Variation Of Conductivity Research Articles

The Permeafor: A Rapid Tool for Field Hydraulic Conductivity Testing in Granular Soils

Abstract There are currently several in situ and laboratory methods of determining the hydraulic conductivity of soils. However, it remains difficult to obtain representative hydraulic conductivity profiles rapidly and economically, especially on projects in which values are required over large areas and at numerous depths. Furthermore, there is an emerging need in geotechnical and geoenvironmental engineering to profile this parameter in situ, such as for the design of water infiltration systems and retention ponds or for evaluation of contaminant fate and transport, which has resulted in a greater demand to improve existing methods or develop new, rapid, and reliable techniques. A proposed alternative to measure hydraulic conductivity in granular soils is to use a Permeafor, an instrument originally developed in France to evaluate variations in hydraulic conductivity in situ. This variation is assessed by observing water flow into the soil, at any given depth, under an applied hydraulic head. The ratio of flow to hydraulic head is used as an indicator of hydraulic conductivity variations with depth. A Permeafor system was designed, built, and field tested at several sites across New Hampshire. The results from more than 120 field tests at sites with granular soils demonstrated the potential of the Permeafor to rapidly generate profiles of hydraulic conductivity. The Permeafor is a useful tool in bridging the gap between time-consuming testing of few locations and large-scale hydraulic conductivity testing. This article introduces the Permeafor design, its supporting equipment, and control software and provides some examples of results obtained at a test site in New Hampshire.

New approach in the reuse of modified ground tire rubber as thermal and acoustic insulation to be used in civil engineering

The concern for the amount of end-of-life tires generated each year has arisen from constant research directed to their valorisation. Herein we propose a new material, which is constituted by GTR with a binder, as acoustic and also as a thermal insulator for civil engineering. The insulator can also include the fibre mat present in the tire, seldomly considered as a recyclable sub-product. To provide insight into the insulating behaviour of these materials, four mathematical models have been tested and compared with the experimental results of thermal conductivity. The Lewis-Nielsen modelization presented good accuracy with deviations of less than 3%. A statistical analysis has also been conducted on the experimental data showing that the parameter with more effect on thermal conductivity is thickness (differences up to 43%) being particle size, less important (ca 6%). In acoustic properties, different effects can be observed depending on the frequency range, being the density the most relevant. From the mathematical, statistical and experimental analysis can be deduced that good insulation properties would be achieved in materials with: low density, porous; including mat and thick. The effect of these parameters causes variations of thermal conductivity from 0.189 to 0.117 W/m·K and in sound absorption coefficient from 0.06 to 0.6.

The effect of in-situ metasomatism on the electrical resistivity of the lower crust

Improved estimates of composition and temperature in the lower crust are vital in characterising crustal rheology and better understanding tectonic processes. Fluids introduced into the lower crust during collisional events leave behind large domains of metasomatised crust which are long-lived and should be observable via magnetotelluric sounding. With this in mind, the electrical conductivity of a subduction-related eclogite and its anhydrous, anorthositic granulite protolith were experimentally determined at atmospheric pressure and lower crustal temperatures (773–1123 K). Complex impedance spectra were collected between 20 Hz and 2 MHz while oxygen fugacity was controlled about the quartz-fayalite-magnetite (QFM) buffer using a CO:CO2 gas mix. At <1000 K, both samples are characterised by impurity conduction with low observed activation enthalpies of 0.48 ± 0.03 eV and 0.39 ± 0.02 eV for the granulite and eclogite respectively. High temperature data from the granulite (>1000 K) indicates a switch to small polarons with an activation enthalpy of 1.02 ± 0.02 eV. Results indicate that conversion of Fe-poor mafic granulite to eclogite does not enhance conductivity at lower crustal temperatures. Comparisons with previous experiments reveal a much stronger relationship between conductivity and FeOT than previously anticipated. Modelling indicates that an increase in FeOT of 2 wt% is equivalent to a temperature increase of 100 K and reasonable variations in FeOT in the lower crust may account for ∼4 orders of magnitude variation in conductivity. Elevated FeOT up to 20 wt% may enhance conductivity to ∼100 S m−1 at a moderate 873 K. A system of linear equations is derived to estimate iron content, electrical conductivity or temperature within dry, mafic lower crust. For the temperature range 773–973 K, conductivity may be predicted to within 0.16 log units using log σ(T,FeOT) = 0.006 T + 0.3FeOT − 11.35. Under the same conditions, FeOT may be predicted to within 0.51 wt% using FeOT (T,σ) = 37–0.0193 T + 3.24 log σ. Finally, lower crustal temperatures may be estimated to within 24 K using T(FeOT,σ) = 1728 − 42FeOT + 139 log σ.

Understanding Polymer Structure and Conductivity in Composite Electrolytes

Lithium ion batteries are a crucial technologies for electric vehicles and portable electronics due to their high energy density. However, flammable liquid electrolytes create a safety concern and transitioning to all solid state batteries allows for the potential of higher energy density by utilizing lithium metal anodes. Two classes of solid materials have been explored to replace liquid electrolytes: ceramic and polymer electrolytes. Composite electrolytes, typically in the form of dispersed ceramic particles or nanowires in polymer matrix, combine these two materials to have good ionic conductivity while maintaining the mechanical properties of the polymer. While they have achieved fairly high conductivity (typically 10-4 S/cm), the mechanism for such ion conduction is not well understood.The polymer likely plays a crucial role as the ceramic volume fractions are typically under 20%.1,2 Four possible ways that polymers could increase in conductivity in the composite have been identified: decreased crystallinity, increased free volume, disruption of polymer alignment, and increased lithium ion dissolution due to acidic surface groups on the ceramic.1,3,4 We have developed thin film model systems to probe the interface of the polymer with and ceramic surfaces. We found that when confined to thin films, the conductivity of the polymer electrolyte increased compared to the bulk. We utilized differential scanning calorimetry to identify the crystallinity and found that the small crystallinity variation could not account for the variation in conductivity. Subsequently, we utilized surface conductivity and transference number measurements to understand the effects of acidic surface groups. X-ray Absorption measurements will be similarly utilized to probe the variation in lithium ion environments within these materials to understand any variation in the lithium salt dissolution. It was found that the variation in conductivity based on this effect is small.In order to probe the possible variation in free volume, Small Angle Neutron Scattering will be utilized to quantify the free volume within thin films, bulk polymer, and composite electrolytes. This can quantify the volume associated with each monomer and therefore how much space is between polymer chains for lithium ion movement.5 Lastly, while the polymer chain alignment has not been extensively discussed composite literature, it has been identified that when polymer electrolytes are cast on a surface, polymer electrolytes typically show anisotropy with measurements parallel to the surface having higher conductivity due to the alignment of the chain.6 Therefore, ceramic fillers in the composites may disrupt this packing and allow for higher conductivity perpendicular to the cast surface, the direction in which they are most commonly measured. In order to probe this effect, we measure the anisotropy of both our thin film electrolytes as well as composite electrolytes to compare the significance of the anisotropy and utilize small angle x-ray scattering to measure any anisotropy in the structure.

Structural Reliability Analysis of Large Planar Steam Solid Oxide Electrolysis Cells

Solid oxide electrolysis cells (SOEC) have been receiving significant attention recently because of their high energy efficiency and fast hydrogen production. In our previous study, a multi-physics modeling framework to simulate the SOEC performance and structural reliability of planar SOEC design was developed and demonstrated. The electrochemical reactions, fluid dynamics, species transport, electron transfer, and heat transfer were modeled in the commercial computational fluid dynamics (CFD) software STAR-CCM+. The thermomechanical analysis and the associated structural reliability evaluations were conducted using the commercial finite element analysis software ANSYS. The electrochemistry model was validated by using the experimentally obtained current-voltage (I-V) characteristics of the electrode-supported SOECs. In this study, this framework was applied on a large 300 cm2 steam planar SOEC design, and systematically studied the structural reliability under combinations of cell operating conditions, with cell voltage 1-1.5 V, steam fraction in fuel inlet 0.7-0.9, air inlet flow rate 0-10 L/min, fuel inlet flow rate 2.5-12.5 L/min, and inlet temperature 600-900 C. In the modeling framework, all the cells were investigated under the adiabatic thermal conditions, which is equivalent to packing the cell in an insulated container. This induced the relatively larger temperature variation than in the smaller cell designs. This cell internal temperature non-uniformity may further enhance the spatial variations of open circuit voltage, activation loss, and ionic conductivity in the cell, which all influence the overall cell performance. This situation is more obvious when the cell voltage is higher than 1.35V, under which the cell is significantly heated along the steam flow direction. Traditionally, it is assumed that the cell internal temperature spatial variation plays an important role on cell structural reliability. However, because it was assumed that all the components in cell are stress free at 850 , the cell temperature deviation from 850 is more critical to the stress distribution and structural reliability in the cell. For the investigated cells in the practical conditions, like 750 C inlet temperature and varying voltage from 1.05 to 1.5 V, the highest first principal stress is always in the air side electrode, which is around 45 MPa. This is explained by the higher coefficient of thermal expansion of LSCF-GDC with respect to the other layers. This may indicate that the failure would possibly occur in the air side electrode, but at low risk due to the relatively higher Weibull characteristic strength.

A novel model for viscoelastic fluid flow and heat near a stretchable plate using variable fluid properties: A computational study

This article is concerned with the boundary layer formations over a deforming plane heated surface in a viscoelastic fluid having temperature-dependent physical properties. Viscoelastic fluid obeys a well-accepted Jeffrey fluid model that characterizes both relaxation and retardation times phenomena. Mathematical modeling is performed by considering exponential variations in viscosity, thermal conductivity, relaxation time, and retardation time with temperature. Transport equations are formulated under the aforesaid assumption and are solved for self-similar solutions using a numerical scheme. Solutions are utilized to generate streamlines and isotherms in both Newtonian and viscoelastic fluids. The momentum and thermal layers are specifically scrutinized for various controlling parameters. Illustrative results are included reflecting the consequences of variable physical properties on the induced viscoelastic fluid motion and accompanying heat transfer. In addition, skin friction factor for Jeffrey fluid with variable properties is evaluated and described.

High temperature CO2 capture in lithium orthosilicate packed fluidized bed: Gamma ray densitometry based numerical model and its experimental validation

BackgroundLithium orthosilicate (Li4SiO4) is steadily emerging as the default solid sorbent for high temperature CO2 capture in industrial settings. Li4SiO4 is also one the few materials qualified to serve as both catalyst and sorbent in sorption enhanced steam reforming process for high purity carbon neutral H2 production. Application of packed fluidization technique to enhance CO2 uptake in packed bed of pure Li4SiO4 particles has not been reported until now. MethodsGamma ray densitometry (GRD) technique is employed to non-intrusively obtain average voidage of Li4SiO4 packed fluidized bed as a function of operating time and axial bed coordinate. Based on the experimental results of GRD technique, a numerical model is developed to obtain the transient cross-sectional profiles of internal bed temperature and gas phase CO2 concentration as high temperature carbonation of Li4SiO4 progresses in packed fluidized bed. The numerical model is validated using experimentally obtained internal bed temperature and breakthrough curves. Temporal variation of bed effective thermal conductivity has been evaluated from model temperature profiles. FindingsIt was observed that the time averaged effective thermal conductivity and net solid weight gain of packed fluidized bed is around 1.7–2.3 and 1.1–1.3 times that of unary packed bed respectively at specified process parameters for high temperature CO2 capture.

Groundwater-surface water interactions in a semi-arid irrigated agricultural valley: A hydrometric and tracer-aided approach

The purpose of this study was to assess hydrological controls (e.g., rainfall, irrigation practices, river discharge, dam operation, evaporation) on surface (SW)- ground water (GW) interactions in an irrigated valley within semi-arid Patagonia Argentina (−65.49 W, −43.29 S). We combined different sampling designs (watershed/sub-watershed scales, longitudinal and monthly samplings) from 2015 to 2019 to investigate the temporal and spatial variation of hydrometrics, electrical conductivity (EC) and stable isotope composition of surface and ground water. Results showed that plant transpiration in the upper basin, evaporation in the middle basin and the reservoir dynamics modified water salinity and left an imprint in stable isotopes. Water tables in the irrigated valley were high (0.5–2 m level from soil surface) and presented higher salinity than river water. Groundwater salinity, temporal variation of water table levels and stable isotopes suggested that groundwater is subjected to evaporation, is recharged from field seepage and, at a lesser extent, from local rainwater. River salinity increased downstream of the irrigated valley during the whole study period (3 years), showing the effects of agriculture and urbanization. EC also responded to the opening and closing of irrigation channels. EC and daily discharge statistical analysis revealed that groundwater recharge the stream below a threshold discharge of 26 m.s−1; with river salinity increasing linearly as daily discharge decrease. This study illustrates the deep modifications that agricultural systems, mainly surface irrigation, produce on semiarid watersheds. Given that SW and GW components are currently not isolated and flow regulation and irrigation practices are playing a critical role in soil quality and river chemistry at low flow conditions, a conjunctive water management strategy must be implemented in order to prevent further land and water quality degradation.

A new pre-conditioned STDP rule and its hardware implementation in neuromorphic crossbar array

This paper proposes a new pre-conditioned spike-timing-dependent plasticity (STDP) learning rule as well as an efficient system-level time-domain circuit modeling and simulation method for the whole crossbar array structure. First, the new pre-conditioned STDP rule is conceived by exercising a slight perturbation to the conventional STDP curve. Software-wise, it can be described in spiking neural network (SNN) codes, while hardware-wise, it is realized by the memristor crossbar array in conjunction with specific spike signals, just as the conventional STDP. The new STDP rule enables the neural network in a neuromorphic chip to achieve better performance both in terms of software and hardware implementation compared with the conventional STDP rule. Second, a time-domain circuit modeling method is proposed for the simulation of the whole crossbar array. Numerical experiments demonstrate that the new pre-conditioned STDP is superior to the conventional STDP both in terms of accuracy and low power consumption. At the software level, a 784 × 100 spiking neural network, trained by the pre-conditioned STDP, for the MNIST handwritten digit recognition achieves an accuracy of 85.90%, which is 3.09% higher than that trained by the conventional STDP. At the hardware level, a downscaled 196 × 10 crossbar array is simulated and trained. The crossbar array trained by the new STDP consumes 21.5% less power than that trained by the conventional STDP. Moreover, it does not compromise the original robustness when subject to non-ideal characteristics such as variation of conductance and resistance of the interconnect in the crossbar array.

Nanoscale Si fishbone structures for manipulating heat transport using phononic resonators for thermoelectric applications

Thermoelectric materials have the potential to convert waste heat into electricity, but their thermoelectric efficiency must be improved before they are effective and economically viable. One promising route to improving thermoelectric efficiency in thin-film thermoelectric materials is to reduce the material’s thermal conductivity through nanopatterning the surface. In this work nanoscale phononic resonators are introduced to the surface, and their potential to reduce thermal conductivity is explored via coupled experimental and theoretical techniques. Atomistic modelling is used to predict the dependence of the thermal conductivity on different design parameters and used to guide the design and fabrication of silicon fishbone nanostructures. The nanostructure design incorporates a variation on design parameters such as barb length, width and spacing along the shaft length to enable correlation with changes in thermal conductivity. The thermal characteristics of the nanostructures are investigated experimentally using the spatial resolution of scanning thermal microscopy to correlate changes in thermal conductivity with the changes in the structure parameters. The method developed uses a microheater to establish a temperature gradient along the structure which will be affected by any local variations in thermal conductivity. The impact on the thermal gradient and consequently on the tip temperature is modelled using finite element computer simulations. Experimental changes as small as 7.5% are shown to be detectable in this way. Despite the experimental technique being shown to be able to detect thermal changes far smaller than those predicted by the modelling, no modifications of the thermal conductivity are detected. It is concluded that in order to realise the effects of phononic resonators to reduce thermal conductivity, that much smaller structures with a greater ratio of resonator to shaft will be needed.

Spatiotemporal variations of sand hydraulic conductivity by microbial application methods

The spatiotemporal distributions of microbes in soil by different methods could affect the efficacy of the microbes to reduce the soil hydraulic conductivity. In this study, the specimens of bio-mediated sands were prepared using three different methods, i.e. injecting, mixing, and pouring a given microbial solution onto compacted sand specimens. The hydraulic conductivity was measured by constant-head tests, while any soil microstructural changes due to addition of the microbes were observed by scanning electron microscope (SEM) and mercury intrusion porosimetry (MIP) tests. The amount of dextran concentration produced by microbes in each type of specimen was quantified by a refractometer. Results show that dextran production increased exponentially after 5–7 d of microbial settling with the supply of culture medium. The injection and mixing methods resulted in a similar amount and uniform distribution of dextran in the specimens. The pouring method, however, produced a nonuniform distribution, with a higher concentration near the specimen surface. As the supply of culture medium discontinued, the dextran content near the surface produced by the pouring method decreased dramatically due to high competition for nutrients with foreign colonies. Average dextran concentration was negatively and correlated with hydraulic conductivity of bio-mediated soils exponentially, due to the clogging of large soil pores by dextran. The hydraulic conductivity of the injection and mixing cases did not change significantly when the supply of culture medium was absent.

Two-phase modeling of fluid injection inside subcutaneous layer of skin

The motivation of this present theoretical investigation comes from the delivery of various drugs and vaccines through subcutaneous injection (SCI) to the human body. In the SCI procedure, a medical person takes a big pinch of skin of the injection applicable area of a patient to pull the subcutaneous layer (SCL) from the underlying muscle layer to smooth the execution of the procedure. Generally, the human skin, particularly SCL, is a heterogeneous and anisotropic living material. The major constituents of the SCL are adipose cells or fat cells and interstitial fluid. These adipose cells are oriented in such a way that the hydraulic conductivity of the SCL exhibits anisotropy. Consequently, one can adopt the field equations of mixture theory to describe the continuum nature of SCL. This mathematical modeling involves a perturbation technique where the small aspect ratio of the SCL provides a valid perturb parameter. This study highlights the issue of the mechanical response of the adipose tissue in terms of the anisotropic hydraulic conductivity variation, the viscosity of the injected drug, the mean depth of subcutaneous tissue, etc. In particular, the computed stress fields can measure the intensity of pain experienced by a patient after this procedure. Also, this study discusses the biomechanical impact of the creation of one or more eddy structure(s) due to the high pressure developed, increased tissue anisotropy, fluid viscosity, etc., within the area of applying injection.

Exploring reservoir computing: Implementation via double stochastic nanowire networks

Neuromorphic computing, inspired by the human brain, uses memristor devices for complex tasks. Recent studies show that self-organizing random nanowires can implement neuromorphic information processing, enabling data analysis. This paper presents a model based on these nanowire networks, with an improved conductance variation profile. We suggest using these networks for temporal information processing via a reservoir computing scheme and propose an efficient data encoding method using voltage pulses. The nanowire network layer generates dynamic behaviors for pulse voltages, allowing time series prediction analysis. Our experiment uses a double stochastic nanowire network architecture for processing multiple input signals, outperforming traditional reservoir computing in terms of fewer nodes, enriched dynamics and improved prediction accuracy. Experimental results confirm the high accuracy of this architecture on multiple real-time series datasets, making neuromorphic nanowire networks promising for physical implementation of reservoir computing.

Remarkable Thermal Conductivity Reduction of Silicon Nanowires during the Bending Process.

The one-dimensional geometry of silicon nanowire helps to overcome the rigid and brittle nature of bulk silicon and enables it to withstand substantial bending stresses. This provides exciting opportunities for the development of flexible electronics. The bending strain introduces atomic displacement in the lattice structure, which inherently has a significant impact on the thermal conductivity. The strain-dependent thermal conductivity of silicon nanowire is crucial to the thermal management and performance of flexible electronic devices. However, in situ thermal conductivity measurement of bending silicon nanowires remains challenging and unreported due to the varying thermal contact resistances between the sample and sensor/heat sink. In this study, the Raman spectroscopy-assisted steady state thermal conductivity measurement method is coupled with a micromanipulation system to successively monitor the thermal conductivity variation of silicon nanowires during the bending process. The result shows that the thermal conductivity of silicon nanowires steeply decreases 55-78% owing to the strain-induced structural deformation during bending. Furthermore, the proposed in situ thermal conductivity measurement method can also be extended to other nanomaterials.

Structural Determinants of Redox Conduction Favor Robustness over Tunability in Microbial Cytochrome Nanowires.

Structural determinants of a 103-fold variation in electrical conductivity for helical homopolymers of tetra-, hexa-, and octa-heme cytochromes (named Omc- E, S, and Z, respectively) from Geobacter sulfurreducens are investigated with the Pathways model for electron tunneling, classical molecular dynamics, and hybrid quantum/classical molecular mechanics. Thermally averaged electronic couplings for through-space heme-to-heme electron transfer in the "nanowires" computed with density functional theory are ≤0.015 eV. Pathways analyses also indicate that couplings match within a factor of 5 for all "nanowires", but some alternative tunneling routes are found involving covalent protein backbone bonds (Omc- S and Z) or propionic acid-ligating His H-bonds on adjacent hemes (OmcZ). Reorganization energies computed from electrostatic vertical energy gaps or a version of the Marcus continuum expression parameterized on the total (donor + acceptor) solvent-accessible surface area typically agree within 20% and fall within the range 0.48-0.98 eV. Reaction free energies in all three "nanowires" are ≤|0.28| eV, even though Coulombic interactions primarily tune the site redox energies by 0.7-1.2 eV. Given the conserved energetic parameters, redox conductivity differs by < 103-fold among the cytochrome "nanowires". Redox currents do not exceed 3.0 × 10-3 pA at a physiologically relevant 0.1 V bias, with the slowest electron transfers being on a (μs) timescale much faster than typical (ms) enzymatic turnovers. Thus, the "nanowires" are proposed to be functionally robust to variations in structure that provide a habitat-customized protein interface. The 30 pA to 30 nA variation in conductivity previously reported from atomic force microscopy experiments is not intrinsic to the structures and/or does not result from the physiologically relevant redox conduction mechanism.

A Review of Physicochemical Stabilization for Improved Engineering Properties of Clays

Severe climatic and environmental conditions warrant the use of stabilization agents in aid of compaction for sustainable improvement in engineering properties of clays. Physicochemical agents are a viable option because they are cost effective, environmentally friendly, and offer improved long-term performance of treated soils. This research developed a fundamental understanding of the clay–water–electrolyte admixtures relations. Based on a comprehensive literature review, the effect of nanomaterials, biopolymers, and geopolymers on the behavior of compacted clays was investigated. It was found that all of these admixtures facilitate the development of an aggregated soil microstructure through unique mechanisms. Biopolymers have the highest water adsorption capacity followed by geopolymers and then by nanomaterials. The effect of admixtures on optimum compaction properties follows a decreasing trend similar to untreated clays (S = 80% ± 20%). The variation of hydraulic conductivity, compression index, and compressive strength are largely within the family of curves identified by typical relationships for compacted clays. These preliminary findings indicate that not all engineering properties are improved to the same level by the different types of physicochemical admixtures. The specific nature of geotechnical engineering (soil type and site conditions) as well as the wide range of admixture types and potential biodegradation of some of the reagents are the major shortcoming of using this class of materials.

ELECTROCHEMICAL EVALUATION OF HUMIDITY BASED PROTON CONDUCTIVITY OF ALUMINIUM(III) TARTRATE

Aluminium(III) tartrate was synthesized by simple solution crystallization and its humidity dependent proton conductivity was evaluated using electrochemical impedance spectroscopy. The compound exhibited very low DC conductivity and AC conductivity in the as synthesized form and dried conditions. However, upon exposing to 100% relative humidity(RH) the AC conductivity of the compound increased significantly with time and is several orders greater than DC conductivity. The structural stability of the compound was analysed by FTIR and PXRD experiments. The compound has good structural stability on hydration, dehydration and rehydration. The proton conductivity of the sample decreased several orders on dehydration and it bounces back to original value on rehydration. The complex exhibited reversible proton conductivity with respect to moisture. The variation of proton conductivity with temperature implies that the compound exhibits Grotthuss type proton conductivity.

Investigation of pressure dependence of anisotropy and elastic modulus of SbSI compound in ferroelectric phase by Ab initio method

The lattice constant of FE SbSI and the positions of the atoms were determined by geometric optimization at different pressures using Quantum Espresso (QE) software. Elastic constants were calculated for different pressure. Using these calculated elastic constants, bulk modulus, Young’s modulus, shear modulus, Poisson ratio, anisotropic factor, acoustic velocity, compressibility, Debye temperature, Grüneisen constant and variation of minimum thermal conductivity with pressure were investigated. In addition, the mechanical stability, ductility/brittle nature and Vicker hardness of the material were evaluated. Its anisotropy was examined in detail. Phase transition pressure was determined theoretically. The obtained results were compared with existing literature data.

Motion Artifact Reduction Algorithm for Wearable Electrocardiogram Monitoring Systems

An electrocardiogram (ECG) test is usually performed through measurement with Ag/AgCl electrodes. However, this method has disadvantages, such as skin irritation, short shelf life, and conductance variation in gels over time, which limit the usability for long-term monitoring. One of the alternatives is adopting conductive fabric-based electrodes, but this method involves a problem in which a motion artifact (MA) becomes more severe because no gel and adhesive are available to provide a stable interface between the electrodes and the skin. To address this problem, this study presents a conductive fabric-based ECG monitoring system and an MA reduction algorithm. The system can simultaneously measure the ECG and the electrode-tissue impedance (ETI) with the proposed shirt. The MA reduction algorithm aims to reduce MA with ETI information. The MAs in Lead I, II, and III ECG measurement are generated by lifting arms, walking, and jogging. Results of the MA reduction are quantified by the correlation coefficient (CORR) and mean squared error (MSE). The quantitative analysis shows that the MA can be suppressed by the proposed algorithm. Moreover, compared with a reproduced existing approach, the proposed algorithm performs better in most cases.

Gas Bubble Evolution during ECM Process can be suppressed by Pulse Parameters: High Speed Videographic Observations during Early Stages of Bubble Evolution

The precision in electrochemical machining (ECM) is adversely affected by the generation of gas bubbles due to the inherent electrochemical reactions occurring at the cathode (tool) and anode (workpiece) surface. These gas bubbles are known to cause variations in electrolyte conductivity and lead to uneven dissolution and limit the achievable flatness and surface finish. The demands for precision ECM make it important to investigate the bubble evolution phenomenon. In the prior state of the art, this has been done by means of transparent electrodes and high-speed video observations. The current work involves high-speed video experiments with a specific intention to observe gas bubbles during the early stages of evolution and attempts to address two main research questions: (i) Is it possible to suppress gas bubble evolution in ECM using pulse parameters? (ii) Is it possible to do ECM without gas bubbles? The results reveal that shorter pulse-on times and longer pulse-off times reduce the growth of the concentration boundary layer, thereby suppressing bubble generation. Furthermore, by combining the aforementioned electrical pulse settings with an appropriate flow rate, there is no significant detection of gas bubbles in the experiments conducted here, as can be concluded from the fact that the interelectrode gap (IEG) remains transparent. The industrial applicability-oriented analysis focused on evaluating the final IEG and did not reveal any significant difference due to shorter flow lengths. It is further suggested that by employing high flow rates in combination with shorter pulse-on times, the pulse-off time can be further shortened to raise duty cycles so as to facilitate economic machining without the influence of gas bubbles.