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There are a set of primordial features and functions expected of any modern information system: a substrate stably carrying data; the ability to repeatedly write, read, erase, reload, and compute on specific data from that substrate; and the overall ability to execute such functions in a seamless and programmable manner. For nascent molecular information technologies, proof of principle realization of this set of primordial capabilities would advance the vision for their continued development. Here, we present a DNA-based store and compute engine that captures these primordial capabilities. This system comprises multiple image files encoded into DNA and adsorbed onto ~50 um diameter, highly porous, hierarchically branched, colloidal substrate particles comprised of naturally abundant cellulose acetate. Their surface areas are over 200 cm2/mg with binding capacities of over 1012 DNA oligos/mg, 10 terabytes/mg, or 104 terabytes/cm3. This “dendricolloid” stably holds DNA files better than bare DNA with an extrapolated ability to be repeatedly lyophilized and rehydrated over 170 times compared to 60 times, respectively. Accelerated aging studies project half-lives of ~6000 and 2 million years at 4 ˚C and -18 ˚C, respectively. The data can also be erased and replaced, and non-destructive file access is achieved through transcribing from distinct synthetic promoters. The resultant RNA molecules can be directly read via nanopore sequencing and can also be enzymatically computed to solve simplified 3x3 chess and sudoku problems. Our study establishes a feasible route for utilizing the high information density and parallel computational advantages of nucleic acids. 

Size-based microfluidic filtration systems can be affected by clogging, which prevents their use in high-throughput and continuous applications. To address these concerns, we have developed two microfluidic lobe filters bioinspired by the filtration mechanism of two species of manta ray. These chips enable filtration of particles around 10–30 μm with precise control and high throughput by using two arrays of equally spaced filter lobes. For each filter design, we investigated multiple inlet flow rates and particle sizes to identify successful operational parameters. Filtration efficiency increases with fluid flow rate, suggesting that particle inertial effects play a key role in lobe filter separation. Microparticle filtration efficiencies up to 99% were obtainable with inlet flow rates of 20 mL min −1 . Each filter design successfully increased microparticle concentrations by a factor of two or greater at different inlet flow rates ranging from 6–16 mL min −1 . At higher inlet flow rates, ANSYS Fluent simulations of each device revealed a complex velocity profile that contains three local maxima and two inflection points. Ultimately, we show that distances from the lobe array to the closest local maxima and inflection point of the velocity profile can be used to successfully estimate lobe filtration efficiency at each operational flow rate.