Towards solving the reproducibility crisis in surface-enhanced Raman spectroscopy-based pesticide detection.

Growing concerns about pesticide residues in agriculture are pushing the scientific community to develop innovative and efficient methods for detecting these substances at low concentrations down to the molecular level. In this context, surface-enhanced Raman spectroscopy (SERS) is a powerful analytical method that has so far already undergone some validation for its effectiveness in pesticide detection. However, despite its great potential, SERS faces significant difficulties obtaining reproducible and accurate pesticide spectra, particularly for some of the most widely used pesticides, such as malathion, chlorpyrifos, and imidacloprid. Those inconsistencies can be attributed to several factors, such as interactions between pesticides and SERS substrates and the variety of substrates and solvents used. In addition, differences in the equipment used to obtain SERS spectra and the lack of standards for control experiments further complicate the reproducibility and reliability of SERS data. This review systematically discusses the problems mentioned above, including a comprehensive analysis of the challenges in precisely evaluating SERS spectra for pesticide detection. We not only point out the existing limitations of the method, which can be traced in previous review works, but also offer practical recommendations to improve the quality and comparability of SERS spectra, thereby expanding the potential applications of the method in such an essential field as pesticide detection.

Nonlinear recurrence analysis of piezo sensor placement for unmanned aerial vehicle motor failure diagnosis.

This paper is focused on the diagnostics of multicopter UAV propulsion system, in which the temporary transient states occur during operation in faulty conditions (eg. not all motor phases working properly). As a diagnostic sensor, the piezo strip has been used, which is very sensitive to any vibrations of the multi-rotor frame. The paper concerns the precise location of the sensor for more effective monitoring of the propulsion system state. For this purpose, a nonlinear analysis of the vibration times series was carefully presented. The obtained non-linear time series were studied with the recurrence analysis in short time windows, which were sensitive to changes in Unmanned Aerial Vehicle motor speeds. The tests were carried out with different percentage of the pulse width modulation signal used for the operation of the brushless motor and for different locations of the piezosensor (side and top planes of the multicopter arm). In the article, it was shown that the side location of the piezosensor is more sensitive to changes in the Unmanned Aerial Vehicle propulsion system, which was studied with the Principal Component Analysis method applied for four main recurrence quantifications. The research presented proves the possibility of using nonlinear recurrence analysis for propulsion system diagnostics and helps to determine the optimal sensor location for more effective health monitoring of multicopter motor.

Multifaceted experiments and photothermal simulations based analysis of laser induced graphene and its fibers.

The interaction of CO2 laser with polyimide results in the formation of laser-induced graphene (LIG) and other morphological transitions based on laser parameters, such as Laser-induced fibers (LIF) on the surface. However, a fundamental investigation of LIF, its properties and potential have not been explored until now. We aim therefore to provide novel insights into the LIF by characterization of its structural, electrical, electrochemical, and mechanical properties. Four different morphologies were identified depending on the laser parameters and the temperature required for their formation were quantified by FEM model. Minimum temperatures of 1800 K were required to form LIG and around 2600 to 5000 K to form LIF. High heterogeneity of the LIF along thickness due to temperature gradients, and the existence of sheet structures underneath the fibers were identified. Due to the loosely bound nature of fibers, LIF dispersion was prepared by ultrasonication to functionalize the carbon electrode for electrochemical characterization. The modification with LIF on the electrodes enhanced the electrochemical response of the electrode towards standard redox couple which confirmed the conductive nature of the fibers. This work provides a solid basis for the versatile tuning of the behavior and properties of LIF for potential applications.

Inkjet-Printed Multiwalled Carbon Nanotube Dispersion as Wireless Passive Strain Sensor.

In this study, a multiwalled carbon nanotube (MWCNT) dispersion is used as an ink for a single-nozzle inkjet printing system to produce a planar coil that can be used to determine strain wirelessly. The MWCNT dispersion is non-covalently functionalized by dispersing the CNTs in an anionic surfactant, namely sodium dodecyl sulfate (SDS). The fabrication parameters, such as sonication energy and centrifugation time, are optimized to obtain an aqueous suspension suitable for an inkjet printer. Planar coils with different design parameters are printed on a flexible polyethylene terephthalate (PET) polymer substrate. The design parameters include a different number of windings, inner diameter, outer diameter, and deposited layers. The electrical impedance spectroscopy (EIS) analysis is employed to characterize the printed planar coils, and an equivalent electrical circuit model is derived based on the results. Additionally, the radio frequency identification technique is utilized to wirelessly investigate the read-out mechanism of the printed planar MWCNT coils. The complex impedance of the inductively coupled sensor undergoes a shift under strain, allowing for the monitoring of changes in resonance frequency and bandwidth (i.e., amplitude). The proposed wireless strain sensor exhibits a remarkable gauge factor of 22.5, which is nearly 15 times higher than that of the wireless strain sensors based on conventional metallic strain gauges. The high gauge factor of the proposed sensor suggests its high potential in a wide range of applications, such as structural health monitoring, wearable devices, and soft robotics.

Detection of H. pylori outer membrane protein (HopQ) biomarker using electrochemical impedimetric immunosensor with polypyrrole nanotubes and carbon nanotubes nanocomposite on screen-printed carbon electrode.

Helicobacter pylori (H. pylori) is classified as a class I carcinogen that colonizes the human gastrointestinal (GI) tract. The detection at low concentrations is crucial in combatting H. pylori. HopQ protein is located on H. pylori's outer membrane and is expressed at an early stage of contamination, which signifies it as an ideal biomarker. In this study, we presented the development of an electrochemical impedimetric immunosensor for the ultra-sensitive detection of HopQ at low concentrations. The sensor employed polypyrrole nanotubes (PPy-NTs) and carboxylated multi-walled carbon nanotubes (MWCNT-COOH) nanocomposite. PPy-NTs were chosen for their excellent conductivity, biocompatibility, and redox capabilities, simplifying sample preparation by eliminating the need to add redox probes upon measurement. MWCNT-COOH provided covalent binding sites for HopQ antibodies (HopQ-Ab) on the biosensor surface. Characterization of the biosensor was performed using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), contact angle measurements, and electrochemical impedance spectroscopy (EIS), complemented by numerical semiempirical quantum calculations. The results demonstrated a dynamic linear range of 5 pg/mL to 1.063 ng/mL and an excellent selectivity, with the possibility of excluding interference using EIS data, specifically charge transfer resistance and double-layer capacitance as multivariants for the calibration curve. Using two EIS components, the limit of detection is calculated to be 2.06 pg/mL. The biosensor was tested with a spiked drinking water sample and showed a signal recovery of 105.5% when detecting 300 pg/mL of HopQ. This novel H. pylori biosensor offers reliable, simple, portable, and rapid screening of the bacteria.

Biocompatibility Testing for Implants: A Novel Tool for Selection and Characterization.

This review article dives into the complex world of biocompatibility testing: chemical, mechanical, and biological characterization, including many elements of biocompatibility, such as definitions, descriptive examples, and the practical settings. The focus extends to evaluating standard documents obtained from reliable organizations; with a particular focus on open-source information, including FDA-USA, ISO 10933 series, and TÜV SÜD. We found a significant gap in this field: biomaterial scientists and those involved in the realm of medical device development in general, and implants in particular, lack access to a tool that reorganizes the process of selecting the appropriate biocompatibility test for the implant being examined. This work progressed through two key phases that aimed to provide a solution to this gap. A straightforward "yes or no" flowchart was initially developed to guide biocompatibility testing decisions based on the previously accumulated information. Subsequently, the Python code was employed, generating a framework through targeted questions. This work reshapes biocompatibility evaluation, bridging theory and practical implementation. An integrated approach via a flowchart and the Python code empowers stakeholders to navigate biocompatibility testing effortlessly. To conclude, researchers are now better equipped for a safer, more effective implant development, propelling the field towards improved patient care and innovative progress.

An Improved Wake-Up Receiver Based on the Optimization of Low-Frequency Pattern Matchers.

Wake-up receivers are gaining importance in power-aware wireless sensor networks, as they significantly reduce power consumption during RF reception, enabling asynchronous communication with low latency. However, the performance of wake-up receivers still lags behind that of off-the-shelf RF transceivers. There is a growing demand for higher sensitivity, enhanced reliability, and lower latency while maintaining the lowest power consumption. In this article, our goal is to advance the performance of wake-up receivers based on off-the-shelf components and low-frequency pattern matchers. Through a systematic investigation, we proposed multiple improvements aimed at enhancing wake-up receiver performance and reliability. We introduced an improved passive envelope detector and realized a wake-up receiver for the 868 MHz band, which achieves a power consumption of 5.71 µW and latency of 9.02 ms. Our proposed wake-up receiver is capable of detecting signals down to an average power level of -61.6 dBm. These achievements represent significant advancements compared to the existing state of research on wake-up receivers based on low-frequency pattern matchers. Recent articles have not been able to attain such improved values in signal detection, power consumption, and latency.

Wearable Electromyography Classification of Epileptic Seizures: A Feasibility Study.

Accurate diagnosis and classification of epileptic seizures can greatly support patient treatments. As many epileptic seizures are convulsive and have a motor component, the analysis of muscle activity can provide valuable information for seizure classification. Therefore, this paper present a feasibility study conducted on healthy volunteers, focusing on tracking epileptic seizures movements using surface electromyography signals (sEMG) measured on human limb muscles. For the experimental studies, first, compact wireless sensor nodes were developed for real-time measurement of sEMG on the gastrocnemius, flexor carpi ulnaris, biceps brachii, and quadriceps muscles on the right side and the left side. For the classification of the seizure, a machine learning model has been elaborated. The 16 common sEMG time-domain features were first extracted and examined with respect to discrimination and redundancy. This allowed the features to be classified into irrelevant features, important features, and redundant features. Redundant features were examined with the Big-O notation method and with the average execution time method to select the feature that leads to lower complexity and reduced processing time. The finally selected six features were explored using different machine learning classifiers to compare the resulting classification accuracy. The results show that the artificial neural network (ANN) model with the six features: IEMG, WAMP, MYOP, SE, SKEW, and WL, had the highest classification accuracy (99.95%). A further study confirms that all the chosen eight sensors are necessary to reach this high classification accuracy.

Novel Sensitive Electrochemical Immunosensor Development for the Selective Detection of HopQ H. pylori Bacteria Biomarker.

Helicobacter pylori (H. pylori) is a highly contagious pathogenic bacterium that can cause gastrointestinal ulcers and may gradually lead to gastric cancer. H. pylori expresses the outer membrane HopQ protein at the earliest stages of infection. Therefore, HopQ is a highly reliable candidate as a biomarker for H. pylori detection in saliva samples. In this work, an H. pylori immunosensor is based on detecting HopQ as an H. pylori biomarker in saliva. The immunosensor was developed by surface modification of screen-printed carbon electrodes (SPCE) with MWCNT-COOH decorated with gold nanoparticles (AuNP) followed by HopQ capture antibody grafting on SPCE/MWCNT/AuNP surface using EDC/S-NHS chemistry. The sensor performance was investigated utilizing various methods, such as cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and scanning electron microscope (SEM) coupled with energy-dispersive X-ray spectroscopy (EDX). H. pylori detection performance in spiked saliva samples was evaluated by square wave voltammetry (SWV). The sensor is suitable for HopQ detection with excellent sensitivity and linearity in the 10 pg/mL-100 ng/mL range, with a 2.0 pg/mL limit of detection (LOD) and an 8.6 pg/mL limit of quantification (LOQ). The sensor was tested in saliva at 10 ng/mL, and recovery of 107.6% was obtained by SWV. From Hill's model, the dissociation constant Kd for HopQ/HopQ antibody interaction is estimated to be 4.60 × 10-10 mg/mL. The fabricated platform shows high selectivity, good stability, reproducibility, and cost-effectiveness for H. pylori early detection due to the proper choice of biomarker, the nanocomposite material utilization to boost the SPCE electrical performance, and the intrinsic selectivity of the antibody-antigen approach. Additionally, we provide insight into possible future aspects that researchers are recommended to focus on.

Ultra-Sensitive and Fast Humidity Sensors Based on Direct Laser-Scribed Graphene Oxide/Carbon Nanotubes Composites.

In this paper, the relative humidity sensor properties of graphene oxide (GO) and graphene oxide/multiwalled nanotubes (GO/MWNTs) composites have been investigated. Composite sensors were fabricated by direct laser scribing and characterized using UV-vis-NIR, Raman, Fourier transform infrared, and X-ray photoemission spectroscopies, electron scanning microscopy coupled with energy-dispersive X-ray analysis, and impedance spectroscopy (IS). These methods confirm the composite homogeneity and laser reduction of GO/MWNT with dominant GO characteristics, while ISresults analysis reveals the circuit model for rGO-GO-rGO structure and the effect of MWNT on the sensor properties. Although direct laser scribing of GO-based humidity sensor shows an outstanding response (|ΔZ|/|Z| up to 638,800%), a lack of stability and repeatability has been observed. GO/MWNT-based humidity sensors are more conductive than GO sensors and relatively less sensitive (|ΔZ|/|Z| = 163,000%). However, they are more stable in harsh humid conditions, repeatable, and reproducible even after several years of shelf-life. In addition, they have fast response/recovery times of 10.7 s and 9.3 s and an ultra-fast response time of 61 ms when abrupt humidification/dehumidification is applied by respiration. All carbon-based sensors' overall properties confirm the advantage of introducing the GO/MWNT hybrid and laser direct writing to produce stable structures and sensors.

Towards Embedded Electrochemical Sensors for On-Site Nitrite Detection by Gold Nanoparticles Modified Screen Printed Carbon Electrodes.

The transition of electrochemical sensors from lab-based measurements to real-time analysis requires special attention to different aspects in addition to the classical development of new sensing materials. Several critical challenges need to be addressed including a reproducible fabrication procedure, stability, lifetime, and development of cost-effective sensor electronics. In this paper, we address these aspects exemplarily for a nitrite sensor. An electrochemical sensor has been developed using one-step electrodeposited (Ed) gold nanoparticles (EdAu) for the detection of nitrite in water, which shows a low limit of detection of 0.38 µM and excellent analytical capabilities in groundwater. Experimental investigations with 10 realized sensors show a very high reproducibility enabling mass production. A comprehensive investigation of the sensor drift by calendar and cyclic aging was carried out for 160 cycles to assess the stability of the electrodes. Electrochemical impedance spectroscopy (EIS) shows significant changes with increasing aging inferring the deterioration of the electrode surface. To enable on-site measurements outside the laboratory, a compact and cost-effective wireless potentiostat combining cyclic and square wave voltammetry, and EIS capabilities has been designed and validated. The implemented methodology in this study builds a basis for the development of further on-site distributed electrochemical sensor networks.

PEDOT: PSS/AuNPs-Based Composite as Voltammetric Sensor for the Detection of Pirimicarb.

An electrochemical sensor for the pesticide Pirimicarb (PMC) has been developed. A screen-printed electrode (SPCE) was used and modified with the conducting polymer poly (3,4-ethylenedioxythiophene) (PEDOT) and gold nanoparticles (AuNPs) to enhance electrochemical proprieties. Electrode characterizations were performed using scattering electron microscopy (SEM) and cyclic voltammetry (CV). With the SPCE/PEDOT:PSS/AuNPs modified electrode, a new peak at 1.0 V appeared in the presence of PMC related to the PMC oxidation. To elucidate the mechanism of PMC oxidation, Gas Chromatography-Mass Spectrometry (GC-MS), where two major peaks were identified, evidencing that the device can both detect and degrade PMC by an electro-oxidation process. Exploring this peak signal, it was possible the sensor development, performing detection from 93.81-750 µmol L-1, limits of quantification (LOQ) and detection (LOD) of 93.91 µmol L-1 and 28.34 µmol L-1, respectively. Thus, it was possible to study and optimization of PMC degradation, moreover, to perform detection at low concentrations and with good selectivity against different interferents using a low-cost printed electrode based on graphite modified with conductive polymer and AuNPs.

k-Tournament Grasshopper Extreme Learner for FMG-Based Gesture Recognition.

The recognition of hand signs is essential for several applications. Due to the variation of possible signals and the complexity of sensor-based systems for hand gesture recognition, a new artificial neural network algorithm providing high accuracy with a reduced architecture and automatic feature selection is needed. In this paper, a novel classification method based on an extreme learning machine (ELM), supported by an improved grasshopper optimization algorithm (GOA) as a core for a weight-pruning process, is proposed. The k-tournament grasshopper optimization algorithm was implemented to select and prune the ELM weights resulting in the proposed k-tournament grasshopper extreme learner (KTGEL) classifier. Myographic methods, such as force myography (FMG), deliver interesting signals that can build the basis for hand sign recognition. FMG was investigated to limit the number of sensors at suitable positions and provide adequate signal processing algorithms for perspective implementation in wearable embedded systems. Based on the proposed KTGEL, the number of sensors and the effect of the number of subjects was investigated in the first stage. It was shown that by increasing the number of subjects participating in the data collection, eight was the minimal number of sensors needed to result in acceptable sign recognition performance. Moreover, implemented with 3000 hidden nodes, after the feature selection wrapper, the ELM had both a microaverage precision and a microaverage sensitivity of 97% for the recognition of a set of gestures, including a middle ambiguity level. The KTGEL reduced the hidden nodes to only 1000, reaching the same total sensitivity with a reduced total precision of only 1% without needing an additional feature selection method.

Self-Powered Synchronized Switching Interface Circuit for Piezoelectric Footstep Energy Harvesting.

Piezoelectric Vibration converters are nowadays gaining importance for supplying low-powered sensor nodes and wearable electronic devices. Energy management interfaces are thereby needed to ensure voltage compatibility between the harvester element and the electric load. To improve power extraction ability, resonant interfaces such as Parallel Synchronized Switch Harvesting on Inductor (P-SSHI) have been proposed. The main challenges for designing this type of energy management circuits are to realise self-powered solutions and increase the energy efficiency and adaptability of the interface for low-power operation modes corresponding to low frequencies and irregular vibration mechanical energy sources. In this work, a novel Self-Powered (SP P-SSHI) energy management circuit is proposed which is able to harvest energy from piezoelectric converters at low frequencies and irregular chock like footstep input excitations. It has a good power extraction ability and is adaptable for different storage capacitors and loads. As a proof of concept, a piezoelectric shoe insole with six integrated parallel piezoelectric sensors (PEts) was designed and implemented to validate the performance of the energy management interface circuit. Under a vibration excitation of 1 Hz corresponding to a (moderate walking speed), the maximum reached efficiency and power of the proposed interface is 83.02% and 3.6 mW respectively for the designed insole, a 10 kΩ resistive load and a 10 µF storage capacitor. The enhanced SP-PSSHI circuit was validated to charge a 10 µF capacitor to 6 V in 3.94 s and a 1 mF capacitor to 3.2 V in 27.64 s. The proposed energy management interface has a cold start-up ability and was also validated to charge a (65 mAh, 3.1 V) maganese dioxide coin cell Lithium battery (ML 2032), demonstrating the ability of the proposed wearable piezoelectric energy harvesting system to provide an autonomous power supply for wearable wireless sensors.

Layer-by-Layer Deposited Multi-Modal PDAC/rGO Composite-Based Sensors.

Different environmental parameters, such as temperature and humidity, aggravate food spoilage, and different volatile organic compounds (VOCs) are released based on the extent of spoilage. In addition, a lack of efficient monitoring of the dosage of pesticides leads to crop failure. This could lead to the loss of food resources and food production with harmful contaminants and a short lifetime. For this reason, precise monitoring of different environmental parameters and contaminations during food processing and storage is a key factor for maintaining its safety and nutritional value. Thus, developing reliable, efficient, cost-effective sensor devices for these purposes is of utmost importance. This paper shows that Poly-(diallyl-dimethyl ammonium chloride)/reduced Graphene oxide (PDAC/rGO) films produced by a simple Layer-by-Layer deposition can be effectively used to monitor temperature, relative humidity, and the presence of volatile organic compounds as indicators for spoilage odors. At the same time, they show potential for electrochemical detection of organophosphate pesticide dimethoate. By monitoring the resistance/impedance changes during temperature and relative humidity variations or upon the exposure of PDAC/rGO films to methanol, good linear responses were obtained in the temperature range of 10-100 °C, 15-95% relative humidity, and 35 ppm-55 ppm of methanol. Moreover, linearity in the electrochemical detection of dimethoate is shown for the concentrations in the order of 102 µmol dm-3. The analytical response to different external stimuli and analytes depends on the number of layers deposited, affecting sensors' sensitivity, response and recovery time, and long-term stability. The presented results could serve as a starting point for developing advanced multi-modal sensors and sensor arrays with high potential for analytical applications in food safety and quality monitoring.

A Biodegradable Bioactive Glass-Based Hydration Sensor for Biomedical Applications.

Monitoring changes in edema-associated intracranial pressure that complicates trauma or surgery would lead to improved outcomes. Implantable pressure sensors have been explored, but these sensors require post-surgical removal, leading to the risk of injury to brain tissue. The use of biodegradable implantable sensors would help to eliminate this risk. Here, we demonstrate a bioactive glass (BaG)-based hydration sensor. Fluorine (CaF2) containing BaG (BaG-F) was produced by adding 5, 10 or 20 wt.% of CaF2 to a BaG matrix using a melting manufacturing technique. The structure, morphology and electrical properties of the resulting constructs were evaluated to understand the physical and electrical behaviors of this BaG-based sensor. Synthesis process for the production of the BaG-F-based sensor was validated by assessing the structural and electrical properties. The structure was observed to be amorphous and dense, the porosity decreased and grain size increased with increasing CaF2 content in the BaG matrix. We demonstrated that this BaG-F chemical composition is highly sensitive to hydration, and that the electrical sensitivity (resistive-capacitive) is induced by hydration and reversed by dehydration. These properties make BaG-F suitable for use as a humidity sensor to monitor brain edema and, consequently, provide an alert for increased intracranial pressure.

Gold Nanoparticles-MWCNT Based Aptasensor for Early Diagnosis of Prostate Cancer.

Prostate cancer is one of the most frequently diagnosed male malignancies and can be detected by prostate-specific antigen (PSA) as a biomarker. To detect PSA, several studies have proposed using antibodies, which are not economical and require a long reaction time. In this study, we propose to use self-assembled thiolated single-strand DNA on electrodes functionalized by multi-walled carbon nanotubes (MWCNT) modified with gold nanoparticles (AuNPs) to realize a low-cost label-free electrochemical biosensor. In this regard, the PSA aptamer was immobilized via electrostatic adsorption on the surface of a screen-printed MWCNT/AuNPs electrode. The immobilization process was enhanced due to the presence of Au nanoparticles on the surface of the electrode. Surface characterization of the electrode at different stages of modification was performed by electrochemical impedance spectroscopy (EIS), atomic force microscopy (AFM) and Fourier transform infrared spectroscopy (FTIR) and contact angle for surface tension properties. The results showed an increase in surface roughness due to the absorbance of the aptamer on the electrode surfaces. The developed sensor has an extended linear range of 1-100 ng/mL, and a very low limit of detection down to 1 pg/mL. In addition, the reaction has a binding time of only five minutes on the developed electrodes. Investigations of the biosensor selectivity against several substances revealed an efficient selectivity for PSA detection. With this approach, low-cost biosensors with high sensitivity can be realized which have a wide linearity range and a low limit of detection, which are necessary for the early detection of prostate cancer.

Homogeneity Characterization of Textile-Integrated Wearable Sensors based on Impedance Spectroscopy.

One of the main challenges during the integration of a carbon/polymer-based nanocomposite sensor on textile substrates is the fabrication of a homogeneous surface of the nanocomposite-based thin films, which play a major role in the reproducibility of the sensor. Characterizations are therefore required in every fabrication step to control the quality of the material preparation, deposition, and curing. As a result, microcharacterization methods are more suitable for laboratory investigations, and electrical methods can be easily implemented for in situ characterization within the manufacturing process. In this paper, several textile-based pressure sensors are fabricated at an optimized concentration of 0.3 wt.% of multiwalledcarbon nanotubes (MWCNTs) composite material in PDMS. We propose to use impedance spectroscopy for the characterization of both of the resistive behavior and capacitive behavior of the sensor at several frequencies and under different loads from 50 g to 500 g. The impedance spectra are fitted to a model composed of a resistance in series with a parallel combination of resistance and a constant phase element (CPE). The results show that the printing parameters strongly influence the impedance behavior under different loads. The deviation of the model parameter α of the CPE from the value 1 is strongly dependent on the nonhomogeneity of the sensor. Based on an impedance spectrum measurement followed by parameter extraction, the parameter α can be determined to realize a novel method for homogeneity characterization and in-line quality control of textile-integrated wearable sensors during the manufacturing process.

Laser-Engineered Multifunctional Graphene-Glass Electronics.

Glass electronics inspire the emergence of smart functional surfaces. To evolve this concept to the next level, developing new strategies for scalable, inexpensive, and electrically conductive glass-based robust nanocomposites is crucial. Graphene is an attractive material as a conductive filler; however, integrating it firmly into a glass with no energy-intensive sintering, melting, or harsh chemicals has not been possible until now. Moreover, these methods have very limited capability for fabricating robust patterns for electronic circuits. In this work, a conductive (160 OΩ sq-1 ) and resilient nanocomposite between glass and graphene is achieved via single-step laser-induced backward transfer (LIBT). Beyond conventional LIBT involving mass transfer, this approach simultaneously drives chemical transformations in glass including silicon compound formation and graphene oxide (GO) reduction. These processes take place together with the generation and transfer of the highest-quality laser-reduced GO (rGO) reported to date (Raman intensity ratio ID /IG  = 0.31) and its integration into the glass. The rGO-LIBT nanocomposite is further functionalized with silver to achieve a highly sensitive (10-9  m) dual-channel plasmonic optical and electrochemical sensor. Besides the electrical circuit demonstration, an electrothermal heater is fabricated that reaches temperatures above 300 °C and continuously operates for over 48 h.

Comparative Study of Measurement Methods for Embedded Bioimpedance Spectroscopy Systems.

Bioimpedance spectroscopy (BIS) is an advanced measurement method for providing information on impedance changes at several frequencies by injecting a low current into a device under test and analyzing the response voltage. Several methods have been elaborated for BIS measurement, calculating impedance with a gain phase detector (GPD), IQ demodulation, and fast Fourier transform (FFT). Although the measurement method has a big influence on the measurement system performance, a systematical comparative study has not been performed yet. In this paper, we compare them based on simulations and experimental studies. To maintain similar conditions in the implementation of all methods, we use the same signal generator followed by a voltage-controlled current source (VCCS) as a signal generator. For performance analysis, three DUTs have been designed to imitate the typical behavior of biological tissues. A laboratory impedance analyzer is used as a reference. The comparison addresses magnitude measurement accuracy, phase measurement accuracy, signal processing, hardware complexity, and power consumption. The result shows that the FFT-based system excels with high accuracy for amplitude and phase measurement while providing the lowest hardware complexity, and power consumption, but it needs a much higher software complexity.