Thermal Dynamics Research Articles

Integrating forecasting methods to support finite element analysis and explore heat transfer complexities

PurposeThis paper aims to reduce the cost of experiments required to test the efficiency of materials suitable for artificial tissue ablation by increasing efficiency and accurately forecasting heating properties.Design/methodology/approachA two-step numerical analysis is used to develop and simulate a bioheat model using improved finite element method and deep learning algorithms, systematically regulating temperature distributions within the hydrogel artificial tissue during radiofrequency ablation (RFA). The model connects supervised learning and finite element analysis data to optimize electrode configurations, ensuring precise heat application while protecting surrounding hydrogel integrity.FindingsThe model accurately predicts a range of thermal changes critical for optimizing RFA, thereby enhancing treatment precision and minimizing impact on surrounding hydrogel materials. This computational approach not only advances the understanding of thermal dynamics but also provides a robust framework for improving therapeutic outcomes.Originality/valueA computational predictive bioheat model, incorporating deep learning to optimize electrode configurations and minimize collateral tissue damage, represents a pioneering approach in interventional research. This method offers efficient evaluation of thermal strategies with reduced computational overhead compared to traditional numerical methods.

Numerical analysis on performance evaluation of photovoltaic thermal systems using ternary hybrid nanofluids and forced convection around copper cylinders

This study evaluates the performance of a photovoltaic thermal (PV/T) system using forced convection and ternary hybrid nanofluids, comprising water with cobalt, zinc, and silver. The PV/T system includes a glass absorber, polycrystalline silicon, and a flow channel with eight copper cylinders, positioned at 20 %, 40 %, 60 %, and 80 % along the channel, both above and below the flow path for optimal thermal conductivity. The working fluid is modeled under turbulent, steady-state conditions using the κ−ε turbulence model.Numerical simulations via COMSOL Multiphysics 6.0 evaluate the system's thermal and fluid dynamics, focusing on local Nusselt numbers and photovoltaic cell thermal efficiency compared to a baseline. The investigation spans Reynolds numbers from 10,000 to 100,000, nanoparticle volume fractions of 1 %–20 %, and aspect ratios of 0.1–0.3. The aspect ratio in this study is defined as the ratio of the height of a square obstacle within the flow channel to the total height of the flow channel. A supervised machine learning framework develops predictive regression models for system analysis. Results show fluid force at the outlet increases by about 1200 % and 1300 % for aspect ratios of 0.1 and 0.3 as the Reynolds number rises. The Nusselt number enhances by 420 % and 466 % at a 20 % nanoparticle volume fraction for aspect ratios of 0.1 and 0.3, respectively, with a 9 % improvement in photovoltaic cell efficiency. This work uniquely applies machine learning to derive regression equations for fluid force, Nusselt number, and electrical efficiency, an approach not previously explored in laminar flow studies.

Model Predictive Control and Service Life Monitoring for Molten Salt Solar Power Towers

A two-component system for control and monitoring of solar power towers with molten salt receivers is proposed. The control component consists of a model predictive control application (MPC) with a flexible objective function and on-line tunable weights, which runs on a Industrial PC and uses a reduced order dynamic model of the receiver’s thermal and flow dynamics. The second component consists of a service-life monitoring unit, which estimates the service-life consumption of the absorber tubes depending on the current mode of operation based on thermal stresses and creep fatigue in the high temperature regime. The calculation of stresses is done based on a detailed finite element study, in which a digital twin of the receiver was developed. By parallelising the model solver, the estimation of service-life consumption became capable of real-time operation. The system has been implemented at a test facility in Jülich, Germany, and awaits field experiments. In this paper, the modeling and architecture are presented along simulation results, which were validated on a hardware-in-the-loop test bench. The MPC showed good disturbance rejection while respecting process variable constraints during the simulation studies.

Understanding AFM-IR Signal Dependence on Sample Thickness and Laser Excitation: Experimental and Theoretical Insights.

Photothermal induced resonance (PTIR), also known as atomic force microscopy-infrared (AFM-IR), enables nanoscale IR absorption spectroscopy by transducing the local photothermal expansion and contraction of a sample with the tip of an atomic force microscope. PTIR spectra enable material identification at the nanoscale and can measure sample composition at depths >1 μm. However, implementation of quantitative, multivariate, nanoscale IR analysis requires an improved understanding of PTIR signal transduction and of the intensity dependence on sample characteristics and measurement parameters. Here, PTIR spectra measured on three-dimensional printed conical structures up to 2.5 μm tall elucidate the signal dependence on sample thickness for different IR laser repetition rates and pulse lengths. Additionally, we develop a model linking sample thermal expansion dynamics to cantilever excitation amplitudes that includes samples that do not fully thermalize between consecutive pulses. Remarkable qualitative agreement between experiments and theory demonstrates a monotonic increase in the PTIR signal intensity with thickness, with decreasing sensitivities at higher repetition rates, while signal intensity is nearly unaffected by laser pulse length. Although we observe slight deviations from linearity over the entire 2.5 μm thickness range, the signal's approximate linearity for bands of sample thicknesses up to ≈500 nm suggests that samples with comparably low topographic variations are most amenable to quantitative analysis. Importantly, we measure absorptive undistorted profiles in PTIR spectra for strongly absorbing modes, up to ≈1650 nm, and >2500 nm for other modes. These insights are foundational toward quantitative nanoscale PTIR analyses and material identification, furthering their impact across many applications.

Numerical and Experimental Study of a Wearable Exo-Glove for Telerehabilitation Application Using Shape Memory Alloy Actuators

Hand paralysis, caused by conditions such as spinal cord injuries, strokes, and arthritis, significantly hinders daily activities. Wearable exo-gloves and telerehabilitation offer effective hand training solutions to aid the recovery process. This study presents the development of lightweight wearable exo-gloves designed for finger telerehabilitation. The prototype uses NiTi shape memory alloy (SMA) actuators to control five fingers. Specialized end effectors target the metacarpophalangeal (MCP), proximal interphalangeal (PIP), and distal interphalangeal (DIP) joints, mimicking human finger tendon actions. A variable structure controller, managed through a web-based Human–Machine Interface (HMI), allows remote adjustments. Thermal behavior, dynamics, and overall performance were modeled in MATLAB Simulink, with experimental validation confirming the model’s efficacy. The phase transformation characteristics of NiTi shape memory wire were studied using the Souza–Auricchio model within COMSOL Multiphysics 6.2 software. Comparing the simulation to trial data showed an average error of 2.76°. The range of motion for the MCP, PIP, and DIP joints was 21°, 65°, and 60.3°, respectively. Additionally, a minimum torque of 0.2 Nm at each finger joint was observed, which is sufficient to overcome resistance and meet the torque requirements. Results demonstrate that integrating SMA actuators with telerehabilitation addresses the need for compact and efficient wearable devices, potentially improving patient outcomes through remote therapy.

Temperature measurement in laser–metal processing using optical sensing: Radiometric calibration and validation of a multispectral camera

In laser–metal processing such as Laser-based Powder Bed Fusion of Metals (PBF-LB/M), the quality of the final product is significantly influenced by the thermal behaviour of the melt pool. Accurate temperature measurements are challenging due to high temperature gradients and rapid cooling. This study introduces Multispectral Imaging (MSI) as a highly effective thermometry technique to address these demanding conditions. MSI captures multiple bands of radiation, enabling the simultaneous determination of absolute temperature and surface emissivity. This capability is crucial for ensuring high-quality outcomes in laser–metal processing such as PBF-LB/M, contingent upon robust radiometric calibration.To enhance reliability, two radiometric calibration models were developed: an empirical model based on linear sensor data correlations and an analytical model leveraging sensor behaviour. An efficient calibration was found for both models across a range of signal-to-noise ratios in the black body calibrator, where the analytical model even performs robust under a high noise level.Additionally, the temperature accuracy in the solid-state case was tested with a thermo-mechanical simulator. Results showed that the empirical and analytical models achieved mean relative errors of 2.0% and 1.6%, respectively, outperforming the state-of-the-art. Further, laser irradiation experiments highlighted the analytical model’s ability to accurately determine the emissivity decrease during the solid-to-liquid transition, allowing for accurate melt pool temperature estimations. Conversely, the empirical model struggled to estimate temperature effectively in the liquid phase.This study not only proposed a robust methodology of MSI in temperature measurement but also confirmed the accuracy and reliability of the system, broadening the scope for further investigation into the intricate thermal dynamics involved in laser–metal interactions.

Orientation, thermal characteristics and structural dimensions of Mangrove Kingfisher Halcyon senegaloides nest cavities in arboreal termitaria in central Mozambique

The breeding ecology of the Mangrove Kingfisher Halcyon senegaloides (family Alcedinidae) remains poorly known. While the few nests recorded in southern and East Africa have been in tree hollows, a seasonal population in central Mozambique woodland breeds in cavities in arboreal termitaria. Despite this breeding strategy being widely recorded in many tropical kingfisher species, it has received little research attention in the Afrotropical realm. We report on the siting and structural characteristics of arboreal termitaria used as nesting sites by Mangrove Kingfishers in central Mozambique and document the thermal dynamics of a nesting cavity in an arboreal termitarium. Arboreal termitaria (average volume 40.1 ± 23.8 l) occurred at a density of 0.52 ± 0.22 termitaria ha−1 in large trees or shrubs, mostly of the families Fabaceae and Malvaceae. Termitaria containing nest cavities were situated 10.8 ± 3.1 m above the ground, and most nests (78.6%) faced north. Nest cavity temperatures averaged 31.4 ± 2.6 °C, which is warmer and more stable than the average ambient temperatures of 28.7 ± 4.0 °C. ‘Carton’ termitaria (comprising a mixture of faecal matter and wood fragments) are thus believed to confer a thermal advantage for summer-nesting Mangrove Kingfishers.

Deep Tectonic Environment Analysis of the Lingshan Conjugate Earthquake within the Qinzhou Fold Belt, South China: Insights Derived from 3D Resistivity Structure Model

The Qinzhou fold belt, situated at the contact zone between the Yangtze and Cathaysia blocks in South China, was affected by the 1936 Lingshan M6¾ earthquake and the 1958 Lingshan M5¾ earthquake, both of which occurred within the conjugate structure. Understanding the deep seismogenic setting and causal mechanism of the Lingshan conjugate earthquake is of great significance for assessing the seismic disaster risk in the region. In this study, we utilized 237 magnetotelluric datasets and employed three-dimensional electromagnetic inversion to characterize the deep-seated three-dimensional resistivity structure of the Qinzhou fold belt and the Lingshan seismic zone. The results reveal that: (1) The NE-trending faults within the Qinzhou fold belt and adjacent areas are classified as trans-crustal faults. The faults exhibit crust-mantle ductile shear zones in their deeper sections, which are essential in governing regional tectonic deformation and seismic activity; (2) The electrical structure of the Qinzhou fold belt is in line with the tectonic characteristics of a composite orogenic belt, having experienced several phases of tectonic modification. The southeastern region is being influenced by mantle-derived magmatic activities originating from the Leiqiong area over a significant distance; (3) In the Lingshan seismic zone, the NE-trending Fangcheng-Lingshan fault is a trans-crustal fault and the NW-trending Zhaixu fault is an intra-crustal fault. The electrical structure pattern “two low, one high” in the zone has a significant impact on the deep tectonic framework of the area and influences the deformation behavior of shallow faults; and (4) The seismogenic structure of the 1936 Lingshan M6¾ earthquake was the Fangcheng-Lingshan fault. The earthquake’s genesis was influenced by the coupling effect of tectonic stress and deep thermal dynamics. The seismogenic structure of the 1958 Lingshan M5¾ earthquake was the Zhaixu fault. The earthquake’s genesis was influenced by tectonic stress and static stress triggering from the 1936 Lingshan M6¾ earthquake. The conjugate rupture mode in the Lingshan seismic zone is influenced by various factors, including differences in physical properties, rheology of deep materials, and the scale and depth of fault development.

Diverse Responses of Upper Ocean Temperatures to Chlorophyll‐Induced Solar Absorption Across Different Coastal Upwelling Regions

AbstractChlorophyll in phytoplankton absorbs solar radiation (SR) and affects the thermal structure and dynamics within upwelling regions. However, research on this process across global‐scale coastal upwelling systems is still lacking. Here, we use a coupled ocean‐biogeochemical model to investigate differing responses to chlorophyll‐induced solar absorption between Pacific and Atlantic coastal upwelling regions. Chlorophyll‐induced solar absorption leads to colder Pacific coastal upwelling but warmer Atlantic coastal upwelling. In the Pacific, the shading effect of the surface chlorophyll maximum leads to colder subsurface water, which is then upwelled, contributing to cooling. The more stratified upper ocean leads to shallower mixed layer depth, intensifying offshore transport and upwelling. In the Atlantic, the absorption of SR by the subsurface chlorophyll maximum causes warmer and weaker upwelling. The processes described, in turn, trigger positive feedback to ocean biogeochemistry and potentially interact with climate dynamics, underscoring the necessity to incorporate them into Earth system models.

Temperature-dependent dynamics and dislocation behavior in nanoscale machining of FeCoNiCrAl high-entropy alloys: Molecular dynamics simulation

This study investigates the impact of machining parameters on forces, thermal dynamics, dislocation behavior, and crystalline structure changes in FeCoNiCrAl high-entropy alloys during nanoscale material removal using molecular dynamics (MD) simulations. Utilizing Embedded Atom Method (EAM) and Tersoff interaction potentials, simulations were performed at cryogenic (73 K) and room (293 K) temperatures. Novel findings reveal that at 73 K, cutting velocities below 200 m/s produced the highest forces along the [001] direction, whereas at 200 m/s, the peak force shifted to [100]. Increasing velocity decreased the force along [001], while [100] exhibited an inverse relationship. At 293 K, the force remained highest along [001] across all velocities. Notably, forces at 73 K were 1.82, 1.79, and 1.58 times higher than at 293 K for velocities of 100, 200, and 300 m/s, respectively. Dislocation density, particularly 1/6<112> (Shockley) dislocations, peaked under all machining conditions, with a slight initial decrease at 293 K before a significant drop with higher cutting speeds. At 293 K and a cutting speed of 100 m/s, dislocation densities for depths of 5, 10, 15, and 20 Å were approximately 1.04, 1.54, 1.17, and 1.14 times greater than those at 73 K, respectively.

Investigating thermal conduction dynamics in ternary Carreau–Yasuda nanofluids under convective boundary conditions and exponential heat source/sink effects

The analysis of the Carreau–Yasuda nanofluid (CYNF) across a stretching surface has practical applications in several fields, such as heat exchange, engineering, and material science. Scholars may discover novel perspectives for increasing heat transfer performance, establishing advanced materials, and enhancing the efficiency of multiple engineering systems by studying the behavior of CYNF in this particular instance. The energy transfer through trihybrid CYNF flow with the effect of magnetic dipole across a stretching sheet is examined in the present study. The ternary hybrid nanofluid (THNF) has been prepared by the addition of ternary nanoparticles (NPs) in the water (50%) and ethylene glycol (50%). Titanium dioxide (TiO2), silicon dioxide (SiO2), and aluminum oxide (Al2O3) are used in base fluid. The fluid velocity and heat transfer are examined under the impact of Darcy–Forchheimer, chemical reaction, convective condition, activation energy, and exponential heat source. The fluid flow has been stated in form of velocity, energy, and concentration equations. The set of modeled equations is simplified to non-dimensional form of ordinary differential equations (ODEs) by using similarity substitutions. Numerically, the system of lowest order ODEs is calculated through the parametric continuation method. It has been noticed that the temperature field augments against the variation of viscous dissipation and heat source term. Furthermore, the magnetic dipole has significant impact to enhance the thermal curve of THNF whereas falloffs the velocity profile. It can be noticed that the energy propagation rate enhances with the rising numbers of ternary NPs, from 1.22% to 5.98% (nanofluid), 2.30% to 9.61% (hybrid nanofluid), and 3.23% to 11.12% (trihybrid nanofluid).

Predicting land use dynamics, surface temperature and urban thermal field variance index in mild cold climate urban area of Pakistan

Rapid urbanization attributed to population growth is affecting the built environment's thermal and landscape dynamics. Using Landsat satellite datasets, this study investigated the complex interplay between urban Land Cover (LC) modification, fluctuation in Land Surface Temperature (LST) and severity of Urban Heat Island (UHI) from 1990 to 2020 in Peshawar City, Pakistan. Thermal bands were used to calculate LST and severity of UHI using the Urban Thermal Field Variance Index (UTFVI). Furthermore, through Cellular Automata (CA), Logistic Regression (LR), and Artificial Neural Network (ANN), future predictions on thermal characteristics associated with land use changes were made. The results showed that the urban areas expanded by ∼25 % from 1990 to 2020, while a ∼10 % decrease occurred in urban vegetation. The city is projected to expand by ∼45 % and ∼56 % in 2035 and 2050, respectively. Notably, the results also demonstrated that urban hotspots were found the warmest with the strongest UHI severity (∼34 °C), followed by the barren land (∼32 °C), and vegetation. The results further predicted an increase of LST (∼55 % and ∼82 %) and UTFVI (∼62 % and ∼83 %) in 2035 and 2050, respectively. These findings provide useful insights for policymakers and city planners to mitigate heat stress and create a sustainable urban environment through the development of effective urban land use policies and urban greening.

Climate warming effects on temperature structure in lentic waters: A bibliometric analysis from the recent 20 years

Global climate warming and intensified summer heatwaves have exacerbated thermal stratification in inland lakes and reservoirs, leading to increased issues of deep-water hypoxia and harmful algae blooms. This study aims to systematically review the developments, barriers, and future directions of thermal phenology in freshwaters under warming conditions through a visualized meta-analysis. According to the Web of Science Core Collection database, we retrieved 3262 articles published between January 1, 2000, and December 31, 2023, using an advanced search query that included terms related to global warming, temperature stratification, and freshwater bodies. The data was then analyzed via bibliometric visualization tools to create comprehensive visual maps, highlighting research hotspots and development trends. Key findings include a significant upward trend on this topic, in the annual number of published articles post-2015, in which China and the USA are leading in the publication output. Keyword co-occurrence analysis identified climate change, global warming, and temperature as central themes, with specific environmental issues linking to lake eutrophication and runoff being prominent as well. The study also delves into the collaboration networks among researchers, institutions, and countries, revealing strong international partnerships primarily between China, the USA, and European nations. Based on the analysis, we recommend future research should focus on integrating machine learning and advanced modeling techniques to better predict and mitigate the impacts of climate warming on thermal dynamics of inland waters. By upscaling the research from traditionally local (or regional) to global perspective, our work is vital, not just for science, but also for management of the aquatic systems under rapidly changing climate conditions.

Flame instability and heat transfer effect during deflagration of premixed hydrogen in tunnel

In the process of hydrogen deflagration, thermal diffusion and fluid dynamics instability lead to the instability of premixed flames. With the enhancement of instability, the behavior of the flame front becomes unstable, leading to an increase in flame surface area and flame speed. This study used the three-dimensional full-speed CFD code GASFLOW-MPI to perform numerical simulations of tunnel model deflagration experiments based on the compressible Navier-Stokes equations. The turbulent combustion model used in the study takes into account the effects of thermal diffusion instability, fluid dynamics instability, and local turbulent disturbances. This paper quantitatively calculates the thermal diffusion and fluid dynamics instability to explore their effects on developing tunnel premixed hydrogen deflagration flames. Based on the effective Lewis number of the unburned premixed gas of the flame front and the ratio of thermal expansion to the flame thickness, the interaction behavior between them is analyzed. Additionally, this paper explores in depth the influence of heat transfer boundary conditions on the propagation of flame instability. Results show that the calculation results of the combustion model considering heat transfer effects are highly consistent with the experimental values, demonstrating the importance of heat loss in the overpressure peak and pressure decay process. During the deflagration process, thermal radiation plays a leading role, while heat convection makes the main contribution to heat loss during pressure decay. As the flame evolves, the destabilizing effect of fluid dynamics instability first increases and then decreases, while the stabilizing effect of thermal diffusion instability gradually weakens and transitions to a destabilizing effect, with both effects mutually reinforcing each other. Heat transfer effects delay mixing hydrogen-premixed gases with fresh air, slowing the transition of thermal diffusion instability from stability to instability, weakening the destabilizing effect of fluid dynamics instability, and thereby delaying the evolution process from competition to promotion between the two.

Supercooling preservation of vascularized composite allografts through CPA optimization, thermal tracking, and stepwise loading techniques

Vascularized composite allografts (VCAs) present unique challenges in transplant medicine, owing to their complex structure and vulnerability to ischemic injury. Innovative preservation techniques are crucial for extending the viability of these grafts, from procurement to transplantation. This study addresses these challenges by integrating cryoprotectant agent (CPA) optimization, advanced thermal tracking, and stepwise CPA loading strategies within an ex vivo rodent model. CPA optimization focused on various combinations, identifying those that effectively suppress ice nucleation while mitigating cytotoxicity. Thermal dynamics were monitored using invasive thermocouples and non-invasive FLIR imaging, yielding detailed temperature profiles crucial for managing warm ischemia time and optimizing cooling rates. The efficacy of stepwise CPA loading versus conventional flush protocols demonstrated that stepwise (un)loading significantly improved arterial resistance and weight change outcomes. In summary, this study presents comprehensive advancements in VCA preservation strategies, combining CPA optimization, precise thermal monitoring, and stepwise loading techniques. These findings hold potential implications for refining transplantation protocols and improving graft viability in VCA transplantation.

3D CFD modelling and experimental validation of conjugate heat transfer in wheel hub motors in micro-mobility vehicles

An experimental and 3D CFD (computational fluid dynamics) based numerical investigation of the in-wheel hub internal permanent magnet synchronous machine (IPMSM) has been carried out to understand the thermal dynamics associated with the power loss within the motor. This study can serve as a clear case baseline for the future development of thermal management systems in micro-powertrain systems. Experimental results show that the maximum winding temperature of 65.9 °C has been observed on the end-windings (EW) for an operating condition of 500 rpm (base speed), 4.5 Nm. Stretching beyond this operating point would increase the winding temperature beyond 65.9 °C, potentially damaging the winding insulation’s capabilities and magnetic properties of the permanent magnets (PMs) and adversely affecting the performance of the wheel motors. The hysteresis and eddy current loss coefficients for the stator core have been identified as 14.5×10-2 and 1.6×10-4 respectively. The experimentally identified losses have been distributed among the motor components for the development of the numerical thermal model in commercial CFD software Star-CCM+™. The CHT (conjugate heat transfer) thermal paths show that 68.4 % and 31.4 % of the total power loss from the stator components undergo convection and conduction, respectively. This indicates that convection heat transfer dominates on the in-wheel hub IPMSM motor topology. Almost 34.5 % of the heat loss is transferred radially through the air gap to the Permanent Magnets. When the air gap size decreased by 80 %, the amount of convection heat transfer through the air gap increased by a factor of 2 (69 %) and reduced the winding temperature by 13 % (57.3 °C).

Engineering Coatings Inspired by Cell Membrane Thermal Dynamics to Enhance Photothermal Therapy and Osteogenesis for Implant Infections.

Photothermal therapy (PTT) encounters challenges of rapid thermal loss and potential tissue damage. In response, we propose a Heat-Boost and Lock implant coating strategy inspired by the thermal adaptation of biological membranes, enabling precise local photothermal utilization. This coating incorporates a poly(tannic acid) (pTA) bridging layer on implants, facilitating stable layer-by-layer integration of a black phosphorus (BP) photothermal layer and a top cell membrane Heat-Boost and Lock layer. The cell membrane layer significantly curtails photothermal loss (extending the heat retention by 17.62%) and stores energy within its phospholipid bilayer, boosting photothermal effects near implants (achieving a temperature increasement of 275%). Theoretical analysis indicates that these local heat preservation properties of the cell membrane arise from its low thermal conductivity and phase-change properties. In a Staphylococcus aureus-infected bone implant model, our coating demonstrates precise antibacterial action around implants (reach an antibacterial ratio of 99.52%). The synergetic locking function of cell membrane and pTA delays BP biodegradation, ensuring favorable photothermal stability and long-term osteo-inductive performance (increasing the bone volume fraction by 53.45%). Beyond providing an endogenic biointerface, this strategy extends the application of cell membrane in local thermal management, offering possibilities for effective and safe PTT modalities.

Exploring thermal flow dynamics in pressurized water reactors using hybrid graphene nanoplatelet coolants

AbstractThis study investigates the impact of hybrid nanoparticles on the temperature of nuclear reactor coolant, with a focus on graphene nanoplatelet (GNP)‐based hybrid nanoparticles. Sixteen different hybrid nanofluids were analyzed, and their performance was compared with a standard water‐based coolant. The criticality values were obtained through MCNP modeling, revealing that higher nanoparticle ratios led to increased criticality, with the highest value of 1.3239 observed in GNP‐Fe3O4 + Al2O3 nanofluids (0.05 wt%) and the lowest value of 1.2935 in GNP–Fe3O4 + SiO2 nanofluids (0.001 wt%). Temperature variations showed that increasing nanoparticle concentrations resulted in slightly higher temperatures, with a maximum of 611.97 K for 0.05 vol.% GNP nanoparticles. Additionally, the departure from nucleate boiling ratio values were consistently above the safety threshold of 2.08, with the lowest value of 3.657 for GNP–Fe3O4 + SiO2 nanofluids (0.05 vol.%). These findings suggest that hybrid nanofluids, particularly those with higher nanoparticle ratios, can enhance the thermal performance and safety margins of nuclear reactor coolants, offering a promising avenue for future research and application.

Sub-bandgap excited photoluminescence probing of deep defect complexes in GaN doped by Si, Ge and C impurities

Abstract With the sub-bandgap optical excitation, thermal dynamics of holes among multiple levels in n-type GaN epilayers with different dopants of Si, Ge and C are investigated via measuring and modelling variable-temperature yellow luminescence (YL) band of the samples. In sharp contrast to the case of above-bandgap optical excitation, the variable-temperature YL band of all the studied GaN samples including unintentionally-doped sample exhibit unusual negative thermal quenching (NTQ) behavior, suggesting a possible physical mechanism, namely thermally induced migration of holes from shallower levels to the luminescent deep level. By considering the possible presence of multiple hole levels in the doped GaN samples, a phenomenological model is developed for the thermal transfer of holes among the multi-levels and the interpretation of the observed NTQ phenomenon of the YL band. Different activation energies of 347.9, 520.8 and 348.5 meV are obtained for the Ge-doped, high C-containing, and Si-doped GaN samples, respectively. The results reveal the existence of multiple hole defect levels in the n-type GaN. Possible microstructural origins causing these different hole levels are further argued. The study may shed some light on the nature of various defect complexes in the technologically important GaN epilayers. Combined microstructural and optical investigations need to be further done for elucidating various optically- and electrically-active defect complexes in GaN.&amp;#xD;

Optimization Analysis of In-Situ Conversion and Displacement in Continental Shale Reservoirs.

In the context of growing global energy demands and the need for efficient extraction techniques, this research, based on numerical analysis, addresses the high-energy demands of in situ conversion by introducing a two-stage development strategy. The strategy begins with an initial continuous heating stage, followed by a thermal stabilization stage. It culminates in a hydrocarbon production stage, which is divided into primary recovery and water injection-enhanced recovery. The findings demonstrate that the reservoir temperature continues to increase even after the stop of heating. Consequently, the reactions within the reservoir persist, leading to increased hydrocarbon generation. The heating stage also helps restore reservoir pressure, enabling high production rates of hydrocarbons during the first year of primary recovery. However, natural depletion subsequently occurs, requiring an enhanced oil recovery (EOR) method. While water injection is a viable EOR method, it proves less effective due to high water breakthroughs in the producer well. Additionally, a comprehensive analysis reveals that hydrocarbon generation and production are closely related to the calibration of energy input and the duration of injection. These results underscore the critical importance of precise energy management and injection timing in optimizing hydrocarbon recovery. By enhancing our understanding of the thermal dynamics and reaction kinetics within the reservoir, this research contributes to the development of more efficient and sustainable extraction technologies, ultimately improving the feasibility of commercial shale oil production.