Lab-on-a-chip (LOC) devices capable of manipulating micro/nano-sized samples have spurred advances in biotechnology and chemistry. Designing and analyzing new and more advanced LOCs require accurate modeling and simulation of sample/particle dynamics inside such devices. In this work, we present a generalized computational physics model to simulate particle/sample trajectories under the influence of dielectrophoretic or optical forces inside LOC devices. The model takes into account time varying applied forces, Brownian motion, fluid flow, collision mechanics, and hindered diffusion caused by hydrodynamic interactions. We develop a numerical solver incorporating the aforementioned physics and use it to simulate two example cases: first, an optical trapping experiment, and second, a dielectrophoretic cell sorter device. In both cases, the numerical results are found to be consistent with experimental observations, thus proving the generality of the model. The numerical solver can simulate time evolution of the positions and velocities of an arbitrarily large number of particles simultaneously. This allows us to characterize and optimize a wide range of LOCs. The developed numerical solver is made freely available through a GitHub repository so that researchers can use it to develop and simulate new designs.

Solid-phase synthesis underpins many advances in synthetic and combinatorial chemistry, biology, and material science. The immobilization of a reacting species on the solid support makes interfacing of reagents an important challenge in this approach. In traditional synthesis columns, this leads to reaction errors that limit the product yield and necessitates excess consumption of the mobile reagent phase. Although droplet microfluidics can mitigate these problems, its adoption is fundamentally limited by the inability to controllably interface microbeads and reagent droplets. Here, we introduce Dielectrophoretic Bead-Droplet Reactor as a physical method to implement solid-phase synthesis on individual functionalized microbeads by encapsulating and ejecting them from microdroplets by tuning the supply voltage. Proof-of-concept demonstration of the enzymatic coupling of fluorescently labeled nucleotides onto the bead using this reactor yielded a 3.2-fold higher fidelity over columns through precise interfacing of individual microreactors and beads. Our work combines microparticle manipulation and droplet microfluidics to address a long-standing problem in solid-phase synthesis with potentially wide-ranging implications.

Solid-phase synthesis techniques underpin the synthesis of DNA, oligopeptides, oligosaccharides, and combinatorial libraries for drug discovery. State-of-the-art solid-phase synthesizers can produce oligonucleotides up to 200-300 nucleotides while using excess reagents. Accumulated errors over multiple reaction cycles prevent the synthesis of longer oligonucleotides for the genome scale engineering of synthetic biological systems. The sources of these errors in synthesis columns remains poorly understood. Here we show that bead-bead stacking significantly contributes to reaction errors in columns by analyzing enzymatic coupling of fluorescently labelled nucleotides onto the initiated beads along with porosity, particle tracking and diffusion calculations. To circumvent stacking, we introduce dielectrophoretic bead-droplet reactor (DBDR); a novel approach to synthesize on individual microbeads within microdroplets. Dielectrophoretic force overcomes the droplet-medium interfacial tension to encapsulate and eject individual beads from microdroplets in a droplet microfluidic device. Faster reagent diffusion in droplets, and non-uniform electric field induced enhancement in reagent concentration at its surface can improve reaction fidelities in DBDR. Fluorescence comparisons suggest around 3-fold enhancement of reaction fidelity compared to columns. DBDR can potentially enable the high-purity synthesis of arbitrarily long strands of DNA to meet the emerging demands in healthcare, environment, agriculture, materials, and computing.