Analysis Of Thermal Conductivity Research Articles

Analysis of the Propagation of Temperature and Thermal Conductivity of Sawdust Pyrolysis Process with Modeling Fea and Experiment

The study uses densified sawdust with heat propagation and thermal conductivity to achieve better pyrolysis and gasification processes. Analysis of sawdust's heat propagation and thermal conductivity during pyrolysis was developed with Finite Element Analysis (FEA). The thermal conductivity values of sawdust (k) obtained from FEA are 1.49, 1.3, 1.1, and 0.7 W/m C considering the sawdust heated with a triggering temperature (T0) 535 ºC and reaches a constant temperature of T1 = 265 ºC, T2 = 165 ºC, T3 = 115, and T4 = 95 ºC respectively after 20 minutes. The temperature distribution of sawdust heated shows between the experimental and FEA results is quite the same; however, differences on graph T1 show the experimental thermal conductivity (k) value is distinct from the simulated thermal conductivity (k) value due to a significant change that occurred as sawdust transformed into charcoal at minute 70, where the distance between point T1 and the trigger point (T0) is 40mm and after 180 minutes the sawdust had turned into charcoal completely. Furthermore, 31 grams (6.46%) of sawdust underwent pyrolysis in this experiment. The findings can aid future research and development in this field and provide valuable insight into the duration of time a bio stove utilizing compacted sawdust can produce a sustainable flame and be used as a reference for future experiments.

A novel candidate shape-stabilized phase change material for building energy conservation based on lauric acid/roasted iron tailings-expanded graphite

This study presents the fabrication of a novel shape-stabilized phase change material (SSPCM) characterized by high thermal capacity and heat transfer efficiency. The material was composed of lauric acid (LA) embedded in roasted iron tailings (RIT) and expanded graphite (EG), utilizing a straightforward, low-cost, and direct impregnation method. The as-prepared LA/RIT-EG SSPCM underwent a comprehensive analysis of leakage tests, surface morphology, chemical compatibility, phase change properties, thermal stability, and reliability. Furthermore, the heat transfer efficiency and thermal conductivity were measured through cooling tests and a laser thermal conductivity analyzer, respectively. The LA/RIT-EG formulation demonstrated an ability to absorb 61.57 wt% LA without leakage, maintaining excellent form-stability with a mass fraction proportion of 29:9.43 for RIT and EG. DSC results revealed phase temperatures and latent heats of 42.49–46.31 °C and 108.1–113.1 J/g, respectively. Compared to pure LA, LA/RIT-EG exhibited a 489.7 % increase in thermal conductivity. Additionally, heat storage and release rates were improved by 81.25 % and 88.24 %, respectively. The study elucidated the mechanism behind the enhancement in encapsulation capacity and thermal conductivity by RIT-EG, validated through specific surface area and wettability tests. Overall, the results suggest that LA/RIT-EG, characterized by high thermal capacity and heat transfer efficiency, holds promise as a potential candidate for thermal energy storage, particularly in the context of energy conservation in buildings.

Preparation processes and thermal conductivities of magnetic field- and torsional vibration-induced superoriented carbon fiber composites

With the advancement of semiconductor technology, advanced electronic devices have become increasingly efficient, highly integrated and multifunctional, producing a large amount of heat during operation, thus decreasing the device efficiency and increasing the requirements for thermal interface materials. The use of a magnetic field to prepare pitch-based carbon fibers (CFs) with ultrahigh axial thermal conductivities and aspect ratios is a promising method for preparing thermal interface materials. However, past methods are not adequately simple or effective. Herein, we propose a simple, efficient method for preparing a novel thermally conductive CF interface material with a superoriented and closely arranged structure. The thermal conductivity of the vertical plane can reach 82.026 W m-1 K-1, which is higher than that of many other alloys. During the experiment, we prove that the torsional vibration of the vibrating plate can greatly resolve the issue of powder bridging generated during preparation. In addition, we discover and explain the heat return conduction phenomenon through numerical simulation. Our innovative preparation process and our analysis of thermal conduction can provide a new method and unique view for the design of thermal interface materials.

Study on the thermal behaviour of spontaneous combustion of open-pit minerals

To study thermal behaviour during spontaneous combustion of an open-pit coal mine, mixed slag (coal, oil shale, and coal gangue) was taken as the research object. Laser thermal conductivity analyser and differential scanning calorimetry were used to test thermophysical parameters and heat release characteristics of the minerals. The parameters can be employed to calculate the apparent activation energy using the Arrhenius equation and evaluate the thermal behaviour of open-pit mixed slag. The results indicate that thermophysical parameters have stage characteristics. Thermal diffusivity and thermal conductivity of minerals, especially mixed slag, have a strong correlation with temperature. Heat flow of minerals exhibits five characteristic stages, and heat flow of the samples is consistent with the change in heating rate. During the heating process, thermal diffusivity and heat flow of the mixed slag are between those of a single mineral. Except for the mixed slag at 15 and 20 °C/min, the initial exothermic temperature of the other samples is mainly concentrated at 50–80 °C. Thermal energy release of the sample is mainly concentrated in the accelerated exothermic stage and rapid exothermic stage. Thermal energy release of mixed slag in rapid exothermic stage is always greater than that in accelerated exothermic stage, and the proportion of thermal energy release in these two stages exceeds 98 %. The apparent activation energy during the accelerated exothermic stage is lower, making it easier to release heat, and rapid exothermic stage is relatively high, which can readily lead to heat accumulation. Thermal analysis reveals that the thermal behaviour of mixed slag is significantly different from that of a single mineral. Its unique exothermic characteristics can provide a more accurate theoretical basis for the prevention and control of environmental pollution caused by slag spontaneous combustion.

Diffusion dominant thermal transport in mixed valent Ba4Sn4Se9

New material developments are of paramount importance from the perspective of developing a fundamental understanding of material properties as well as transitioning from materials to devices. Among the different classes of materials of interest, mixed valence Sn compositions have been known to display technologically important properties and are of interest for the design and synthesis of novel compositions for targeted applications. Herein, we report on electronic, optical and thermal properties of the previously unexplored mixed valence composition Ba4Sn4Se9, a material with a direct optical band gap of 2.36 eV. As revealed by single crystal synchrotron X-ray diffraction, Ba4Sn4Se9 crystallizes in the orthorhombic space group Pnma with a large unit cell comprised of 58 atoms. Heat capacity data reveals a low Debye temperature with many low frequency optic modes. Our low temperature thermal conductivity data and analyses show that thermal diffusion dominates thermal transport above 80 K. Furthermore, high lattice anharmonicity contributes to the very low thermal conductivity. Our results and analyses will motivate further investigations of this as well as other compositions in the Ba-Sn-Se system, as well as other mixed valence chalcogenides for technological applications.

Coconut shell-derived activated carbon-enhanced water phase change material for cold thermal energy storage.

In building cooling, the demand for cooling surges during specific times, stressing air-conditioner operation, and additional cooling is often wasted during low-demand periods. Water-phase change material (W-PCM)-based thermal energy storage (TES) allows for load shifting and effective management of peak demand by storing cooling energy when the demand is low. This stored energy can be deployed during peak hours, decreasing energy usage and associated CO2 emissions. However, the use of W-PCMs was hindered by phase separation, slow energy transfer, and high supercooling degree (SCD). We synthesized coconut shell (CNS)-produced activated carbon (ACC) to use as a thermal enhancer in W-PCMs for the first time. First, ACC was synthesized from CNS via steam activation. Then, transmission electron microscopy was used to confirm the pore morphology of the CNS-ACC.The synthesis of the W-PCM with various weight percentages (0.1, 0.6, and 1.2) of CNS-ACC was accomplished in two steps. Zeta potential distribution analysis revealed that the W-PCM with CNS-ACC exhibited colloidal stability. Thermal conductivity (TC) and thermogram analyses revealed that a dose of 1.2 wt% CNS-ACC enhanced liquid and solid TC by 9% and 22%, respectively, despite a 6% and 8% decrease in specific heat and latent heat. More specifically, solidification assessment in a spherical enclosure revealed 100% suppression of SCD with 1.2 wt% CNS-ACC. As a result of this and the enhanced TC, the overall solidification process was accelerated, reducing the overall duration by 18.5%. Thus, the combination of CNS-derived ACC and W-PCM for TES in building cooling could reduce energy consumption and associated CO2 emissions.

Machine learning backpropagation network analysis of permeability, Forchheimer coefficient, and effective thermal conductivity of macroporous foam–fluid systems

Macroporous materials exhibit outstanding properties in heat and mass transfer due to their high pore volume, high surface area, and high Young's modulus. Consequently, understanding their thermofluidic properties is crucial in the design, synthesis, and optimal application of these materials. Therefore, this study, premieres, the use of a machine learning (ML) backpropagation network to develop and train a series of datasets for permeability, Forchheimer coefficient, and effective thermal conductivity of variable macroporous foam–fluid systems with respect to degrees of interstices, fluid and solid properties. To account for permeability values for flowing fluids in the Darcy regime, numerical simulations of slow–moving fluids were implemented over the materials' interstices. In comparison to similarly substantiated values of permeability in the Forchheimer regime, these values were a bit lower. The ML-based backpropagation algorithm was used to analyze data, which produced predictions (output signals) that are more than 90 % in correlation to CFD datasets. This provided insight into the effect of porosity and reduced mean pore openings on macroporous structures' thermofluidic behaviour. Material porosity was observed to play a dominant role in estimating Forchheimer coefficients and effective thermal conductivities for these foam-fluid systems. However, reduced mean pore openings were observed to be more critical for estimating permeability. The contributory effects of reduced mean pore openings on the effective thermal conductivity for these macroporous foam–fluid systems were determined to vary between 5.8 and 13.2 percent. Furthermore, the effective thermal conductivity of macroporous foam–fluid systems was also evaluated in relation to changes in the interstitial fluid and solid matrix thermal conductivity.

The Influence of Copper Oxide Particle Size on the Properties of Epoxy Resin

This study examines the relationship between the size of copper particles and the properties of epoxy resin. Epoxy resin is a type of thermosetting resin commonly used as a matrix in polymer matrix composite materials reinforced with glass or carbon fibers. As part of this study, three microscale and two nanoscale composite samples modified with copper oxide particles of varying sizes were produced. This study included mechanical property tests such as static tensile tests, static bending tests, and impact tests. The results of the strength tests were compared to modeling results. Additionally, an accelerated thermal aging process was conducted to determine the impact of external conditions on the behavior of the produced composites. This study concluded with an analysis of thermal conductivity. The test results revealed that the size of the copper particles significantly impacted the tested properties. The composites with copper oxide particles on the nanoscale demonstrated the best results. These composites have promising applications in the automotive and aviation industries due to their strength, resistance to external factors, and increased thermal conductivity, suggesting their potential for producing materials that effectively dissipate heat.

Study on three-dimensional model of ventilation drying and heat and mass transfer of bulk grain pile based on discrete-continuous media

Abstract In order to ensure the safety of grain storage and explore the mechanisms of water and heat transfer during the drying process of grain piles, this paper takes wheat as the research object, uses a thermal conductivity analyzer to measure the thermal conductivity and specific heat capacity of wheat, and obtains a linear relationship between the heat constant and water content of wheat. COMSOL software was used to establish a three-dimensional model of ventilation drying and heat and mass transfer of bulk grain piles based on discrete continuum media, which simulated the temperature and humidity changes during the drying process of the grain pile. The model was verified by a thin layer drying experiment. The results show that the simulated values of temperature and water content obtained by the wet heat transfer model are in good agreement with the experimental values, and the maximum errors are 2.14 % and 5.68 % respectively. During the drying process, the grain temperature of wheat at the bottom of the grain pile increased rapidly, compared with that at the top of the grain pile, and the temperature of the wheat at the center was higher than that at the edge. At the end of drying, the moisture content from highest to lowest was top edge > top center > bottom edge > bottom center. Therefore, the model can be used to further study the changes of grain pile temperature gradient and water gradient.

Thermal Conductivity Analysis of Polymer‐Derived Nanocomposite via Image‐Based Structure Reconstruction, Computational Homogenization, and Machine Learning

Macroscopic thermal properties of engineered or inherent composites depend substantially on the composite structure and the interface characteristics. While it is acknowledged that unveiling such dependency relation is essential for materials design, the complexity involved in, e.g., microstructure representation and limited data impedes the research progress. Herein, this issue is tackled by machine learning techniques on image‐based microstructure and property data predicted from physics simulations, along with experimental validation. The methodology is demonstrated for the model system ultrahigh‐temperature ceramic nanocomposite. The structure is reconstructed from scanning electron microscope images, and is resolved by a diffuse‐interface representation, which is advantageous in handling complicated structure and interface properties. Subsequently, hierarchical finite element homogenization is carried out to evaluate the effective thermal conductivity. A thorough comparison between the computed results and experimentally measured data, conducted across diverse temperatures and varying interface thermal resistances, reveals a high level of agreement. The observed agreement allows for the inverse estimation of the interface thermal resistance, a parameter typically challenging to ascertain directly through experimental means. Utilizing comprehensive data, a machine learning surrogate model has been meticulously trained to accurately predict the effective thermal conductivity of composite structures with exceptional performance.

Application of constant proportional caputo (CPC) fractional derivative for natural convective casson nanofluid flow on an infinite cylinder

The article focuses on the application of fractional derivatives in the context of drilling fluids composed of clay nanoparticles (NPs) suspended in a Casson fluid. The main points of this research are composition of clay NPs with Casson fluid, mathematical approach (PDEs), flow processes, geometric and temperature conditions, Constant Proportional Caputo (CPC) fractional derivatives, analytical solution, verification through Mathcad, effect of volume fraction, thermal conductivity analysis, comparison of fractional derivatives, and accuracy of results. This article discusses the application of hybrid fractional derivatives in analyzing heat transmission in nanofluid drilling, particularly focusing on clay NP suspensions in a Casson fluid. The study aims to provide analytical solutions for temperature and velocity distributions by transformed into new hybrid fractional derivatives (CPC) and the fluid dynamics are influenced by the circular geometry and temperature changes. While also investigating the impact of different parameters and comparing the accuracy of different fractional derivative approaches.

Thermal transports of 2D phosphorous carbides by machine learning molecular dynamics simulations

Carbon phosphide is a newly discovered two-dimensional semiconductor material which wrinkles and has a significant carrier mobility. Due to lack an accurate force field, the use of molecular dynamics to study its phonon-dominated thermal conductivity which lead to inaccurate results. At present, the use of machine learning to construct a high-precision force field has become the mainstream research method to solve this problem. The main work of this study is to construct a comprehensive training sets for Phosphorus-Doped Graphene (PCn) (n = 3, 5, 6) and to use the fitted potential to calculate the related thermal properties. The research found that (PC5) exhibited anisotropic behavior, with a thermal conductivity of 106.6 Wm−1K−1 in the y-direction and 63.6 Wm−1K−1 in the x-direction. In comparison, (PC6) and (PC3) showed isotropic behavior, with thermal conductivity of approximately 104 Wm−1K−1 and 76.83 Wm−1K−1, respectively. Compared to monolayer graphene, the lower thermal conductivity of PCn is mainly attributed to phonon-phonon scattering effects, which are limited by the regular wrinkled structure. Additionally, low-frequency phonon have been found to have a significant impact on the thermal performance of PCn. Furthermore, we investigated the influence of uniaxial strain on the PC6 and observed an increase in the thermal conductivity with increasing strain. This study used key computational and analytical techniques, including phonon dispersion relations, homogeneous nonequilibrium molecular dynamics method, spectral thermal conductivity analysis. These findings provide a theoretical basis for understanding the thermal transport properties of PCn and will guide its potential applications value.

Time resolved calorimetric investigations of photoinduced isomeric molecular changes in the nematic phase of an azobenzene compound

By monitoring the time dependence of the thermal conductivity of a p,p’-diheptylazobenzene sample irradiated with UV light of various intensities, a quantitative study is presented on the effects played by the photo-induced trans to cis isomerization on the degree of the homeotropic alignment in its nematic phase. In particular, the kinetics of the changes eventually leading to the nematic–isotropic phase transformation has been investigated. Unlike the case of the thermal diffusivity analyzed in a recent study, the thermal conductivity analysis has enabled the quantitative evaluation of the trans–cis transformation rates since it is not affected by the specific heat critical behavior and, therefore, it is determined only by changes in the molecular structure induced by the photo-isomerization. The study has been possible thanks to the peculiarity of the adopted photopyroelectric calorimetric setup that enabled both the calorimetric evaluations, as well as the sample texture characterization, to be performed during the UV illumination of the sample.

Thermal Properties and Characterization of n-Decanol-Capric Acid/Expanded Graphite/Boron Nitride for Thermal Energy Storage

To find a low temperature phase change material (PCM) that can be applied to the middle constant temperature chamber of the three chamber refrigerator, this study proposes a binary eutectic PCM of n-decanol and capric acid as a base liquid, expanded graphite as a support material, and boron nitride as a thermal conductivity enhanced particle to modify the material. The composite PCM with suitable phase change temperature and high phase change latent heat is prepared by the solution blending method. The leakage rate experiment determines the maximum adsorption ratio of expanded graphite to be 92 %. The chemical structure, microstructure and thermodynamic properties are characterized by Fourier transform infrared spectroscopy, differential scanning calorimetry, scanning electron microscopy, thermal conductivity analyzer and thermogravimetric analyzer. The results show that the n-decanol and capric acid binary eutectic PCM is fully wrapped in the porous structure of expanded graphite, and boron nitride thermal conductivity enhanced particles are well adsorbed on the surface and pores of expanded graphite. The n-decanol and capric acid phase change material, boron nitride thermal conductivity enhanced particles and expanded graphite support material are only physically combined and no chemical reaction occurred. The phase change temperature of CPCM-2 with 3 % boron nitride thermal conductivity enhanced particles is -3.68 °C, the phase change latent heat is 129.2 J/g, and the thermal conductivity is 0.75 W/m·K. It has good thermal stability and reliability in the application temperature range.

Thermal conductivity analysis for peristalsis of hybrid nanofluid with Darcy–Forchheimer law

Thermal conductivity analysis for peristalsis of hybrid nanofluid with Darcy–Forchheimer law

Enhanced thermal conductivity of plasma generated ZnO–MgO based hybrid nanofluids: An experimental study

Hybrid nanofluids (HNFs) of metallic oxide-based nanoparticles (NPs) have been prepared in different basefluids (BFs) employing the thermal plasma technique. NPs of ZnO–MgO were directly dispersed into pristine coolant, engine oil, distilled water (DW), and coconut oil. Plasma was generated between two identical electrodes applying 8.0 kV at the ambient conditions and proved economically viable in preparing stable HNFs. X-ray Diffractometry (XRD) showed ZnO and MgO NPs possessed hexagonal and cubic crystal structures, respectively. The band gap is calculated through UV-visible spectroscopy. The thermal conductivity (TC) of the HNFs has been measured using a thermal conductivity analyzer based on the transient hot wire method. The band gaps of pristine coolant and its HNFs were obtained to be 3.35 eV and 3.33 eV, respectively. In engine oil and its HNFs, band gaps of 3.16 eV and 3.02 eV have been extracted. There appears to be a slight reduction in band gap for coolant and engine oil-based HNFs. The band gap value of coconut oil-based HNFs was 4.05 eV, which showed a higher value than the pristine coconut oil-based HNFs (3.95 eV). The band gap calculated in the case of DW-based HNFs was 3.79 eV. TC of HNFs with volume concentration of 0.019 % for DW, 0.020 % for coolant, 0.016 % for engine oil, and 0.017 % for coconut oil were tested between 20 and 60 °C. An increase in TC was observed with the rise in temperature of the HNFs. Maximum increment in TC was observed at 60 °C for coolant-based HNFs, which was 19 %, followed by DW (18%), coconut oil (18%), and engine oil (16%), respectively. DW-based HNFs can be used as a coolant and optical filter for optoelectronics devices like photovoltaic cells for better performance. The study underscores precise control of NPs size as pivotal for band gap influence. HNFs hold promise as the next-gen heat transfer fluids (HTFs), revolutionizing thermal conductivity across industries. This research lays a firm foundation for plasma-synthesized HNFs' application in enhanced heat transfer and optoelectronic devices. Coolant-based HNFs excel in thermal conductivity, addressing heat transfer challenges.

Current advancements in fluid-flow Problems: A brief review

This specific article is a compilation of a few current studies on fluid flow issues. This article provides an overview of current research on the experimental and theoretical analysis of various nanofluids' thermal conductivity. The current study examines a number of variables that have a significant impact on a nanofluid's ability to transfer heat, including temperature, solid volume fraction, type, size, shape, magnetic field, pH, ultrasonic time, and surfactant. In addition, some plausible and appealing theories that enhance the thermal conductivity of nanofluids are mentioned. The final important heat transmission mechanisms that play a significant part in improving thermal conductivity are Brownian motion, thermophoresis, nanoclustering, interfacial nano-layer, and osmophoresis. Thus, consideration is given to the heat transmission properties of nanofluids. And also discussed some Numerical method to solve fluid flow problems.

Development of machine learning force field for thermal conductivity analysis in MoAlB: Insights into anisotropic heat transfer mechanisms

The MAB phases have garnered significant attention as a new generation high-temperature structural materials due to their outstanding high-temperature mechanical properties, resistance to oxidation at elevated temperatures, low-temperature synthesis, and machining capabilities. The chemically anisotropic bonding within MAB phases leads to unique anisotropic elastic properties, oxidation behavior, and electrical characteristics, posing challenges in understanding the structure-property relationships.To address this challenge, we leveraged recent advances in machine learning force fields based on quantum mechanics methods. Using ab initio molecular dynamics simulations, we constructed a comprehensive dataset and developed an accurate machine learning force field for the Mo–Cr–Al–B system based on deep neural network. We then employed non-equilibrium molecular dynamics simulations to calculate the phonon thermal conductivity of MoAlB, investigating its temperature dependence and anisotropy. Our analysis includes phonon density of states, phonon participation ratio, and spectral heat flux analysis, shedding light on the temperature-dependent anisotropy of phonon thermal conductivity in MoAlB. This work not only provides a reliable force field for large-scale molecular dynamics simulations but also advances our understanding of the composition-structure-performance relationship in MAB phases.

Experimental Analysis of Moisture-Dependent Thermal Conductivity, and Hygric Properties of Novel Hemp-shive Insulations with Numerical Assessment of Their In-Built Hygrothermal and Energy Performance.

The use of lime as a binder in hemp-lime considerably increases the drying time of hemp-lime after casting. Furthermore, lime is a non-renewable mineral resource. As such, this paper explores the effectiveness of using an alternative non-mineral binder instead of lime to formulate a novel hemp-shive insulation. The moisture-dependent thermal conductivity, adsorption isotherm, vapour diffusion resistance factor, and in-built hygrothermal performance of four variants of a novel bio-based insulation were investigated. The hygrothermal performance of the novel hemp-shive insulation was compared with that of a previously developed novel hemp-lime insulation. No significant variation in thermal conductivity of hemp-shive insulations between the equilibrium moisture contents (EMC) at 0% and 50% relative humidity (RH) was observed, but there was a substantial increase in thermal conductivity hemp-shive insulations when the material reached the EMC at 98% RH. The average dry thermal conductivity values of hemp-shive and hemp-lime insulations were also similar. The adsorption isotherms of hemp-shive insulations were determined at 0%, 20%, 50%, 70%, 90%, and 98% relative humidity steps. At 98% RH, the moisture adsorption capacity of hemp-shive insulations was 4-to-5-times higher than that of hemp-lime insulation. Hemp-shive insulations' vapour diffusion resistance factor (µ value) was about double the µ value of hemp-lime insulation. Hemp-shive insulations exhibited 4-to-5-times higher water absorption resistance than that of hemp-lime insulation. Numerically determined porosity values of hemp-shive agree with the values of wood-based insulation materials of similar density. Finally, using all experimentally acquired data as inputs, dynamic whole-building hygrothermal simulations were carried out and the results show that novel hemp-shive insulation materials perform at a similar level to the hemp-lime insulation in terms of heating and cooling energy demand but require 45% less energy for humidification. However, the relative humidity inside the hemp-shive wall remains higher than 70%, which can potentially induce mould growth.

The Effect of Incorporating Juncus Fibers on the Properties of Compressed Earth Blocks Stabilized with Portland Cement

This study investigates the impact of incorporating Juncus fibers (JF) into compressed earth blocks (CEBs) stabilized with varying Portland cement contents, aiming to enhance local construction materials’ performance and reduce housing costs. CEB composites were produced with soil stabilized using different cement contents (4%, 8%, and 12% by weight) and JF reinforcement (0 to 0.2% by weight), compressed at 10 MPa with a hydraulic press. After 28 days of drying, the CEBs underwent diverse experimental characterizations to assess their physical, mechanical, thermal, and durability properties. The results revealed that incorporating JF led to a reduction in unit weight, ultrasonic pulse velocity (up to 36%), and dry compressive strength (approximately 17%). Higher fiber content correlated with increased water absorption and an increased capillarity coefficient. Thermal conductivity analysis indicated improved thermal performance, decreasing from 0.4350 W/m·K (12% cement without fibers) to 0.2465 W/m·K (4% cement with 0.2% JF). Despite the decrease in mechanical strength, CEBs with lower cement (4%) and higher fiber content (0.2%) demonstrated satisfactory durability (abrasion and erosion) and thermal insulation properties. This research suggests the potential of this material as a promising composite for the building materials industry. The findings contribute valuable insights into sustainable construction materials and have implications for cost-effective housing solutions.