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A ground-breaking solution that combines solar thermal energy and lithium-bromide vapor absorption technology to produce energy-efficient cooling and heating is the Intelligent Solar Assist 1kW Lithium Bromide Vapor Absorption system. This cutting-edge system uses the sun’s energy to power the absorption cycle, offering environmentally friendly and economically viable thermal management. Solar thermal collectors, a lithium bromide absorption chiller, a thermal energy storage device, and sophisticated control algorithms comprise the system’s main parts. Sunlight is captured and converted by solar thermal collectors into thermal energy, which is then used to produce the necessary heat for the lithium bromide absorption chiller. This chiller uses the absorption refrigeration cycle to efficiently cool or heat the specified area or process. When intelligent control algorithms are incorporated, the system performs and operates more effectively and efficiently. These algorithms regulate the thermal energy storage unit and optimize the use of solar energy, delivering a constant and dependable supply of cooling or heating as needed. Advanced monitoring and diagnostics features are also built into the system, allowing for remote control and in-the-moment performance evaluation. Disadvantages are ethical issues, lack of generalization, interpretability and complexity, scalability and processing resources, and scientific agreement. A novel Chimp-based recurrent model (CbRM) has been planned to be designed to predict the desired efficiency from the Evacuated Tube Collector (ETC) to overcome this issue. Comparing the Intelligent Solar Assist system to conventional heating and cooling systems, several benefits must be had. It minimizes greenhouse gas emissions, lessens reliance on traditional energy sources, and promotes a more sustainable future. The system also saves money using solar energy, lowering power costs and enhancing energy efficiency. Moreover, the proposed system implementation is done in Matlab. The method achieves the high efficiency of ETC in the range of about 0.9% which increases by 0.3% and the higher rate of COP was about 9.5% which increases up to 6%, as the increased concentration level of the strong solution was about 6.5% it was nearly 5% increase. The parameters in the suggested model were compared to the current parameters for the comparison analysis, and it was discovered that the proposed model had superior presenting efficiency.

Highly crystalline ZnO nanopillars were successfully synthesized using the mist chemical vapor deposition (Mist-CVD) technique. This environmentally friendly and low-cost method operates under atmospheric pressure and low temperatures. By varying the growth temperature from 300C to 500^∘C, we demonstrated control over the structural, optical and morphological properties of ZnO. X-ray diffraction (XRD) analysis confirmed a transition in the preferential growth orientation from (100) to (002) as the temperature increased, with nanopillars showing a highly c-axis orientation at 450^∘C. SEM and AFM analyses revealed vertically aligned, homogeneously distributed nanopillars with high surface roughness, favorable for photocatalytic applications. Optical transmittance decreased with growth temperature, while the bandgap narrowed due to intrinsic defects. These findings highlight the potential of Mist-CVD for producing high-quality ZnO nanostructures tailored for advanced applications.

The optical and thermodynamic properties of aluminum oxide (Al₂O₃) were investigated through the density functional theory. In this paper, to examine the structural parameters the GGA-PBEsol potential was used. The Becke–Johnson (TB-mBJ) potential was applied to estimate the optical properties, and the Gibbs2 code was used to examine the thermodynamic behavior of Al₂O₃. The optical analysis shows that the optical properties were improved and the spectrum red-shifted occurs under high pressure. The thermodynamics behavior of the Al₂O₃ in temperatures ranging from 0K to 1400K and the pressure ranging from 0GPa to 60GPa were achieved using the quasi-harmonic Debye model to elucidate the relationships between thermodynamic parameters and temperature under variant pressure. The results show that the optical and thermodynamic properties of Al₂O₃ are significantly improved under high pressure. This enhancement suggests that Al₂O₃ could be used more effectively in many industrial applications, including high-performance ceramics, thermal barrier coatings and as an optical material in devices such as lasers and sensors. In addition, the findings provide important insights into the behavior of Al₂O₃ compounds under high-pressure environments, which could enhance material design procedures for advanced technologies.

Due to the error between the strain measured by the fiber grating sensor pasted on the surface of the substrate and the real strain of the substrate, the analysis of the relationship between the strain measured by the fiber and the actual strain of the substrate is the focus of this research. Since structures are subjected to various harsh conditions in actual service, such as temperature changes, fatigue, corrosion, aging, cracks and other external factors, when using surface-adhesive fiber Bragg grating (FBG) sensors for structural health monitoring, all external factors may affect the measurement accuracy of the sensors and cause measurement errors, so it is necessary to consider some specific factors in a comprehensive manner. In this paper, we theoretically study the average strain transfer rate of the three-layer strain transfer model of a surface-adhesive fiber grating sensor under the effects of temperature change and fatigue load, derive the formula for the average dynamic strain transfer rate under the combined effects of two external factors using the shear-lag method and analyze the parameters of the fiber-optic sensor to correct the error and optimize the measurement accuracy of the sensor in order to better monitor the structure under temperature change and fatigue load. The shear hysteresis method is also used to analyze the parameters of the fiber-optic sensor to correct the errors and optimize the measurement accuracy of the sensor in order to better monitor the real dynamic strain of the substrate under temperature and fatigue loads and provide theoretical guidance for its measurement.

In this paper, an experimental investigation of the machinability of Titanium grade 23 has been carried out using hybrid micro-textures on the cutting tool. The different types of micro-textures have been fabricated on the rake surface as well as on the flank surface of the cutting tool. The performance of textured tools with the presence of a chip breaker has been investigated. The selected patterns were vertical grooved rake face (VT-R), diagonal grooved rake face (DT-R), vertical grooved flank face (VT-F) and hybrid textured tools namely, vertical rake and flank (V+V), diagonal rake and vertical flank (D+V). A comparative study has been carried out to acknowledge the performance of textured tools while dry turning Titanium Grade 23 alloy. The machinability has been made to acknowledge the performance of textured tools with the variation of machining time in case of dry turning operation. The machinability criteria are investigated based on cutting forces, cutting temperature and tool wear mechanisms involved while machining. The performance of the cutting tool with DT-R and VT-F micro-texture is observed to be better in comparison to others. Innovative applications of micro-textured tools are for dry green machining without any environmental hazards and proper chip-flow control.

Ferroelectric ceramics, such as barium titanate, have garnered significant interest due to their unique electrical and mechanical properties. In particular, their ability to undergo significant deformation under an applied electric field aids in their utilization in many applications, including actuators and sensors. The deformation behavior of ferroelectric ceramics is complex and is influenced by various factors, such as crystal structure, defect density, and processing conditions. This study focuses on the mechanics of ferroelectric ceramics and seeks to offer a thorough comprehension of the barium titanate’s deformation behavior. The study begins by discussing the crystal structure of barium titanate and how it influences the ferroelectric behavior of the material. It then delves into the various mechanisms of deformation, including domain wall motion, phase transformation, and twinning. The study also discusses the effects of temperature, electric field strength, and microstructure on the deformation behavior of barium titanate. Furthermore, the study explores the relationship between the deformation behavior and the mechanical characteristics of barium titanate, including Poisson’s ratio and Young’s modulus. Finally, the study concludes with a discussion of the potential applications of ferroelectric ceramics and the need for further research in this area. Overall, this study provides a comprehensive understanding of the deformation behavior of barium titanate showcasing distinct influences of grain size, texture, and anisotropy. Notably, varying grain sizes significantly impact deformation behavior. For instance, smaller grain sizes ($<10\mu$m) exhibit superior deformation characteristics, correlating with higher permittivity values (2731–5801) compared to larger grain counterparts (18.4$\mu$m). Additionally, transition temperatures ($T_{\mathrm{\text{O}}–\mathrm{\text{T}}}$) for different grain sizes (18.0–$30.1^{\circ }$C for smaller grains, 21.5–$30.6^{\circ }$C for larger grains) underscore the impact of phase transitions on grain size. These results underscore the paramount importance of grain size, texture, and anisotropy in governing the mechanical traits of barium titanate, emphasizing their consideration during fabrication and processing for optimal performance in diverse applications.

The effect of temperature on the adsorption of a sulphur atom on the Fe(110) surface has been investigated using molecular dynamics simulations at a temperature of 353K, 373K and 398K. The most favorable adsorption site for a sulphur atom on the Fe(110) is found at a hollow site. The perpendicular height of the sulphur atom position is 4.017Å above the Fe surface at a temperature of 398K. The Fe–S bonding strength was affected by temperature, it becomes weaker with increasing temperature. The adsorption energy is calculated to be −6.640eV, −6.579eV and −1.841eV for the system at a temperature of 353K, 373K and 398K, respectively. This condition is confirmed by experimental results where the corrosion rate of the samples began to appear at 353K, with darker physical characteristics of the corrosion.

In this paper, we give a systematic review of the theory of Gibbs measures of Potts model on Cayley trees (developed since 2013) and discuss many applications of the Potts model to real world situations: mainly biology, physics, and some examples of alloy behavior, cell sorting, financial engineering, flocking birds, flowing foams, image segmentation, medicine, sociology, etc.

Vagus nerve stimulation (VNS) is a widely used neuromodulation technique that is currently used or being investigated as therapy for a wide array of human diseases such as epilepsy, depression, Alzheimer’s disease, tinnitus, inflammatory diseases, pain, heart failure and many others. Here, we report a pronounced decrease in brain and core temperature during VNS in freely moving rats. Two hours of rapid cycle VNS (7s on/18s off) decreased brain temperature by around $3^{\circ }$C, while standard cycle VNS (30s on/300s off) was associated with a decrease of around $1^{\circ }$C. Rectal temperature similarly decreased by more than $3^{\circ }$C during rapid cycle VNS. The hypothermic effect triggered by VNS was further associated with a vasodilation response in the tail, which reflects an active heat release mechanism. Despite previous evidence indicating an important role of the locus coeruleus-noradrenergic system in therapeutic effects of VNS, lesioning this system with the noradrenergic neurotoxin DSP-4 did not attenuate the hypothermic effect. Since body and brain temperature affect most physiological processes, this finding is of substantial importance for interpretation of several previously published VNS studies and for the future direction of research in the field.

AIM. Vagus nerve stimulation (VNS) modulates hippocampal dentate gyrus (DG) electrophysiology and induces hypothermia in freely moving rats. This study evaluated whether hippocampal (CA1) electrophysiology is similarly modulated and to what extent this is associated with VNS-induced hypothermia. METHODS. Six freely moving rats received a first 4h session of rapid cycling VNS (7s on/18s off), while CA1 evoked potentials, EEG and core temperature were recorded. In a second 4h session, external heating was applied during the 3rd and 4thh of VNS counteracting VNS-induced hypothermia. RESULTS. VNS decreased the slope of the field excitatory postsynaptic potential (fEPSP), increased the population spike (PS) amplitude and latency, decreased theta (4–12Hz) and gamma (30–100Hz) band power and theta peak frequency. Normalizing body temperature during VNS through external heating abolished the effects completely for fEPSP slope, PS latency and gamma band power, partially for theta band power and theta peak frequency and inverted the effect on PS amplitude. CONCLUSIONS. Rapid cycle VNS modulates CA1 electrophysiology similarly to DG, suggesting a wide-spread VNS-induced effect on hippocampal electrophysiology. Normalizing core temperature elucidated that VNS-induced hypothermia directly influences several electrophysiological parameters but also masks a VNS-induced reduction in neuronal excitability.

The construction of very good hyperspectral sensors operating in the thermal infrared bands from 8 to 12 microns arouses much interest for the development of data exploitation tools. Temperature emissivity separation (TES) algorithms are very important components of a future toolbox, because they make it possible to extract these two fundamental targets’ parameters. The emissivity relies on the nature of the target's surface materials, while the temperature gives information related to their use and relationship with the environment. The TES technique presented in this paper is based on iteration on temperature principle, where a total square error criterion is used to estimate the temperature. The complete procedure is described in the paper. Its sensitivity to noise is studied and a mathematical behavior model is provided. The model is validated through a Monte-Carlo simulation of the technique's operation.

The gate-all-around junctionless field-effect transistor (GAA JL FET)-based biosensor has recently attracted worldwide attention due to its good sensitivity to gate-all-around architecture and overall conduction mechanism. The effect of temperature usually affects the performance of transistors and sensors. Therefore, the impact of temperature on the 3D GAA JL FET-based biosensor has been investigated in this work. The dielectric modulation (DM) approach has been considered for including biomolecules. Consequently, the main proprieties of this biosensor have been investigated by ranging the temperature from 77K to 400K. The simulated results showed that the on-state current lowers as the temperature rises, but the off-state current increases. The off-current variation concerning the temperature is higher than the on-current change. Also, this type of biosensor appears to have a finer threshold voltage. Furthermore, the obtained results reveal that the current sensitivity is increased when ranging from temperature from 200K to 400K, and deteriorates for lower temperature values, like 100K and 77K. In addition, the GAA JL FET-based biosensor is more reliable for the detection of neutral biomolecules at high temperatures.

The two most popular algorithms for dissipative particle dynamics (DPD) are critically discussed. In earlier papers, the Groot–Warren algorithm with λ = 1/2 was recommended over the original Hoogerbrugge–Koelman scheme on the basis of a marked difference in their equilibrium temperatures. We show, however, that both schemes produce identical trajectories. Expressions for the temperatures of an ideal gas and a liquid as functions of the simulation parameters are presented. Our findings indicate that the current DPD algorithms do not possess a unique temperature because of the way in which the dissipative and random forces are included. The commonly used large time steps are beyond the stability limits of the conservative force field integrator.

It is difficult to predict the dynamics of systems which are nonlinear and whose characteristic is unknown. In order to build a model of the system from input and output data without any knowledge about the system, we try automatically to build prediction model by Genetic Programming (GP).

GP has been used to discover the function that describes nonlinear system to study the effect of wavelength and temperature on the refractive index of the fiber core. The predicted distribution from the GP based model is compared with the experimental data. The discovered function of the GP model has proved to be an excellent match to the experimental data.

Genetic Algorithm (GA) has been used to find the optimal neural network (NN) solution (i.e., hybrid technique) which represents dispersion formula of optical fiber. An efficient NN has been designed by GA to simulate the dynamics of the optical fiber system which is nonlinear. Without any knowledge about the system, we have used the input and output data to build a prediction model by NN. The neural network has been trained to produce a function that describes nonlinear system which studies the dependence of the refractive index of the fiber core on the wavelength and temperature. The trained NN model shows a good performance in matching the trained distributions. The NN is then used to predict refractive index that is not presented in the training set. The predicted refractive index had been matched to the experimental data effectively.

A solid–solid contact model of a rough surface with a single peak was established to explore the thermal effect of interfacial friction. From the perspective of friction force, temperature and energy, the law of the thermal effect was revealed. The results showed that the temperature of the asperities gradually increased during the shearing process, and a stress concentration formed in the shearing zone. After contact, the asperities had undergone unrecoverable plastic deformation. At each indentation depth, as the rotation angle of the crystal increased, the friction force, average temperature, and the sum of the changes in thermal kinetic and thermal potential energy first increased and then decreased; the trends of the three parameters changing with the rotation angle of the crystal were consistent. The average decreases in the friction force, average temperature, and the sum of the changes in thermal kinetic and thermal potential energy were 52.47%, 30.91% and 56.75%, respectively, for a crystal structure with a rotation angle of 45^∘ compared to a crystal structure with a rotation angle of 0^∘. The methods used in this study provide a reference for the design of frictional pairs and the reduction of the thermal effect of interfacial friction.

In this letter, by using the properties of the entropy function and the fundamental equation of thermodynamics, we discuss the reasons that there exist different proposals for relativistic temperature transformation. Further, we illustrate this point by studying a concrete thermodynamic system-blackbody radiation.

The Hagedorn temperature, T_H is determined from the number of hadronic resonances including all mesons and baryons. This leads to a stable result T_H = 174 MeV consistent with the critical and the chemical freeze-out temperatures at zero chemical potential. We use this result to calculate the speed of sound and other thermodynamic quantities in the resonance hadron gas model for a wide range of baryon chemical potentials following the chemical freeze-out curve. We compare some of our results to those obtained previously in other papers.

Currently the quantitative description of confinement inside nuclear matter is exclusively limited to computer experiments, mainly on lattices, and concentrating upon calculating the static potential. There is no independent reference for comparison and support of the results, especially when it comes to the quark potential in the continuum limit. Yet, we are entitled to be optimistic, for the basic results of these calculations seem to be correct from an entirely different point of view, suggested by Manton's geometrization of Skyrme theory. The present work shows the reasons of this point of view, and offers a static potential that might serve as independent reference for comparison and endorsement of any lattice calculations, and in fact of any structural hypotheses of nuclear matter. A historical review of the pertinent key moments in the history of modeling of nuclear matter, as well as an outlook anticipating the necessary future work, close the argument.

Single particle transverse mass spectra and HBT radii of identical pion and identical kaon are analyzed with a blast-wave parametrization under the assumptions of local thermal equilibrium and transverse expansion. Under the assumptions, temperature parameter $T$ and transverse expansion rapidity $\rho$ are sensitive to the shapes of transverse mass $m_{\mathrm{\text{T}}}$ spectrum and HBT radius $R_{\mathrm{\text{s}}}(K_{\mathrm{\text{T}}})$. Negative and positive correlations between $T$ and $\rho$ are observed by fitting $m_{\mathrm{\text{T}}}$ spectrum and HBT radius $R_{\mathrm{\text{s}}}(K_{\mathrm{\text{T}}})$, respectively. For a Monte Carlo simulation using the blast-wave function, $T$ and $\rho$ are extracted by fitting $m_{\mathrm{\text{T}}}$ spectra and HBT radii together utilizing a combined optimization function ${\chi }^2$. With this method, $T$ and $\rho$ of the Monte Carlo sources can be extracted. Using this method for A Multi-Phase Transport (AMPT) model at Relativistic Heavy Ion Collider (RHIC) energy, the differences of $T$ and $\rho$ between pion and kaon are observed obviously, and the tendencies of $T$ and $\rho$ versus collision energy $\sqrt{s_{\mathrm{\text{NN}}}}$ are similar with the results extracted directly from the AMPT model.