Maximum Conductivity Research Articles

Exploring indigenous fungal isolates for efficient dye degradation: A comprehensive study on sustainable bioremediation in the total environment

Synthetic dyes used in textile industries are hazardous and toxic to the environment, as some of the dyes used in these industries are non-biodegradable. Sustainable technologies using microbes are an eco-friendly and economical approach. Fungal decolorization processes are gaining much importance as biomass absorbs enzymes used in biodegradation. In the current study, six samples of dye wastewater were collected from different industries in the Faisalabad industrial area in Pakistan. The physiological characteristics of these samples were analyzed, and various parameters, including pH, temperature, BOD, COD, and electric conductivity, were investigated. Among six different (sample A-F) wastewater samples, the maximum reduction in BOD was observed in sample E, i.e.,1.3.In contrast, the maximum reduction in COD of sample C, i.e., 30, was observed. These samples' hydrogen ion concentration (pH) was mainly in an alkaline ratio, and a maximum electric conductivity of 8810 µS/cm of sample A was observed. In contrast, a minimum sample E (540 mg/L) was observed. Three indigenous fungal strains were screened and purified from dye wastewater for detoxification of dyes and were identified morphologically and on a molecular basis as Aspergillus iranicus, Penicillium crustosum, and Aspergillus terreus. A comparative analysis of two methods, the tube overlay method and the liquid medium method, were conducted to biodetoxification synthetic dyes, including malachite green, methylene blue, and nigrosine. Spectrophotometric analysis showed that indigenous fungal strains, i.e., Penicillium crustosum decolorizing methylene blue at about 93%, followed by Aspergillus iranicus decolorizing malachite green at about 80% and Aspergillus terreus decolorizing about 90% of malachite green have good potential for degradation of dyes. These strains can be a potential source for treating textile dye effluent.

Low-carbon shape-stable phase change composite utilizing semi-coke ash for building thermal energy storage

To enhance the efficiency and cost-effectiveness of heating, air-conditioning, and solid waste recycling in buildings, this work proposed the solid waste semi-coke ash as skeleton material and the sodium carbonate as phase-change material to produce shape-stable phase-change composites using the cold compression-hot sintering method for building thermal energy storage. Eight shape-stable phase-change composites were prepared and the detailed chemical compatibility, thermal property, structural and mechanical performance, and micromorphology were investigated by X-ray diffraction, differential scanning calorimetry, laser flash analysis, N2 adsorption and desorption method, constant speed pressurization method, and scanning electron microscopy. Results demonstrated that semi-coke ash is suitable with sodium carbonate for fabricating shape-stable phase-change composites. The optimal mass ratio of semi-coke ash to Na2CO3 powder for sample CC3 was determined to be 52.5:47.5. This particular sample demonstrated a thermal energy storage density of 961.58 J/g and a maximum thermal conductivity of 1.306 W/(m ∙ K). It also exhibited excellent chemical compatibility between its components. Furthermore, sample CC3 displayed a mechanical strength of 23.57 MPa, with elements evenly distributed throughout. Importantly, CO2 emission from the production of sample CC3 was significantly low, indicating great potential for commercialization.

Using different Heuristic strategies and an adaptive Neuro-Fuzzy inference system for multi-objective optimization of Hybrid Nanofluid to provide an efficient thermal behavior

The importance of multi-objective optimization in hybrid nanofluid research lies in its wide-ranging applications across fields such as microelectronics, aerospace, and renewable energy. These specialized fluids hold the potential to elevate the performance and efficiency of diverse systems through enhanced heat transfer capabilities. This research endeavor is centered around optimizing a hybrid nanofluid composed of Silicon Oxide-MWCNT-Alumina/Water by leveraging a mix of heuristic approaches and an adaptive neuro-fuzzy inference system. To this end, the most influential set of input parameters has been identified using four state-of-the-art algorithms: Non-dominated Genetic Algorithm, multi-objective particle swarm optimization, Strength Pareto Evolutionary Algorithm 2, and Pareto Envelope-based Selection Algorithm 2. The goal of the optimization process is to modify the temperature (T = 20 °C to 60 °C) and the volume fraction of nanoparticles (SVF=0.1 % to 0.5 %). Finding the optimal combination of these parameters that results in the hybrid nanofluid with the maximum thermal conductivity (knf) and the lowest dynamic viscosity is the main objective. The findings of this research have the potential to drastically improve the performance of systems in a variety of applications and to change the creation of sophisticated, high-efficiency heat transfer fluids.

Vacancies tailoring lattice anharmonicity of Zintl-type thermoelectrics

While phonon anharmonicity affects lattice thermal conductivity intrinsically and is difficult to be modified, controllable lattice defects routinely function only by scattering phonons extrinsically. Here, through a comprehensive study of crystal structure and lattice dynamics of Zintl-type Sr(Cu,Ag,Zn)Sb thermoelectric compounds using neutron scattering techniques and theoretical simulations, we show that the role of vacancies in suppressing lattice thermal conductivity could extend beyond defect scattering. The vacancies in Sr2ZnSb2 significantly enhance lattice anharmonicity, causing a giant softening and broadening of the entire phonon spectrum and, together with defect scattering, leading to a ~ 86% decrease in the maximum lattice thermal conductivity compared to SrCuSb. We show that this huge lattice change arises from charge density reconstruction, which undermines both interlayer and intralayer atomic bonding strength in the hierarchical structure. These microscopic insights demonstrate a promise of artificially tailoring phonon anharmonicity through lattice defect engineering to manipulate lattice thermal conductivity in the design of energy conversion materials.

Fracture conductivity and rock appearance in volcanic reservoirs treated by various stimulation techniques

Volcanic reservoirs have complex mineral compositions and highly heterogeneous physical and mechanical properties, making their stimulation quite problematic. This study aimed at clarifying acid-rock reaction and stimulation mechanisms in volcanic reservoirs using 3D scanners and conductivity testing devices. Tests on rock sample conductivity and appearance under such mainstream stimulation technologies as hydraulic fracturing, acid fracturing, and proppant-carrying acid fracturing (PCAF) were performed. The effects of proppant particle size, proppant concentration, acid volume and type, proppant-carrying acid type, and proppant-carrying acid concentration on conductivity and rock sample appearance were analyzed. The appearance of rock samples included dot-, pit-, and strip-like embeddings, as well as acid-etching pits and channels. Larger particle sizes and higher proppant concentrations produced wider propped fractures and higher flow conductivity. Due to complex mineral distribution, acid fracturing failed to produce long etched channels, and the obtained conductivity was low, with a maximum of 8 D·cm at a 5 MPa closure stress. Hydraulic fracturing and PCAF reached a maximum flow conductivity of 155 D·cm at a 5 MPa closure stress, indicating their applicability to volcanic reservoir stimulation. This work helps reveal the acid-rock reaction and stimulation mechanisms of volcanic reservoirs and provides a theoretical basis for their development.

Effect of Sonication Batch on Electrical Properties of Graphitic-Based PVDF-HFP Strain Sensors for Use in Health Monitoring.

In this study, flexible nanocomposites made from PVDF-HFP reinforced with carbon nanotubes (CNTs) and graphene nanoplatelets (GNPs) are manufactured using a sonication and solvent casting method for monitoring purposes. More specifically, the effect of the volume batch under the sonication process is explored. For CNT-based composites, the electrical conductivity decreases as the batch volume increases due to less effective dispersion of the CNTs during the 30-min sonication. The maximum electrical conductivity achieved in this type of sensor is 1.44 ± 0.17 S/m. For the GNP-based nanocomposites, the lower the batch volume is, the more breakage of nanoplatelets is induced by sonication, and the electrical response decreases. This is also validated by AC analysis, where the characteristic frequencies are extracted. Here, the maximum electrical conductivity measured is 8.66 ± 1.76 S/m. The electromechanical results also show dependency on the batch volume. In the CNT-based nanocomposites, the higher gauge factor achieved corresponds to the batch size, where the sonication may be more effective because it leads to a dispersed pathway formed by aggregates connected by tunneling mechanisms. In contrast, in the CNT-based nanocomposites, the GF depends on the lateral size of the GNPs. The biggest GF of all sensors is achieved with the PVDF-HFP/GNP sensors, having a value of 69.36 × 104 at 35% of strain, while the highest GF achieved with a PVDF-HFP/CNT sensor is 79.70 × 103 at 70%. In addition, cycling tests show robust electromechanical response with cycling for two different strain percentages for each type of nanocomposite. The sensor with the highest sensitivity is selected for monitoring two joint movements as proof of the applicability of the sensors manufactured.

Влияние концентрации перхлората лития на числа переноса катиона лития в сульфолановых растворах

To increase the accuracy of determining the lithium cation transference numbers we proposed to measure them at different values of the polarizing voltage and extrapolate the calculated values to the zero value of the polarizing voltage. It was established that the lithium cation transference numbers increased linearly with the increasing concentration of LiClO4 solutions in sulfolane. It is assumed that the increase in the lithium cation transference numbers takes place due to the change in lithium perchlorate state in sulfolane solution and the mechanism of ion transfer. It was shown that the maximum cation conductivity was achieved at the concentration of lithium perchlorate sulfolane solution of about 2M.

Optimizing the structural, thermal, gas sensing and electrical properties of in-situ polymerized poly(thiophene-co-indole)/silicon carbide nanocomposites for energy storage applications

Conducting copolymer nanocomposites of thiophene and indole incorporated with silicon carbide nanoparticles [poly (thiophene-co-indole-SiC) (PPSiC)] has been developed by in-situ copolymerization and these nanocomposites were characterized by different analytical techniques. The FTIR peak at 865 cm−1 signifies the successful incorporation of SiC nanoparticles in the copolymer matrix. The intensity of the UV-Vis absorbance of the copolymer nanocomposites increased with the nanoparticle concentrations, and PPSiC7 showed the highest intensity. This was in correlation with its low optical bandgap energy (3.032 eV) and high refractive index (2.388) value. XRD revealed the consistent positioning of sharp and distinct crystalline peaks of SiC in the copolymer. SEM revealed the effective dispersion of nanoparticles throughout the matrix and uniform dispersion was obtained for PPSiC7 nanocomposite. HR-TEM images validated the presence of spherical-shaped particles in the nanocomposite with the nano-size distribution of SiC. The surface roughness of the copolymer nanocomposite was evident from AFM analysis. TGA and DSC revealed that PPSiC nanocomposites have better thermal properties than the copolymer. AC conductivity increased with frequency and temperature. The PPSiC7 exhibits a maximum conductivity of 1.5×10−2 S/cm at 106 Hz and an activation energy of 0.064 eV. PPSiC nanocomposites demonstrated excellent results in degrading dye and detecting ammonia gas at ambient temperature. All analyses showed that the PPSiC7 nanocomposite exhibited superior properties than the copolymer. These admirable properties can be exploited in developing optoelectronic devices, energy storage devices and gas sensors.

Investigation of electrochemical characteristics of intergel systems based on polyacrylic acid

Currently, hydrogels are polymer materials in high demand due to their physicochemical properties, and recent years have seen significant attention given to the study of their physicochemical properties [1,2]. The purpose of this research is to investigate the effect of remote interaction on the electrochemical properties of intergel systems containing hydrogels of polyacrylic acid, poly-4-vinylpyridine, poly-2-methyl-5-vinylpyridine, and polyethyleneimine hydrogels with various initial states. The dependency of conductivity and pH levels in aqueous solutions of intergel systems was examined. The obtained results have shown thatin the 5:1 ratio of the PAAswollen:P4VPdry intergel system, the conductivity of the aqueous medium reaches its maximum value after 24 hours, with a corresponding decrease in pH level. For the PAAdry:P2M5VPdry hydrogels at ratios of 5:1, 1:5, and 2:4, the high electroconductivity was observed at the sixth hour. The maximum pH value was achieved at a ratio of 4:2, indicating a low presence of nitrogen heteroatoms in the aqueous solution. The maximum conductivity in the PAAswollen:PEIswollen system at a 3:3 ratio was reached after 8.5 hours, while the pH showed its minimum value. In the study of the PAAdry:PEIdry intergel system, the pH of the aqueous medium decreased over time in all hydrogel ratios. An exception was noted at a 4:2 ratio, where pH slightly increased after 0.5 hours, then fell again, showing a deviation from the general pH trend. Conclusion. The conducted research has shown that specific conductivity varies across all molar ratios of hydrogels. It was established that changes in pairs and states of hydrogels in the intergel system affect specific conductivity, indicating the ratio of ionized and dissociated groups in the chain changes normally. These results demonstrate that these intergel systems can be used to get high-selectivity sorbents.

Experimental measurement of thermal conductivity and viscosity of Al2O3-GO (80:20) hybrid and mono nanofluids: A new correlation

This study examines the thermophysical properties of Aluminum oxide (Al2O3) and graphene oxide (GO) based mono and hybrid nanofluid mixture at different volume concentrations for heat transfer application. Firstly, Al2O3 and GO nanoparticles were mixed with base fluid (deionized water) separately at 1.0 % of volume concentration for mono nanofluid preparation. Then, Al2O3-GO hybrid nanofluid (80:20) was prepared for volume concentrations of 0.25 %, 0.5 %, 0.75 % and 1.0 %. The stability of both nanofluids was evaluated based on Zeta potential and pH measurements. Meanwhile, the viscosity and thermal conductivity were investigated for temperatures starting from 30 °C to 50 °C. The experimental thermal conductivity and viscosity measurements were correlated using the analytical regression method to predict the thermal conductivity and dynamic viscosity of Al2O3-GO hybrid nanofluid. The maximum thermal conductivity improvement of hybrid Al2O3-GO nanofluid (1 %) was about 4.30 % and 4.34 % higher than Al2O3 and GO mono nanofluid, respectively. In contrast, the viscosity of 1 % Al2O3-GO hybrid nanofluid showed the least reduction of 4.6 %, which is 4.1 % and 6.6 % less than both Al2O3 and GO mono nanofluids. Compared to experimental values, the new model resulted in a high level of predictive accuracy for both thermal conductivity and viscosity, with a maximum error of 6 % and 4 %.

Effect of impurities and carrier concentration on conductivity of bilayer graphene double layer system in different dielectric environments

The electronic transport properties of the bilayer graphene double layer (BLGDL) system at [Formula: see text][Formula: see text]K using the Boltzmann transport equation are reported here. The conductivity of the BLGDL system has been calculated with varying parameters as relative carrier concentration [Formula: see text], short-range (point defect) and long-range (Coulomb charge) impurity concentration, relative dielectric constant [Formula: see text] and interlayer distance [Formula: see text]. The maximum conductivity has been achieved in the absence of short-range impurity. The short-range impurity plays a non-trivial meaningful role in high dielectric and high carrier concentration regimes and limits the conductivity. For higher [Formula: see text] and higher [Formula: see text] values, the nature of the conductivity curve turns out to be of a sublinear nature, while in all other cases, it shows a superlinear trend. Suitable selection of relative dielectric constants, relative carrier concentration and interlayer distance helps to improve the conductivity of the BLGDL system. If the dielectric constant of the spacer is higher than the substrate material, the thickness of the spacer material helps remarkably in enhancing conductivity. Moreover, a comparison of BLGDL with our previously reported MLG–MLG double layer graphene system (DLGS) confirms that higher conductivity is achieved in the case of BLG–BLG system compared to DLGS.

Modeling hydraulic conductivity function of frozen soil

Hydraulic conductivity function for frozen soils (HCFF) is crucial for accurately simulating the water transfer process in cold regions, impacting hydrological states and frost heave diseases. However, the HCFF model capturing the relation between hydraulic conductivity and unfrozen water content (θ) or temperature (T) remains an open question. This study delves into HCFF encompassing both empirical and prediction models. This study begins with introducing θ-form and innovative T-form empirical HCFF models, showcasing their solid performance in fitting measured hydraulic conductivity data. Furthermore, the extension of the T-form empirical model to incorporate vapor flow and bimodal soils, through the introduction of maximum vapor conductivity and weighting factors, demonstrates a closer alignment with physical mechanisms and observed trends. In terms of predicting HCFF, the study provides a theoretical foundation through statistical hydraulic conductivity models and thermodynamic equilibrium in frozen soils. Additionally, it clarifies three routes for HCFF prediction—single Soil Freeze Characteristic Curve (SFCC), single Soil Water Characteristic Curve (SWCC), and a combination of the two—and validates their effectiveness through test results and comparison of HCFF prediction outcomes using SWCC and SFCC data from specific soil samples. In practice, the empirical and prediction models are recommended for available hydraulic conductivity data and available SFCC or SWCC data, respectively. Overall, this study not only lays the theoretical groundwork for most prediction models but also presents a valid empirical equation for modeling hydraulic conductivity function tailored specifically for frozen soils.

High-aligned oppositely-charged nanocellulose/MXene aerogel membranes through synergy of directional freeze-casting and structural densification for osmotic-energy harvesting

Optimization of ion-transport paths can considerably improve ion-transport capabilities in charged nanochannels. Thus, the assembly of high-charge-density one- and two-dimensional nanomaterials into aligned nanochannels is necessary for high-performance osmotic-energy harvesting. Herein, we prepared cellulose/MXene aerogel membranes with opposite charges and aligned nanochannels via chemical modification on algal cellulose nanofibers and MXene nanosheets, unidirectional freeze casting, and structural densification to considerably enhance the ionic conductivity in low-concentration solutions (maximum conductivity of 2.88 × 10−3 S cm−1). In particular, the aligned membrane had an output power density of 2.97 and 4.89 times higher than membranes used for suction filtration and isotropic nanochannels, respectively, demonstrating the necessity for nanostructure control. In addition, due to the photothermal effect of MXene, the positively–negatively (P–N) charged unit produced a maximum output power density of 8.87 W m−2 under a concentration gradient of artificial seawater and river water and simulated sunlight. Moreover, the unit maintained 90.4% of its original output capacity after 168 h of operation. As a proof of concept, we created nine series of P–N units and successfully powered an electronic calculator with an output voltage of 1.85 V. This study reveals improvements in developing renewable materials with an aligned nanostructure for high-performance osmotic-energy conversion.

The effect of multiscale parameters on the spiking properties of the morphological neuron with excitatory autapse

The excitatory autapse has been discovered recently by researchers in the pyramidal neurons, which could regulate the neuronal firing, while the spiking properties of the neuron with excitatory autapse (NWEA) have not been adequately studied. To further shorten such a gap, in this paper, a mathematical model is constructed for the NWEA to examine its spiking characteristics from two large scales: the external factors (which include the magnitude and location of the electrode current and the ambient temperature) and the internal factors (which consist of the location and maximum conductance of the excitatory autapse). The interspike interval (ISI), the spiking count (SC) and the spiking rhythm (SR) are used to analyse the spike trains. It is shown that the numerical results are coincident with the biological experiments, i.e. the excitatory autapse wholly enhances the bursting phenomenon and increases the neuronal responsiveness. In addition, as the maximum conductance of the excitatory autapse increases, the SC is gradually reduced but the SR is more active. With the variation of the current locations, the spike trains of the NWEA are more sensitive than those of the neuron without excitatory autapse. Furthermore, the ISI, SC and SR are all sensitive to the five types of parameters in various degrees. The results obtained in this paper may provide some instructions in regulating the firing of NWEA from the above five factors, and the proposed model for the NWEA provides a basis to perform more complex studies for the neurons with autapse.

The Role of the Intraspecific Variability of Hydraulic Traits for Modeling the Plant Water Use in Different European Forest Ecosystems

AbstractThe drought resilience of forest ecosystems is generally believed to depend on the dominant tree species' hydraulic traits. These traits define the maximum water transport capacity and the degree of vulnerability to hydraulic failure of a tree species. This work evaluates the effect of the intraspecific variability of hydraulic traits on the simulated tree water use in the Community Land Model (CLM, version 5.0). We selected two contrasting broadleaved tree species and performed a series of numerical experiments by modifying the parameters of the plant vulnerability curve and the maximum xylem hydraulic conductance accounting for the variability within each species. Our prescribed parameter sets represent vulnerable and resistant tree responses to the water deficit. At sites with an ample water supply, the resistant configuration simulates reduced water stress and increased transpiration compared to the vulnerable configuration. Meanwhile, the model results are counter‐intuitive at temporarily dry sites when water availability is the limiting factor. The numerical experiments demonstrate the emergent role of the maximum xylem conductance as a modulator of the plant water use strategy and the simulated transpiration within the model. Using the default value for maximum xylem conductance, the model tends to overestimate the early summer transpiration at drier sites, forcing the vegetation to experience unrealistic water stress later in the year. Our findings suggest that the parameterization of maximum xylem conductance is an important yet unresolved problem in the CLM and similar land surface models.

Electrochemical performance of Pr0.6Sr0.4Fe0.8Co0.2O3−δ as potential cathode material for IT-SOFC

Solid oxide fuel cells (SOFCs) are renowned for being effective energy sources that have potential to influence how energy is developed in future. SOFCs operate at low temperatures provides different benefits for widespread commercialization. In the present study a perovskite material Pr0.6Sr0.4Fe0.8Co0.2O3−δ (PSFCo) was investigated as cathode for SOFC in intermediate temperature range. Glycine nitrate process was used for the preparation of the samples. PSFCo exhibited cubic structure having small particle size (100–200 nm). The electrical conductivity of the PSFCo was measured as function of temperature up to 850 ℃. The sample displayed maximum electrical conductivity of 370 Scm−1 at around 550–600 ℃. The polarization behavior of PSFCo was calculated by means of AC impedance with Sm0.8Ce0.2O2 (SDC) as electrolyte. The value of area specific resistance (ASR) was calculated as 0.146 Ωcm2 at 800 ℃ and 0.248 Ωcm2 at 700 ℃.

Universal Short-Time Conductance Behavior Emerges between Two Adjacent Reservoirs

When a shutter, which differentiates between two adjacent particles’ reservoirs with a voltage gap, is lifted, a current emerges. In this paper, the temporal dynamics of this emerging current is analyzed. The main results are as follows: (A) the current’s prefactor in the short-time behavior is related to the long-time frequencies, by which the current converges to its equilibrium value (the conductance quantum unit 2e2/h). (B) In the short-time regime, the current is proportional to the square root of the time. (C) The maximum overshoot conductance is bounded by Gmax = ζe2/h, where ζ is a universal value which is very close to Euler’s number. (D) Most of these results are valid for a thin wire in 3D, even in the presence of electron–electron interactions.

Studies on structural, dielectric and charge transport properties of PVA:LiBr solid polymer electrolyte films

AbstractIn the present study, solid polymer electrolytes (SPEs) based on poly (vinyl alcohol) (PVA) doped with lithium bromide (LiBr) were prepared by solution casting method. Fourier transform infrared spectroscopy results affirm the complexation of LiBr with PVA. X‐ray diffraction results exhibit the increase of amorphous nature of the polymer electrolytes, which is also observed in scanning electron microscopy images and atomic force microscopy topographs. Thermogravimetric analysis thermographs endorse the increase of thermal stability of the polymer due to doping. Dielectric studies exhibit non‐Debye nature of the polymer electrolytes. Conductivity spectra reveal the maximum ionic conductivity (1.15 × 10−4 S/cm) for 20 wt% LiBr/PVA electrolyte at ambient temperature. Impedance analysis reveals the decrease of ionic relaxation in the polymer electrolytes and the studied transport properties of the electrolyte show that the major contribution to the conduction in this polymer electrolyte is ions.

The Effect of Cetyl Trimethylammonium Bromide Addition as Surfactant in Multiwalled Carbon Nanotube-Based Nanofluid for Quench Medium in Steel Heat Treatment Application

Nanoparticle addition into a fluid can increase the thermal conductivity. Such fluid is commonly called a nanofluid. Due to its improved heat transfer characteristic, nanofluid is widely used as coolant in engine or electronic equipment. In the steel heat treatment industry, nanofluid can be utilized as a quench medium. By controlling the amount of nanoparticle added in the nanofluid quench medium, the cooling rate can be adjusted. To preserve the heat transfer effectivity, the stability of the nanoparticle become very important. Hence, surfactant is quite essential to improve the particle stability and avoid particle agglomeration and sedimentation. In this study, a multiwalled carbon nanotube (MWCNT) was used as the nanoparticle in the distilled water. The concentration of the MWCNT was varied at 0.1, 0.3, and 0.5 % w/v. For the surfactant, Cetyl Trimethylammonium Bromide (CTAB) was chosen to disperse the particle better. In each of the three MWCNT variations, CTAB was added from 3 – 30% w/v. The maximum thermal conductivity obtained was in the nanofluid with 0.3% MWCNT and 5% CTAB at 0.72 W/mK. For the steel hardness, the value was roughly stable at 33 – 35 HRC in the nanofluid with no CTAB and 3 – 5% CTAB addition. Excessive surfactant addition at 30% CTAB decrease the hardness significantly up to 17 HRC.

Experimental and analytical investigations on heat transfer performance of naphthalene heat pipe heat exchanger

The heat transfer performance of a naphthalene heat pipe (HP) heat exchanger (HE) was theoretically analyzed and experimentally confirmed. The tested HE comprised a staggered 9 × 17 array of copper tubes with 144 U-bends, forming a closed loop. The working fluid was naphthalene with a filling ratio of 45 %. The operating temperature range was 80–300 °C, and the airflow rate was 100, 150, 200, or 400 m3/h. The maximum heat transfer rate was discovered to be 3.86 kW, and the HP thermal resistance was approximately 0.00553 K/W for an air flow rate of 100 m3/h and at an operating temperature of 300 °C; the maximum thermal conductivity was 7155.43 W/m·K. The experimental data were compared with the predictions of empirically derived equations; the best predictions were obtained when the Jouhara and Robinson correlation for condensation was combined with the Kutateladze correlation for evaporation. The mean deviations of the predictions were 36.05 % for the overall thermal resistance and 17.34 % for the average temperature difference between the evaporation and the air side. Although the thermal conductivity of the naphthalene HP was much lower than that of a water HP, it improved as the temperature increased; hence, naphthalene HPs are effective for high-temperature heat recovery.