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Sensing of clinically relevant biomolecules such as neurotransmitters at low concentrations can enable an early detection and treatment of a range of diseases. Several nanostructures are being explored by researchers to detect biomolecules at sensitivities beyond the picomolar range. It is recognized, however, that nanostructuring of surfaces alone is not sufficient to enhance sensor sensitivities down to the femtomolar level. In this paper, we break this barrier/limit by introducing a sensing platform that uses a multi-length-scale electrode architecture consisting of 3D printed silver micropillars decorated with graphene nanoflakes and use it to demonstrate the detection of dopamine at a limit-of-detection of 500 attomoles. The graphene provides a high surface area at nanoscale, while micropillar array accelerates the interaction of diffusing analyte molecules with the electrode at low concentrations. The hierarchical electrode architecture introduced in this work opens the possibility of detecting biomolecules at ultralow concentrations. Here, the authors introduce a biosensing platform with multi-length-scale electrode architecture consisting of 3D printed silver micropillars decorated with graphene flakes. They demonstrate that this breaks a barrier to the biomolecule limit-of-detection, enabling detection down to femtomolar level.

To promote sustainability, this review explores: 1) the utilization of affordable high‐performance sensors that can enhance food safety and quality, plant growth, and disease management and 2) the Internet of Things (IoT)‐supported sensors to empower farmers, stakeholders, and agro‐food industries via rapid testing and predictive analysis based on sensing generated informatics using artificial intelligence (AI). The performance of such sensors is noticeable, but this technology is still not suitable to be used in real applications owing to the lack of focus, scalability, well‐coordinated research, and regulations. To cover this gap, this review carefully and critically analyzes state‐of‐the‐art sensing technologies developed for food quality assurance (i.e., contaminants, toxins, and packaging testing) and plant growth monitoring (i.e., phenotyping, stresses, volatile organic components, nutrient levels, hormones, and pathogens) along with the possible challenges. The following has been proposed for future research: 1) promoting the optimized combination of green sensing units supported by IoT to perform testing at the location, considering the remote and urban areas as a key focus, and 2) analyzing generated informatics via AI should also be a focus for risk assessment understanding and optimizing necessary safety majors. Finally, the perspectives of IoT‐enabled sensors, along with their real‐world limitations, are discussed. This Review demonstrates that the advanced sensors that can enhance food safety and quality, plant growth, and disease management to promote sustainability. The authors also discuss the Internet of Things‐supported sensors to empower farmers, stakeholders, and agro‐food industries via rapid testing and predictive analysis based on sensing‐generated informatics using artificial intelligence.

Biosensors hold great potential for revolutionizing personalized medicine and environmental monitoring. Their construction is the key factor which depends on either manufacturing techniques or robust sensing materials to improve efficacy of the device. Functional graphene is an attractive choice for transducing material due to its various advantages in interfacing with biorecognition elements. Graphene and its derivatives such as graphene oxide (GO) are thus being used extensively for biosensors for monitoring of diseases. In addition, graphene can be patterned to a variety of structures and is incorporated into biosensor devices such as microfluidic devices and electrochemical and plasmonic sensors. Among biosensing materials, GO is gaining much attention due to its easy synthesis process and patternable features, high functionality, and high electron transfer properties with a large surface area leading to sensitive point-of-use applications. Considering demand and recent challenges, this perspective review is an attempt to describe state-of-the-art biosensors based on functional graphene. Special emphasis is given to elucidating the mechanism of sensing while discussing different applications. Further, we describe the future prospects of functional GO-based biosensors for health care and environmental monitoring with a focus on additive manufacturing such as 3D printing.

The diagnosis of milk fever or hypocalcemia in lactating cows has a significant economic impact on the dairy industry. It is challenging to identify asymptomatic subclinical hypocalcemia (SCH) in transition dairy cows. Monitoring subclinical hypocalcemia in milk samples can expedite treatment and improve the health, productivity, and welfare of dairy cows. In this study, an attomolar-sensitive sensor is developed using extrusion-based 3D-printed sensing structures to detect the ratio of ionized calcium to phosphate levels in milk samples. The unique geometries of the lateral structure of 3D-printed sensors, along with the wrinkled surfaces, provide a limit of detection down to the attomole (138 a m ) concentration of the target analyte. The calcium-to-phosphate ratio in milk samples not only provides early disease indications but also enables on-site testing. This highly selective test is validated using real milk and blood samples, and the results are compared with those of commercial meters. This fast response (~10 s) low-cost sensor opens a promising tool for the farm-side diagnostic of dairy cows that can promote best practice management of dairy cows. A 3D-printed sensor with surface-wrinkled structures detects subclinical hypocalcemia in dairy cows by measuring the calcium-to-phosphate ratio in milk. With attomolar sensitivity and rapid results, it enables early treatment, improving cow health and productivity.

There is an increased interest toward the development of bioelectronic devices for food toxin (mycotoxins) detection. Mycotoxins are highly toxic secondary metabolites produced by fungi like Fusarium, Aspergillus, and Penicillium that are frequently found in crops or during storage of food including cereals, nuts, fruits, etc. The contamination of food by mycotoxins has become a matter of increasing concern. High levels of mycotoxins in the diet can cause adverse, acute, and chronic effects on human health and a variety of animal species. Side effects may particularly affect the liver, kidney, nervous system, endocrine system, and immune system. Among 300 mycotoxins known till date, there are a few that are considered to play an important part in food safety, and for these, a range of analytical methods have been developed. Some of the important mycotoxins include aflatoxins, ochratoxins, fumonisins, citreoviridin, patulin, citrinin, and zearalenon. The conventional methods of analysis of mycotoxins normally require sophisticated instrumentation, e.g., liquid chromatography with fluorescence or mass detectors, combined with extraction procedures for sample preparation. Hence, new analysis tools are necessary to attain more sensitive, specific, rapid, and reliable information about the desired toxin. For the last about two decades, the research and development of simpler and faster analytical procedures based on affinity biosensors has aroused much interest due to their simplicity and sensitivity. The nanomaterials have recently had a great impact on the development of biosensors. The functionalized nanomaterials are used as catalytic tools, immobilization platforms, or as optical or electroactive labels to improve the biosensing performance to obtain higher sensitivity, stability, and selectivity. Nanomaterials, such as carbon nanomaterials (carbon nanotubes and graphene), metal nanoparticles, nanowires, nanocomposites, and nanostructured metal oxide nanoparticles are playing an increasing role in the design of sensing and biosensing systems for mycotoxin determination. Furthermore, these nanobiosystems are also bringing advantages in terms of the design of novel food toxin detection strategies. We will focus on some of the recent results related to fabrication of nanomaterial-based biosensors for food toxin detection obtained in our laboratories.

On‐site rapid multi‐ion sensing accelerates early identification of environmental pollution, water quality, and disease biomarkers in both livestock and humans. This study introduces a pocket‐sized 3D‐printed sensor, manufactured using additive manufacturing, specifically designed for detecting iron (Fe2+), nitrate (NO3–), calcium (Ca2+), and phosphate (HPO42−). A unique feature of this device is its utilization of a universal ion‐to‐electron transducing layer made from highly redox‐active poly‐octylthiophene (POT), enabling an all‐solid‐state electrode tailored to each ion of interest. Manufactured with an extrusion‐based 3D printer, the device features a periodic pattern of lateral layers (width = 80 µm), including surface wrinkles. The superhydrophobic nature of the POT prevents the accumulation of nonspecific ions at the interface between the gold and POT layers, ensuring exceptional sensor selectivity. Lithography‐free, 3D‐printed sensors achieve sensitivity down to 1 ppm of target ions in under a minute due to their 3D‐wrinkled surface geometry. Integrated seamlessly with a microfluidic system for sample temperature stabilization, the printed sensor resides within a robust, pocket‐sized 3D‐printed device. This innovation integrates with milking parlors for real‐time calcium detection, addressing diagnostic challenges in on‐site livestock health monitoring, and has the capability to monitor water quality, soil nutrients, and human diseases. This work introduces a pocket‐sized, milker‐attachable 3D‐printed sensing platform designed for rapid, on‐site detection of Fe2+, NO3−, Ca2+, and HPO42−. Featuring a universal ion‐to‐electron transducing layer, the device provides exceptional selectivity and sensitivity down to 1 ppm. Its innovative 3D‐wrinkled surface, integrated with a microfluidic system, allows for real‐time monitoring of milk Ca2+ levels, facilitating on‐site livestock health management.

Sensing of viral antigens has become a critical tool in combating infectious diseases. Current sensing techniques have a tradeoff between sensitivity and time of detection; with 10–30 min of detection time at a relatively low sensitivity and 6–12 h of detection at a high (picomolar) sensitivity. In this research, uniquely nanoengineered interfaces are demonstrated on 3D electrodes that enable the detection of spike antigens of SARS‐CoV‐2 and their variants in seconds at femtomolar concentrations with excellent specificity, thus, overcoming this tradeoff. The 3D electrodes, manufactured using a high‐resolution aerosol jet 3D nanoprinter, consist of a microelectrode array of sintered gold nanoparticles coated with graphene and antibodies specific to severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) spike antigens. An impedance‐based sensing modality is employed to sense several pseudoviruses of SARS‐CoV‐2 variants of concern (VOCs). This device is sensitive to most of the pseudoviruses of SARS‐CoV‐2 VOCs. A high sensitivity of 100 fm, along with a low limit‐of‐detection of 9.2 fm within a test range of 0.1–1000 pm, and a detection time of 43 s are shown. This work illustrates that effective nano‐bioengineering of interfaces can be used to create an ultrafast and ultrasensitive healthcare diagnostic tool for combating emerging infections. A 3D microelectrode‐based sensor manufactured by a high‐resolution Aerosol Jet 3D printer serves to detect several pseudoviruses of SARS‐CoV‐2 variants of concern. The high‐performance sensor shows a femtomolar sensitivity with a low limit of detection of 9.2 fm and a detection time of 43 s. This manufacturing modality creates a fast diagnostic tool for combating emerging infections.

The authors describe a nanostructured hybrid platform for amperometic determination of the plasticizer bisphenol A (BPA). It consists of two dimensional sheets of reduced graphene oxide (rGO) that are decorated with Mn 3 O 4 nanoparticles. The enzyme tyrosinase was immobilized on the surface of the hybrid nanosheets placed on an ITO electrode. The larger surface area and enhanced charge transfer properties of the rGO/Mn 3 O 4 nanosheets provide a synergistic effect that results in excellent sensing performance including fast electron transfer kinetics, high electroactivity, good reproducibility and selectivity compared to other electrodes of that kind. Figures of merit include a sensitivity of 93.2 μA⋅nM −1 ⋅cm −2 , an analytical range that extends from 0.01 to 100 μM, and a 10 nM lower detection limit. Its long-term stability of 8 weeks suggests the use of such enzyme electrodes as potential tools in clinical diagnostics. Graphical abstract Schematic of the fabrication of graphene based hybrid electrode using reduced graphene oxide and colloidal Mn 3 O 4 nanostructures in presence of chitosan polymer. Further we demonstrate the electrochemical assay of the hybrid electrode for Bisphenol A detection.

This report describes the fabrication of a novel microfluidics nanobiochip based on a composite comprising of nickel oxide nanoparticles (nNiO) and multiwalled carbon nanotubes (MWCNTs), as well as the chip's use in a biomedical application. This nanocomposite was integrated with polydimethylsiloxane (PDMS) microchannels, which were constructed using the photolithographic technique. A structural and morphological characterization of the fabricated microfluidics chip, which was functionalized with a bienzyme containing cholesterol oxidase (ChOx) and cholesterol esterase (ChEt), was accomplished using X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy. The XPS studies revealed that 9.3% of the carboxyl (COOH) groups present in the nNiO-MWCNT composite are used to form amide bonds with the NH 2 groups of the bienzyme. The response studies on this nanobiochip reveal good reproducibility and selectivity and a high sensitivity of 2.2 mA/mM/cm 2 . This integrated microfluidics biochip provides a promising low-cost platform for the rapid detection of biomolecules using minute samples.

We have fabricated an immunosensor based on carbon nanotubes and chitosan (CNT-CH) composite for detection of low density lipoprotein (LDL) molecules via electrochemical impedance technique. The CNT-CH composite deposited on indium tin oxide (ITO)-coated glass electrode has been used to covalently interact with anti-apolipoprotein B (antibody: AAB) via a co-entrapment method. The biofunctionalization of AAB on carboxylated CNT-CH surface has been confirmed by Fourier transform infrared spectroscopic and electron microscopic studies. The covalent functionalization of antibody on transducer surface reveals higher stability and reproducibility of the fabricated immunosensor. Electrochemical properties of the AAB/CNT-CH/ITO electrode have been investigated using cyclic voltammetric and impedimetric techniques. The impedimetric response of the AAB/CNT-CH/ITO immunoelectrode shows a high sensitivity of 0.953 Ω/(mg/dL)/cm² in a detection range of 0–120 mg/dL and low detection limit of 12.5 mg/dL with a regression coefficient of 0.996. The observed low value of association constant (0.34 M–¹s–¹) indicates high affinity of AAB/CNT-CH/ITO immunoelectrode towards LDL molecules. This fabricated immunosensor allows quantitative estimation of LDL concentration with distinguishable variation in the impedance signal.