Impedance Technique Research Articles

Application of novel Dy0.06Gd0.02Er0.02Bi1.9O3 oxide ion electrolyte for intermediate-temperature reversible solid oxide cells

Bismuth-based oxides are promising electrolyte materials for Reversible Solid Oxide Cells (RSOCs) due to their high ion conductivity and rapid surface oxygen exchange kinetics. In this work we propose a multi-element doping strategy to obtain a novel Dy0.06Gd0.02Er0.02Bi1.9O3 (DGESB) quaternary oxide bismuth material whose ionic conductivities and crystal structure are characterized by AC impedance and X-ray diffraction technique in the temperature range from 600 to 700 °C. Along with promising structure stability and durability, our novel DGESB showed a remarkable ionic conductivity that is 65 times higher than the commercial yttria-stabilized zirconia (YSZ) electrolyte at 700 °C. With composite electrode of DGESB + LCN (LaCo0.6Ni0.4O3) and DGESB/YSZ bilayer electrolyte consisting of RSOC symmetric cell, which achieves a high peak power density (PPD) of 1.62 W/cm2 in fuel cell mode which is 2.7 times higher than that of YSZ single-layer electrolyte, while the electrolysis current density is as high as 1.66 A/cm2 at 1.3 V under H2/H2O:50/50 in electrolysis mode at the same operation temperature of 700 °C. The electrochemical performance measurements revealed a certain stable operation for 200 h in fuel cell mode. The performance degradation can be attributed to the microstructure evolution at the interface between electrolyte and electrodes. The high ionic conductive DGESB proves to be an excellent intermediate electrolyte layer for improving cell performance in RSOCs

Numerical Analysis of Steel Frame Using Electro-Mechanical Impedance Technique

Nowadays, piezoelectric materials are most widely used in structural health monitoring (SHM) system for nondestructive evaluation. In this paper the damage study using electro-mechanical impedance (EMI) technique, which is nondestructive method of SHM. This paper presents a numerical analysis of four-story steel frame and multiple damages were induced in the steel frame by utilizing smart material like Lead Zirconate Titanate (PZT). A PZT-4 piezoelectric material was embedded in the beam of the frame. The type of damping used in steel frame model was Rayleigh damping. The numerical analysis was done in COMSOL MULTIPHYSICS 6.2 and frequency domain analysis was done, from that admittance values were find out for 30-300KHz frequency range. The real part of the admittance gives conductance values. Then, conductance verses frequency graph was created that will indicate the structural health and performance. Moreover, root mean square deviation (RMSD) index was found out for each case that provides a quantitative measure of deviation.

Fabrication of ultra-sensitive and disposable electrochemical biosensor: Detection of kidney injury molecule-1 protein in urine for diagnosis of kidney injury

This research study indicates the development of the indium tin oxide-polyethylene terephthalate (ITO-PET) coated electrode-based electrochemical biosensor system to sensitively and specifically detect kidney injury molecule-1 (KIM-1), an acute kidney injury (AKI) biomarker. The ITO-PET electrode surface was modified with 3-(Trimethoxysilyl)-1-propanethiol (3-TMESP) silane agent. Electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and single frequency impedance (SFI) techniques were utilized to examine the interactions between anti-KIM-1 antibody and KIM-1 antigen. The ITO-PET electrode surface was observed by scanning electron microscopy (SEM) and atomic force microscopy (AFM) to analyze the morphological characterization at each electrode development stage. Optimization studies have been conducted to determine the optimal concentrations for detecting the 3-TMESP silane agent, the NHS crosslinker, the anti-KIM-1 antibody, and the optimum incubation period for the anti-KIM-1 antibody and the KIM-1 antigen. Analytical characteristic properties of the developed biosensor, including linear determination range, and the studies of reproducibility, regeneration, repeatability, storage life, and selectivity were investigated. The KIM-1 biosensor system, based on 3-TMESP, has a broad linear range and is capable of providing sensitive measurements between 0.1 fg/mL and 1000 fg/mL. The values of low limits of detection (0.26 fg/mL) and of quantification (0.87 fg/mL) were calculated, highlighting its high sensitivity and precision in detecting KIM-1. In addition, five different commercially purchased human urine samples were tested to validate the practicability of the developed biosensor.

Start-Up and Fault-Ride-Through Strategy for Offshore Wind Power via DRU-HVDC Transmission System

The diode-rectifier unit (DRU)-based high-voltage direct current (HVDC) transmission system offers an economical solution for offshore wind power transmission. However, this approach requires offshore wind farms to establish a strong grid voltage. To meet this requirement while fulfilling the dynamic characteristics of the DRU, this paper proposes an advanced grid-forming (GFM) control strategy for offshore wind turbines connected to DRU-HVDC. The strategy incorporates a P-U controller and a Q-ω controller based on reactive power synchronization. Furthermore, a novel virtual power-based pre-synchronization method and an adaptive virtual impedance technique are integrated into the proposed GFM control to improve system performance during wind turbine (WT) integration and low-voltage ride-through (LVRT) scenarios. The virtual power-based pre-synchronization method reduces voltage spikes during the integration of new wind turbines, while the adaptive virtual impedance technique effectively suppresses fault currents during low-voltage faults, enabling faster recovery. Simulation results validate the effectiveness of the proposed GFM control strategy, demonstrating improved start-up and LVRT performance through the pre-synchronization and adaptive virtual impedance methods.

A-147 Comparative Precision of Platelet Counting by Optical, Fluorescent, and Impedance Techniques in Thrombocytopenia and Microcytosis Patients

Abstract Background In today's era of automation driven by Artificial Intelligence, even the most efficient automated hematology analyzer may struggle to accurately determine platelet count in patients with low platelet count and microcytosis. The Sysmex XN-series analyzer (Sysmex, Kobe, Japan) uses optical density, fluorescence, and electronic impedance methods for platelet counting. This study aimed to evaluate the accuracy of optical, fluorescence, and electrical impedance methods in estimating precise platelet counts in thrombocytopenic and microcytic patient samples. Methods A cross-sectional study was conducted in the Department of Laboratory Medicine at AIIMS, New Delhi, for 30 days consecutively. A total of 200 blood samples collected, of which 100 samples were of thrombocytopenia (<100x10^9/L) and 100 samples were of microcytosis (Mean corpuscular volume <76 femtoliters). MCV<76 fl was further categorized into 2 groups- MCV 60-70 fl and MCV 71-76 fl accordingly. Males and females were categorized and analyzed distinctly for thrombocytopenia and microcytosis. Statistical analysis was performed using SPSS 16.0 for Windows (SPSS Inc., Chicago, IL, USA) and the Bland Altman plot was analyzed. Results Of the 100 patients with thrombocytopenia (platelet<1 lakh/L) females were predominantly 54% while males were 46% and the median age was 29 years (0.02-70). Of the 100 patients with low MCV (<76 fl) females were 53%, while males were 47% and the median age was 29 years (0.3-69). The findings were compared against the standard manual platelet count method in peripheral smears verified by two expert pathologists. The Bland Altman plot for Platelet <1 lakh/L and MCV <76 fl were compared with standard manual platelet count method and the following findings were obtained i) In female with PLT- <1 lakh/L, PLT-O showed least bias (9.8) followed by PLT-F (10.4) and PLT-I (12.1) ii) In males with PLT-<1 lakh/L, PLT-O showed least bias(14.1) followed by PLT-F(16.5) and PLT-I(17.0) iii) For MCV 61-70fl, PLT-O showed the least bias (4.4) followed by PLT-F (6.7) and PLT-I (28.5) iv)For MCV 71-76fl, PLT-F showed least bias (-0.2) followed by PLT-O (1.5) and PLT-I(31.2). Conclusions Platelet count by optical method (PLT-O) detects platelet count more accurately with minimum bias when compared with PLT-F and PLT-I in patients with thrombocytopenia. In patients with microcytosis, PLT-I is less reliable in comparison to PLT-O and PLT-F. A limitation of the automated hematology analyzer is the inability to detect platelet clumps which is appreciated in peripheral smears.

Electrografted Laser-Induced Graphene: Direct Detection of Neurodegenerative Disease Biomarker in Cerebrospinal Fluid.

There are more than 50 neurodegenerative disorders, and amyotrophic lateral sclerosis (ALS) is one of the most common disorders that poses diagnostic and treatment challenges. The poly glycine-proline (polyGP) dipeptide repeat is a toxic protein that has been recognized as a pharmacodynamic biomarker of C9orf72-associated (c9+) ALS, a subtype of ALS that originates from genetic mutation. Early detection of polyGP will help healthcare providers start timely gene therapy. Herein, we developed a label-free electrochemical immunoassay for the simple detection of polyGP in unprocessed cerebrospinal fluid (CSF) samples collected from ALS patients in the National ALS Biorepository. For the first time, an electrografted laser-induced graphene (E-LIG) electrode system was employed in a sandwich format to detect polyGP using a label-free electrochemical impedance technique. The results show that the E-LIG-modified surface exhibited high sensitivity and selectivity in buffer and CSF media with limit of detection values of 0.19 and 0.27 ng/mL, respectively. The precision of the calibration model was better in CSF than in the buffer. The E-LIG immunosensor can easily select polyGP targets in the presence of other dipeptide proteins translated from the c9 gene. Further study with CSF samples from ALS patients demonstrated that the label-free E-LIG-based immunosensor not only quantified polyGP in the complex CSF matrix but also distinguished between c9+ and non-c9- ALS patients.

Effect of Pr6O11 addition on the electrical properties of Sm0.2Ce0.8O1.9 electrolyte materials for solid oxide fuel cells

Sm[Formula: see text]Ce[Formula: see text]O[Formula: see text] (SDC) solid electrolyte powder for solid oxide fuel cells was prepared by sol-gel method, and Pr6O[Formula: see text] was added to improve the electrochemical performance. The effect of Pr6O[Formula: see text] addition on the electrical properties was studied. X-ray diffraction (XRD) analyses confirmed that the structure of SDC and Pr6O[Formula: see text] does not change, the two materials still maintain their original structure in Pr6O[Formula: see text]-Sm[Formula: see text]Ce[Formula: see text]O[Formula: see text] composite. Scanning electron microscopy (SEM) results showed that the Pr6O[Formula: see text]-Sm[Formula: see text]Ce[Formula: see text]O[Formula: see text] composite exhibits superior sintering activity and can form a dense ceramic structure after sintering at 1250∘C. The electrochemical performance of the electrolyte was tested in air using AC impedance technique in the temperature range of 500–650∘C. The results showed that the conductivity of Sm[Formula: see text]Ce[Formula: see text]O[Formula: see text] can significantly increase by adding the right amount of Pr6O[Formula: see text], and the highest conductivity of 0.053 S/cm can be seen in the 15% Pr-SDC sample at 650∘C. In conclusion, the Pr6O[Formula: see text]/Sm[Formula: see text]Ce[Formula: see text]O[Formula: see text] composite electrolyte shows a promising prospect as an electrolyte material for medium or low-temperature solid oxide fuel cells due to its excellent electrical properties.

Assessing cement paste strength evolution under curing: An experimental and numerical investigation through equivalent stiffness parameter identified by embedded piezo sensors

Equivalent stiffness is one of the most important mechanical parameters of any concrete structure which allows engineers to predict the behaviour of the structure. This paper identifies the equivalent stiffness parameter through an embedded piezo sensor (EPS) in the strength development of cement paste using the electro-mechanical impedance (EMI) technique through experimental and numerical investigation. The experiments were conducted on the cement paste specimens; and the compressive strength (destructively) and EMI response were obtained during curing process. Further, a numerical model of cement paste specimen with EPS is developed to validate the EMI response. In addition, an equivalent stiffness parameter is identified from the experimental and simulation EMI data. It is found that the variation in conductance signature during curing process and strength development is effectively captured by the EPS. The identified equivalent stiffness either calculated from experimental or simulation data followed a similar behaviour of the compressive strength.

A monitoring platform based on electrical impedance and AI techniques to enhance the resilience of the built environment

Structural Health Monitoring (SHM) and early warning systems (EWSs) play a pivotal role in enhancing seismic resilience for both buildings and occupants. This paper introduces a monitoring platform that collects electrical impedance data from scaled concrete beams undergoing load and accelerated degradation tests. Artificial Intelligence (AI) algorithms are employed for predictive analysis, scrutinizing historical impedance data, and forecasting future trends. These algorithms adapt to environmental parameters, becoming valuable tools in data-driven decision-making processes. In particular, the study investigates concrete specimens in different test conditions, utilizing a distributed sensor network based on electrical impedance as well as temperature and relative humidity sensors. Real-time data are transmitted to a cloud infrastructure during accelerated degradation tests (both in water and in chloride-rich solution) and in room conditions. An AI-based forecasting approach using Prophet is proposed, ingesting electrical impedance and temperature data, and tested to predict electrical impedance corresponding to approximately 10 % of the time series balancing responsiveness with predictive accuracy, crucial for effective EWS operations and management requirements. The performance of the tested models is evaluated employing metrics such as Mean Average Error (MAE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and correlation. The proposed approach surpasses statistical methods and deep learning techniques, reporting a MAPE always lower than 3.20 % and a correlation higher than 81.65 % (in wet-dry cycles in water these values are 0.65 Ω and 91.85 %, respectively). This proves to be a promising step towards transparent SHM, which integrates AI models facilitating self-monitoring and early maintenance prediction, thus enhancing the resilience of the built environment.

An unusual impedimetric biosensor design based on 3-MPDS for highly sensitive detection of AFB1 in food samples

Aflatoxin B1 (AFB1), a mycotoxin produced by fungi of the genus Aspergillus, particularly Aspergillus flavus, is recognized as the aflatoxin with the highest carcinogenic and mutagenic potential. This study presents a cost-effective, disposable AFB1 biosensor system based on 3-mercaptopropyltrimethoxysilane (3-MPDS) and the highly sensitive impedance technique. The surfaces of the ITO-PET (indium tin oxide/polyethylene terephthalate) electrodes were modified with 3-MPDS, and N-hydroxysuccinimide (NHS) was used as a crosslinker. Electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) techniques were employed for immobilization, optimization, and analytical studies. Additionally, the surface morphology of the biosensor was analyzed using scanning electron microscopy (SEM) and atomic force microscopy (AFM). The biosensor demonstrated a linear range from 0.01 fg/mL to 200 fg/mL, with a limit of detection (LOD) of 0.01 fg/mL and a limit of quantification (LOQ) of 0.04 fg/mL. Finally, the proposed biosensor was tested and validated with real food samples, including rice, peanuts, milk, chili pepper, and corn.

Volume Regulation and Nonosmotic Volume of Individual Human Platelets Quantified by High-Speed Scanning Ion Conductance Microscopy.

Platelets are anucleate cells that play an important role in wound closure following vessel injury. Maintaining a constant platelet volume is critical for platelet function. For example, water-induced swelling can promote procoagulant activity and initiate thrombosis. However, techniques for measuring changes in platelet volume such as light transmittance or impedance techniques have inherent limitations as they only allow qualitative measurements or do not work on the single-cell level. Here, we introduce high-speed scanning ion conductance microscopy (HS-SICM) as a new platform for studying volume regulation mechanisms of individual platelets. We optimized HS-SICM to quantitatively image the morphology of adherent platelets as a function of time at scanning speeds up to 7 seconds per frame and with 0.1 fL precision. We demonstrate that HS-SICM can quantitatively measure the rapid swelling of individual platelets after a hypotonic shock and the following regulatory volume decrease (RVD). We found that the RVD of thrombin-, ADP-, and collagen-activated platelets was significantly reduced compared with nonactivated platelets. Applying the Boyle-van't Hoff relationship allowed us to extract the nonosmotic volume and volume fraction on a single-platelet level. Activation by thrombin or ADP, but not by collagen, resulted in a decrease of the nonosmotic volume, likely due to a release reaction, leaving the total volume unaffected. This work shows that HS-SICM is a versatile tool for resolving rapid morphological changes and volume dynamics of adherent living platelets.

Facile construction of binary metal oxide heterojunction with hexagonal boron nitride nanohybrid electrocatalyst for the detection of flutamide

BackgroundFlutamide (FU) is a potential anti-androgen drug significantly prescribed to all human beings. The high solubility and poor degradability of its metabolites can adversely affect the balance of the ecosystem. Therefore, developing an efficient and reliable technique to detect this pollutant is essential. Consequently, electrochemical sensors have been widely used for the monitoring of various real-world samples. MethodsHence, nickel-zinc oxide (NZO) with hexagonal boron nitride (h-BN) nanocomposite was prepared as a proficient electrocatalyst in FU detection. Several spectroscopic measurements were carried out to characterize the prepared materials. Our NZO/h-BN nanocomposite was utilized to modify the glassy carbon electrode (GCE) and its relative catalytic activity was scrutinized with impedance and various voltammetric techniques. Significant findingsBased on the results, our NZO/h-BN/GCE sensor exhibited high conductance, appreciable linear ranges, low detection limit (0.002 μM), optimal sensitivity (2.149 µA µM−1 cm−2), and high selectivity with good repeatability, and reproducibility results. Furthermore, the practical utility of the sensor was studied by monitoring FU in human and environmental samples. Based on the outcomes, our NZO/h-BN/GCE is a promising electrochemical platform for the detection of FU.

Accelerating Measurement Times by Correlating Electrode/Electrolyte Interface Properties with Cycle and Calendar Lifetimes

Electrochemical performance measurements on novel battery technologies are slow and require substantial resources. For example, a common metric for assessing the cycle lifetime of a cell is by charging and discharging at a rate of one cycle every six hours (C/3) for 1000 cycles and reporting the remaining capacity after the measurement. At this rate, a single measurement takes eight months to acquire useful data. Even worse, the benchmark for an acceptable shelf-life (calendar life) is to retain 80% of the initial cell capacity through 10 years. As of now, the only reliable method for acquiring this value is to hold the cell at open circuit for the duration of the time (10 years) while performing intermittent reference performance tests. The ability to quickly screen new chemistries for LIB applications offers tremendous value for accelerating discovery. Here, I will present an electrochemical impedance technique that measures a key parameter of the solid|electrolyte interface. This method uses the Helmholtz and Gouy-Chapman-Stern models of electrochemical interfaces to approximate the ‘health’ of the anode|electrolyte interface. These measurements strongly correlate to the average Coulombic efficiency of batteries with different cell chemistries which may offer predictive power for assessing the long-term cycle and calendar lifetimes.

Corrosion monitoring for transmission line based on electromechanical impedance instrumented circular piezoelectric corrosion sensor

Corrosion-induced thickness loss is a common form structural damage in transmission lines. In our previous work, a novel circular piezoelectric-metal transducer for corrosion sensing using the electromechanical impedance (EMI) technique was proposed. This transducer was fabricated by attaching a lead zirconate titanate (PZT) patch to a metal plate. In the present study, the piezoelectric-metal transducer was encapsulated and enhanced, and two types of corrosion sensors were developed: piezoelectric-steel and piezoelectric-zinc sensors. To assess the practical performance of the corrosion sensors, the piezoelectric-steel and piezoelectric-zinc sensors were connected to the angle steels and the steel strands, which are highly prone to corrosion in transmission lines. Corrosion monitoring experiments were conducted in the laboratory. The results demonstrate that the peak frequencies in the conductance signatures decrease linearly with increasing corrosion-induced thickness loss. Furthermore, it was found that piezoelectric-steel sensors are effective for quantitative monitoring of metallic corrosion, whereas piezoelectric-zinc sensors are better suited for early-stage corrosion monitoring and warning.

Emulsions stability in weightlessness: Droplets size, droplets coalescence and phases spatial distribution

This work presents experiments for the stability study of oil-in-water emulsions at varying gravity conditions. A key factor influencing emulsions stability is droplet size which can be assessed by several techniques employing different physical principles. Experiments are performed during the 79th Parabolic Flight Campaign of European Space Agency (October 2022). A pulsatile miniature emulsification device is used to produce emulsions in ∼0 g conditions while using varying experimental parameters (oil volumetric fraction, surfactant concentration, pulsation frequency, number of strokes). The device resembles the Soft Matter Dynamics facility onboard the International Space Station whereas the examined parameters are also alike to Soft Matter Dynamics experiment. Optical measurements are employed to determine the droplet size distribution as well as, to observe coalescence events in the aqueous phase. Electrical measurements with a non-intrusive, on-line, impedance spectroscopy technique are carried out to track the evolution of oil volumetric fraction at the central region of the emulsification cell. As expected, in the absence of gravity, the buoyancy related phenomena are eliminated and, thus, phase gravitational separation between the two phases (creamy and aqueous) does not take place. Yet, the residual motion at the end of emulsification affects (a) the spatial homogeneity (distribution) of the two phases in the cell and (b) the capacity for coalescence of colliding droplets. In the absence of gravity, these two emulsion parameters are controlled solely by hydrodynamics and interfacial phenomena whereas on earth they are masked by buoyant phenomena. It is found that the oil fraction evolution curves resulting from electrical measurements are compatible with a bidisperse oil droplet size distribution. The characteristic sizes of the two droplet modes are estimated using theoretical arguments. Both the electrically volume-based determined droplet sizes and the number-based ones from high resolution image analysis are discussed in detail.

Decentralized Retrofit Model Predictive Control of Inverter-Interfaced Small-Scale Microgrids

In recent years, small-scale microgrids have become popular in the power system industry because they provide an efficient electrical power generation platform to guarantee autonomy and independence from the power grid, which is a critical feature in cases of catastrophic events or remote areas. On the other hand, due to the short distances among multiple distribution generation systems in small-scale microgrids, the interconnection couplings among them increase significantly, which jeopardizes the stability of the entire system. Therefore, this work proposes a novel method to design decentralized robust controllers based on a retrofit model predictive control scheme to tackle the issue of instability due to the short distances among generation systems. In this approach, the retrofit model predictive controller receives the measured feedback signal from the interconnection current and generates a control command signal to limit the interconnection current to prevent instability. To design a retrofit controller, only the model of a robust closed-loop system, as well as an interconnection line, is required. The model predictive control signal is added in parallel to the control signal from the existing robust voltage source inverter controller. Simulation results demonstrate the superior performance of the proposed technique as compared with the virtual impedance and retrofit linear quadratic regulator techniques (benchmarks) with respect to peak-load demand, plug-and-play capability, nonlinear load, and inverter efficiency.

Open-source design of low-cost sensorised elastic actuators for collaborative prosthetics and orthotics

Collaborative robots, or cobots, have become popular due to their ability to safely operate alongside humans in shared environments. These robots use compliant actuators as a key design element to prevent damage during unintended collisions. In prosthetic and orthotic applications, compliant actuators are crucial for ensuring user safety and comfort. However, most compliant cobots for these applications are excessively expensive and complex to construct. Our study introduces an innovative, cost-effective, and sensorised elastic actuator design tailored for prosthetics and orthotics. The design uses a modular approach and leverages 3D printing technology for rapid customisation, enabling efficient and affordable fabrication. Both hardware and software components are open-source, facilitating unrestricted access for students, researchers, and practitioners. Our design supports impedance and admittance control techniques, enhancing the system’s capabilities. Validation results show a standard deviation of 9.67 Nm between calculated and measured torque in impedance control and 0.2563 radians between calculated and measured angles in admittance control. This allows for improved adaptability to varying operational requirements in prosthetics and orthotics. By introducing this educational framework encompassing a low-cost, sensorised elastic actuator design, we aim to address the need for accessible solutions in the field of collaborative robotics for prosthetics and orthotics.

Integrating PZT-based WP and EMI techniques with multi-criteria analysis for monitoring and assessment of mechanical properties of structural adhesives under curing

Structural adhesives are commonly employed as bonding agents in FRP strengthening systems. Measuring and assessing the mechanical properties of adhesives during the curing process is essential, as these properties directly influence the overall effectiveness of the strengthening system. This study investigated the development of mechanical properties in structural adhesives at various curing times using two PZT-based monitoring techniques, specifically wave propagation (WP) and electromechanical impedance (EMI) techniques. Two types of structural adhesives and two distinct curing temperatures (ambient temperature and mild temperature) were selected for examination. Throughout the adhesive curing process, both methods were utilized for monitoring. Subsequently, tensile tests were conducted to obtain the mechanical properties at different curing durations. The results demonstrate that monitoring indicators from both PZT-based techniques effectively captured the enhancement in adhesive performance during the curing process. Moreover, the tensile strength of the Sika and Carbon adhesives reached stability at ambient temperature after five and three days, respectively, while elevated temperatures accelerated the curing process. Furthermore, two Multi-Criteria Decision Making (MCDM) methods were employed to select monitoring indicators with the least deviation and the closest correlations with mechanical properties. These indicators have the potential to predict mechanical properties, potentially reducing the need for tensile tests.

Identification of structural parameters in a prestressed concrete beam under chloride-induced corrosion using embedded and smart-probe-based piezo sensors

In prestressed concrete (PSC) structures, corrosion in prestressing wire is one of the main problems affecting its service life. Therefore, structural health monitoring (SHM) is essential for performance evaluation and safety maintenance to prevent and reduce engineering accidents. In SHM, corrosion monitoring using the piezo sensor-based electro-mechanical impedance (EMI) technique has become a research hotspot. This paper presents the effectiveness of embedded and smart-probe-based piezo sensors (SPPS) for identifying structural parameters such as stiffness, mass, and damping in a prestressed concrete beam subjected to chloride-induced corrosion using electro-mechanical impedance (EMI) technique. The accelerated corrosion tests were conducted on a PSC beam in which SPPS was indirectly bonded, and an embedded piezo sensor (EPS) was attached to the prestressing wire inside the beam to monitor the variation in the EMI signature during the exposure of corrosion. Further, a physical model was developed in the form of spring, mass, and damper combinations to identify the deterioration in terms of structural parameters during exposure to corrosion. Based on the experimental results, it is found that EPS is effective in identifying the corrosion initiation phase, while SPPS is for the corrosion propagation and cracking phase. In terms of percentage loss, the identified stiffness loss from SPPS and EPS in the propagation phase of corrosion is about 61.56 % and 5 %, respectively.

Diagnosis and assessment of cyclic freeze–thaw damage in tunnel lining concrete using piezoelectric-based electromechanical impedance technique

Cold regional tunnel linings extensively suffer from severe cyclic freeze–thaw damage, which adversely influences their stability, durability and in-service safety. Consequently, the diagnosis and assessment of cyclic freeze–thaw damage in concrete linings have garnered worldwide attention. This study presents a pioneering effort in using the PZT-based electromechanical impedance (EMI) technique to monitor the evolving damage within lining concrete concurrently exposed to bending loads and freeze–thaw cycles. First of all, ultrasonic measurements and four-point bending tests were performed on cyclically freeze-thawed concrete specimens under two different bending loads. Both the degrading flexural strength and the diminishing ultrasonic wave velocity were measured. Particularly, the damage evolution was characterized by the flexural strength degradation ratio, which exponentially increased by 44.81% and 64.28% under two bending scenarios, respectively. Moreover, conductance signatures driven by two vibration modes (d31 and d33 modes) of embedded piezoelectric transducers were recorded, and both localized and overall variations in the signals were analyzed. It is concluded that both the resonant frequency shift and the statistic metric RMSD within the d31-dominated frequency range could accurately indicate the cyclic freeze–thaw damage of lining concrete. Their linear correlation coefficients with the damage variable reached 0.957 and 0.935, respectively. This research establishes a quantitative framework for monitoring the progressive damage of tunnel lining subjected to freeze–thaw cycling using the EMI technique and lays the groundwork for a broader range of future applications in structure damage diagnosis and assessment.