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This paper presents a novel CMOS RF-to-DC converter for ultra-low-power wireless sensor nodes powered by RF wireless power transfer. The proposed converter achieves 10% higher power conversion efficiency than a conventional rectifier, with only a 1% increase in power consumption. The system employs a reconfigurable Dickson topology, operates on the unlicensed 868 MHz ISM band, and includes a built-in power-efficient MPPT system architecture. Experimental measurements show a maximum power conversion efficiency of 55% in the power range from −22 dBm to 0 dBm, with a power sensitivity of −22 dBm for a DC output voltage of 2.4 V. The proposed converter offers a promising solution for efficient wireless power transfer and energy harvesting in ultra-low-power wireless sensor nodes.

Permissible limits of Pb2+ in drinking water are being reduced from 10 μgL−1 to 5 μgL−1, which calls for rapid, and highly reliable detection techniques. Electrochemical sensors have garnered attention in detection of heavy metal ions in environmental samples due to their ease of operation, low cost, and rapid detection responses. Selectivity, sensitivity and detection capabilities of these sensors, can be enhanced by modifying their working electrodes (WEs) with iron oxide nanoparticles (IONPs) and/or their composites. Therefore, this review is an in-depth analysis of the deployment of IONPs/nanocomposites in modification of electrochemical sensors for detection of Pb2+ in drinking water over the past decade. From the analyzed studies (n = 23), the optimal solution pH, deposition potential, and deposition time ranged between 3 and 5.6, −0.7 to −1.4 V vs Ag/AgCl, and 100–400 s, respectively. Majority of the studies employed square wave anodic stripping voltammetry (n = 16), in 0.1 M acetate buffer solution (n = 19) for detection of Pb2+. Limits of detection obtained (2.5 x 10−9 - 4.5 μg/L) were below the permissible levels which indicated good sensitivities of the modified electrodes. Despite the great performance of these modified electrodes, the primary source of IONPs has always been commercial iron-based salts in addition to the use of so many materials as modifying agents of these IONPs. This may limit reproducibility and sustainability of the WEs due to lengthy and costly preparation protocols. Steel and/or iron industrial wastes can be alternatively employed in generation of IONPs for modification of electrochemical sensors. Additionally, biomass-based activated carbons enriched with surface functional groups are also used in modification of bare IONPs, and subsequently bare electrodes. However, these two areas still need to be fully explored.

Abstract A variety of biosensors have been proposed to quickly detect and measure the properties of individual microorganisms among heterogeneous populations, but challenges related to cost, portability, stability, sensitivity, and power consumption limit their applicability. This study proposes a portable microfluidic device based on impedance flow-cytometry and electrical impedance spectroscopy that can detect and quantify the size of microparticles larger than 45 µm, such as algae and microplastics. The system is low cost ($300), portable (5 cm $$\times$$ × 5 cm), low-power (1.2 W), and easily fabricated utilizing a 3D-printer and industrial printed circuit board technology. The main novelty we demonstrate is the use of square wave excitation signal for impedance measurements with quadrature phase-sensitive detectors. A linked algorithm removes the errors associated to higher order harmonics. After validating the performance of the device for complex impedance models, we used it to detect and differentiate between polyethylene microbeads of sizes between 63 and 83 µm, and buccal cells between 45 and 70 µm. A precision of 3% is reported for the measured impedance and a minimum size of 45 µm is reported for the particle characterization.

In order to deepen the understanding of the role of transition metal oxides in electron transfer at the electrochemical interface, the performance of Zn x Ni1−x Fe2O4 (x = 0, 0.2, 0.4, 0.6, 0.8, 1) nanomaterials in electrochemical sensing is studied. Nanomaterials are synthesized by simple autocombustion synthesis procedure. Field‐emission scanning electron microscopy characterization shows that the particles have a size between 30 and 70 nm with an average crystallite size between 24 and 35 nm. The bandgap energies of the nanomaterials, as estimated by UV–vis experiments, are in the 2.32–2.56 eV range. The valence band maximum is evaluated using X‐ray photoelectron spectroscopy and the position of the conduction band minimum is estimated. The ZnFe2O4 sensor has the best performances: highest rate constant (13.1 ± 2.8 ms−1), lowest peak‐to‐peak separation (386 ± 2 mV), and highest sensitivity (37.75 ± 0.17 μA mM−1). Its limit of detection (7.94 ± 0.04 μM) is second best, and its sensitivity is more than twice the sensitivity of the bare sensor (16.7 ± 0.9 μA mM−1). Nanomaterials energy bands mapping with the experimental redox potentials is performed to predict the electron transfer at the electrochemical interface, and the importance of surface states/defects is highlighted in the electron transfer mechanism.

The expanding interest in digital biomarker analysis focused on non-invasive human bodily fluids, such as sweat, highlights the pressing need for easily manufactured and highly efficient soft lab-on-skin solutions. Here, we report, for the first time, the integration of microfluidic paper-based devices (μPAD) and non-enhanced Raman-scattering-enabled optical biochemical sensing (Raman biosensing). Their integration merges the enormous benefits of μPAD, with high potential for commercialization and use in resource-limited settings, with biorecognition-element-free (but highly selective) optical Raman biosensing. The introduced thin (0.36 mm), ultra-lightweight (0.19 g), and compact footprint (3 cm2) opto-paperfluidic sweat patch is flexible, stretchable, and conforms, irritation-free, to hairless or minimally haired body regions to enable swift sweat collection. As a great advantage, this new bio-chemical sensory system excels through its absence of onboard biorecognition elements (bioreceptor-free) and omission of plasmonic nanomaterials. The proposed easy fabrication process is adaptable to mass production by following a fully sustainable and cost-effective process utilizing only basic tools by avoiding typically employed printing or laser patterning. Furthermore, efficient collection and transportation of precise sweat volumes, driven exclusively by the wicking properties of porous materials, shows high efficiency in liquid transportation and reduces biosensing latency by a factor of 5 compared to state-of-the-art epidermal microfluidics. The proposed unit enables electronic chip-free and imaging-less visual sweat loss quantification as well as optical biochemical analysis when coupled with Raman spectroscopy. We investigated the multimodal quantification of sweat urea and lactate levels ex vivo (with syntactic sweat including +30 sweat analytes on porcine skin) and achieved a linear dynamic range from 0 to 100 mmol/L during fully dynamic continuous flow characterization.

There has been a lot of interest in developing and producing biodegradable polymers to address the current environmental problem caused by the continued usage of synthetic polymers derived from petroleum products. Bioplastics have been identified as a possible alternative to the use of conventional plastics since they are biodegradable and/or derived from renewable resources. Additive manufacturing, also referred to as 3D printing, is a field of growing interest and can contribute towards a sustainable and circular economy. The manufacturing technology also provides a wide material selection with design flexibility increasing its usage in the manufacture of parts from bioplastics. With this material flexibility, efforts have been directed towards developing 3D printing filaments from bioplastics such as Poly (lactic acid) to substitute the common fossil- based conventional plastic filaments such as Acrylonitrile butadiene styrene. Plant biomass is now utilized in the development of biocomposite materials. A lot of literature presents work done toward improving the biodegradability of printing filaments. However, additive manufacture of biocomposites from plant biomass is faced with printing challenges such as warping, low agglomeration between layers and poor mechanical properties of the printed parts. The aim of this paper is to review the technology of 3D printing using bioplastics, study the materials that have been utilized in this technology and how challenges of working with biocomposites in additive manufacture have been addressed.

Abstract We present here, for the first time, a fabrication technique that allows manufacturing scallop free, non-tapered, high aspect ratio in through-silicon vias (TSVs) on silicon wafers. TSVs are among major technology players in modern high-volume manufacturing as they enable 3D chip integration. However, the usual standardized TSV fabrication process has to deal with scalloping, an imperfection in the sidewalls caused by the deep reactive ion etching. The presence of scalloping causes stress and field concentration in the dielectric barrier, thereby dramatically impacting the following TSV filling step, which is performed by means of electrochemical plating. So, we propose here a new scallop free and non-tapered approach to overcome this challenge by adding a new step to the standard TSV procedure exploiting the crystalline orientation of silicon wafers. Thank to this new step, that we called “Michelangelo”, we obtained an extremely well polishing of the TSV holes, by reaching atomic-level smoothness and a record aspect ratio of 28:1. The Michelangelo step will thus drastically reduce the footprint of 3D structures and will allow unprecedented efficiency in 3D chip integration.

Therapeutic drug monitoring (TDM) of conventional cytotoxic chemotherapies is strongly supported yet poorly implemented in daily practice in hospitals. Analytical methods for the quantification of cytotoxic drugs are instead widely presented in the scientific literature, while the use of these therapeutics is expected to keep going for longer. There are two main issues hindering the implementation of TDM: turnaround time, which is incompatible with the dosage profiles of these drugs, and exposure surrogate marker, namely total area under the curve (AUC). Therefore, this perspective article aims to define the adjustment needed from current to efficient TDM practice for cytotoxics, namely point-of-care (POC) TDM. For real-time dose adjustment, which is required for chemotherapies, such POC TDM is only achievable with analytical methods that match the sensitivity and selectivity of current methods, such as chromatography, as well as model-informed precision dosing platforms to assist the oncologist with dose fine-tuning based on quantification results and targeted intervals.

One paramount challenge in multi-ion-sensing arises from ion interference that degrades the accuracy of sensor calibration. Machine learning models are here proposed to optimize such multivariate calibration. However, the acquisition of big experimental data is time and resource consuming in practice, necessitating new paradigms and efficient models for these data-limited frameworks. Therefore, a novel approach is presented in this work, where a multi-ion-sensing emulator is designed to explain the response of an ion-sensing array in a mixed-ion environment. A case study is performed emulating the concurrent monitoring of sodium, potassium, lithium, and lead ions, in a medium representative of sweat samples. These analytes are relevant examples of sweat ion-sensing applications for physiology, therapeutic drug monitoring, and heavy metal contamination. It is demonstrated that calibration datasets output by the emulator explain accurately the experimental response of polymeric solid-contact ion-selective electrodes, where root-mean-squared error of 1.37, 1.44, 1.78, $2\,mV$ are obtained, respectively, for Na+, K+, Li+, Pb2+ sensor calibration in artificial sweat. Besides, synthetic datasets of custom size are generated to train, validate, and evaluate different types of multivariate regressors. A Multi-Output Support Vector Regressor (M-SVR) is proposed as a compact, accurate, robust, and efficient multivariate calibration model. It features 13.22% normalized root mean squares, and 20.29% mean root squares improvement compared to a simple linear regression model. It is an unbiased estimator for medium to large datasets, and its average generalization error is of 3.22%. Besides, M-SVR models have a lower computational complexity than single-output SVR or neural network models, making them a suitable solution for memory and energy-constrained edge devices used for continuous and real-time multi-ion monitoring.

In this work, novel platforms for paracetamol sensing were developed by the deposition of Bi2O3, Bi5O7NO3 and their heterostructures onto screen-printed carbon-paste electrodes. An easy and scalable solid state synthesis route was employed, and by setting the calcination temperatures at 500 °C and 525 °C we induced the formation of heterostructures of Bi2O3 and Bi5O7NO3. Cyclic voltammetry measurements highlighted that the heterostructure produced at 500 °C provided a significant enhancement in performance compared to the monophases of Bi2O and Bi5O7NO3, respectively. That heterostructure showed a mean peak-to-peak separation Ep of 411 mV and a sensitivity increment of up to 70% compared to bare electrodes. A computational study was also performed in order to evaluate the geometrical and kinetic parameters of representative clusters of bismuth oxide and subnitrate when they interact with paracetamol.

Wearable devices are nowadays at the edge-front in both academic research as well as in industry, and several wearable devices have been already introduced in the market. One of the most recent advancements in wearable technologies for biosensing is in the area of the remote monitoring of human health by detection on-the-skin. However, almost all the wearable devices present in the market nowadays are still providing information not related to human ‘metabolites and/or disease’ biomarkers, excluding the well-known case of the continuous monitoring of glucose in diabetic patients. Moreover, even in this last case, the glycaemic level is acquired under-the-skin and not on-the-skin. On the other hand, it has been proven that human sweat is very rich in molecules and other biomarkers (e.g., ions), which makes sweat a quite interesting human liquid with regards to gathering medical information at the molecular level in a totally non-invasive manner. Of course, a proper collection of sweat as it is emerging on top of the skin is required to correctly convey such liquid to the molecular biosensors on board of the wearable system. Microfluidic systems have efficiently come to the aid of wearable sensors, in this case. These devices were originally built using methods such as photolithographic and chemical etching techniques with rigid materials. Nowadays, fabrication methods of microfluidic systems are moving towards three-dimensional (3D) printing methods. These methods overcome some of the limitations of the previous method, including expensiveness and non-flexibility. The 3D printing methods have a high speed and according to the application, can control the textures and mechanical properties of an object by using multiple materials in a cheaper way. Therefore, the aim of this paper is to review all the most recent advancements in the methods for 3D printing to fabricate wearable fluidics and provide a critical frame for the future developments of a wearable device for the remote monitoring of the human metabolism directly on-the-skin.

Nanostructured materials have attracted considerable interest over the last few decades to enhance sensing capabilities thanks to their unique properties and large surface area. In particular, noble metal nanostructures offer several advantages including high stability, non-toxicity and excellent electrochemical behaviour. However, in recent years the great expansion of point-of-care (POC) and wearable systems and the attempt to perform measurements in tiny spaces have also risen the need of increasing sensors miniaturization. Fast constant potential electrodeposition techniques have been proven to be an efficient way to obtain conformal platinum and gold nanostructured layers on macro-electrodes. However, this technique is not effective on micro-electrodes. In this paper, we investigate an alternative one-step deposition technique of platinum nanoflowers on micro-electrodes by linear sweep voltammetry (LSV). The effective deposition of platinum nanoflowers with similar properties to the ones deposited on macro-electrodes is confirmed by morphological analysis and by the similar roughness factor (~200) and capacitance (~18 μ F/mm 2 ). The electrochemical behaviour of the nanostructured layer is then tested in an solid-contact (SC) L i + -selective micro-electrode and compared to the case of macro-electrodes. The sensor offers Nernstian calibration with same response time (~15 s) and a one-order of magnitude smaller limit of detection (LOD) ( 2.6 × 10 − 6 ) with respect to the macro-ion-selective sensors (ISE). Finally, sensor reversibility and stability in both wet and dry conditions is proven.

Recent advances in microelectronics and biosensors are enabling developments of innovative biochips for advanced healthcare by providing fully integrated platforms for continuous monitoring of a large set of human disease biomarkers. Continuous monitoring of several human metabolites can be addressed by using fully integrated and minimally invasive devices located in the sub-cutis, typically in the peritoneal region. This extends the techniques of continuous monitoring of glucose currently being pursued with diabetic patients. However, several issues have to be considered in order to succeed in developing fully integrated and minimally invasive implantable devices. These innovative devices require a high-degree of integration, minimal invasive surgery, long-term biocompatibility, security and privacy in data transmission, high reliability, high reproducibility, high specificity, low detection limit and high sensitivity. Recent advances in the field have already proposed possible solutions for several of these issues. The aim of the present paper is to present a broad spectrum of recent results and to propose future directions of development in order to obtain fully implantable systems for the continuous monitoring of the human metabolism in advanced healthcare applications.

We report on the electrochemical detection of anti-cancer drugs in human serum with sensitivity values in the range of 8–925 nA/µM. Multi-walled carbon nanotubes were functionalized with three different cytochrome P450 isoforms (CYP1A2, CYP2B6, and CYP3A4). A model used to effectively describe the cytochrome P450 deposition onto carbon nanotubes was confirmed by Monte Carlo simulations. Voltammetric measurements were performed in phosphate buffer saline (PBS) as well as in human serum, giving well-defined current responses upon addition of increasing concentrations of anti-cancer drugs. The results assert the capability to measure concentration of drugs in the pharmacological ranges in human serum. Another important result is the possibility to detect pairs of drugs present in the same sample, which is highly required in case of therapies with high side-effects risk and in anti-cancer pharmacological treatments based on mixtures of different drugs. Our technology holds potentials for inexpensive multi-panel drug-monitoring in personalized therapy.

The pharmaceutical industry is facing enormous challenges due to high drug attribution rates. For the past decades, novel methods have been developed for safety and efficacy testing, as well as for improving early development stages. In vitro screening methods for drug-receptor binding are considered to be good alternatives for decreasing costs in the identification of drug candidates. However, these methods require lengthy and troublesome labeling steps. Biosensors hold great promise due to the fact that label-free detection schemes can be designed in an easy and low-cost manner. In this paper, for the first time in the literature, we aimed to compare the potential of label-free optical and impedimetric electrochemical biosensors for the screening of antipsychotic drugs (APDs) based on their binding properties to dopamine receptors. Particularly, we have chosen a currently-used atypical antipsychotic drug (Buspirone) for investigating its dopamine D3 receptor (D3R) binding properties using an impedimetric biosensor and a nanoplasmonic biosensor. Both biosensors have been specifically functionalized and characterized for achieving a highly-sensitive and reliable analysis of drug-D3R binding. Our biosensor strategies allow for comparing different affinities against the D3R, which facilitates the identification of strong or weak dopamine antagonists via in vitro assays. This work demonstrates the unique potential of label-free biosensors for the implementation of cost-efficient and simpler analytical tools for the screening of antipsychotic drugs.

Further advances in molecular medicine and cell biology also require new electrochemical systems to detect disease biomarkers and therapeutic compounds. Microelectronic technology offers powerful circuits and systems to develop innovative and miniaturized biochips for sensing at the molecular level. However, microelectronic biochips proposed in the literature often do not show the right specificity, sensitivity, and reliability required by biomedical applications. Nanotechnology offers new materials and solutions to improve the surface properties of sensing probes. The aim of the present paper is to review the most recent progress in Nano-Bio-Technology in the area of the development of new electrochemical systems for molecular detection in personalized therapy and cell culture monitoring.