Conductivity Data Research Articles

Imatinib cation based MOIFs with [Fe(CN)5NO]2−, [Fe(CN)6]3− [Fe(CN)6]4− as adsorbent of organic pollutants, and their protein interaction study

Inorganic-organic hybrid (IOH) compounds are being widely used in the design of multifunctional materials owing to their rich properties and flexible assembly. Here, we report three metal organic ionic frameworks (MOIFs)/ IOH, for the adsorption of toxic organic pollutants and Bovine Serum Albumin (BSA) interaction, synthesized via simple ion-exchange mechanism in water using Na2[Fe(CN)5NO], K3[Fe(CN)6], K4[Fe(CN)6] and 4-[(4-methylpiperazin-1-yl)methyl]-N-(4-methyl-3-{[4-(pyridin-3-yl)pyrimidin-2yl]amino}phenyl) mesylate (ImM). These were characterized through powder XRD, NMR, UV/ Vis and FTIR techniques for their structural elucidation. The thermal gravimetric analysis (TGA) revealed their two transitions due to loss of water and organic compound. Additionally, the band gap was found in the range of 3.2 to 3.3 eV, inferred their applicability in the field of semiconductors. MOIFs have shown the adsorption of toxic pollutants (Organic dyes) investigated through thermal kinetics and activation parameters which inferred about the interaction between organic dyes and MOIFs as characteristics for the adsorption system. Adsorption has also been analyzed through conductivity data where according to Ostwald's dilution law for weak electrolytes was applied. For knowing medicinal aspects, MOIFs have also been tested for BSA binding activity analyzed with UV–Vis, fluorescence and docking studies, which showed good quenching efficacy as well as interaction ability.

Critical Review of Transport Properties of HCl, KOH, and NaOH in High Temperature Water and Correlations for Transport Properties of H3O+ and OH−

High-temperature tracer diffusion coefficients for H3O+ and OH− are important parameters in the modeling of diffusion-controlled reaction kinetics and mass transport processes under hydrothermal conditions, and these tracer diffusion coefficients are directly related to the ionic electrical conductivities in the limit of infinite dilution through the Nernst–Einstein relationship. The limiting conductivity of H3O+ and OH− in water is controlled by two separate mechanisms of ionic movement: (i) the bulk ionic diffusion and (ii) proton hopping, also known as “Grotthuss” mechanism and/or “prototropic transfer.” This work reports a critical assessment of the limiting electrical conductivity data (Λ°) for aqueous HCl, KOH, and NaOH measured above room temperature. The initial assessed dataset included temperatures from 273.15 K up to 873.15 K and water densities from 1000 kg m−3 down to 270 kg m−3 and was reduced down to a final critically evaluated dataset spanning temperatures between 273.15 and 678.15 K and densities between 346 and 1006 kg m−3. The results were used to derive values for the excess conductivity due to prototropic transfer, λE°, of H3O+ and OH− using correlations previously reported for aqueous KCl. Simple empirical correlations of water viscosity and density were derived for Λ°(HCl), Λ°(KOH), Λ°(NaOH), λE°(H3O+), and λE°(OH−). Tests using the λE°(OH−) correlation and a previously reported function for Λ°(NaCl) show that the NaOH data can be accurately reproduced to within the estimated uncertainties. The reported correlations provide a means to model more accurately the tracer diffusion coefficients for H3O+ and OH− to supercritical conditions.

Weibull distribution models for describing soil hydraulic properties over the entire matric suction range

Accurate descriptions of soil hydraulic properties over the entire matric suction range require the consideration of both capillary and noncapillary processes. This study extended the Weibull distribution models of hydraulic properties to complete dryness by the modular frameworks of Peters-Durner-Iden (PDI) and Brunswick (BW). Model-data comparison results showed that the original Weibull distribution models, accounting solely for capillary phenomena, provided inadequate descriptions of measurements in the dry range of water retention curve and hydraulic conductivity curve. The improved models of PDI and BW, accounting for both capillary and noncapillary processes, effectively described the hydraulic properties data from saturation to complete dryness, although the BW model violated the linearity requirement for water retention in dry soils with wide pore-size distributions. The PDI model overall performed better than the BW model in terms of their capability to fit the retention data and predict the conductivity data. Adopting the physically-based approach developed recently, the improved PDI and BW models can reliably predict the hydraulic conductivity along the complete matric suction range from water retention only, without use of fitted conductivity parameters. Thus, the improved PDI and BW models are applicable to cases where measured conductivity data (particularly noncapillary-dominated range) are not available.

Deep Learning Approaches for Numerical Modeling and Historical Reconstruction of Water Quality Parameters in Lower Seine

Water quality monitoring is essential for managing water resources and ensuring human and environmental health. However, obtaining reliable data can be challenging and costly, especially in complex systems such as estuaries. To address this problem, we propose a novel deep learning-based approach that uses limited available data to accurately estimate and reconstruct critical water quality variables, such as electrical conductivity, dissolved oxygen, and turbidity. Our approach included two tasks, numerical modeling and historical reconstruction, and was applied to the Seine River in the Normandy region of France at four quality stations. In the first task, we evaluated four deep learning approaches (GRU, BiLSTM, BiLSTM-Attention, and CNN-BiLSTM-Attention) to numerically simulate each variable for each station under different input data selection scenarios. We found that incorporating the quality data with the water level data collected at the various stations into the input data improved the accuracy of the water quality data simulation. Combining water levels from multiple stations reliably reproduced electrical conductivity, especially at stations near the sea where tidal fluctuations control saltwater intrusion in the area. While each model had its strengths, the CNN-BiLSTM-Attention model performed best in complex tasks with dissimilar input trends, and the GRU model outperformed other models in simple monitoring tasks with similar input-target trends. The second task involved automatically searching the optimal configurations for completing the missing historical data in sequential order using the modeling task results. The electrical conductivity data were filled before the dissolved oxygen data, which were in turn more reliable than the turbidity simulation. The deep learning models accurately reconstructed 15 years of water quality data using only six and a half years of modeling data. Overall, this research demonstrates the potential of deep learning approaches with their limitations and discusses the best configurations to improve water quality monitoring and reconstruction.

Defect Chemistry and Mixed Conduction in Lithium Lanthanum Titanate During the Transition from Electrolyte to Anode Material

Lithium lanthanum titanate Li0.29+δ La0.57TiO3 (LLTO) is a promising material in Li ion battery application, due to its ambient stability and high ionic conductivity. When it is subjected to a high Li chemical potential, additional Li ions intercalate into vacant A sites, which is balanced by the reduction of Ti4+ ions to Ti3+. At this point, LLTO becomes a mixed ion and electron conductor, which means that it undergoes a transition from an electrolyte to a high rate capable electrode material in the potential range below ca 1.7 V vs Li metal. However, the exact voltage of the transition from electrolyte to the electrode, as well as the electronic conductivity of reduced LLTO were still unknown. Here, we investigate the thermodynamics of lithium insertion as well as ion and electron conductivity of reduced LLTO by employing a galvanostatic intermittent titration technique (GITT) and electrochemical impedance spectroscopy (EIS). We can show that LLTO gradually changes from electrolyte material to a mixed conductor, with an ion transference number that depends on the Li chemical potential. Lastly, we present a defect chemical model that fits excellently to the U(δ) curves and the conductivity data.

Developing an Open-Source IoT Platform for Optimal Irrigation Scheduling and Decision-Making: Implementation at Olive Grove Parcels

Climate change has reduced the availability of good quality water for agriculture, while favoring the proliferation of harmful insects, especially in Mediterranean areas. Deploying IoT-based systems can help optimize water-use efficiency in agriculture and address problems caused by extreme weather events. This work presents an IoT-based monitoring system for obtaining soil moisture, soil electrical conductivity, soil temperature and meteorological data useful in irrigation management and pest control. The proposed system was implemented and evaluated for olive parcels located both at coastal and inland areas of the eastern part of Crete; these areas face severe issues with water availability and saltwater intrusion (coastal region). The system includes the monitoring of soil moisture and atmospheric sensors, with the aim of providing information to farmers for decision-making and at the future implementation of an automated irrigation system, optimizing the use of water resources. Data acquisition was performed through smart sensors connected to a microcontroller. Data were received at a portal and made available on the cloud, being monitored in real-time through an open-source IoT platform. An e-mail alert was sent to the farmers when soil moisture was lower than a threshold value specific to the soil type or when climatic conditions favored the development of the olive fruit fly. One of the main advantages of the proposed decision-making system is a low-cost IoT solution, as it is based on open-source software and the hardware on edge devices consists of widespread economic modules. The reliability of the IoT-based monitoring system has been tested and could be used as a support service tool offering an efficient irrigation and pest control service.

Effect of DC bias on dipolar response of yttrium iron garnet

Yttrium iron garnet (YIG) is a prominent magnetic (ferrimagnetic) insulator and an excellent material for wide ranging microwave and millimeter-wave applications. In polycrystalline form it exhibits high dielectric loss due to contributions coming from grain & grain boundaries, and Fe heterovalency. We have investigated the effect of dc bias voltage on the dielectric properties of YIG in a wide range of temperature (100 - 600 K) and frequencies (100 Hz - 1 MHz). Consistent with previous observations, without bias a dominant frequency dispersion due to hopping of the Fe2＋ & Fe3＋ is observed in low temperature region and a wider frequency dispersion is observed at higher temperatures arising due to grain-grain boundary contributions. Application of a small dc bias voltage increases the dielectric constant and reduces the dielectric loss significantly at higher frequencies. The DC bias-induced improvements are much more dramatic at higher temperatures, where grain boundary contributions dominate. Our detailed analysis of dc and ac conductivity data show that the dc bias suppresses the grain boundary contributions significantly and at the same time it boosts the polarizability due to the Fe2＋/Fe3＋ hopping.

Inelastic Neutron Scattering Study of Phonon Dispersion Relation in Higher Manganese Silicides

We report inelastic neutron scattering (INS) measurements of the phonon dispersion relation in higher manganese silicides (HMSs). A large ingot of HMS is synthesized using a slow cooling method, which is found to have Mn15Si26 as the primary phase. The sample is composed of highly oriented crystallites as confirmed by a neutron pole-figure study and thermal conductivity data. Our INS results are mostly consistent with earlier experimental and theoretical phonon studies in HMS, including the presence of a low-lying twisting mode. However, some discrepancies are also observed. Most notably, a 5 meV gap at the zone center and the softer dispersion relation of the low-lying twisting mode. We discuss the potential origins of these observations and their implications for the thermal properties of HMS.

Examining ionicity and conductivity in poly(methyl methacrylate) containing imidazolium-based ionic liquids

Ionic liquid (IL) interactions with amorphous polymers or polyelectrolytes attract interests due to their propensity to form ionogels with enhanced viscosity and reduced ionic conductivity when compared to their neat IL. A good understanding on the interactions between polymer and IL is needed to design better IL-based hybrid electrolytes. This study examines the mixtures of IL-polymer electrolytes with relatively low polymer concentration to improve their conductivity. Ion transport properties of three types of imidazolium-based ionic liquids are investigated with the addition of linear poly(methyl methacrylate) (PMMA) homopolymer. Dielectric properties of PMMA/IL mixtures indicated the enhancement of apparent ionicity of ILs, which is attributed to the preferential interactions between PMMA and bis(trifluoromethylsulfonyl)imide (TFSI-) anions. The frequency-dependent conductivity data analyzed by the Jonscher universal power law infer that ion–dipole coupling interactions between PMMA and IL help in the solvation and enhance the ionicity by disrupting the cage structure and facilitating the fast ion motions of IL.

Preparation, spectroscopic analysis, and biological assessment of heteroleptic Zr(II) and Pd(II) complexes from Otc/Sal mixed ligands

The two new novel heteroleptic complexes of the type [M(II)L1.L2] (M= Zr(II) & Pd(II), L1= oxytetracycline (Otc), and L2=salicylaldehyde (Sal)) have been synthesized and analyzed by physical measurements such as CHN, pH, and conductivity. The conductivity data revealed the electrolytic nature of Pd(II)Otc/Sal and the non-electrolytic nature of the Zr(II)Otc/Sal metal complex of mixed ligand. The structural characterizations of the metal complex were approved by spectroscopic analysis methods, such as IR, 1H & 13C-NMR, UV/ Visible, and ESI-MS studies. Thermal analysis (TGA/DTA) determines the thermal and kinetic stabilities of the metal complexes using a popular Coats-Redfern equation through which the activation parameters can be calculated easily. SEM can determine the surface morphology of metal complexes. The selected bond lengths, bond angles, final optimized energy, and geometry of complexes were obtained by running an optimization task in the 3D molecular modeling software program via Chem 3D Pro. 12.0.2. The final geometrical energy was found to be 921.7712 for Zr(II)Otc/Sal and 914.6006 Kcal/mol for Pd(II)Otc/Sal complexes. Based on the above study, Zr(II)Otc/Sal complex has tetrahedral geometry and the Pd(II)Otc/Sal complex has square planar geometry. The complexes were tested in vitro for antibacterial susceptibility study against various strains of clinical pathogenic bacteria such as Staphylococcus aureus (Gram-positive), Proteus mirabilis, and Escherichia coli (Gram-negative). For the antibacterial study, the Kirby-Bauer paper disc diffusion technique is applied by using 50, 25, and 12.5 μg/μL concentrations of the metal complex. Good antibacterial sensitivity was found against all tested pathogens in all synthesized complexes.

Experimental investigation of nanofluids for heat pipes used in solar photovoltaic panels

The current study is aimed to measure and analyze the impact of temperature (10°C < T < 90°C) and particle concentration (0.05% < ϕ < 1.5%) on thermo-physical properties of TiO2, ZnO and CuO nanoparticles suspended in Therminol-55. The nanoparticles were characterized by using various techniques, including TEM, XRD, FTIR, TGA/DSC. TEM images reveal that the morphology of TiO2 and ZnO as spherical nanoparticles whereas that of CuO is in the form of flakes. XRD pattern for TiO2, ZnO and CuO nanoparticles possess anatase, heaxagonal and monoclinic phase respectively. TGA results show that that TiO2 losses less mass than the ZnO and CuO nanoparticles at each stage of decomposition. Thereby making it more stable thermally as compared to the other samples. Two-step method has been employed to formulate stable Therminol-55 based nanofluids containing TiO2, ZnO and CuO nanoparticles for varying particle concentrations. Results show that the thermal conductivity of suspensions containing solid conducting particles increase with increasing nanoparticle content and temperature of dispersions in the fluid. The thermal conductivity of TiO2/Therminol-55, ZnO/Therminol-55 and CuO/Therminol-55 nanofluids increases up to 17.62%, 21.55% and 24.32% at particle concentration of 1.5 wt%. Further, the experimental results demonstrate that the density of nanofluids increased significantly with increase in concentration and decreased with temperature. Surface tension of nanofluids shows decrease with increase in particle concentration. This indicates that adding nanoparticles improve thermo-physical properties of nanofluid, making it suitable for use in heat pipe. The measured data for thermal conductivity and density are compared with existing theoretical models of nanofluids to check the effectivity of conventional models. A multi-variable new generalized correlations for thermal conductivity and density of Therminol-55 based nanofluids containing TiO 2, ZnO and CuO nanoparticles are proposed.

Prediction of the absolute hydraulic conductivity function from soil water retention data

Abstract. For modeling flow and transport processes in the soil–plant–atmosphere system, knowledge of the unsaturated hydraulic properties in functional form is mandatory. While much data are available for the water retention function, the hydraulic conductivity function often needs to be predicted. The classical approach is to predict the relative conductivity from the retention function and scale it with the measured saturated conductivity, Ks. In this paper we highlight the shortcomings of this approach, namely, that measured Ks values are often highly uncertain and biased, resulting in poor predictions of the unsaturated conductivity function. We propose to reformulate the unsaturated hydraulic conductivity function by replacing the soil-specific Ks as a scaling factor with a generally applicable effective saturated tortuosity parameter τs and predicting total conductivity using only the water retention curve. Using four different unimodal expressions for the water retention curve, a soil-independent general value for τs was derived by fitting the new formulation to 12 data sets containing the relevant information. τs was found to be approximately 0.1. Testing of the new prediction scheme with independent data showed a mean error between the fully predicted conductivity functions and measured data of less than half an order of magnitude. The new scheme can be used when insufficient or no conductivity data are available. The model also helps to predict the saturated conductivity of the soil matrix alone and thus to distinguish between the macropore conductivity and the soil matrix conductivity.

An improvement in drainage flow equation of EPA SWMM green roof module.

Green roofs are among the important green infrastructures which decrease the negative impacts of urbanization. In this study, the green roof modeling capability of U.S. Environmental Protection Agency Storm Water Management Model (EPA SWMM) is evaluated and the modeling methods used in EPA SWMM, which need improvements, are determined. In particular, the drainage flow, which is originally calculated with Manning's equation in SWMM, is improved by introducing the drainage mat void thickness and adapting a new value for the exponential coefficient of depth in the equation. In addition, the capability of the percolation equation is further investigated, i.e., the value of the coefficient of the exponential function of soil moisture content that considers the percolation through the soil layer is determined for different substrates using the existing unsaturated hydraulic conductivity and soil moisture content data from steady-state tests. A comparison of the improved equation of drainage flow results with the existing experimental data shows that the improved equation represents the drainage flow more accurately than the one used in EPA SWMM.

Relation between Viscosity and Conductivity of CaO-MgO-FeO-Al2O3-SiO2 System for Copper Smelting Slags

The viscosity and conductivity of the smelting slag of copper oxide concentrate are important for reducing the operating temperature. In this study, seven slag samples were prepared by the reductive smelting of copper oxide concentrate with different ferrous oxide contents. The viscosity and conductivity data of these CaO-MgO-FeO-Al2O3-SiO2 samples were measured in the temperature range of 1290~1410 °C. Based on the structural features of aluminosilicate melts, the change and dependency relationships of their viscosity and conductivity were analyzed. The results show that there is a strong tendency to form orthosilicate even when the slag composition is acidic. The formation of fayalite would allow more Al3+ to form pyroxene with the six-coordinated structure. As a result, the polymerization degree and viscosity of the melt will be reduced. The [AlO]45− as a network former will reduce the bonding strength of the structural units, thus reducing the slag viscosity at high temperature. In the experimental range, the logarithm of viscosity of each slag sample has a good linear relationship with its logarithm of conductivity. However, there is no uniform linear equation for these complex slags with wide composition variations. These results have potential guiding significance for the copper smelting process.

Mechanochemical Synthesis and Fluoride Ion Conductivity Studies in SrSnF4 Polymorphs

Investigations on SnF2-based solid electrolytes are gaining significant scientific attention because of their promising applications as solid electrolytes for all-solid-state fluoride ion batteries (FIBs) operating at room temperature. FIBs are potential alternatives for expensive Li-ion batteries with toxic and flammable liquid electrolytes. SrSnF4 belongs to the MSnF4 (M: Pb, Ba, and Sr)-type materials exhibiting a layered structure. Here, we present the structural and transport characteristics of two polymorphs of SrSnF4 using X-ray diffraction and impedance spectroscopy techniques. SrSnF4 crystallizing in a cubic fluorite structure is obtained just by mechanical milling the powder samples of SrF2 and SnF2 taken in a 1:1 ratio for 10 h, whereas annealing the milled powder at 623 K in the N2 atmosphere transforms SrSnF4 from its cubic phase to the stable tetragonal structure. The structural details of both the cubic and tetragonal SrSnF4 have been obtained by performing the Rietveld refinement. The resultant phase change after soft annealing enhances the room-temperature conductivity value from 2.05 × 10–6 S/cm for the cubic phase to 1.16 × 10–5 S/cm for the tetragonal phase. The transport number measurement by the dc polarization technique with the cell of configuration Ag/SrSnF4/Ag reveals that the conductivity is due to the ions. The frequency response of conductivity data is analyzed using the Almond–West formalism to find their hopping frequency and mobile carrier concentration factor at different temperatures. The scaling of the frequency-dependent conductivity spectra shows that the relaxation behavior of the mobile ions is temperature independent.

Quinoid-Based Three-Dimensional Metal–Organic Framework Fe2(dhbq)3: Porosity, Electrical Conductivity, and Solid-State Redox Properties

We report the synthesis, characterization, and electronic properties of the quinoid-based three-dimensional metal-organic framework [Fe2(dhbq)3]. The MOF was synthesized without using cations as a template, unlike other reported X2dhbq3-based coordination polymers, and the crystal structure was determined by using single-crystal X-ray diffraction. The crystal structure was entirely different from the other reported [Fe2(X2dhbq3)]2-; three independent 3D polymers were interpenetrated to give the overall structure. The absence of cations led to a microporous structure, investigated by N2 adsorption isotherms. Temperature dependence of electrical conductivity data revealed that it exhibited a relatively high electrical conductivity of 1.2 × 10-2 S cm-1 (Ea = 212 meV) due to extended d-π conjugation in a three-dimensional network. Thermoelectromotive force measurement revealed that it is an n-type semiconductor with electrons as the majority of charge carriers. Structural characterization and spectroscopic analyses, including SXRD, Mössbauer, UV-vis-NIR, IR, and XANES measurements, evidenced the occurrence of no mixed valency based on the metal and the ligand. [Fe2(dhbq)3] upon incorporating as a cathode material for lithium-ion batteries engendered an initial discharge capacity of 322 mAh/g.

Mixed ionic-electronic transport in Na2O doped glassy electrolytes: Promising candidate for new generation sodium ion battery electrolytes

In the present communication, newly developed glassy electrolytes, Na2O–ZnO–CdO, have been considered to discuss their electrical transport behavior at ambient temperature. The AC conductivity and relaxation behavior of them have been studied in the light of Almond-West formalism. The electrical conductivity (mixed conduction) is found to be a function of frequency as well as temperature. In the low-frequency range, it shows a flat conductivity owing to the diffusional motion of Na+ ions, whereas at high frequency, the conductivity shows dispersion. The DC conductivity ( σ dc ) and hopping frequency have been computed from the best fitted plots of experimental data. The AC conductivity at different concentrations and a constant temperature has been reported. The variation in the conductivity data with reciprocal temperatures indicates the dynamical behavior of charge carriers via hopping conduction in sodium oxide glassy systems. Mixed conduction in the present system may be dominated by polaron hopping in the samples with a lower Na2O content with a percolation type of motion of the electron/polaron. On the other hand, three-dimensional Na+ motion is the dominating charge carrier for the samples with a higher Na2O content. A negligible small difference in pathways in the I–V characteristics in both the directions should make the present system a promising candidate for the new generation battery electrolyte.

Research on Cotton Field Irrigation Amount Calculation Based on Electromagnetic Induction Technology

The rapid and efficient acquisition of field-scale farmland soil profile moisture-distribution information is very important for achieving precise irrigation and the adjustment and deployment of irrigation strategies in farmland. EM38-MK2 is a portable, non-invasive device that induces electric currents in soil to generate secondary magnetic fields for the rapid measurement of apparent electrical conductivity in the field. In this study, cotton fields were used as experimental objects to obtain soil apparent conductivity data for three periods, which were combined with soil-moisture content data collected simultaneously from soil samples and measured in the laboratory to construct an apparent soil-profile moisture regression model. A simple kriging interpolation method was used to map the distribution of the irrigation volume in the field, considering only the highest irrigation volume in the field as the maximum water-holding capacity in the field. The results showed that EM38 could accurately detect the spatial variation of soil moisture in the field. The R2 of the linear fit between measured and predicted soil-water content ranged from 0.51 to 0.89; the RMSE ranged from 0.66 to 1.87; and the R2 and RPD of each soil-layer water content model of the single-period model were higher than those of the full-period model. By plotting the distribution of field irrigation, it could be seen that by comparing the predicted field irrigation with the actual irrigation, at least 160 m3 ha−1 of irrigation could be saved in all three periods at an irrigation depth of 40 cm, which is about 30% of the actual irrigation; at an irrigation depth of 60 cm, about 30% and 15% of irrigation could be reduced in July and August, respectively. There are three areas in the study area with high fixed-irrigation volumes located in the northwest corner, near 500 m in the northern half of the study area and 750 m east of the southern half of the study area. The results of this study proved that the use of EM38-MK2 to monitor and evaluate the soil-moisture content of the farmland at different periods can, to a certain extent, guide the irrigation amount needed to achieve efficient and precise irrigation in the field.

Laminar forced convection in a tube with a nano-encapsulated phase change materials: Minimizing exergy losses and maximizing the heat transfer rate

The present work investigates the potential of NEPCM mixtures via analyses of convective heat transfer and exergy losses, and trade-offs between them inside a tube with a constant wall temperature. Experimental data for viscosity and thermal conductivity of the mixture was used within numerical simulations over a broad range of dimensionless parameters, including Reynolds number, mass fraction, melting strength, phase change zone thickness, and location of phase change zone. The effect of these parameters on the melting process, convective heat transfer and exergy loss is evaluated. The findings indicate that, although employing a NEPCM can boost the Nusselt number and heat transfer rate by 9.3 % and 16.1 %, as compared to the water, the exergy losses were enhanced up to 17 %. Additionally, in some circumstances, the Nusselt number and heat transfer rate both increased by 5.9 % and 2.5 %, respectively, whereas the exergy losses were zero. An optimal value of ω=0.02 was found to provide reasonable improvement in heat transfer rate increase with no exergy losses. Importantly, the present study shows that although higher NEPCM mass fractions can continue to increase the heat transfer performance, their benefit is rapidly offset above ω=0.02 due to heat transfer related exergy losses. Additionally, it was concluded that, in comparison to other parameters, the location of the phase change and the mass concentration of NEPCMS substantially affected the percentage of molten NEPCM and the latent heat efficacy.

Seasonal Variations of Soil Thermal Conductivity at the InSight Landing Site

AbstractThe heat flow and physical properties package measured soil thermal conductivity at the landing site in the 0.03–0.37 m depth range. Six measurements spanning solar longitudes from 8.0° to 210.0° were made and atmospheric pressure at the site was simultaneously measured using InSight's Pressure Sensor. We find that soil thermal conductivity strongly correlates with atmospheric pressure. This trend is compatible with predictions of the pressure dependence of thermal conductivity for unconsolidated soils under martian atmospheric conditions, indicating that heat transport through the pore filling gas is a major contributor to the total heat transport. Therefore, any cementation or induration of the soil sampled by the experiments must be minimal and soil surrounding the mole at depths below the duricrust is likely unconsolidated. Thermal conductivity data presented here are the first direct evidence that the atmosphere interacts with the top most meter of material on Mars.