Gate Electrodes Enable Tunable Nanofluidic Particle Traps.

The ability to control the location of nanoscale objects in liquids is essential for fundamental and applied research from nanofluidics to molecular biology. To overcome their random Brownian motion, the electrostatic fluid trap creates local minima in potential energy by shaping electrostatic interactions with a tailored wall topography. However, this strategy is inherently static; once fabricated, the potential wells cannot be modulated. Here, we propose and experimentally demonstrate that such a trap can be controlled through a buried gate electrode. We measure changes in the average escape times of nanoparticles from the traps to quantify the induced modulations of 0.7 kBT in potential energy and 50 mV in surface potential. Finally, we summarize the mechanism in a parameter-free predictive model, including surface chemistry and electrostatic fringing, that reproduces the experimental results. Our findings open a route toward real-time controllable nanoparticle traps.

Dynamic control of high-voltage actuator arrays by light-pattern projection on photoconductive switches.

The ability to control high-voltage actuator arrays relies, to date, on expensive microelectronic processes or on individual wiring of each actuator to a single off-chip high-voltage switch. Here we present an alternative approach that uses on-chip photoconductive switches together with a light projection system to individually address high-voltage actuators. Each actuator is connected to one or more switches that are nominally OFF unless turned ON using direct light illumination. We selected hydrogenated amorphous silicon (a-Si:H) as our photoconductive material, and we provide a complete characterization of its light to dark conductance, breakdown field, and spectral response. The resulting switches are very robust, and we provide full details of their fabrication processes. We demonstrate that the switches can be integrated into different architectures to support both AC and DC-driven actuators and provide engineering guidelines for their functional design. To demonstrate the versatility of our approach, we demonstrate the use of the photoconductive switches in two distinctly different applications-control of µm-sized gate electrodes for patterning flow fields in a microfluidic chamber and control of cm-sized electrostatic actuators for creating mechanical deformations for haptic displays.

Selective Extraction of Biomolecules Using a Bidirectional Flow Filter.

We present a microfluidic device for selective separation and extraction of molecules based on their diffusivity. The separation relies on electroosmotically driven bidirectional flows in which high-diffusivity species experience a net-zero velocity and lower diffusivity species are advected to a collection reservoir. The device can operate continuously and is suitable for processing low sample volumes. Using several model systems, we show that the extraction efficiency of the system is maintained at more than 90% over tens of minutes with a purity of more than 99%. We demonstrate the applicability of the device to the extraction of genomic DNA from short DNA fragments.

Biocatalysed synthesis planning using data-driven learning.

Enzyme catalysts are an integral part of green chemistry strategies towards a more sustainable and resource-efficient chemical synthesis. However, the use of biocatalysed reactions in retrosynthetic planning clashes with the difficulties in predicting the enzymatic activity on unreported substrates and enzyme-specific stereo- and regioselectivity. As of now, only rule-based systems support retrosynthetic planning using biocatalysis, while initial data-driven approaches are limited to forward predictions. Here, we extend the data-driven forward reaction as well as retrosynthetic pathway prediction models based on the Molecular Transformer architecture to biocatalysis. The enzymatic knowledge is learned from an extensive data set of publicly available biochemical reactions with the aid of a new class token scheme based on the enzyme commission classification number, which captures catalysis patterns among different enzymes belonging to the same hierarchy. The forward reaction prediction model (top-1 accuracy of 49.6%), the retrosynthetic pathway (top-1 single-step round-trip accuracy of 39.6%) and the curated data set are made publicly available to facilitate the adoption of enzymatic catalysis in the design of greener chemistry processes.

Reconfigurable microfluidics.

Lab-on-a-chip devices leverage microfluidic technologies to enable chemical and biological processes at small scales. However, existing microfluidic channel networks are typically designed for the implementation of a single function or a well-defined protocol and do not allow the flexibility and real-time experimental decision-making essential to many scientific applications. In this Perspective, we highlight that reconfigurability and programmability of microfluidic platforms can support new functionalities that are beyond the reach of current lab-on-a-chip systems. We describe the ideal fully reconfigurable microfluidic device that can change its shape and function dynamically, which would allow researchers to tune a microscale experiment with the capacity to make real-time decisions. We review existing technologies that can dynamically control microscale flows, suggest additional physical mechanisms that could be leveraged towards the goal of reconfigurable microfluidics and highlight the importance of these efforts for the broad scientific community.

Microscale Hydrodynamic Cloaking and Shielding via Electro-Osmosis.

We demonstrate theoretically and experimentally that injection of momentum in a region surrounding an object in microscale flow can yield both "cloaking" conditions, where the flow field outside the cloaking region is unaffected by the object, and "shielding" conditions, where the hydrodynamic forces on the object are eliminated. Using field-effect electro-osmosis as a mechanism for injection of momentum, we present a theoretical framework and analytical solutions for a range of geometrical shapes, validate these both numerically and experimentally, and demonstrate the ability to dynamically switch between the different states.

Tunable Bidirectional Electroosmotic Flow for Diffusion-Based Separations.

We present a new concept for on-chip separation that leverages bidirectional flow, to tune the dispersion regime of molecules and particles. The system can be configured so that low diffusivity species experience a ballistic transport regime and are advected through the chamber, whereas high diffusivity species experience a diffusion dominated regime with zero average velocity and are retained in the chamber. We detail the means of achieving bidirectional electroosmotic flow using an array of alternating current (AC) field-effect electrodes, experimentally demonstrate the separation of particles and antibodies from dyes, and present a theoretical analysis of the system, providing engineering guidelines for its design and operation.

Electroosmotic Flow Dipole: Experimental Observation and Flow Field Patterning.

We experimentally demonstrate the phenomenon of electroosmotic dipole flow that occurs around a localized surface charge region under the application of an external electric field in a Hele-Shaw cell. We use localized deposition of polyelectrolytes to create well-controlled surface charge variations, and show that, for a disk-shaped spot, the internal pressure distribution that arises results in uniform flow within the spot and dipole flow around it. We further demonstrate the superposition of surface charge spots to create complex flow patterns, without the use of physical walls.

Dynamic microscale flow patterning using electrical modulation of zeta potential.

The ability to move fluids at the microscale is at the core of many scientific and technological advancements. Despite its importance, microscale flow control remains highly limited by the use of discrete channels and mechanical valves, and relies on fixed geometries. Here we present an alternative mechanism that leverages localized field-effect electroosmosis to create dynamic flow patterns, allowing fluid manipulation without the use of physical walls. We control a set of gate electrodes embedded in the floor of a fluidic chamber using an ac voltage in sync with an external electric field, creating nonuniform electroosmotic flow distributions. These give rise to a pressure field that drives the flow throughout the chamber. We demonstrate a range of unique flow patterns that can be achieved, including regions of recirculating flow surrounded by quiescent fluid and volumes of complete stagnation within a moving fluid. We also demonstrate the interaction of multiple gate electrodes with an externally generated flow field, allowing spatial modulation of streamlines in real time. Furthermore, we provide a characterization of the system in terms of time response and dielectric breakdown, as well as engineering guidelines for its robust design and operation. We believe that the ability to create tailored microscale flow using solid-state actuation will open the door to entirely new on-chip functionalities.

On Chip Protein Pre-Concentration for Enhancing the Sensitivity of Porous Silicon Biosensors.

Porous silicon (PSi) nanomaterials have been widely studied as label-free optical biosensors for protein detection. However, these biosensors' performance, specifically in terms of their sensitivity (which is typically in the micromolar range), is insufficient for many applications. Herein, we present a proof-of-concept application of the electrokinetic isotachophoresis (ITP) technique for real-time preconcentration of a target protein on a PSi biosensor. With ITP, a highly concentrated target zone is delivered to the sensing area, where the protein target is captured by immobilized aptamers. The detection of the binding events is conducted in a label-free manner by reflective interferometric Fourier transformation spectroscopy (RIFTS). Up to 1000-fold enhancement in local concentration of the protein target and the biosensor's sensitivity are achieved, with a measured limit of detection of 7.5 nM. Furthermore, the assay is successfully performed in complex media, such as bacteria lysate samples, while the selectivity of the biosensor is retained. The presented assay could be further utilized for other protein targets, and to promote the development of clinically useful PSi biosensors.

Isotachophoresis-Based Surface Immunoassay.

In the absence of amplification methods for proteins, the immune-detection of low-abundance proteins using antibodies is fundamentally limited by binding kinetic rates. Here, we present a new class of surface-based immunoassays in which protein-antibody reaction is accelerated by isotachophoresis (ITP). We demonstrate the use of ITP to preconcentrate and deliver target proteins to a surface decorated with specific antibodies, where effective utilization of the focused sample is achieved by modulating the driving electric field (stop-and-diffuse ITP mode) or applying a counter flow that opposes the ITP motion (counterflow ITP mode). Using enhanced green fluorescent protein (EGFP) as a model protein, we carry out an experimental optimization of the ITP-based immunoassay and demonstrate a 1300-fold improvement in limit of detection compared to a standard immunoassay, in a 6 min protein-antibody reaction. We discuss the design of buffer chemistries for other protein systems and, in concert with experiments, provide full analytical solutions for the two operation modes, elucidating the interplay between reaction, diffusion, and accumulation time scales and enabling the prediction and design of future immunoassays.