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

"On-plant" wearable electrochemical sensor for atmospheric lead monitoring

Considering the extremely high toxicity of lead (Pb), early detection of atmospheric Pb levels is paramount for the implementation of preventive measures, to contain sources of emission, to minimize both human and plant exposure and to prevent accumulation in the biosphere. This work demonstrates a wearable "on-plant" sensor for electrochemical Pb detection in atmospheric aerosol samples. The sensor is screen-printed onto a flexible self-adhesive vinyl-based matte substrate which enables its attachment on plant leaves. It features a bismuth/Nafion-coated carbon working electrode transducer covered with a polyvinyl alcohol (PVA) membrane which serves as a passive in-situ gas collection layer and as an electrolyte-containing matrix. The Pb collected at the interface between the sample in the gas phase and the acetate buffer solution (ABS) embedded within the PVA membrane is measured by square wave anodic stripping voltammetry (SWASV). Different steps of the fabrication process were optimized and the detection of on plant leaves was demonstrated. Simulation experiments were conducted with a Pb-containing aerosol sprayed on the leaves to evaluate the effect of various operational parameters such as long-term stability, spraying time, accumulation time, or sensor/leaf bending. The "on-plant" sensor allows remote near real-time monitoring of Pb levels as low as 50 μg L-1 in ambient air using a portable miniaturized potentiostat, and can be expanded to other target metals, forming the basis of an early warning system for atmospheric heavy metals exposure.

Classifying Storage Temperature for Mandarin (Citrus reticulata L.) Using Bioimpedance and Diameter Measurements with Machine Learning

Mandarin (Citrus reticulata L.) is consumed worldwide. Improper storage temperatures cause flavor loss and shorten shelf lives, reducing marketability. Mandarins' quality is difficult to assess visually, as they show no apparent changes during storage. Therefore, a simple, non-destructive method is needed to assess their freshness as affected by temperature. This work utilized non-invasive bioimpedance spectroscopy (BIS) on mandarins stored at different temperatures. Eight machine learning (ML) models were trained with bioimpedance data to classify storage temperature. Also, we confirmed whether integrating diameter and time-series changes into the bioimpedance could improve the ML models' accuracies by minimizing sample variations. Additionally, we evaluated the effectiveness of equivalent circuit (EC) parameters derived from bioimpedance data for ML training. Although slightly less accurate than using raw bioimpedance data, EC parameters can efficiently reduce data dimensionality. Among all models, the SVM model trained with changes in bioimpedance integrated with diameter data achieved the highest accuracy of 0.92. It was a significant improvement compared to the accuracy of 0.76 achieved when using only the raw bioimpedance data. Thus, this study suggests a novel method of integrating diameter and bioimpedance changes to assess the storage temperature of mandarins. This approach can also be applied to other fruits when utilizing BIS.

Epidermal electronic-tattoo for plant immune response monitoring

Real-time monitoring of plant immune responses is crucial for understanding plant immunity and mitigating economic losses from pathogen and pest attacks. However, current methods relying on molecular-level assessment are destructive and time-consuming. Here, we report an ultrathin, substrate-free, and highly conductive electronic tattoo (e-tattoo) designed for plants, enabling immune response monitoring through non-invasive electrical impedance spectroscopy (EIS). The e-tattoo's biocompatibility, high conductivity, and sub-100 nm thickness allow it to conform to leaf tissue morphology and provide robust impedance data. We demonstrate continuous EIS analysis of live transgenic Arabidopsis thaliana plants for over 24 h, capturing the onset of NLR-mediated acute immune responses within three hours post-induction, prior to visible symptoms. RNA-seq and tissue ion leakage tests validate that EIS data accurately represent the physiological and molecular changes associated with immune activation. This non-invasive tissue-assessment technology has the potential to enhance our comprehension of immune activation mechanisms in plants and paves the way for real-time monitoring for plant health management.

Wearable Standalone Sensing Systems for Smart Agriculture

Monitoring crops' biotic and abiotic responses through sensors is crucial for conserving resources and maintaining crop production. Existing sensors often have technical limitations, measuring only specific parameters with limited reliability and spatial or temporal resolution. Wearable sensing systems are emerging as viable alternatives for plant health monitoring. These systems employ flexible materials attached to the plant body to detect nonchemical (mechanical and optical) and chemical parameters, including transpiration, plant growth, and volatile organic compounds, alongside microclimate factors like surface temperature and humidity. In smart farming, data from real-time monitoring using these sensors, integrated with Internet of Things technologies, can enhance crop production efficiency by supporting growth environment optimization and pest and disease management. This study examines the core components of wearable standalone systems, such as sensors, circuits, and power sources, and reviews their specific sensing targets and operational principles. It further discusses wearable sensors for plant physiology and metabolite monitoring, affordability, and machine learning techniques for analyzing multimodal sensor data. By summarizing these aspects, this study aims to advance the understanding and development of wearable sensing systems for sustainable agriculture.

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.

Autonomous Aerosol and Plasma Co-Jet Printing of Metallic Devices at Ambient Temperature

Additive manufacturing of metallic materials holds the potential to revolutionize the fabrication of functional devices unattainable via traditional methods. Despite recent advancements, printing metallic materials typically requires thermal processing at elevated temperatures to form dense structures with desired properties, which presents a major challenge for direct printing and integration with temperature-sensitive materials. Herein, a unique co-jet printing (CJP) method is reported integrating an aerosol jet and a non-thermal, atmospheric pressure plasma jet to enable concurrent aerosol deposition of metal nanoparticle inks and in situ sintering at ambient temperature. A machine learning algorithm is integrated with the CJP to perform real-time defect detection and autonomous correction, enhancing the yield of printed films with high electrical conductivity from 44% to 94%. Concurrent printing and sintering eliminate the need for post-printing processing, reducing the overall manufacturing time by multiple folds depending on product size. CJP enables direct printing of functional devices on a variety of temperature-sensitive materials including biological materials. Direct printing of hydration sensors on living plant leaves is demonstrated for long-duration monitoring of hydration level in the plant. The versatile CJP method opens tremendous opportunities to harmoniously integrate abiotic and biotic materials for emerging applications in wearable/implantable devices and biohybrid systems.

Ultradense Electrochemical Chip and Machine Learning for High-Throughput, Accurate Anticancer Drug Screening

Despite the potentialities of electrochemical sensors, these devices still encounter challenges in devising high-throughput and accurate drug susceptibility testing. The lack of platforms for providing these analyses over the preclinical trials of drug candidates remains a significant barrier to developing medicines. In this way, ultradense electrochemical chips are combined with machine learning (ML) to enable high-throughput, user-friendly, and accurate determination of the viability of 2D tumor cells (breast and colorectal) aiming at drug susceptibility assays. The effect of doxorubicin (anticancer drug model) was assessed through cell detachment electrochemical assays by interrogating Ru(NH3)63+ with square wave voltammetry (SWV). This positive probe is presumed to imply sensitive monitoring of the on-sensor cellular death because of its electrostatic preconcentration in the so-called nanogap zone between the electrode surface and adherent cells. High-throughput assays were obtained by merging fast individual SWV measurements (9 s) with the ability of chips to yield analyses of Ru(NH3)63+ in series. The approach's applicability was demonstrated across two analysis formats, drop-casting and microfluidic assays. One should also mention that fitting a multivariate descriptor from selected input data via ML proved to be essential to providing accurate determinations (98 to 104%) of cell viability and half-maximal lethal concentration of the drug. The achieved results underscore the potential of the method in steering electrochemical sensors toward enabling high-throughput drug screening in practical applications.

New horizons in smart plant sensors: key technologies, applications, and prospects

As the source of data acquisition, sensors provide basic data support for crop planting decision management and play a foundational role in developing smart planting. Accurate, stable, and deployable on-site sensors make intelligent monitoring of various planting scenarios possible. Recent breakthroughs in plant advanced sensors and the rapid development of intelligent manufacturing and artificial intelligence (AI) have driven sensors towards miniaturization, intelligence, and multi-modality. This review outlines the key technologies in developing new advanced sensors, such as micro-nano technology, flexible electronics technology, and micro-electromechanical system technology. The latest technological frontiers and development trends in sensor principles, fabrication processes, and performance parameters in soil and different segmented crop scenarios are systematically expounded. Finally, future opportunities, challenges, and prospects are discussed. We anticipate that introducing advanced technologies like nanotechnology and AI will rapidly and radically revolutionize the accuracy and intelligence of agricultural sensors, leading to new levels of innovation.

Sensing Technologies for Outdoor/Indoor Farming

To face the increasing requirement for grains as the global population continues to grow, improving both crop yield and quality has become essential. Plant health directly impacts crop quality and yield, making the development of plant health-monitoring technologies essential. Variable sensing technologies for outdoor/indoor farming based on different working principles have emerged as important tools for monitoring plants and their microclimates. These technologies can detect factors such as plant water content, volatile organic compounds (VOCs), and hormones released by plants, as well as environmental conditions like humidity, temperature, wind speed, and light intensity. To achieve comprehensive plant health monitoring for multidimensional assessment, multimodal sensors have been developed. Non-invasive monitoring approaches are also gaining attention, leveraging biocompatible and flexible sensors for plant monitoring without interference with its natural growth. Furthermore, wireless data transmission is crucial for real-time monitoring and efficient farm management. Reliable power supplies for these systems are vital to ensure continuous operation. By combining wearable sensors with intelligent data analysis and remote monitoring, modern agriculture can achieve refined management, resource optimization, and sustainable production, offering innovative solutions to global food security and environmental challenges.

Fire up Biosensor Technology to Assess the Vitality of Trees after Wildfires

The development of tools to quickly identify the fate of damaged trees after a stress event such as a wildfire is of great importance. In this context, an innovative approach to assess irreversible physiological damage in trees could help to support the planning of management decisions for disturbed sites to restore biodiversity, protect the environment and understand the adaptations of ecosystem functionality. The vitality of trees can be estimated by several physiological indicators, such as cambium activity and the amount of starch and soluble sugars, while the accumulation of ethanol in the cambial cells and phloem is considered an alarm sign of cell death. However, their determination requires time-consuming laboratory protocols, making the approach impractical in the field. Biosensors hold considerable promise for substantially advancing this field. The general objective of this review is to define a system for quantifying the plant vitality in forest areas exposed to fire. This review describes recent electrochemical biosensors that can detect plant molecules, focusing on biosensors for glucose, fructose, and ethanol as indicators of tree vitality.

Advancing abiotic stress monitoring in plants with a wearable non-destructive real-time salicylic acid laser-induced-graphene sensor

Drought and salinity stresses present significant challenges that exert a severe impact on crop productivity worldwide. Understanding the dynamics of salicylic acid (SA), a vital phytohormone involved in stress response, can provide valuable insights into the mechanisms of plant adaptation to cope with these challenging conditions. This paper describes and tests a sensor system that enables real-time and non-invasive monitoring of SA content in avocado plants exposed to drought and salinity. By using a reverse iontophoretic system in conjunction with a laser-induced graphene electrode, we demonstrated a sensor with high sensitivity (82.3 nA/[μmol L-1⋅cm-2]), low limit of detection (LOD, 8.2 μmol L-1), and fast sampling response (20 s). Significant differences were observed between the dynamics of SA accumulation in response to drought versus those of salt stress. SA response under drought stress conditions proved to be faster and more intense than under salt stress conditions. These different patterns shed light on the specific adaptive strategies that avocado plants employ to cope with different types of environmental stressors. A notable advantage of the proposed technology is the minimal interference with other plant metabolites, which allows for precise SA detection independent of any interfering factors. In addition, the system features a short extraction time that enables an efficient and rapid analysis of SA content.

Wearable sensor supports in-situ and continuous monitoring of plant health in precision agriculture era

Plant health is intricately linked to crop quality, food security and agricultural productivity. Obtaining accurate plant health information is of paramount importance in the realm of precision agriculture. Wearable sensors offer an exceptional avenue for investigating plant health status and fundamental plant science, as they enable real-time and continuous in-situ monitoring of physiological biomarkers. However, a comprehensive overview that integrates and critically assesses wearable plant sensors across various facets, including their fundamental elements, classification, design, sensing mechanism, fabrication, characterization and application, remains elusive. In this study, we provide a meticulous description and systematic synthesis of recent research progress in wearable sensor properties, technology and their application in monitoring plant health information. This work endeavours to serve as a guiding resource for the utilization of wearable plant sensors, empowering the advancement of plant health within the precision agriculture paradigm.

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.

A Roadmap from Functional Materials to Plant Health Monitoring (PHM)

Soft bioelectronics have great potential for the early diagnosis of plant diseases and the mitigation of adverse outcomes such as reduced crop yields and stunted growth. Over the past decade, bioelectronic interfaces have evolved into miniaturized conformal electronic devices that integrate flexible monitoring systems with advanced electronic functionality. This development is largely attributable to advances in materials science, and micro/nanofabrication technology. The approach uses the mechanical and electronic properties of functional materials (polymer substrates and sensing elements) to create interfaces for plant monitoring. In addition to ensuring biocompatibility, several other factors need to be considered when developing these interfaces. These include the choice of materials, fabrication techniques, precision, electrical performance, and mechanical stability. In this review, some of the benefits plants can derive from several of the materials used to develop soft bioelectronic interfaces are discussed. The article describes how they can be used to create biocompatible monitoring devices that can enhance plant growth and health. Evaluation of these devices also takes into account features that ensure their long-term durability, sensitivity, and reliability. This article concludes with a discussion of the development of reliable soft bioelectronic systems for plants, which has the potential to advance the field of bioelectronics.

Wearable electrochemical sensors for plant small-molecule detection

Small molecules in plants - such as metabolites, phytohormones, reactive oxygen species (ROS), and inorganic ions - participate in the processes of plant growth and development, physiological metabolism, and stress response. Wearable electrochemical sensors, known for their fast response, high sensitivity, and minimal plant damage, serve as ideal tools for dynamically tracking these small molecules. Such sensors provide producers or agricultural researchers with noninvasive or minimally invasive means of obtaining plant signals. In this review we explore the applications of wearable electrochemical sensors in detecting plant small molecules, enabling scientific assessment of plant conditions, quantification of environmental stresses, and facilitation of plant health monitoring and disease prediction.

Recent progress and future perspectives of polydopamine nanofilms toward functional electrochemical sensors

Since its discovery in 2007, polydopamine nanofilms have been widely used in many areas for surface functionalization. The simple and low-cost preparation method of the nanofilms with tunable thickness can incorporate amine and oxygen-rich chemical groups in virtually any interface. The remarkable advantages of this route have been successfully used in the field of electrochemical sensors. The self-adhesive properties of polydopamine are used to attach nanomaterials onto the electrode's surface and add chemical groups that can be explored to immobilize recognizing species for the development of biosensors. Thus, the combination of 2D materials, nanoparticles, and other materials with polydopamine has been successfully demonstrated to improve the selectivity and sensitivity of electrochemical sensors. In this review, we highlight some interesting properties of polydopamine and some applications where polydopamine plays an important role in the field of electrochemical sensors.

Optimized paper-based electrochemical sensors treated in acidic media to detect carbendazim on the skin of apple and cabbage

Wearable sensors such as those made with paper are needed for non-destructive routine analysis of pesticides on plants, fruits, and vegetables. Herein we report on electrochemical sensors made with screen-printed carbon electrodes on kraft and parchment papers to detect the fungicide carbendazim. A systematic optimization was performed to find that electrochemical sensors on kraft paper treated in an acidic medium led to the highest performance, with a detection limit of 0.06 µM for carbendazim. The enhanced sensitivity for this sensor was attributed to the porous nature of kraft paper, which allowed for a large electrode surface area, and to the carboxylic groups formed during electrochemical activation. As a proof-of-concept, the electrochemical sensor attached to the skin of apple and cabbage was used to detect carbendazim with the same performance as the gold standard method, thus demonstrating that the sensor can be used in the farm and on supermarket shelves.

In-Time Detection of Plant Water Status Change by Self-Adhesive, Water-Proof, and Gas-Permeable Electrodes

Leaf capacitance can reflect plant water content. However, the rigid electrodes used in leaf capacitance monitoring may affect plant health status. Herein, we report a self-adhesive, water-proof, and gas-permeable electrode fabricated by in situ electrospinning of a polylactic acid nanofiber membrane (PLANFM) on a leaf, spraying a layer of the carbon nanotube membrane (CNTM) on PLANFM, and in situ electrospinning of PLANFM on CNTM. The electrodes could be self-adhered to the leaf via electrostatic adhesion due to the charges on PLANFM and the leaf, thus forming a capacitance sensor. Compared with the electrode fabricated by a transferring approach, the in situ fabricated one did not show obvious influence on plant physiological parameters. On that basis, a wireless leaf capacitance sensing system was developed, and the change of plant water status was detected in the first day of drought stress, which was much earlier than direct observation of the plant appearance. This work paved a useful way to realize noninvasive and real-time detection of stress using plant wearable electronics.

Non-invasive in-vivo glucose-based stress monitoring in plants

Plant stress responses involve a suite of genetically encoded mechanisms triggered by real-time interactions with their surrounding environment. Although sophisticated regulatory networks maintain proper homeostasis to prevent damage, the tolerance thresholds to these stresses vary significantly among organisms. Current plant phenotyping techniques and observables must be better suited to characterize the real-time metabolic response to stresses. This impedes practical agronomic intervention to avoid irreversible damage and limits our ability to breed improved plant organisms. Here, we introduce a sensitive, wearable electrochemical glucose-selective sensing platform that addresses these problems. Glucose is a primary plant metabolite, a source of energy produced during photosynthesis, and a critical molecular modulator of various cellular processes ranging from germination to senescence. The wearable-like technology integrates a reverse iontophoresis glucose extraction capability with an enzymatic glucose biosensor that offers a sensitivity of 22.7 nA/(μM·cm²), a limit of detection (LOD) of 9.4 μM, and a limit of quantification (LOQ) of 28.5 μM. The system's performance was validated by subjecting three different plant models (sweet pepper, gerbera, and romaine lettuce) to low-light and low-high temperature stresses and demonstrating critical differential physiological responses associated with their glucose metabolism. This technology enables non-invasive, non-destructive, real-time, in-situ, and in-vivo identification of early stress response in plants and provides a unique tool for timely agronomic management of crops and improving breeding strategies based on the dynamics of genome-metabolome-phenome relationships.

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.

Current understanding, challenges and perspective on portable systems applied to plant monitoring and precision agriculture

The devastating effects of global climate change on crop production and exponential population growth pose a major challenge to agricultural yields. To cope with this problem, crop performance monitoring is becoming increasingly necessary. In this scenario, the use of sensors and biosensors capable of detecting changes in plant fitness and predicting the evolution of their morphology and physiology has proven to be a useful strategy to increase crop yields. Flexible sensors and nanomaterials have inspired the emerging fields of wearable and on-plant portable devices that provide continuous and accurate long-term sensing of morphological, physiological, biochemical, and environmental parameters. This review provides an overview of novel plant sensing technologies by discussing wearable and integrated devices proposed for engineering plant and monitoring its morphological traits and physiological processes, as well as plant-environment interactions. For each application scenario, the state-of-the-art sensing solutions are grouped according to the plant organ on which they have been installed highlighting their main technological advantages and features. Finally, future opportunities, challenges and perspectives are discussed. We anticipate that the application of this technology in agriculture will provide more accurate measurements for farmers and plant scientists with the ability to track crop performance in real time. All of this information will be essential to enable rapid optimization of plants development through tailored treatments that improve overall plant health even under stressful conditions, with the ultimate goal of increasing crop productivity in a more sustainable manner.

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.

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.

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.