Machine learning toward high-performance electrochemical sensors.

The so-coined fourth paradigm in science has reached the sensing area, with the use of machine learning (ML) toward data-driven improvements in sensitivity, reproducibility, and accuracy, along with the determination of multiple targets from a single measurement using multi-output regression models. Particularly, the use of supervised ML models trained on large data sets produced by electrical and electrochemical bio/sensors has emerged as an impacting trend in the literature by allowing accurate analyses even in the presence of usual issues such as electrode fouling, poor signal-to-noise ratio, chemical interferences, and matrix effects. In this trend article, apart from an outlook for the coming years, we present examples from the literature that demonstrate how helpful ML algorithms can be for dispensing the adoption of experimental methods to address the aforesaid interfering issues, ultimately contributing to translate testing technologies into on-site, practical, and daily applications.

Inexpensive and nonconventional fabrication of microfluidic devices in PMMA based on a soft-embossing protocol.

This study describes an inexpensive and nonconventional soft-embossing protocol to produce microfluidic devices in poly(methyl methacrylate) (PMMA). The desirable microfluidic structure was photo-patterned in a poly(vinyl acetate) (PVAc) film deposited on glass substrate to produce a low-relief master. Then, this template was used to generate a high-relief pattern in stiffened PDMS by increasing of curing agent /monomer ratio (1:5) followed by thermal aging in a laboratory oven (200°C for 24 h). The stiffened PDMS masters were used to replicate microfluidic devices in PMMA based on soft embossing at 220-230°C and thermal sealing at 140°C. Both embossing and sealing stages were performed by using binder clips. The proposed protocol has ensured the replication of microfluidic devices in PMMA with great fidelity (>94%). Examples of MCE devices, droplet generator devices and spot test array were successfully demonstrated. For testing MCE devices, a mixture containing inorganic cations was selected as model and the achieved analytical performance did not reveal significant difference from commercial PMMA devices. Water droplets were successfully generated in an oil phase at rate of ca. 60 droplets/min (fixing the continuous phase flow rate at 100 µL/h) with size of ca. 322 ± 6 µm. Glucose colorimetric assay was performed on spot test devices and good detectability level (5 µmol/L) was achieved. The obtained results for two artificial serum samples revealed good agreement with the certified concentrations. Based on the fabrication simplicity and great analytical performance, the proposed soft-embossing protocol may emerge as promising approach for manufacturing PMMA devices.

Low-Cost and Rapid-Production Microfluidic Electrochemical Double-Layer Capacitors for Fast and Sensitive Breast Cancer Diagnosis.

This technical note describes a new microfluidic sensor that combines low-cost (USD $0.97) with rapid fabrication and user-friendly, fast, sensitive, and accurate quantification of a breast cancer biomarker. The electrodes consisted of cost-effective bare stainless-steel capillaries, whose mass production is already well-established. These capillaries were used as received, without any surface modification. Microfluidic chips containing electrical double-layer capillary capacitors (µEDLC) were obtained by a cleanroom-free prototyping that allows the fabrication of dozens to hundreds of chips in 1 h. This sensor provided the successful quantification of CA 15-3, a biomarker protein for breast cancer, in serum samples from cancer patients. Antibody-anchored magnetic beads were utilized for immunocapture of the marker, and then, water was added to dilute the protein. Next, the CA 15-3 detection (<2 min) was made without using redox probes, antibody on electrode (sandwich immunoassay), or signal amplification strategies. In addition, the capacitance tests eliminated external pumping systems and precise volumetric sampling steps, as well as presented low sample volume (5 µL) and high sensitivity using bare capillaries in a new design for double-layer capacitors. The achieved limit-of-detection (92.0 µU mL-1) is lower than that of most methods reported in the literature for CA 15-3, which are based on nanostructured electrodes. The data shown in this technical note support the potential of the µEDLC toward breast cancer diagnosis even at early stages. We believe that accurate analyses using a simple sample pretreatment such as magnetic field-assisted immunocapture and cost-effective bare electrodes can be extended to quantify other cancer biomarkers and even biomolecules by changing the biorecognition element.

Simple, rapid and, cost-effective fabrication of PDMS electrophoresis microchips using poly(vinyl acetate) as photoresist master.

This study describes a simple, rapid, and cost-effective fabrication of PDMS electrophoresis microchips using poly(vinyl acetate) (PVAc) emulsion as photoresist master. High-relief microfluidic structures were defined on poly(vinyl acetate) previously deposited on printed circuit boards surfaces without cleanroom facilities and sophisticated instrumentation. After a UV exposure, channels with heights ranging from 30 to 140 µm were obtained by controlling the emulsion mass deposited on the master surface. The developing stage was performed using water rather than the organic solvents that are applied for conventional masks. The surface morphology was characterized by optical imaging, profilometry, and SEM. Based on the achieved results, the proposed method offers suitable reproducibility for the prototyping of electrophoresis microchips in PDMS. The feasibility of the resulting PDMS electrophoresis chips was successfully demonstrated with the separation of major inorganic cations within 100 s using a contactless conductivity detection system. The separation efficiencies ranged from ca. 67 900 to 125 600 plates/m. Due to the satisfactory performance and simplified instrumentation, we believe this fabrication protocol presents potential to be implemented in any chemical, biochemical, or biological laboratory.

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

The contamination, passivation, or fouling of the detection electrodes is a serious problem undermining the analytical performance of electroanalytical devices. The methods to regenerate the electrochemical activity of the solid electrodes involve mechanical, physical, or chemical surface treatments that usually add operational time, complexity, chemicals, and further instrumental requirements to the analysis. In this paper, we describe for the first time a reproducible method for renewing solid electrodes whenever their morphology or composition are nonspecifically changed without any surface treatment. These renewable electrodes are the closest analogue to the mercury drop electrodes. Our approach was applied in microfluidics, where the downsides related to nonspecific modifications of the electrode are more critical. The renewal consisted in manually sliding metal-coated microwires across a channel with the sample. For this purpose, the chip was composed of a single piece of polydimethylsiloxane (PDMS) with three parallel channels interconnected to one perpendicular and top channel. The microwires were inserted in each one of the parallel channels acting as working, counter, and pseudoreference electrodes for voltammetry. This assembly allowed the renewal of all the three electrodes by simply pulling the microwires. The absence of any interfaces in the chips and the elastomeric nature of the PDMS allowed us to pull the microwires without the occurrence of leakages for the electrode channels even at harsh flow rates of up to 40.0 mL min-1. We expect this paper can assist the researchers to develop new microfluidic platforms that eliminate any steps of electrode cleaning, representing a powerful alternative for precise and robust analyses to real samples.

Microemulsification: an approach for analytical determinations.

We address a novel method for analytical determinations that combines simplicity, rapidity, low consumption of chemicals, and portability with high analytical performance taking into account parameters such as precision, linearity, robustness, and accuracy. This approach relies on the effect of the analyte content over the Gibbs free energy of dispersions, affecting the thermodynamic stabilization of emulsions or Winsor systems to form microemulsions (MEs). Such phenomenon was expressed by the minimum volume fraction of amphiphile required to form microemulsion (Φ(ME)), which was the analytical signal of the method. Thus, the measurements can be taken by visually monitoring the transition of the dispersions from cloudy to transparent during the microemulsification, like a titration. It bypasses the employment of electric energy. The performed studies were: phase behavior, droplet dimension by dynamic light scattering, analytical curve, and robustness tests. The reliability of the method was evaluated by determining water in ethanol fuels and monoethylene glycol in complex samples of liquefied natural gas. The dispersions were composed of water-chlorobenzene (water analysis) and water-oleic acid (monoethylene glycol analysis) with ethanol as the hydrotrope phase. The mean hydrodynamic diameter values for the nanostructures in the droplet-based water-chlorobenzene MEs were in the range of 1 to 11 nm. The procedures of microemulsification were conducted by adding ethanol to water-oleic acid (W-O) mixtures with the aid of micropipette and shaking. The Φ(ME) measurements were performed in a thermostatic water bath at 23 °C by direct observation that is based on the visual analyses of the media. The experiments to determine water demonstrated that the analytical performance depends on the composition of ME. It shows flexibility in the developed method. The linear range was fairly broad with limits of linearity up to 70.00% water in ethanol. For monoethylene glycol in water, in turn, the linear range was observed throughout the volume fraction of analyte. The best limits of detection were 0.32% v/v water to ethanol and 0.30% v/v monoethylene glycol to water. Furthermore, the accuracy was highly satisfactory. The natural gas samples provided by the Petrobras exhibited color, particulate material, high ionic strength, and diverse compounds as metals, carboxylic acids, and anions. These samples had a conductivity of up to 2630 µS cm(-1); the conductivity of pure monoethylene glycol was only 0.30 µS cm(-1). Despite such downsides, the method allowed accurate measures bypassing steps such as extraction, preconcentration, and dilution of the sample. In addition, the levels of robustness were promising. This parameter was evaluated by investigating the effect of (i) deviations in volumetric preparation of the dispersions and (ii) changes in temperature over the analyte contents recorded by the method.

Ultradense Array of On-Chip Sensors for High-Throughput Electrochemical Analyses.

High-throughput sensors are valuable tools for enabling massive, fast, and accurate diagnostics. To yield this type of electrochemical device in a simple and low-cost way, high-density arrays of vertical gold thin-film microelectrode-based sensors are demonstrated, leading to the rapid and serial interrogation of dozens of samples (10 µL droplets). Based on 16 working ultramicroelectrodes (UMEs) and 3 quasi-reference electrodes (QREs), a total of 48 sensors were engineered in a 3D crossbar arrangement that devised a low number of conductive lines. By exploiting this design, a compact chip (75 × 35 mm) can enable performing 16 sequential analyses without intersensor interferences by dropping one sample per UME finger. In practice, the electrical connection to the sensors was achieved by simply switching the contact among WE adjacent fingers. Importantly, a short analysis time was ensured by interrogating the UMEs with chronoamperometry or square wave voltammetry using a low-cost and hand-held one-channel potentiostat. As a proof of concept, the detection of Staphylococcus aureus in 15 samples was performed within 14 min (20 min incubation and 225 s reading). Additionally, the implementation of peptide-tethered immunosensors in these chips allowed the screening of COVID-19 from patient serum samples with 100% accuracy. Our experiments also revealed that dispensing additional droplets on the array (in certain patterns) results in the overestimation of the faradaic current signals, a phenomenon referred to as crosstalk. To address this interference, a set of analyses was conducted to design a corrective strategy that boosted the testing capacity by allowing using all on-chip sensors to address subsequent analyses (i.e., 48 samples simultaneously dispensed on the chip). This strategy only required grounding the unused rows of QRE and can be broadly adopted to develop high-throughput UME-based sensors. In practice, we could analyze 48 droplets (with [Fe(CN)6]4-) within ∼8 min using amperometry.

Tuning the Chemical and Electrochemical Properties of Paper-Based Carbon Electrodes by Pyrolysis of Polydopamine.

Electrochemical paper-based analytical devices represent an important platform for portable, low-cost, affordable, and decentralized diagnostics. For this kind of application, chemical functionalization plays a pivotal role to ensure high clinical performance by tuning surface properties and the area of electrodes. However, controlling different surface properties of electrodes by using a single functionalization route is still challenging. In this work, we attempted to tune the wettability, chemical composition, and electroactive area of carbon-paper-based devices by thermally treating polydopamine (PDA) at different temperatures. PDA films were deposited onto pyrolyzed paper (PP) electrodes and thermally treated in the range of 300-1000 °C. After deposition of PDA, the surface is rich in nitrogen and oxygen, it is superhydrophilic, and it has a high electroactive area. As the temperature increases, the surface becomes hydrophobic, and the electroactive area decreases. The surface modifications were followed by Raman, X-ray photoelectron microscopy (XPS), laser scanning confocal microscopy (LSCM), contact angle, scanning electron microscopy (SEM-EDS), electrical measurements, transmission electron microscopy (TEM), and electrochemical experiments. In addition, the chemical composition of nitrogen species can be tuned on the surface. As a proof of concept, we employed PDA-treated surfaces to anchor [AuCl4]- ions. After electrochemical reduction, we observed that it is possible to control the size of the nanoparticles on the surface. Our route opens a new avenue to add versatility to electrochemical interfaces in the field of paper-based electrochemical biosensors.

Ultradense Electrochemical Chips with Arrays of Nanostructured Microelectrodes to Enable Sensitive Diffusion-Limited Bioassays.

Nanostructured microelectrodes (NMEs) are an attractive alternative to yield sensitive bioassays in unprocessed samples. However, although valuable for different applications, nanoporous NMEs usually cannot boost the sensitivity of diffusion-limited analyses because of the enlarged Debye length within the nanopores, which reduces their accessibility. To circumvent this limitation, nanopore-free gold NMEs were electrodeposited from 45 µm SU-8 apertures, featuring nanoridged microspikes on a recessed surface of gold thin film while carrying interconnected crown-like and spiky structures along the edge of a SU-8 passivation layer. These structures were grown onto ultradense, vertical array chips that offer a promising strategy for translating reproducible, high-resolution, and cost-effective sensors into real-world applications. The NMEs yielded reproducible analyses, while machine learning allowed us to predict the analytical responses from NME electrodeposition data. By taking advantage of the high surface area and accessible structure of the NMEs, these structures provided a sensitivity for [Fe(CN)6]3-/4- that was 5.5× higher than that of bare WEs while also delivering a moderate antibiofouling property in undiluted human plasma. As a proof of concept, these electrodes were applied toward the fast (22 min) and simple determination of Staphylococcus aureus by monitoring the oxidation of [Fe(CN)6]4-, which acted as a cellular respiration rate redox reporter. The sensors also showed a wide dynamic range, spanning 5 orders of magnitude, and a calculated limit of detection of 0.2 CFU mL-1.

Single-Response Duplexing of Electrochemical Label-Free Biosensor from the Same Tag.

Multiplexing is a valuable strategy to boost throughput and improve clinical accuracy. Exploiting the vertical, meshed design of reproducible and low-cost ultra-dense electrochemical chips, the unprecedented single-response multiplexing of typical label-free biosensors is reported. Using a cheap, handheld one-channel workstation and a single redox probe, that is, ferro/ferricyanide, the recognition events taking place on two spatially resolved locations of the same working electrode can be tracked along a single voltammetry scan by collecting the electrochemical signatures of the probe in relation to different quasi-reference electrodes, Au (0 V) and Ag/AgCl ink (+0.2 V). This spatial isolation prevents crosstalk between the redox tags and interferences over functionalization and binding steps, representing an advantage over the existing non-spatially resolved single-response multiplex strategies. As proof of concept, peptide-tethered immunosensors are demonstrated to provide the duplex detection of COVID-19 antibodies, thereby doubling the throughput while achieving 100% accuracy in serum samples. The approach is envisioned to enable broad applications in high-throughput and multi-analyte platforms, as it can be tailored to other biosensing devices and formats.

Determination of glyphosate and AMPA on polyester-toner electrophoresis microchip with contactless conductivity detection.

This paper reports a method for rapid, simple, direct, and reproducible determination of glyphosate and its major metabolite aminomethylphosphonic acid (AMPA). The platform described herein uses polyester-toner microchips incorporating capacitively coupled contactless conductivity detection and electrophoresis separation of the analytes. The polyester-toner microchip presented 150 µm-wide and 12 µm-deep microchannels, with injection and separation lengths of 10 and 40 mm long, respectively. The best results were obtained with 320 kHz frequency, 4.5 Vpp excitation voltage, 80 mmol/L CHES/Tris buffer at pH 8.8, injection in -1.0 kV for 7 s, and separation in -1.5 kV. RSD values related to the peak areas for glyphosate and AMPA were 1.5 and 3.3% and 10.1 and 8.6% for intra- and interchip assays, respectively. The detection limits were 45.1 and 70.5 µmol/L, respectively, without any attempt of preconcentration of the analytes. Finally, the method was applied to river water samples in which glyphosate and AMPA (1.0 mmol/L each) were added. The recovery results were 87.4 and 83.7% for glyphosate and AMPA, respectively. The recovery percentages and LOD values obtained here were similar to others reported in the literature.

Single-Response Electronic Tongue and Machine Learning Enable the Multidetermination of Extracellular Vesicle Biomarkers for Cancer Diagnostics Without Recognition Elements.

Platforms based on impedimetric electronic tongue (nonselective sensor) and machine learning are promising to bring disease screening biosensors into mainstream use toward straightforward, fast, and accurate analyses at the point-of-care, thus contributing to rationalize and decentralize laboratory tests with social and economic impacts being achieved. By combining a low-cost and scalable electronic tongue with machine learning, in this chapter, we describe the simultaneous determination of two extracellular vesicle (EV) biomarkers, i.e., the concentrations of EV and carried proteins, in mice blood with Ehrlich tumor from a single impedance spectrum without using biorecognizing elements. This tumor shows primary features of mammary tumor cells. Pencil HB core electrodes are integrated into polydimethylsiloxane (PDMS) microfluidic chip. The platform shows the highest throughput in comparison with the methods addressed in the literature to determine EV biomarkers.

Scalable and green formation of graphitic nanolayers produces highly conductive pyrolyzed paper toward sensitive electrochemical sensors.

While pyrolyzed paper (PP) is a green and abundant material that can provide functionalized electrodes with wide detection windows for a plethora of targets, it poses long-standing challenges against sensing assays such as poor electrical conductivity, with resistivities generally higher than 200.0 mΩ cm (e.g., gold and silver show resistivities 1000-fold lower, ∼0.2 mΩ cm). In this regard, the fundamental hypothesis that drives this work is whether a scalable, cost-effective, and eco-friendly strategy is capable of significantly reducing the resistivity of PP electrodes toward the development of sensitive electrochemical sensors, whether faradaic or capacitive. We address this hypothesis by simply annealing PP under an isopropanol atmosphere for 1 h, reaching resistivities as low as 7 mΩ cm. Specifically, the annealing of PP at 800 or 1000 °C under isopropanol vapor leads to the formation of a highly graphitic nanolayer (∼15 nm) on the PP surface, boosting conductivity as the delocalization of π electrons stemming from carbon sp2 is favored. The reduction of carbonyl groups and the deposition of dehydrated isopropanol during the annealing process are hypothesized herein as the dominant PP graphitization mechanisms. Electrochemical analyses demonstrated the capability of the annealed PP to increase the charge-transfer kinetics, with the optimum heterogeneous standard rate constant being roughly 3.6 × 10-3 cm s-1. This value is larger than the constants reported for other carbon electrodes and indium tin oxide. Furthermore, freestanding fingers of the annealed PP were prototyped using a knife plotter to fabricate impedimetric on-leaf electrodes. These wearable sensors ensured the real-time and in situ monitoring of the loss of water content from soy leaves, outperforming non-annealed electrodes in terms of reproducibility and sensitivity. Such an application is of pivotal importance for precision agriculture and development of agricultural inputs. This work addresses the foundations for the achievement of conductive PP in a scalable, low-cost, simple, and eco-friendly way, i.e. without producing any liquid chemical waste, providing new opportunities to translate PP-based sensitive electrochemical devices into practical use.

Real-Time and In Situ Monitoring of the Synthesis of Silica Nanoparticles.

The real-time and in situ monitoring of the synthesis of nanomaterials (NMs) remains a challenging task, which is of pivotal importance by assisting fundamental studies (e.g., synthesis kinetics and colloidal phenomena) and providing optimized quality control. In fact, the lack of reproducibility in the synthesis of NMs is a bottleneck against the translation of nanotechnologies into the market toward daily practice. Here, we address an impedimetric millifluidic sensor with data processing by machine learning (ML) as a sensing platform to monitor silica nanoparticles (SiO2NPs) over a 24 h synthesis from a single measurement. The SiO2NPs were selected as a model NM because of their extensive applications. Impressively, simple ML-fitted descriptors were capable of overcoming interferences derived from SiO2NP adsorption over the signals of polarizable Au interdigitate electrodes to assure the determination of the size and concentration of nanoparticles over synthesis while meeting the trade-off between accuracy and speed/simplicity of computation. The root-mean-square errors were calculated as ∼2.0 nm (size) and 2.6 × 1010 nanoparticles mL-1 (concentration). Further, the robustness of the ML size descriptor was successfully challenged in data obtained along independent syntheses using different devices, with the global average accuracy being 103.7 ± 1.9%. Our work advances the developments required to transform a closed flow system basically encompassing the reactional flask and an impedimetric sensor into a scalable and user-friendly platform to assess the in situ synthesis of SiO2NPs. Since the sensor presents a universal response principle, the method is expected to enable the monitoring of other NMs. Such a platform may help to pave the way for translating "sense-act" systems into practice use in nanotechnology.

Using machine learning and an electronic tongue for discriminating saliva samples from oral cavity cancer patients and healthy individuals.

The diagnosis of cancer and other diseases using data from non-specific sensors - such as the electronic tongues (e-tongues) - is challenging owing to the lack of selectivity, in addition to the variability of biological samples. In this study, we demonstrate that impedance data obtained with an e-tongue in saliva samples can be used to diagnose cancer in the mouth. Data taken with a single-response microfluidic e-tongue applied to the saliva of 27 individuals were treated with multidimensional projection techniques and non-supervised and supervised machine learning algorithms. The distinction between healthy individuals and patients with cancer on the floor of mouth or oral cavity could only be made with supervised learning. Accuracy above 80% was obtained for the binary classification (YES or NO for cancer) using a Support Vector Machine (SVM) with radial basis function kernel and Random Forest. In the classification considering the type of cancer, the accuracy dropped to ca. 70%. The accuracy tended to increase when clinical information such as alcohol consumption was used in conjunction with the e-tongue data. With the random forest algorithm, the rules to explain the diagnosis could be identified using the concept of Multidimensional Calibration Space. Since the training of the machine learning algorithms is believed to be more efficient when the data of a larger number of patients are employed, the approach presented here is promising for computer-assisted diagnosis.

Fast and efficient electrochemical thinning of ultra-large supported and free-standing MoS2 layers on gold surfaces.

Molybdenum disulfide (MoS2) is a very promising layered material for electrical, optical, and electrochemical applications because of its unique and outstanding properties. To unlock its full potential, among different preparation routes, electrochemistry has gain interest due to its simple, fast, scalable and simple instrumentation. However, obtaining large-area monolayer MoS2 that will enable the fabrication of novel electronic and electrochemical devices is still challenging. In this work, we reported a simple and fast electrochemical thinning process that results in ultra-large MoS2 down to monolayer on Au surfaces. The high affinity of MoS2 by Au surfaces enables the removal of bulk layers while preserving the first layer attached to the electrode. With a proper choice of the applied potential, more than 90% of the bulk regions can be removed from large-area MoS2 crystals, as confirmed by atomic force microscopy, photoluminescence, and Raman spectroscopy. We further address a set of contributions that are helpful to elucidate the features of MoS2, namely, the hyphenation of electrochemistry and optical microscopy for real-time observation of the thinning process that was revealed to occur from the edges to the center of the flake, an image treatment to estimate the thinning area and thinning rate, and the preparation of free-standing MoS2 layers by electrochemically thinning bulk flakes on microhole-structured Ni/Au meshes.

In Situ Nanocoating on Porous Pyrolyzed Paper Enables Antibiofouling and Sensitive Electrochemical Analyses in Biological Fluids.

Electrochemical detection in complex biofluids is a long-standing challenge as electrode biofouling hampers its sensing performance and commercial translation. To overcome this drawback, pyrolyzed paper as porous electrode coupled with the drop casting of an off-the-shelf polysorbate, that is, Tween 20 (T20), is described here by taking advantage of the in situ formation of a hydrophilic nanocoating (2 nm layer of T20). The latter prevents biofouling while providing the capillarity of samples through paper pores, leveraging redox reactions across both only partially fouled and fresh electrodic surfaces with increasing detection areas. The nanometric thickness of this blocking layer is also essential by not significantly impairing the electron-transfer kinetics. These phenomena behave synergistically to enhance the sensibility that further increases over long-term exposures (4 h) in biological fluids. While the state-of-the-art antibiofouling strategies compromise the sensibility, this approach leads to peak currents that are up to 12.5-fold higher than the original currents after 1 h exposure to unprocessed human plasma. Label-free impedimetric immunoassays through modular bioconjugation by directly anchoring spike protein on gold nanoparticles are also allowed, as demonstrated for the COVID-19 screening of patient sera. The scalability and simplicity of the platform combined with its unique ability to operate in biofluids with enhanced sensibility provide the generation of promising biosensing technologies toward real-world applications in point-of-care diagnostics, mass testing, and in-home monitoring of chronic diseases.

Biocompatible Wearable Electrodes on Leaves toward the On-Site Monitoring of Water Loss from Plants.

Impedimetric wearable sensors are a promising strategy for determining the loss of water content (LWC) from leaves because they can afford on-site and nondestructive quantification of cellular water from a single measurement. Because the water content is a key marker of leaf health, monitoring of the LWC can lend key insights into daily practice in precision agriculture, toxicity studies, and the development of agricultural inputs. Ongoing challenges with this monitoring are the on-leaf adhesion, compatibility, scalability, and reproducibility of the electrodes, especially when subjected to long-term measurements. This paper introduces a set of sensing material, technological, and data processing solutions that overwhelm such obstacles. Mass-production-suitable electrodes consisting of stand-alone Ni films obtained by well-established microfabrication methods or ecofriendly pyrolyzed paper enabled reproducible determination of the LWC from soy leaves with optimized sensibilities of 27.0 (Ni) and 17.5 kΩ %-1 (paper). The freestanding design of the Ni electrodes was further key to delivering high on-leaf adhesion and long-term compatibility. Their impedances remained unchanged under the action of wind at velocities of up to 2.00 m s-1, whereas X-ray nanoprobe fluorescence assays allowed us to confirm the Ni sensor compatibility by the monitoring of the soy leaf health in an electrode-exposed area. Both electrodes operated through direct transfer of the conductive materials on hairy soy leaves using an ordinary adhesive tape. We used a hand-held and low-power potentiostat with wireless connection to a smartphone to determine the LWC over 24 h. Impressively, a machine-learning model was able to convert the sensing responses into a simple mathematical equation that gauged the impairments on the water content at two temperatures (30 and 20 °C) with reduced root-mean-square errors (0.1% up to 0.3%). These data suggest broad applicability of the platform by enabling direct determination of the LWC from leaves even at variable temperatures. Overall, our findings may help to pave the way for translating "sense-act" technologies into practice toward the on-site and remote investigation of plant drought stress. These platforms can provide key information for aiding efficient data-driven management and guiding decision-making steps.

Modular Label-Free Electrochemical Biosensor Loading Nature-Inspired Peptide toward the Widespread Use of COVID-19 Antibody Tests.

Limitations of the recognition elements in terms of synthesis, cost, availability, and stability have impaired the translation of biosensors into practical use. Inspired by nature to mimic the molecular recognition of the anti-SARS-CoV-2 S protein antibody (AbS) by the S protein binding site, we synthesized the peptide sequence of Asn-Asn-Ala-Thr-Asn-COOH (abbreviated as PEP2003) to create COVID-19 screening label-free (LF) biosensors based on a carbon electrode, gold nanoparticles (AuNPs), and electrochemical impedance spectroscopy. The PEP2003 is easily obtained by chemical synthesis, and it can be adsorbed on electrodes while maintaining its ability for AbS recognition, further leading to a sensitivity 3.4-fold higher than the full-length S protein, which is in agreement with the increase in the target-to-receptor size ratio. Peptide-loaded LF devices based on noncovalent immobilization were developed by affording fast and simple analyses, along with a modular functionalization. From studies by molecular docking, the peptide-AbS binding was found to be driven by hydrogen bonds and hydrophobic interactions. Moreover, the peptide is not amenable to denaturation, thus addressing the trade-off between scalability, cost, and robustness. The biosensor preserves 95.1% of the initial signal for 20 days when stored dry at 4 °C. With the aid of two simple equations fitted by machine learning (ML), the method was able to make the COVID-19 screening of 39 biological samples into healthy and infected groups with 100.0% accuracy. By taking advantage of peptide-related merits combined with advances in surface chemistry and ML-aided accuracy, this platform is promising to bring COVID-19 biosensors into mainstream use toward straightforward, fast, and accurate analyses at the point of care, with social and economic impacts being achieved.

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.