Renewable Solid Electrodes in Microfluidics: Recovering the Electrochemical Activity without Treating the Surface

Recent advances and challenges in temperature monitoring and control in microfluidic devices

Temperature is a critical-yet sometimes overlooked-parameter in microfluidics. Microfluidic devices can experience heating inside their channels during operation due to underlying physicochemical phenomena occurring therein. Such heating, whether required or not, must be monitored to ensure adequate device operation. Therefore, different techniques have been developed to measure and control temperature in microfluidic devices. In this contribution, the operating principles and applications of these techniques are reviewed. Temperature-monitoring instruments revised herein include thermocouples, thermistors, and custom-built temperature sensors. Of these, thermocouples exhibit the widest operating range; thermistors feature the highest accuracy; and custom-built temperature sensors demonstrate the best transduction. On the other hand, temperature control methods can be classified as external- or integrated-methods. Within the external methods, microheaters are shown to be the most adequate when working with biological samples, whereas Peltier elements are most useful in applications that require the development of temperature gradients. In contrast, integrated methods are based on chemical and physical properties, structural arrangements, which are characterized by their low fabrication cost and a wide range of applications. The potential integration of these platforms with the Internet of Things technology is discussed as a potential new trend in the field.

Bifunctional Metal Meshes Acting as a Semipermeable Membrane and Electrode for Sensitive Electrochemical Determination of Volatile Compounds

The monitoring of toxic inorganic gases and volatile organic compounds has brought the development of field-deployable, sensitive, and scalable sensors into focus. Here, we attempted to meet these requirements by using concurrently microhole-structured meshes as (i) a membrane for the gas diffusion extraction of an analyte from a donor sample and (ii) an electrode for the sensitive electrochemical determination of this target with the receptor electrolyte at rest. We used two types of meshes with complementary benefits, i.e., Ni mesh fabricated by robust, scalable, and well-established methods for manufacturing specific designs and stainless steel wire mesh (SSWM), which is commercially available at a low cost. The diffusion of gas (from a donor) was conducted in headspace mode, thus minimizing issues related to mesh fouling. When compared with the conventional polytetrafluoroethylene (PTFE) membrane, both the meshes (40 μm hole diameter) led to a higher amount of vapor collected into the electrolyte for subsequent detection. This inedited fashion produced a kind of reverse diffusion of the analyte dissolved into the electrolyte (receptor), i.e., from the electrode to bulk, which further enabled highly sensitive analyses. Using Ni mesh coated with Ni(OH)₂ nanoparticles, the limit of detection reached for ethanol was 24-fold lower than the data attained by a platform with a PTFE membrane and placement of the electrode into electrolyte bulk. This system was applied in the determination of ethanol in complex samples related to the production of ethanol biofuel. It is noteworthy that a simple equation fitted by machine learning was able to provide accurate assays (accuracies from 97 to 102%) by overcoming matrix effect-related interferences on detection performance. Furthermore, preliminary measurements demonstrated the successful coating of the meshes with gold films as an alternative raw electrode material and the monitoring of HCl utilizing Au-coated SSWMs. These strategies extend the applicability of the platform that may help to develop valuable volatile sensing solutions.

Converging Multidimensional Sensor and Machine Learning Toward High-Throughput and Biorecognition Element-Free Multidetermination of Extracellular Vesicle Biomarkers

Extracellular vesicles (EVs) are a frontier class of circulating biomarkers for the diagnosis and prognosis of different diseases. These lipid structures afford various biomarkers such as the concentrations of the EVs (C_V) themselves and carried proteins (C_P). However, simple, high-throughput, and accurate determination of these targets remains a key challenge. Herein, we address the simultaneous monitoring of C_V and C_P from a single impedance spectrum without using recognizing elements by combining a multidimensional sensor and machine learning models. This multidetermination is essential for diagnostic accuracy because of the heterogeneous composition of EVs and their molecular cargoes both within the tumor itself and among patients. Pencil HB cores acting as electric double-layer capacitors were integrated into a scalable microfluidic device, whereas supervised models provided accurate predictions, even from a small number of training samples. User-friendly measurements were performed with sample-to-answer data processing on a smartphone. This new platform further showed the highest throughput when compared with the techniques described in the literature to quantify EVs biomarkers. Our results shed light on a method with the ability to determine multiple EVs biomarkers in a simple and fast way, providing a promising platform to translate biofluid-based diagnostics into clinical workflows.

Pencil graphite core for pattern recognition applications

A new concept of pattern sensors based on ready-to-use sensing probes has been designed towards low-cost and rapid sample recognition applications.

Gravity-assisted distillation on a chip: Fabrication, characterization, and applications

Distillation is widely used in industrial processes and laboratories for sample pre-treatment. The conventional apparatus of flash distillation is composed of heating source, distilling flask, condenser, and receiving flask. As disadvantages, this method shows manual and laborious analyses with high consumption of chemicals. In this paper, all these limitations were addressed by developing a fully integrated microscale distiller in agreement with the apparatus of conventional flash distillation. The main challenge facing the distillation miniaturization is the phase separation since surface forces take over from the gravity in microscale channels. Otherwise, our chip had ability to perform gravity-assisted distillations because of the somewhat large dimensions of the distillation chamber (roughly 900 μL) that was obtained by 3D-printing. The functional distillation units were integrated into a single device composed of polydimethylsiloxane (PDMS). Its fabrication was cost-effective and simple by avoiding the use of cleanroom and bonding step. In addition to user-friendly analysis and low consumption of chemicals, the method requires cost-effective instrumentation, namely, voltage supply and analytical balance. Furthermore, the so called distillation-on-a-chip (DOC) eliminates the use of membranes and electrodes (usually employed in microfluidic desalinations reported in the literature), thus avoiding drawbacks such as liquid leakage, membrane fouling, and electrode passivation. The DOC promoted desalinations at harsh salinity (NaCl 600.0 mmol L^-1) with high throughput and salt removal efficiency (roughly 99%). Besides, the method was used for determination of ethanol in alcoholic beverages to show the potential of the approach toward quantitative purposes.

Monitoring the Surface Chemistry of Functionalized Nanomaterials with a Microfluidic Electronic Tongue

Advances in nanomaterials have led to tremendous progress in different areas with the development of high performance and multifunctional platforms. However, a relevant gap remains in providing the mass-production of these nanomaterials with reproducible surfaces. Accordingly, the monitoring of such materials across their entire life cycle becomes mandatory to both industry and academy. In this paper, we use a microfluidic electronic tongue (e-tongue) as a user-friendly and cost-effective method to classify nanomaterials according to their surface chemistry. The chip relies on a new single response e-tongue with association of capacitors in parallel, which consisted of stainless steel microwires coated with SiO₂, NiO₂, Al₂O₃, and Fe₂O₃ thin films. Utilizing impedance spectroscopy and a multidimensional projection technique, the chip was sufficiently sensitive to distinguish silica nanoparticles and multiwalled carbon nanotubes dispersed in water in spite of the very small surface modifications induced by distinct functionalization and oxidation extents, respectively. Flow analyses were made acquiring the analytical readouts in a label-free mode. The device also allowed for multiplex monitoring in an unprecedented way to speed up the tests. Our goal is not to replace the traditional techniques of surface analysis, but rather propose the use of libraries from e-tongue data as benchmark for routine screening of modified nanomaterials in industry and academy.

Functionalization-Free Microfluidic Electronic Tongue Based on a Single Response

Electronic tongues (e-tongues) are promising analytical devices for a variety of applications to address the challenges of quality control in water monitoring and industries of foods, beverages, and pharmaceuticals. A crucial drawback in the current e-tongues is the need to recalibrate the device when one or more sensing units (usually with modified surface) are replaced. Another downside is the necessity to perform subsequent surface modifications and analyses to each of the diverse sensing units, undermining the simplicity and velocity of the method. These features have prevented widespread commercial use of the e-tongues. In this paper, we introduce a microfluidic e-tongue that overcomes all such limitations. The key principle of global selectivity of the e-tongue was achieved by recording only a single response, namely, the equivalent admittance spectrum of an association of resistors in parallel. Such resistors consisted of five nonfunctionalized stainless steel microwires (sensing units), which were short-circuited and coated with gold, platinum, nickel, iron, and aluminum oxide films. The microwires were inserted in a chip composed of a single piece of polydimethylsiloxane (PDMS). Using impedance spectroscopy, the e-tongue was successfully applied in classification of basic tastes at a concentration below the threshold for the human tongue. In addition, our chip allowed the distinction of various chemicals used in oil industry. Finally, our cleanroom-free prototyping allows the mass production of chips with easily replaceable and reproducible sensing units. Hence, one can now envisage the widespread dissemination of e-tongues with fast and reproducible data.