An intelligent digital microfluidic system with fuzzy-enhanced feedback for multi-droplet manipulation

Drug screening on digital microfluidics for cancer precision medicine

Drug screening based on in-vitro primary tumor cell culture has demonstrated potential in personalized cancer diagnosis. However, the limited number of tumor cells, especially from patients with early stage cancer, has hindered the widespread application of this technique. Hence, we developed a digital microfluidic system for drug screening using primary tumor cells and established a working protocol for precision medicine. Smart control logic was developed to increase the throughput of the system and decrease its footprint to parallelly screen three drugs on a 4 × 4 cm2 chip in a device measuring 23 × 16 × 3.5 cm3. We validated this method in an MDA-MB-231 breast cancer xenograft mouse model and liver cancer specimens from patients, demonstrating tumor suppression in mice/patients treated with drugs that were screened to be effective on individual primary tumor cells. Mice treated with drugs screened on-chip as ineffective exhibited similar results to those in the control groups. The effective drug identified through on-chip screening demonstrated consistency with the absence of mutations in their related genes determined via exome sequencing of individual tumors, further validating this protocol. Therefore, this technique and system may promote advances in precision medicine for cancer treatment and, eventually, for any disease.

Combining sensors and actuators with electrowetting-on-dielectric (EWOD): advanced digital microfluidic systems for biomedical applications

The concept of digital microfluidics (DMF) enables highly flexible and precise droplet manipulation at a picoliter scale, making DMF a promising approach to realize integrated, miniaturized "lab-on-a-chip" (LOC) systems for research and clinical purposes. Owing to its simplicity and effectiveness, electrowetting-on-dielectric (EWOD) is one of the most commonly studied and applied effects to implement DMF. However, complex biomedical assays usually require more sophisticated sample handling and detection capabilities than basic EWOD manipulation. Alternatively, combined systems integrating EWOD actuators and other fluidic handling techniques are essential for bringing DMF into practical use. In this paper, we briefly review the main approaches for the integration/combination of EWOD with other microfluidic manipulation methods or additional external fields for specified biomedical applications. The form of integration ranges from independently operating sub-systems to fully coupled hybrid actuators. The corresponding biomedical applications of these works are also summarized to illustrate the significance of these innovative combination attempts.

One-shot high-resolution melting curve analysis for KRAS point-mutation discrimination on a digital microfluidics platform

Single-nucleotide polymorphism (SNP) plays a critical role in personalized medicine, forensics, pharmacogenetics, and disease diagnostics. Among different existing SNP genotyping techniques, melting curve analysis (MCA) becomes increasingly popular due to its high accuracy and straightforward procedures in extracting the melting temperature (T_m). Yet, its study on existing digital microfluidic (DMF) platforms has intrinsic limitations due to the temperature inhomogeneity within a thickened droplet during the on-chip rapid heating process. Although the utilization of an on-chip thermostat can regulate and monitor the dynamic melting process in real time, the limited T_m accuracy resulting from the insufficient system response time to accommodate the fast-melting evolution still poses a great challenge for precise MCA with high throughput. This work proposes a one-shot MCA on a DMF platform. The tailoring of a functional substrate with hierarchical micro/nano structure enables high-resolution patterning of pL-scale droplets. Specifically, the hydrothermal and photocatalysis treatment allows the functional substrate to exhibit a superwettability contrast of >170°, facilitating passive isolation of the pL-scale DNA sample into highly-resolved pL droplets above the 200 μm superhydrophilic patterns. This high-resolution MCA technique can successfully discriminate KRAS gene targets with single-nucleotide mutations in 3 seconds. The high accuracy and consistency in the acquired T_m when compared with off-chip results demonstrate its opportunities for near-patient diagnostics, precision medicines, genetic counseling, and prevention strategies on DMF platforms.

Machine vision-based driving and feedback scheme for digital microfluidics system

A digital microfluidic system based on electrowetting-on-dielectric is a new technology for controlling microliter-sized droplets on a plane. By applying a voltage signal to an electrode, the droplets can be controlled to move, merge, and split. Due to device design, fabrication, and runtime uncertainties, feedback control schemes are necessary to ensure the reliability and accuracy of a digital microfluidic system for practical application. The premise of feedback is to obtain accurate droplet position information. Therefore, there is a strong need to develop a digital microfluidics system integrated with driving, position, and feedback functions for different areas of study. In this article, we propose a driving and feedback scheme based on machine vision for the digital microfluidics system. A series of experiments including droplet motion, merging, status detection, and self-adaption are performed to evaluate the feasibility and the reliability of the proposed scheme. The experimental results show that the proposed scheme can accurately locate multiple droplets and improve the success rate of different applications. Furthermore, the proposed scheme provides an experimental platform for scientists who focused on the digital microfluidics system.

Closed-loop feedback control of microfluidic cell manipulation via deep-learning integrated sensor networks

Microfluidic technologies have long enabled the manipulation of flow-driven cells en masse under a variety of force fields with the goal of characterizing them or discriminating the pathogenic ones. On the other hand, a microfluidic platform is typically designed to function under optimized conditions, which rarely account for specimen heterogeneity and internal/external perturbations. In this work, we demonstrate a proof-of-principle adaptive microfluidic system that consists of an integrated network of distributed electrical sensors for on-chip tracking of cells and closed-loop feedback control that modulates chip parameters based on the sensor data. In our system, cell flow speed is measured at multiple locations throughout the device, the data is interpreted in real-time via deep learning-based algorithms, and a proportional-integral feedback controller updates a programmable pressure pump to maintain a desired cell flow speed. We validate the adaptive microfluidic system with both static and dynamic targets and also observe a fast convergence of the system under continuous external perturbations. With an ability to sustain optimal processing conditions in unsupervised settings, adaptive microfluidic systems would be less prone to artifacts and could eventually serve as reliable standardized biomedical tests at the point of care.

An integrated digital microfluidic bioreactor for fully automatic screening of microalgal growth and stress-induced lipid accumulation

Algae are the promising feedstock of biofuel. The screening of competent species and proper fertilizer supply is of the most important tasks. To accelerate this rather slow and laborious step, we developed an integrated high-throughput digital microfluidic (DMF) system that uses a discrete droplet to serve as a microbioreactor, encapsulating microalgal cells. On the basis of fundamental understanding of various droplet hydrodynamics induced by the existence of different sorts of ions and biological species, incorporation of capacitance-based position estimator, electrode-saving-based compensation, and deterministic splitting approach, was performed to optimize the DMF bioreactor. Thus, it enables all processes (e.g., nutrient gradient generation, algae culturing, and analyzing of growth and lipid accumulation) occurring automatically on-chip especially in a high-fidelity way. The ability of the system to compare different microalgal strains on-chip was investigated. Also, the Chlorella sp. were stressed by various conditions and then growth and oil accumulation were analyzed and compared, which demonstrated its potential as a powerful tool to investigate microalgal lipid accumulation at significantly lower laborites and reduced time.

Elevating Chemistry Research with a Modern Electronics Toolkit

With the rapid development of high technology, chemical science is not as it used to be a century ago. Many chemists acquire and utilize skills that are well beyond the traditional definition of chemistry. The digital age has transformed chemistry laboratories. One aspect of this transformation is the progressing implementation of electronics and computer science in chemistry research. In the past decade, numerous chemistry-oriented studies have benefited from the implementation of electronic modules, including microcontroller boards (MCBs), single-board computers (SBCs), professional grade control and data acquisition systems, as well as field-programmable gate arrays (FPGAs). In particular, MCBs and SBCs provide good value for money. The application areas for electronic modules in chemistry research include construction of simple detection systems based on spectrophotometry and spectrofluorometry principles, customizing laboratory devices for automation of common laboratory practices, control of reaction systems (batch- and flow-based), extraction systems, chromatographic and electrophoretic systems, microfluidic systems (classical and nonclassical), custom-built polymerase chain reaction devices, gas-phase analyte detection systems, chemical robots and drones, construction of FPGA-based imaging systems, and the Internet-of-Chemical-Things. The technology is easy to handle, and many chemists have managed to train themselves in its implementation. The only major obstacle in its implementation is probably one's imagination.

An efficient protocol to use feedback-controlling digital microfluidic fluorimetric sensor for detection of mercury (II) in coastal seawaters

Mercury ion is a highly toxic anthropogenic pollutants and has serious well-known effects on human. There is an ever-growing demand for convenient detection of mercury driven contaminants in environment, including coastal seawater. However, most of the reported methods are instrument-based and are not easy for portable detection. Our protocol described an efficient Digital Microfluidics method for detecting mercury in coastal seawater samples. It combined the miniaturization/automation potential of digital microfluidics and the sensitivity of fluorescence probe. To overcome a potential risk of driven failure, induced by diversity ion ingredients in seawater, a feedback control loop was included into control system. The method showed satisfied stability and selectivity in Hg sensing under high salinity condition, with the sensitivity of Hg²⁺ at the parts-per-billion level and total testing time of less than 20 s. With the advantages of being fast, amenable to automation and low cost, this protocol is promising for the formation of simple and rapid sensor device, especially for a routine monitoring and emergency detection of Hg/or other metals in coastal waters.

A feedback-controlling digital microfluidic fluorimetric sensor device for simple and rapid detection of mercury (II) in costal seawater

By combination of miniaturization potential of digital microfluidics (DMF) and sensitivity of fluorescence probe, an integrated sensor device has been initially constructed for mercury detection in coastal waters. The actuation feature of the detecting target, seawater droplet, which remains unclear, was basically explored. To overcome a potential risk of driven failure, induced by diversity ion ingredients in seawater, a feedback control loop was included into control system. Analyzing method for coastal waters was well established on DMF, which showed satisfied stability and selectivity in Hg sensing under high salinity condition, with the sensitivity of Hg²⁺ at the parts per billion level and total testing time less than 20s. With the advantages of being fast, amenable to automation and low cost, this device is promising for the formation of simple and rapid sensor device, especially for a routine monitoring and emergency detection of Hg/or other metals in coastal waters.

Coexistence and Sudden Entrapment between Two Dissimilar, Miscible Oil Lenses

The property of substrates is one of the important factors determining the interaction between two lenses (droplets). There likely exist different interactions between two dissimilar oil lenses (droplets) floating on the surface of a liquid phase from the interaction between two dissimilar oil droplets on a rigid substrate, for example, coalescence or coexistence. The interaction between two dissimilar oil lenses (droplets) is dependent on the intrinsic properties of both oil lenses (droplets) and external environmental factors. In this work, we investigate the contact interaction between two dissimilar, miscible oil lenses (toluene and silicone oil) on the surface of deionized water (DI water). The morphological evolution of two dissimilar, miscible oil lenses during the interaction under different experimental conditions is recorded and analyzed. The effects of the volume ratio of two dissimilar, miscible oil lenses, temperature of DI water, and viscosity of silicone oil on characteristic parameters are systematically studied. A sudden "entrapment" of a toluene lens into a silicone oil lens occurs after a period of the "mass exchange" (coexistence) between these two oil lenses. Several characteristic parameters, including the duration of the "mass exchange" and critical sizes of the toluene lens at the onset of the entrapment and after the entrapment, are found to be dependent on experimental conditions.

Detection of contaminants in water supply: A review on state-of-the-art monitoring technologies and their applications

Water monitoring technologies are widely used for contaminants detection in wide variety of water ecology applications such as water treatment plant and water distribution system. A tremendous amount of research has been conducted over the past decades to develop robust and efficient techniques of contaminants detection with minimum operating cost and energy. Recent developments in spectroscopic techniques and biosensor approach have improved the detection sensitivities, quantitatively and qualitatively. The availability of in-situ measurements and multiple detection analyses has expanded the water monitoring applications in various advanced techniques including successful establishment in hand-held sensing devices which improves portability in real-time basis for the detection of contaminant, such as microorganisms, pesticides, heavy metal ions, inorganic and organic components. This paper intends to review the developments in water quality monitoring technologies for the detection of biological and chemical contaminants in accordance with instrumental limitations. Particularly, this review focuses on the most recently developed techniques for water contaminant detection applications. Several recommendations and prospective views on the developments in water quality assessments will also be included.

A digital microfluidic system for loop-mediated isothermal amplification and sequence specific pathogen detection

A digital microfluidic (DMF) system has been developed for loop-mediated isothermal amplification (LAMP)-based pathogen nucleic acid detection using specific low melting temperature (T_m) Molecular Beacon DNA probes. A positive-temperature-coefficient heater with a temperature sensor for real-time thermal regulation was integrated into the control unit, which generated actuation signals for droplet manipulation. To enhance the specificity of the LAMP reaction, low-T_m Molecular Beacon probes were designed within the single-stranded loop structures on the LAMP reaction products. In the experiments, only 1 μL of LAMP reaction samples containing purified Trypanosoma brucei DNA were required, which represented over a 10x reduction of reagent consumption when comparing with the conventional off-chip LAMP. On-chip LAMP for unknown sample detection could be accomplished in 40 min with a detection limit of 10 copies/reaction. Also, we accomplished an on-chip melting curve analysis of the Molecular Beacon probe from 30 to 75 °C within 5 min, which was 3x faster than using a commercial qPCR machine. Discrimination of non-specific amplification and lower risk of aerosol contamination for on-chip LAMP also highlight the potential utilization of this system in clinical applications. The entire platform is open for further integration with sample preparation and fluorescence detection towards a total-micro-analysis system.

Image-based feedback and analysis system for digital microfluidics

Digital microfluidics (DMF) is a technology that provides a means of manipulating nL-μL volumes of liquids on an array of electrodes. By applying an electric potential to an electrode, these discrete droplets can be controlled in parallel which can be transported, mixed, reacted, and analyzed. Typically, an automation system is interfaced with a DMF device that uses a standard set of basic instructions written by the user to execute droplet operations. Here, we present the first feedback method for DMF that relies on imaging techniques that will allow online detection of droplets without the need to reactivate all destination electrodes. Our system consists of integrating open-source electronics with a CMOS camera and a zoom lens for acquisition of the images that will be used to detect droplets on the device. We also created an algorithm that uses a Hough transform to detect a variety of droplet sizes and to detect singular droplet dispensing and movement failures on the device. As a first test, we applied this feedback system to test droplet movement for a variety of liquids used in cell-based assays and to optimize different feedback actuation schemes to improve droplet movement fidelity. We also applied our system to a colorimetric enzymatic assay to show that our system is capable of biological analysis. Overall, we believe that using our approach of integrating imaging and feedback for DMF can provide a platform for automating biological assays with analysis.

Sub-7-second genotyping of single-nucleotide polymorphism by high-resolution melting curve analysis on a thermal digital microfluidic device

We developed a thermal digital microfluidic (T-DMF) device enabling ultrafast DNA melting curve analysis (MCA). Within 7 seconds, the T-DMF device succeeded in differentiating a melting point difference down to 1.6 °C with a variation of 0.3 °C in a tiny droplet sample (1.2 μL), which was 300 times faster and with 20 times less sample spending than the standard MCA (35 minutes, 25 μL) run in a commercial qPCR machine. Such a performance makes it possible for a rapid discrimination of single-nucleotide mutation relevant to prompt clinical decision-making. Also, aided by electronic intelligent control, the T-DMF device facilitates sample handling and pipelining in an automatic serial manner. An optimized oval-shaped thermal electrode is introduced to achieve high thermal uniformity. A device-sealing technique averts sample contamination and permits uninterrupted chemical/biological reactions. Simple fabrication using a single chromium layer fulfills both the thermal and typical transport electrode requirements. Capable of thermally modulating DNA samples with ultrafast MCA, this T-DMF device has the potential for a wide variety of life science analyses, especially for disease diagnosis and prognosis.

A palm-size μNMR relaxometer using a digital microfluidic device and a semiconductor transceiver for chemical/biological diagnosis

Herein, we describe a micro-nuclear magnetic resonance (μNMR) relaxometer miniaturized to palm-size and electronically automated for multi-step and multi-sample chemical/biological diagnosis. The co-integration of microfluidic and microelectronic technologies enables an association between the droplet managements and μNMR assays inside a portable sub-Tesla magnet (1.2 kg, 0.46 Tesla). Targets in unprocessed biological samples, captured by specific probe-decorated magnetic nanoparticles (NPs), can be sequentially quantified by their spin-spin relaxation time (T2) via multiplexed μNMR screening. Distinct droplet samples are operated by a digital microfluidic device that electronically manages the electrowetting-on-dielectric effects over an electrode array. Each electrode (3.5 × 3.5 mm(2)) is scanned with capacitive sensing to locate the distinct droplet samples in real time. A cross-domain-optimized butterfly-coil-input semiconductor transceiver transduces between magnetic and electrical signals to/from a sub-10 μL droplet sample for high-sensitivity μNMR screening. A temperature logger senses the ambient temperature (0 to 40 °C) and a backend processor calibrates the working frequency for the transmitter to precisely excite the protons. In our experiments, the μNMR relaxometer quantifies avidin using biotinylated Iron NPs (Φ: 30 nm, [Fe]: 0.5 mM) with a sensitivity of 0.2 μM. Auto-handling and identification of two targets (avidin and water) are demonstrated and completed within 2.2 min. This μNMR relaxometer holds promise for combinatorial chemical/biological diagnostic protocols using closed-loop electronic automation.

Universal electronics for miniature and automated chemical assays

This minireview discusses universal electronic modules (generic programmable units) and their use by analytical chemists to construct inexpensive, miniature or automated devices. Recently, open-source platforms have gained considerable popularity among tech-savvy chemists because their implementation often does not require expert knowledge and investment of funds. Thus, chemistry students and researchers can easily start implementing them after a few hours of reading tutorials and trial-and-error. Single-board microcontrollers and micro-computers such as Arduino, Teensy, Raspberry Pi or BeagleBone enable collecting experimental data with high precision as well as efficient control of electric potentials and actuation of mechanical systems. They are readily programmed using high-level languages, such as C, C++, JavaScript or Python. They can also be coupled with mobile consumer electronics, including smartphones as well as teleinformatic networks. More demanding analytical tasks require fast signal processing. Field-programmable gate arrays enable efficient and inexpensive prototyping of high-performance analytical platforms, thus becoming increasingly popular among analytical chemists. This minireview discusses the advantages and drawbacks of universal electronic modules, considering their application in prototyping and manufacture of intelligent analytical instrumentation.

Adhesion promoter for a multi-dielectric-layer on a digital microfluidic chip

A silane-based adhesion promoter suitable for a multi-dielectric-layer coating on a digital microfluidic chip is reported.

NMR–DMF: a modular nuclear magnetic resonance–digital microfluidics system for biological assays

We present a modular nuclear magnetic resonance–digital microfluidics (NMR–DMF) system as a portable diagnostic platform for miniaturized biological assays.

Droplet morphometry and velocimetry (DMV): a video processing software for time-resolved, label-free tracking of droplet parameters

Emerging assays in droplet microfluidics require the measurement of parameters such as drop size, velocity, trajectory, shape deformation, fluorescence intensity, and others. While micro particle image velocimetry (μPIV) and related techniques are suitable for measuring flow using tracer particles, no tool exists for tracking droplets at the granularity of a single entity. This paper presents droplet morphometry and velocimetry (DMV), a digital video processing software for time-resolved droplet analysis. Droplets are identified through a series of image processing steps which operate on transparent, translucent, fluorescent, or opaque droplets. The steps include background image generation, background subtraction, edge detection, small object removal, morphological close and fill, and shape discrimination. A frame correlation step then links droplets spanning multiple frames via a nearest neighbor search with user-defined matching criteria. Each step can be individually tuned for maximum compatibility. For each droplet found, DMV provides a time-history of 20 different parameters, including trajectory, velocity, area, dimensions, shape deformation, orientation, nearest neighbour spacing, and pixel statistics. The data can be reported via scatter plots, histograms, and tables at the granularity of individual droplets or by statistics accrued over the population. We present several case studies from industry and academic labs, including the measurement of 1) size distributions and flow perturbations in a drop generator, 2) size distributions and mixing rates in drop splitting/merging devices, 3) efficiency of single cell encapsulation devices, 4) position tracking in electrowetting operations, 5) chemical concentrations in a serial drop dilutor, 6) drop sorting efficiency of a tensiophoresis device, 7) plug length and orientation of nonspherical plugs in a serpentine channel, and 8) high throughput tracking of >250 drops in a reinjection system. Performance metrics show that highest accuracy and precision is obtained when the video resolution is >300 pixels per drop. Analysis time increases proportionally with video resolution. The current version of the software provides throughputs of 2-30 fps, suggesting the potential for real time analysis.