International Journal of Thermophysics最新文献

{"title":"The Similarity Relation for the Boyle Line","authors":"Evgeny M. Apfelbaum","doi":"10.1007/s10765-026-03828-1","DOIUrl":"10.1007/s10765-026-03828-1","url":null,"abstract":"<div><p>The Boyle curve is shown to be nearly a parabola on the density–temperature plane. This similarity follows from the van der Waals equation, analogously to some other ideal or characteristic lines like the Zeno line. The accuracy of the found similarity was estimated on the basis of the analysis of numerical and experimental data for the model systems (Mie potentials in 3D and 2D spaces) and real substances. For the model systems, the maximal errors can reach <span>(sim )</span> 5 %, near the crossing point between the Boyle curves and binodals. For most of the considered real substances, they can reach <span>(sim )</span> 10 %, although there are exceptions—helium and methanol—with higher deviations.</p></div>","PeriodicalId":598,"journal":{"name":"International Journal of Thermophysics","volume":"47 9","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Similarity Relation for the Boyle Line","authors":"Evgeny M. Apfelbaum","doi":"10.1007/s10765-026-03828-1","DOIUrl":"10.1007/s10765-026-03828-1","url":null,"abstract":"<div><p>The Boyle curve is shown to be nearly a parabola on the density–temperature plane. This similarity follows from the van der Waals equation, analogously to some other ideal or characteristic lines like the Zeno line. The accuracy of the found similarity was estimated on the basis of the analysis of numerical and experimental data for the model systems (Mie potentials in 3D and 2D spaces) and real substances. For the model systems, the maximal errors can reach <span>(sim )</span> 5 %, near the crossing point between the Boyle curves and binodals. For most of the considered real substances, they can reach <span>(sim )</span> 10 %, although there are exceptions—helium and methanol—with higher deviations.</p></div>","PeriodicalId":598,"journal":{"name":"International Journal of Thermophysics","volume":"47 9","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Direct Identification of the Spectral Effective Radiative Characteristics of Semi-transparent Insulators for Macroscopic Transient Coupled Conduction–Radiation Simulation","authors":"Loïc Seyer,&nbsp;Cyril Daoût,&nbsp;Denis Rochais,&nbsp;Olivier Rozenbaum","doi":"10.1007/s10765-026-03824-5","DOIUrl":"10.1007/s10765-026-03824-5","url":null,"abstract":"<div><p>A Monte Carlo Ray Tracing (MCRT) homogenization is proposed to compute the spectral effective radiative and optical characteristics (<span>(alpha _textrm{eff})</span>, <span>(sigma _textrm{eff})</span>, <span>(g_textrm{eff})</span>, <span>(n_textrm{eff})</span>, <span>(k_textrm{eff})</span>) of real heterogeneous semi-transparent media. Performed on statistically representative numerical microstructures, with the knowledge of the intrinsic indices of the constituents identified from normal-hemispherical reflectance and transmittance measurements, the method delivers all five characteristics in a single forward pass, with no further inversion: in particular, the asymmetry factor is read directly from the ray statistics, and the effective refractive index is obtained by a numerical time-of-flight method free of any external assumption. Because it operates on the microstructure itself, the approach assumes no particular object shape. It is demonstrated on two real aluminosilicate fibrous insulators, MAFTEC 96 and FOX. The practical relevance of the identified characteristics is illustrated by coupled conductive–radiative simulations compared against transient temperature measurements for both materials. The comparison shows that the identified characteristics capture the radiative contribution to heat transfer, and that a gray diffusion (Rosseland) approximation remains insufficient even for thick semi-transparent media, so that full spectral coupling is needed to reproduce the experimental response.</p></div>","PeriodicalId":598,"journal":{"name":"International Journal of Thermophysics","volume":"47 9","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Density and Viscosity of Ethyl Isobutyrate + 2-Alkanol Mixtures: Experimental Measurements and RM-NTGC Modeling","authors":"Yi Liu,&nbsp;Mingcheng Feng,&nbsp;Aymen Bourezgui,&nbsp;Mustafa Bayram,&nbsp;Mohammad Almasi","doi":"10.1007/s10765-026-03826-3","DOIUrl":"10.1007/s10765-026-03826-3","url":null,"abstract":"<div><p>Densities and viscosities of binary mixtures containing ethyl isobutyrate (EIB) and a homologous series of secondary alcohols, from 2-propanol to 2-octanol, were determined over the full composition range at 293.15 K, 303.15 K, 313.15 K, and 323.15 K under atmospheric pressure. Excess molar volumes <i>V</i>^E, calculated from the density data, were positive for all investigated systems and increased with both temperature and alcohol chain length. These trends suggest that the expansion caused by disruption of the hydrogen-bonded alcohol structure, together with steric and packing effects associated with the branched ester and secondary hydroxyl groups, outweighs the volume contraction arising from ester–alcohol cross-association. To provide a unified representation of the volumetric behavior, a reduced modified Nitta–Chao group contribution model (RM-NTGC) was developed by incorporating composition, temperature, and alcohol carbon number dependencies into a transferable excess volume expression. A single set of parameters was fitted simultaneously to 240 experimental <i>V</i>^E values for the six binary systems, without introducing individual parameters for each alcohol. The model reproduced the complete database with an average absolute deviation of 0.0139 cm³·mol⁻¹, a root-mean-square deviation of 0.0185 cm³·mol⁻¹, and a coefficient of determination of R² = 0.9942. The proposed formulation therefore provides an accurate and compact description of the effects of composition, temperature, and alcohol chain length on the volumetric properties of EIB + 2-alkanol mixtures and may be useful for thermophysical property estimation and process design calculations within the investigated range.</p></div>","PeriodicalId":598,"journal":{"name":"International Journal of Thermophysics","volume":"47 9","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148837807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Density and Viscosity of Ethyl Isobutyrate + 2-Alkanol Mixtures: Experimental Measurements and RM-NTGC Modeling","authors":"Yi Liu,&nbsp;Mingcheng Feng,&nbsp;Aymen Bourezgui,&nbsp;Mustafa Bayram,&nbsp;Mohammad Almasi","doi":"10.1007/s10765-026-03826-3","DOIUrl":"10.1007/s10765-026-03826-3","url":null,"abstract":"<div><p>Densities and viscosities of binary mixtures containing ethyl isobutyrate (EIB) and a homologous series of secondary alcohols, from 2-propanol to 2-octanol, were determined over the full composition range at 293.15 K, 303.15 K, 313.15 K, and 323.15 K under atmospheric pressure. Excess molar volumes <i>V</i>^E, calculated from the density data, were positive for all investigated systems and increased with both temperature and alcohol chain length. These trends suggest that the expansion caused by disruption of the hydrogen-bonded alcohol structure, together with steric and packing effects associated with the branched ester and secondary hydroxyl groups, outweighs the volume contraction arising from ester–alcohol cross-association. To provide a unified representation of the volumetric behavior, a reduced modified Nitta–Chao group contribution model (RM-NTGC) was developed by incorporating composition, temperature, and alcohol carbon number dependencies into a transferable excess volume expression. A single set of parameters was fitted simultaneously to 240 experimental <i>V</i>^E values for the six binary systems, without introducing individual parameters for each alcohol. The model reproduced the complete database with an average absolute deviation of 0.0139 cm³·mol⁻¹, a root-mean-square deviation of 0.0185 cm³·mol⁻¹, and a coefficient of determination of R² = 0.9942. The proposed formulation therefore provides an accurate and compact description of the effects of composition, temperature, and alcohol chain length on the volumetric properties of EIB + 2-alkanol mixtures and may be useful for thermophysical property estimation and process design calculations within the investigated range.</p></div>","PeriodicalId":598,"journal":{"name":"International Journal of Thermophysics","volume":"47 9","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148837808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Photoacoustic Experiment Optimization via Machine Learning-Based Reduction of Measurement Points","authors":"Gia M. Kovacevic,&nbsp;Jose Ordonez-Miranda,&nbsp;Dragan D. Markushev,&nbsp;Dragana K. Markushev","doi":"10.1007/s10765-026-03825-4","DOIUrl":"10.1007/s10765-026-03825-4","url":null,"abstract":"<div><p>To optimize the photoacoustic measurement of metal and semiconductor solid samples acting as surface absorbers, we shorten the data acquisition time by 90 % compared to standard photoacoustic acquisition time by reducing the number of measurement points. We utilize Principal Component Analysis to identify the key measurement points that will serve as inputs to a neural network for predicting the thickness <i>l</i> and cutoff frequency <i>f</i>₀ of samples. Principal component analysis variants based on covariance and correlation matrices are applied and comparatively analyzed for thermoelastic signals modeled <i>via</i> the composite piston approach across 300 modulation frequencies (10 Hz to 10 MHz) for aluminum samples in an open-cell photoacoustic setup. Our results based on experimentally obtained data show that using these selected points the neural network can accurately predict <i>l</i> and <i>f</i>₀ with relative errors below 5 %.</p></div>","PeriodicalId":598,"journal":{"name":"International Journal of Thermophysics","volume":"47 9","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148783120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Photoacoustic Experiment Optimization via Machine Learning-Based Reduction of Measurement Points","authors":"Gia M. Kovacevic,&nbsp;Jose Ordonez-Miranda,&nbsp;Dragan D. Markushev,&nbsp;Dragana K. Markushev","doi":"10.1007/s10765-026-03825-4","DOIUrl":"10.1007/s10765-026-03825-4","url":null,"abstract":"<div><p>To optimize the photoacoustic measurement of metal and semiconductor solid samples acting as surface absorbers, we shorten the data acquisition time by 90 % compared to standard photoacoustic acquisition time by reducing the number of measurement points. We utilize Principal Component Analysis to identify the key measurement points that will serve as inputs to a neural network for predicting the thickness <i>l</i> and cutoff frequency <i>f</i>₀ of samples. Principal component analysis variants based on covariance and correlation matrices are applied and comparatively analyzed for thermoelastic signals modeled <i>via</i> the composite piston approach across 300 modulation frequencies (10 Hz to 10 MHz) for aluminum samples in an open-cell photoacoustic setup. Our results based on experimentally obtained data show that using these selected points the neural network can accurately predict <i>l</i> and <i>f</i>₀ with relative errors below 5 %.</p></div>","PeriodicalId":598,"journal":{"name":"International Journal of Thermophysics","volume":"47 9","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148783392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simultaneous Determination of Interfacial Thermal Resistance and Optical Phonon-Acoustic Phonon Energy Coupling Factor in MoS2 Supported by SiO2","authors":"Zhicheng Deng,&nbsp;Lei Ma,&nbsp;Yiqun Zhang,&nbsp;Guantong Wang,&nbsp;Jiahao Cai,&nbsp;Zexi Li,&nbsp;Jing Liu","doi":"10.1007/s10765-026-03821-8","DOIUrl":"10.1007/s10765-026-03821-8","url":null,"abstract":"<div><p>Under highly focused photon irradiation, the energy cascade induces a marked thermal non-equilibrium between optical phonons (OPs) and acoustic phonons (APs) in 2D material, which is critical in optothermal Raman-based thermal transport characterization. Previous optothermal Raman techniques ignored the thermal non-equilibrium effect between OPs and APs, introducing serious errors into the measurement of interfacial thermal resistance. Here, we combine Raman-based experiments, three-dimensional finite element thermal simulation, and rigorous optical interference consideration to simultaneously determine interfacial thermal resistance and the lumped energy coupling factor between OPs and APs. When the OPs–APs thermal non-equilibrium is considered, the interfacial thermal resistance for the nm-thick MoS₂ supported by SiO₂ is determined to be 1.1 to 11.2 × 10^–7 m²·K·W⁻¹, respectively. In comparison, <span>(R_{tc}^{^{primeprime}})</span> is found to be overestimated by 374% when OPs–APs non-equilibrium effect is ignored. Meanwhile, the energy coupling factor between OPs and APs is determined in the range of 0.7–3.63 × 10¹⁴ W·m⁻³·K⁻¹. Our methodology can be generalized to Raman-based interfacial thermal resistance measurement of supported 2D materials and provides insights for the intelligent thermal management design for 2D materials-based nanoscale electronic devices.</p></div>","PeriodicalId":598,"journal":{"name":"International Journal of Thermophysics","volume":"47 9","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148782221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simultaneous Determination of Interfacial Thermal Resistance and Optical Phonon-Acoustic Phonon Energy Coupling Factor in MoS2 Supported by SiO2","authors":"Zhicheng Deng,&nbsp;Lei Ma,&nbsp;Yiqun Zhang,&nbsp;Guantong Wang,&nbsp;Jiahao Cai,&nbsp;Zexi Li,&nbsp;Jing Liu","doi":"10.1007/s10765-026-03821-8","DOIUrl":"10.1007/s10765-026-03821-8","url":null,"abstract":"<div><p>Under highly focused photon irradiation, the energy cascade induces a marked thermal non-equilibrium between optical phonons (OPs) and acoustic phonons (APs) in 2D material, which is critical in optothermal Raman-based thermal transport characterization. Previous optothermal Raman techniques ignored the thermal non-equilibrium effect between OPs and APs, introducing serious errors into the measurement of interfacial thermal resistance. Here, we combine Raman-based experiments, three-dimensional finite element thermal simulation, and rigorous optical interference consideration to simultaneously determine interfacial thermal resistance and the lumped energy coupling factor between OPs and APs. When the OPs–APs thermal non-equilibrium is considered, the interfacial thermal resistance for the nm-thick MoS₂ supported by SiO₂ is determined to be 1.1 to 11.2 × 10^–7 m²·K·W⁻¹, respectively. In comparison, <span>(R_{tc}^{^{primeprime}})</span> is found to be overestimated by 374% when OPs–APs non-equilibrium effect is ignored. Meanwhile, the energy coupling factor between OPs and APs is determined in the range of 0.7–3.63 × 10¹⁴ W·m⁻³·K⁻¹. Our methodology can be generalized to Raman-based interfacial thermal resistance measurement of supported 2D materials and provides insights for the intelligent thermal management design for 2D materials-based nanoscale electronic devices.</p></div>","PeriodicalId":598,"journal":{"name":"International Journal of Thermophysics","volume":"47 9","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148782220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced Thermophysical Properties of 40:60 % Ethylene Glycol and Water Mixture Based MgO + Fe3O4 Hybrid Nanofluids: An Experimental and ANN Predictions","authors":"L. S. Sundar,&nbsp;Sérgio M. O. Tavares,&nbsp;Antonio C. M. Sousa","doi":"10.1007/s10765-026-03817-4","DOIUrl":"10.1007/s10765-026-03817-4","url":null,"abstract":"<div><p>The growing demand for efficient heat transfer and energy conversion systems require advanced working fluids with superior thermal transport properties. In this work, MgO, and Fe₃O₄ nanoparticles were synthesized by using chemical coprecipitation method. Then, 40:60 % ethylene glycol and water mixture based MgO + Fe₃O₄ hybrid nanofluids were produced by the two-step method. Three different compositions like 1:2, 1:1, and 2:1 of MgO and Fe₃O₄ were used in this study. The hybrid nanofluids of 0.2–1.0 vol % were prepared, and thermal conductivity, viscosity, density, and specific heat were measured over temperatures ranging from 20 °C to 60 °C. Sodium dodecylbenzene sulfonate surfactant was used to enhance the stability of the hybrid nanofluids. Transmission electron microscopy, and X-ray diffraction techniques were used for the morphological characterization of the nanoparticles. Results show that thermal conductivity increases with increase of nanoparticles concentration as well as temperatures, whereas the viscosity decreases with temperature, but increases with nanoparticle concentration. Moreover, the density increases with nanoparticles concentration but decreased with temperatures, and the specific heat decreases with increase of nanoparticles, but increases with temperature. The same trend is observed for the three nanoparticles composition. At 1.0 vol % and 60 °C, thermal conductivity improved by 22.09 %, 25.12 %, and 29.07 % relative to base fluid, whereas, at 1.0 %, and 20 °C the viscosity improved by 51.3 %, 53.9 %, and 56.8 %, relative to base fluid at nanoparticles composition of 1:2, 1:1, and 2:1 in the base fluid. The useful empirical correlations were developed for all the prepared hybrid nanofluids for thermal conductivity, viscosity, density, and specific heat, which demonstrates the high predictive accuracy, with <i>R</i>² values between 0.942 and 0.993. Artificial Neural Network (ANN)- Levenberg–Marquardt (LM) algorithm were used to train the experimental datasets to model nonlinear interactions between temperature, concentration, and thermophysical properties. Among all the datasets, the particle composition of 1:2 based hybrid nanofluids yielded the highest accuracy coupled with the lowest error values of the studied properties, e.g. thermal conductivity, MSE = 2.5036e⁻⁵, <i>R</i> = 0.99768; viscosity, MSE = 0.0035, <i>R</i> = 0.99925; density, MSE = 9.8186, <i>R</i> = 0.99142; specific heat, MSE = 28.941, <i>R</i> = 0.99783, respectively. Overall, the combined experimental and intelligent-modelling framework provides robust predictive capability for optimizing MgO + Fe₃O₄ hybrid nanofluids.</p></div>","PeriodicalId":598,"journal":{"name":"International Journal of Thermophysics","volume":"47 9","pages":""},"PeriodicalIF":3.6,"publicationDate":"2026-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148751636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}