectives of this project are: 1) to optimize the design of the underlying holographic microscopy system without compromising the quality of results; 2) to enable quantitative concentration determination including corrections for perturbations introduced by flow dynamics; 3) to expand the domain of operation to characterize non-spherical particles and 4) to apply machine-learning algorithms for automated robust operation. Using holographic video microscopy for commercial applications requires adaptation and innovation in the design of the prototype instrument that was used to demonstrate feasibility. Streamlining the optical train will require advanced modeling and the creation of new methods of correcting optical aberrations to enable ease of manufacture. Additional improvements in design will include advances in improving microfluidic flow control to generate accurate concentration determination, to adapt holographic analysis algorithms for characterizing the structure of aspheric particles, and to extend analytical capabilities for turbid fluids. Finally, innovative machine-learning using neural network algorithms demonstrated significant improvements for analytical robustness in Phase I and will be extended to a wider range of applications. The Phase II effort will enable holographic video microscopy of real-world samples with typical measurement times of a few minutes.
