Multi-energy polygeneration systems offer significant potential to improve energy utilization, enhance operational flexibility and integrate diverse energy sources into advanced infrastructure. This study proposes a long-term, large-scale and cross-regional CO2-based polygeneration system for energy conversion and management in integrated energy hubs, particularly ports and energy islands. The system integrates a direct air capture module, a carbon dioxide energy storage module and a power-to-fuel module to utilize renewable electricity during charging and to deliver electricity, heating, cooling and transportable fuels during discharging. Thermodynamic models are developed to optimize the system energy, exergy, electricity, heating, cooling and fuel utilization factors, as well as the levelized cost of energy. Under optimal conditions, the system achieves an energy utilization factor of up to 146%, with electricity, heating, cooling and fuel utilization factors of 30%, 79%, 19% and 18%, respectively. The CO2 secondary distribution coefficient regulates the system's power-to-fuel ratio, while the heat allocation ratio of the high-temperature thermal energy storage governs the overall power-to-heat ratio. The introduction of external waste heat significantly improves the system energy, exergy, electricity and heating utilization factors while reducing the levelized cost of energy from $0.075/kWh to $0.039/kWh. High-temperature waste heat primarily enhances electricity output, whereas low-temperature waste heat predominantly increases heating output. Overall, the proposed system can flexibly deliver multiple forms of energy to meet end-user demands. It therefore provides a promising pathway for efficient energy conversion, carbon utilization and sustainable development across diverse application scenarios.

Carnot batteries are investigated as a potential alternative to electro-chemical batteries for grid-scale electricity storage, which is a crucial element to the decarbonisation of energy systems via variable renewable energy sources. In this work, a comprehensive life cycle assessment of the construction and end-of-life phases of two Rankine-based Carnot battery system configurations is presented, comparing water and thermal oil as hot thermal energy storage fluid. Both are benchmarked against lithium-ion batteries as the most common electrochemical battery alternative. To enhance the robustness of the analysis, uncertainties in the input parameters and life cycle inventory data are explicitly considered and analysed. The deterministic results show that the Carnot battery using water as hot storage fluid performs best in 13 of 18 environmental impact categories. For example, the climate change impact is up to 23% lower. Thermal energy storage systems are identified as the dominant contributors, accounting for more than 50% of the environmental impact across most impact categories. The stochastic results considering uncertainty show that the Carnot battery with water tends to have environmental impacts on par with lithium-ion batteries, while the Carnot battery with thermal oil tends to perform the worst.

Nanoparticle-enhanced fluids are increasingly investigated for thermal management, energy conversion, lubrication and process applications, but their formulation is complicated by coupled changes in thermal conductivity, viscosity, stability and pressure-loss characteristics. This structured narrative review critically examines how artificial intelligence, machine learning, physics-informed modeling and adaptive experimental design are being used across the nanoparticle-enhanced-fluid research workflow. The review organizes methods by research task and data structure rather than by an assumed performance ranking: classical regression and feed-forward networks for tabular property data; convolutional models for images and spatial fields; recurrent and transformer-based models for time-dependent stability data; graph models for molecular representations; Gaussian-process and Bayesian methods for uncertainty-aware optimization; and physics-informed or reduced-order approaches for constrained field prediction. The evidence indicates that supervised models for formulation-specific thermophysical-property prediction are comparatively mature, whereas transferable benchmarks, external validation and uncertainty reporting remain limited. Physics-informed methods can improve conservation and boundary-condition consistency, but they do not automatically eliminate data requirements, optimization difficulties or interpretability concerns. Autonomous discovery loops, reinforcement learning and large language models are promising for experiment planning and knowledge integration, but remain exploratory for end-to-end nanofluid discovery. The review therefore proposes validation and reporting practices, identifies industrial implementation barriers, and presents a staged roadmap toward reproducible, physically credible and scalable artificial intelligence assisted fluid development.

Hybrid concentrated photovoltaic–thermoelectric (CPV-TEG) systems have been proposed as a means to enhance solar energy utilization by recovering photovoltaic waste heat. However, their system-level performance under solar concentration remains debated, with existing studies reporting contradictory conclusions. A validated thermal-electrical model is employed in this work to establish quantitative performance boundaries for hybrid CPV-TEG systems, through systematic comparison with standalone CPV over various operating conditions. The effects of optical concentration ratio, cooling capacity, CPV cell characteristics, and thermoelectric (TE) material properties are examined. The results demonstrate that TEG integration does not provide net system-level benefits for silicon-based CPV cells across practical concentration ratios, due to temperature-induced efficiency degradation. In contrast, hybrid CPV-TEG systems become advantageous only within specific design regimes, characterized by medium-to-high concentration ratios, sufficiently strong cooling capacity, and CPV cells with low temperature coefficients. At high CR, a hybrid system employing a low-efficiency, temperature-insensitive CPV cell achieves a 24% efficiency improvement over standalone CPV. Furthermore, a system-constrained material selection framework is applied to evaluate TE materials based on their coupled impact on system efficiency and photovoltaic operating temperature, enhancing the hybrid system efficiency to 41%. These results provide clear performance assessment and practical design guidance for hybrid CPV–TEG systems.

This study investigates the integration of solar technologies and energy storage at the individual building level within fifth-generation district heating and cooling networks. Nine distinct building configurations are evaluated, incorporating photovoltaic (PV) systems, solar thermal collectors, photovoltaic-thermal (PV-T) systems, thermal energy storage (TES), and electric batteries. The techno-economic performance of these configurations is assessed for three user types: data centres (thermal prosumers) and residential and office buildings (thermal consumers). To capture dynamic interactions among thermodynamic components, an integrated thermal model is developed using an object-oriented methodology. Key findings for a case study in northern Italy show that combining PV systems with solar thermal collectors and energy storage results in primary energy savings of 57 % for residential buildings and 55 % for offices, compared to a reference scenario without solar technologies. Replacing PV systems with PV-T systems of equivalent area eliminates the need for solar thermal collectors, achieving over 50 % space savings. From a techno-economic perspective, the configuration for residential buildings that combines PV systems, solar thermal collectors, batteries, and TES achieves a payback-time (PBT) of 18 years without electricity exports, reduced to 14 years when excess electricity is exported. For offices, the PV-T system proves more cost-effective, achieving a PBT of 14.6 years, reduced to 11 years with electricity exports. The PBTs observed for the PV-only configuration are 5.9 years for offices and 5.8 years for the data centre. In the community-based approach, where investments are made collectively by users, PV-T systems achieve a low PBT of 6.4 years.

This study employs machine learning approaches to develop a back propagation (BP) model for capturing flow boiling heat transfer characteristics of ZnO/TiO2-R123 in a horizontal tube and conducts a bi-objective optimization considering heat transfer performance and flow resistance simultaneously. The BP neural network model is established with 750 groups of experimental data as training samples and 150 groups of experimental data as testing samples. The training accuracy and predictive accuracy of the BP model are analysed in detail. The effects of six operation parameters on heat transfer coefficient and pressure drop are examined, along with a bi-objective optimization conducted to maximize heat transfer coefficient and minimize pressure drop. The results indicate that the BP neural network model achieves a very high prediction accuracy, with a relative error of +/- 1.5 % for the prediction of heat transfer coefficient pressure drop. The heat transfer coefficient is negatively correlated with the vapor quality and increases slowly with the mass flux. The pressure drop increases slightly with the outlet temperature and decreases slowly with the outlet pressure at first, then gradually becomes steeper. The optimal solution for heat transfer coefficient and pressure drop are 4500 W/(m2 & sdot;K) and 0.022 MPa, respectively.

This vision article accompanies a Special Issue of Applied Thermal Engineering dedicated to the 14th International Conference on Circulating Fluidized Bed Technology (CFB-14), held in Taiyuan, China from 21 to 24 July 2024. The conference brought together prominent and young researchers, educators and practitioners to share research, achievements and practicing experience on circulating fluidized bed (CFB) technology. The conference featured representatives from 15 countries. A total of 164 articles were presented, of which 30 were keynotes, 109 were oral presentations, and 25 were poster presentations. Following peer review, 19 articles were selected for publication in this Special Issue, which collectively highlight recent advances in gas-solid fluidized beds for novel thermal reaction, energy conversion and storage. In this article, these contributions are reviewed, along with a selection of relevant studies in the literature. Based on this review and a brief identification of the state-of-the-art in CFB technology, the article provides a perspective for scientists, researchers and engineers that outlines key challenges, gaps, and identifies promising directions for future research and innovation. The need for further research is identified as being of importance in key areas of CFB design and process optimization in a variety of applications, ranging from the development of advanced processes with improved performance and efficiency, to the realization of novel decarbonization pathways. Focal areas include the development of high-fidelity computational modelling approaches, high-spatial and high-temporal measurement methods for large-scale CFB reactors, and integrated CFD simulation and process measurement to enables the next-generation of CFB designs for thermal reaction, energy conversion and storage.

This review examines recent advances in topology optimization for thermal energy storage, covering sensible, latent and thermochemical systems. Reported improvements range from about 10% to several-fold, with representative studies showing 30–50% shorter phase-change times and up to 47% higher heat release in closed thermochemical reactors. Emerging directions, including multi-operating-condition design, AI-assisted acceleration, and manufacturability-aware optimization, are also discussed, highlighting the role of topology optimization in next-generation thermal energy storage technologies.

Salt hydrate-based thermochemical energy storage (TCES) represents a promising pathway toward a sustainable energy future. A numerical model incorporating a multiscale dual-porosity framework that couples external transport phenomena with intra-particle diffusion is developed and experimentally validated in this article. Based on this, the heat-discharge characteristics of composite thermochemical material in a lab-scale fixed-bed reactor are numerically analyzed. The decoupling analysis, combining the unified dimensionless framework, examines the independent effect of heat/mass transport and reaction kinetics for this open TCES reactor. Results manifest that under the specified experimental conditions, the lab-scale reactor maintains an output temperature exceeding 35 degrees C for 70.2% of the total discharge duration. The variations in dimensionless parameters, such as mass transfer Peclet number (Pem) and Nusselt number (Nu), fundamentally confirm the intensification of heat-mass transport and reaction kinetics with increasing Reynolds number (Re) and relative humidity (RH). For the scaled-up reaction bed, elevating the inlet RH from 55% to 95% amplifies the temperature lift (Tup) from 19.6 degrees C to 30.5 degrees C; while beyond a threshold of around 1200, further increases in Re induce a slight drop in Tup. The output power, however, increases with both RH and Re, reaching a maximum value of 2830 W within the parameter range studied. Coordinated matching of reaction kinetics with the heat-mass transfer capabilities is practically required. Relative to the intrinsic gas-solid reaction, the primary pathway for enhancing discharge performance of a pilot-scale TCES reactor is the mitigation of transport resistances across both microscopic and macroscopic scales. This work provides theoretical guidance for the design and optimization of next-generation reactors for efficient salt hydrate-based TCES.

This study investigates a low-concentration, parabolic-trough photovoltaic–thermal collector for industrial heat and electricity cogeneration applications. A fully coupled 3-D optical, electrical, and thermal model of the collector was developed in COMSOL, based upon which a full-scale prototype was designed, constructed and tested in Monterrey, Mexico. A comparison between modelling predictions and experimental results at steady-state conditions revealed an RMSE of about 4% for the thermal efficiency and 1% for the electrical efficiency. The experimental results revealed maximum (zero reduced temperature) thermal and electrical efficiencies of 60% and 8%, corresponding to peak thermal and electrical power of 1.6 kWth and 210 Wel, respectively, from the 3.6 m2 collector Additionally, the collector was characterized following international standards: dynamic testing guidelines for thermal (ISO 9806) and electrical characterisation (IEC 62670-3) for a more rigorous analysis. Results obtained demonstrates that the developed simulation model is suitable for predicting the performance and may be used as basis for optimizing the collector.

Carnot batteries (CBs) have emerged as a scalable long-duration energy storage solution. Their reliance on thermal energy storage highlights the importance of cascaded latent heat and cold stores (CLHCSs), which can offer flexible thermal management but lack transient operation and performance studies. In this paper, a dynamic model of CLHCSs tailored for CB systems is developed, and the CLHCS operating modes enabling combined cooling, heating and power (CCHP) supply are proposed. Key parameters, including tube number, stage length, stage number, and charging-discharging duration, are investigated. The results show that CLHCSs demonstrate superior thermodynamic performance in pure electricity supply mode, achieving roundtrip efficiency of 99% and 94% respectively. The parameter analysis indicates that a smaller tube number enhances roundtrip and exergy efficiencies, while increasing stage number yields limited benefits. In contrast to moderate overcharging, insufficient charging more severely compromises the thermal energy storage and release performance of CLHCSs. Moreover, the case optimisation results reveal that exergy efficiency serves as a more effective objective function than the roundtrip efficiency for the CLHCSs of CB systems to enhance thermodynamic performance. This study suggests that there are promising reasons to continue to advance CLHCS technology in CB-based CCHP systems.

According to the IEA, soiling on a global scale has been identified as the second most significant factor affecting the energy production of photovoltaic (PV) systems after solar irradiance. Soiling directly affects the transmittance of PV glass and also disrupts the thermal balance (heat flows) within PV modules, thus impacting both the amount of solar irradiance received by and the temperature of the cells. In this work, we develop and validate a coupled opto-thermal-electrical model capable of assessing the impact of soiling on PV module performance. The model goes beyond other models, commercial and in the literature, by accounting explicitly for the effects of soiling on the optical transmission and the thermal balance through PV modules, while also being capable of accounting for electrical output limitations caused by non-uniform soiling. The validated model, which is shown to predict experimentally obtained losses due to soiling with a RMSE of 6 %, is then used to investigate the impact of natural soiling on yearly PV system energy production while considering the local weather conditions at different geographical locations (Oman, Nigeria, Iran, Indonesia, Australia and Spain), as well as the module tilt angle and module cleaning frequency. For a monthly cleaning frequency, and thus exposure period, maximum yearly soiling losses (relative to modules kept continuously clean) of between 5 % in Nigeria and 18 % in Oman are obtained for horizontally oriented modules. For a seasonal cleaning frequency, the yearly losses can reach values up to 27 % in Nigeria and 32 % in Oman, with the lowest predicted loss being 12 % in Australia. Based on the results, it is concluded that soiling losses can be significant (>30 % for horizontal, but also >20 % for optimally-tilted modules, in the worst case), and that the cleaning frequency can have a significant effect on yearly PV energy production, motivating the development of improved soiling mitigation practices.

District cooling system (DCS) integrated with large-scale photovoltaic (PV) is essential for sustainable urban energy transitions. However, most existing planning studies rely on representative-day simplifications, which lead to biased system design and economic assessment. This study develops a holistic planning and operational optimization framework for a fully PV-driven DCS integrating hybrid energy storage technologies, including batteries, ice storage, and hydrogen. Full-year hourly operations are explicitly resolved to examine the influence of planning horizons on system configuration and techno-economic performance. Renewable-driven systems are systematically compared with conventional grid-driven DCSs in terms of configuration, operation, and techno-economic performance. Results show that representative-day planning underestimates the levelized cost of energy (LCOE) by 6.8% for grid-driven systems and by up to 35% for renewable systems, due to their inability to capture prolonged renewable shortages and inter-seasonal storage dynamics. Although renewable-based DCS requires about 5 times higher capital investment ($13 million versus $2.3 million), it can achieve a 3.5% lower LCOE under the base scenario (55 cents/kWhc versus 57 cents/kWhc). Ice storage remains the dominant storage option in both systems because of its low capital cost, serving primarily as nocturnal load shifting in grid-driven systems and diurnal solar buffering in PV-based systems. Hydrogen storage, despite its high cost and low round-trip efficiency, plays a critical role for maintaining supply security during consecutive multi-day solar deficits. Sensitivity analyses reveal strong substitution effects among storage technologies, while PV module cost remains the most influential parameter, increasing LCOE by up to 17% under a high-cost scenario.

This Editorial introduces a Special Issue of Applied Thermal Engineering dedicated to selected articles from the 10th World Conference on Experimental Heat Transfer, Fluid Mechanics and Thermodynamics (ExHFT-10), held in Rhodes, Greece, in August 2024. The conference gathered 183 participants from 28 countries, and featured a rich scientific programme, including 21 oral presentation sessions, a poster session, 5 plenary and 8 keynote lectures. Of the 165 articles (125 oral and 40 poster contributions) presented at the conference, 14 articles were selected for publication in this Special Issue following peer review; these represent a curated sample of high-quality contributions addressing fundamental transport phenomena, innovative thermal management concepts, advanced materials, and emerging energy technologies. Together, these articles demonstrate the central role of experimentation in advancing physical understanding, validating models, and enabling engineering design. They also reveal clear research trends, including multi-scale analysis, integration of materials science with thermal engineering and increased focus on sustainable energy systems. This Special Issue aims to provide readers with both a concise overview of current developments and a forward-looking perspective on future directions in thermal science and engineering.

This vision article accompanies a Special Issue of Applied Thermal Engineering dedicated to the 14th International Conference on Circulating Fluidized Bed Technology (CFB-14), held in Taiyuan, China from 21 to 24 July 2024. Drawing upon a collection of contributions from the conference, which have been included in the Special Issue, and a selection of recent studies in the published literature, this article synthesizes recent advances in gas-solids fluidized bed technology, with an emphasis on circulating fluidized beds for thermochemical conversion processes and energy storage, highlighting emerging trends and critical research directions. The article also explores carbon management pathways, including biomass co-firing, oxy-fuel combustion, and chemical looping combustion, emphasizing their roles in reducing COQ emissions and enhancing process efficiency. Based on this review and an identification of the state-of-the-art in CFB technology, the article provides a perspective for scientists, researchers and engineers that outlines key challenges, gaps, and identifies promising directions for future research and innovation. Challenges related to advanced experimental methods and measurement accuracy, model development and validation, novel reactor design and technology scale-up, and operational flexibility are discussed. The integration of artificial intelligence and machine learning with physical models and multimodal sensing is identified as a transformative direction for real-time optimization, predictive control, and digital twin development. The paper concludes with a forward-looking perspective that underscores the need for advanced in-situ measurement techniques, multi-scale, multi-physics simulation frameworks, and hybrid AI-enhanced approaches to enable the next generation of efficient, flexible, and sustainable fluidized bed technologies for clean energy conversion and carbon neutrality.

Managing extreme thermal loads in safety-critical quenching and emergency cooling systems remains a critical bottleneck for energy-intensive industrial processes, where vapour-mediated interfacial resistance suppresses energy extraction and constrains operational stability. Existing passive and active strategies are constrained by their inherent latency in enabling effective thermal energy transport pathways during critical transient cooling periods. To address this bottleneck, a hybrid strategy is developed that couples an additive manufactured pointcontact cellular surface architecture with electrohydrodynamic (EHD) interfacial actuation. The synergistic effects of architected interfacial pathways and EHD actuation are evaluated on stainless steel (SS316L) substrates using high-speed visualization and transient heat flux analysis. The hybrid approach effectively suppresses vapour-mediated insulation, increasing the minimum film boiling temperature (Tmin) from 281 degrees C to 436 degrees C. By expanding the operational window of efficient cooling to higher temperatures, the system achieves 2.7 times increase in cumulative energy extraction, reaching 1.8 MJ/m2 during the critical initial period of quenching. Furthermore, the active control modulates the energy release profile, converting stochastic thermal shock into a rate-controlled dissipation trajectory. These results establish a scalable design principle for safety-critical systems, in which energy extraction rate, operational stability, and auxiliary energy cost are simultaneously constrained.

Triply periodic minimal surface structures have emerged as promising candidates for compact thermal-hydraulic components in supercritical carbon dioxide Brayton cycles. However, under high heat flux or low mass flux scenarios, the drastic density gradients near the pseudo-critical point cause buoyancy forces to become comparable to inertial forces. This transition from forced to mixed convection induces significant flow distortion and thermal stratification, which can cause localized overheating and threaten equipment integrity. Unlike in circular tubes, the coupling mechanism between buoyancy forces and complex TPMS topologies remains unclear. To address this gap, this study employed pore-scale numerical simulations to investigate the flow and heat transfer characteristics of supercritical pressure carbon dioxide in horizontal I-WP and Primitive channels. The results indicate that the I-WP channel eliminates thermal stratification through intense turbulent mixing, while the straight-through pore structure of the Primitive channel results in high-velocity flows with relatively lower TKE under identical conditions, rendering its heat transfer more susceptible to buoyancy effects. Increasing mass flux suppresses buoyancy through enhanced inertia, whereas higher heat flux amplifies it through larger density gradients. Furthermore, the buoyancy parameter (Gr/Re2) is employed to quantitatively evaluate the competition between buoyancy and inertia. In the Primitive channel, this competition is dictated by the coupled effects of thermal property variations and geometric non-uniformity.

The global energy transition emphasizes emission reduction, energy efficiency, and renewable integration. However, according to the second law of thermodynamics, all energy conversion systems inherently lose a portion of input energy as waste heat, representing a vast, underutilized resource for sustainable power generation and efficiency enhancement. Earlier studies focused solely on material-specific advancements or single-source applications. This study provides a comprehensive and integrative assessment of thermoelectric generator (TEG) heat recovery systems, encompassing artificial intelligence (AI) and machine learning (ML)-assisted materials design, techno-economic analysis, multi-physics modeling, dynamic system performance under different feasible heat sources, critical challenges and future approaches. The review begins with an in-depth assessment of diverse waste heat sources, including solar ponds, photovoltaic cells, cookstoves, biomass gasifiers, automotive engines, and industrial processes. It highlights suitable semiconductor materials across broad temperature ranges and systematically discusses recent advancements in TEG systems design, optimization, and performance enhancement for efficient waste heat recovery. The performance of TEGs highlights that Bi2Te3-based compounds remain ideal for low temperature heat sources while PbTe, skutterudites, and Mg3Sb2 alloys perform efficiently with mid-temperature sources. Integration of AI/ML, and multiphysics simulation has accelerated design optimization, improved prediction accuracy, and reduced computational cost. Hybrid configurations of TEGs with photovoltaic cells, biomass-driven systems, and automotive engines demonstrate strong potential in improving fuel efficiency, reducing emissions, and enhancing energy utilization. Despite the inherent advantages, commercialization remains limited by material costs and moderate conversion efficiencies. Therefore, future research needs to focus on scalable manufacturing, recyclable and non-toxic materials, and hybrid system integration. Aligning with circular economy principles, next-generation TEG systems will contribute significantly to global decarbonization and sustainable energy transitions. This review offers a unified roadmap connecting scientific, engineering, and economic insights toward real-life deployment of efficient, durable, and eco-friendly TEG technologies.

In this paper, we present the results of techno-economic evaluations of a range of optimised solar energy systems for heat and/or power provision in buildings located in hot, solar-rich climatic regions. Hybrid photovoltaic-thermal (PVT), solar thermal (ST), photovoltaic (PV), and combined PV and ST (PV-ST) systems are assessed using annual simulations. The systems are evaluated for electricity generation, space heating, and domestic hot water supply for a hotel in Fayoum, Egypt, which serves as a representative case study. Multi-objective optimisations are conducted to maximise the annual energy-saving ratio while minimising the payback time. For each technology, four representative commercial products with a spread of performance and cost characteristics are selected for comparison. The results demonstrate that detailed techno-economic assessments are essential for identifying the most economical solution, as relying solely on systems with the lowest upfront cost can be misleading. Energetic analyses show that, for a constrained maximum installation area of 150 m(2), the best-performing PVT system outperforms the alternatives in terms of energy savings. Specifically, it achieves a maximum annual energy-saving ratio of 43 % across the available area. The economic assessments show that the proposed systems are profitable in the specified case study, i.e., payback < 25 years, if appropriately sized and operated. For the same energy savings, the PVT systems are the most profitable with the shortest payback time (min. 6.2 years) and lowest levelised cost of electricity (min. 0.028 $/kWh), thanks to their lower investment costs per unit displaced energy. The payback time and levelised cost PV-ST systems (min. 8.1 years, 0.036 $/kWh) are close to those of ST systems (min. 8.1 years, 0.035 $/kWh), while PV systems are less attractive in this context (min. 8.6 years, 0.041 $/kWh). From an environmental perspective, the CO2 emission reduction potential of PVT systems is considerably higher (by 20-52 %) than those of all other systems, reaching a maximum of 31 tCO(2)/year. The proposed systems, especially the PVT systems, show excellent decarbonisation potential and cost effectiveness, thus motivating further development for applications in buildings in such climate zones.