Efficient Heat Research Articles

Numerical investigation on the enhanced heat transfer characteristics of non-Newtonian viscoelastic fluids in microchannel with chip arrays

Elastic turbulence is an efficient heat transfer method at microscale. In this work, we conduct a systematic investigation on the flow and heat transfer performances of viscoelastic polymer solutions in microchannels with chip arrays by means of high-fidelity numerical simulations. Focusing on the effects of fluid elasticity [i.e. polymer relaxation time (λ)] and flow Reynolds number (Re), we find that the synergistic interplay between inertial and elastic forces is strategically exploited to amplify convection, thereby facilitating an enhanced heat transfer performance. For highly elastic fluid, the Nusselt number (Nu) can be improved by 76.13 % compared to that of less elastic fluid, while the pressure drop is reduced appropriately. In addition, as the fluid elasticity increases, the pressure drop decreases and eventually converges to a constant. In the zone of elastic turbulence, the fluid reinforces the convective heat transfer, which can be ascribe to the deformation of long-chain polymer molecules. Particularly, we consider the effect of temperature-dependent λ on the heat transfer performance. Our results demonstrate that the increased temperature-dependent λ decreases the value of Nu, and the variation between values of variable and constant λ is reduced with increasing Re or λ. Hence, in some cases of large fluid elasticity or high Re, it is possible to safely ignore the impact of temperature-dependent λ with an acceptable accuracy. The present work provides important insights into the enhanced heat transfer via elastic turbulence, which could guide the applications in the field of chip cooling.

Control of Anisotropy and Magnetic Hyperthermia Effect by Addition of Cobalt on Magnetite Nanoparticles.

Magnetic hyperthermia (MH) has emerged as a promising technology with diverse applications in medical and technological fields, leveraging the remote induction of temperature elevation through an alternating magnetic field. While Fe3O4 nanoparticles with an average size around 12-25 nm are commonly employed in MH systems, this study introduces a strategy to produce smaller particles (less than or equal to 10 nm) with enhanced heating efficiency, as measured by specific power absorption (SPA). We conducted an exhaustive and detailed investigation into the morphological and magnetic properties of CoxFe3-xO4 nanoparticles, aiming to optimize their MH response. By varying the Co content, we successfully tuned the effective magnetic anisotropy while maintaining saturation magnetization nearly constant. The MH analysis indicates that these nanoparticles predominantly heat through the Néel mechanism, demonstrating robust reproducibility across different concentrations, viscosity mediums, and ac field conditions. Notably, we identified an optimal anisotropy or Co concentration that maximizes SPA, crucial for developing magnetic systems requiring particles with specific sizes. This work contributes to advancing the understanding and application of MH, particularly in tailoring nanoparticle properties for targeted and efficient heat generation in various contexts.

Experimental study on improving the thermal performance of isobutane refrigeration system by parameter optimization

Improvement of thermal efficiency for isobutane refrigeration system could match well with the building requirements of low-carbon, and sustainable development. The electric radiant heater (ERH) is widely used for the freeze and cold storage (FCS) system, but it has problems of high electric consumption and high freezer compartment temperature rise (FCTR) as a result of low heat-transfer efficiency under defrosting. Therefore, a novel FCS system with an additional electric radiant heater (AERH) based on the heat required for frost melted and synchronous defrosting is proposed. The defrosting consumption and the FCTR of the novel FCS system are comprehensively evaluated by a novel evaluation method. Besides, the effect of the thermal parameters (i.e., the defrosting pause temperature, the position, and electric power of the AERH) on the heat transfer characteristics are compared and optimized by the experimental method. Finally, a novel method is presented to predict the optimum thermal conditions. The results show that the optimum system thermal performance is obtained, the defrosting duration and defrosting consumption are reduced by 44.02 % and 37.03 %, and the defrosting efficiency and energy efficiency could be increased by 17.92 % and 9.96 %, respectively, as compared to the conventional FCS system. The proposed FCS system has better economic performance and heat transfer efficiency. Meanwhile, 30.54 kg of CO2 emissions could be avoided during the annual operation period, and the environmental benefits are also considerable. This study not only reaffirms the benefit of using the AERH for defrosting in the FCS system but also provides a reference for the promotion and application of efficient heat transfer technology in building refrigeration engineering.

A gradient-based strategy to construct efficient heat conduction path for arbitrary configurations

The heat conduction optimization problem is a widely investigated abstraction of various heat dissipation problems in industry and electronics cooling. This paper studies the optimization strategy that produces optimized heat conduction path made of high thermal conductivity materials, with the objective of lowering the hot spot temperature or improving temperature uniformity. The automatic differentiation (AD) technique is a general-purpose method to calculate the partial derivatives of any continuous function composed by elementary functions with respect to multiple independent variables. It is introduced to calculate the gradient of the objective function with respect to the thermal conductivity field, so that the optimization procedure can be guided directly towards the minimization of the desired objective function. This paper investigated the configurations of both continuous-value thermal conductivity and discrete-value thermal conductivity. Results indicate that the present optimization strategy is able to handle various types of boundary conditions and objective functions. The present method is compared with the iterative method based on variational principle (Var), showing that the AD method performs better than the Var method in most situations.

Minute level ultra-rapid and thousand copies level high-sensitive pathogen nucleic acid identification based on contactless impedance detection microsensor

Early screening for pathogens is crucial during pandemic outbreaks. Nucleic acid testing (NAT) is a valuable method for keeping pathogens from spreading. However, the long detection time and large size of the instruments involved significantly limited the efficiency of detection. This work described an integrated NAT microsensor that facilitated rapid and extremely sensitive detection based on nucleic acid amplification (NAA) on a chip. The biochip consisted of two layers incorporating a heater, a thermometer, an interdigital electrode (IDE) and a reaction chamber. The Pt electrode based heater and thermometer were utilized to maintain a specific temperature for the sample in the chamber. The thermometer exhibited a good linear correlation with a sensitivity of 9.36 Ω/°C and the heater achieved a heating efficiency of approximately 6.5 °C/s. Multiple ions were released during NAA, resulting in a decrease in the impedance of the amplification system solution. A large signal of impedance was generated by the released ions due to its linear correlation with the logarithm of the ion concentration. With this detection principle, IDE was employed for real-time monitoring of the in-chip reaction system impedance and NAA process. Specific nucleic acids from two pathogens (SARS-CoV-2, Vibrio vulnificus) were detected with this microsensor. The samples were qualitatively analyzed on microchip within 3 min, with a limit of detection (LOD) of 103 copies/μL. The proposed sensor presented several advantages, including reduced NAT time and increased sensitivity. Consequently, it has shown significant potential in rapid and high-quality nucleic acid testing for the field of epidemic prevention.

Study of the Electron cyclotron power deposition in TOMAS

Efficient Electron Cyclotron Resonance Heating (ECRH) breakdown and pre-ionization can be achieved with fundamental X-mode, while higher harmonics can introduce excessive stray radiation. Fundamental heating however is characterized by a low cut-off density, introducing additional power absorption mechanisms in the plasma. A good knowledge of these mechanisms is necessary to use fundamental X-mode as an efficient pre-ionization method. Numerous experiments were performed on the TOroidally MAgnetized System (TOMAS) to study the power deposition for ECRH in helium. It is a facility designed to study plasma production, wall conditioning and plasma-surface interactions and is operated by LPP-ERM/KMS at the FZ-Jülich. The influence of the injected power P EC and the magnetic field B 0 on the absorption mechanisms is examined, in order to reduce stray radiation and improve the absorption efficiency. This will allow to determine the best scenarios for plasma start-up and pre-ionization.

Asymptotic analysis of MHD chemically reacting boundary layer flow of Jeffrey hybrid nanofluid

AbstractFluids with enhanced heat transport characteristics are essential for efficient convection heat transportation. Hybrid nanofluids have demonstrated their effectiveness as viable substitutes for conventional heat transport fluids. This study explores the heat and mass exchange occurring within a chemically reactive, unsteady boundary layer flow of a copper oxide‐multi‐walled carbon nanotubes (CuO‐MWCNTs)/ethylene glycol Jeffrey hybrid nanofluid. Additionally, the influence of heat source/sink effects in a hydromagnetic environment is carefully added. The study employs a non‐Newtonian flow model and incorporates the Arrhenius activation energy for analysis. The hybrid nanofluid consists of a base fluid, ethylene glycol, enriched with copper oxide nanoparticles and multi‐walled carbon nanotubes. The governing coupled non‐linear partial differential equations are transformed into ordinary differential equations using similarity transformations, considering appropriate free stream, and wall boundary conditions; then, the Shooting method is employed to solve the resulting ordinary differential equations (ODEs) in MATLAB. The graphical and numerical outcomes are studied for various parameter combinations. The graphs illustrate the numerical results for the CuO‐MWCNTs/ethylene glycol hybrid nanofluid. These results are comprehensively discussed to analyze the influence of different thermo‐fluidic parameters on the Jeffrey hybrid nanofluid's heat, mass, and flow characteristics. The skin friction, Nusselt number, and Sherwood number are provided in a numerical table that displays the alterations of these parameters across various parameter values. As the Jeffrey fluid parameter rises, the Nusselt number and skin friction escalate, while the Sherwood number diminishes. Conversely, as the Deborah number rises, the Nusselt number and skin friction decline, but the Sherwood number increases. A comparative analysis with published results confirms the consistency of the present results.

Bioinspired, anti-fogging and de-icing transparent surfaces with flexible property

In cold environments, natural phenomena like icing, frost, and fog can significantly impede the functionality of optical windows. Consequently, there is a growing demand for optical windows that demonstrate anti-fogging and de-icing characteristics while maintaining flexibility and transparency with high optical clarity. The development of cost-effective and straightforward anti-fogging and de-icing elements encounters various challenges. The remarkable visual acuity of polar bear eyes in challenging weather conditions can be attributed to a tear film that covers the cornea and the thermoregulatory characteristics of their eyeballs. Inspired by the anti-fogging and anti-icing properties of polar bear eyes, a new flexible, transparent surface with heating capabilities has been developed. To address the limitations of conventional slippery surfaces that solely offer anti-fouling properties, a flexible internal heating unit is integrated into the slippery surface through a layered nesting technique to emulate the homothermal features of polar bear eyeballs. The slippery property of the PDMS surface can be attributed to a gel layer containing an auto-secretory lubricant. To preserve its optical properties, a new processing method that combines liquid metal microfluidics and femtosecond laser processing is employed. This technique can create narrow channels with a high length-to-diameter ratio, thereby reducing the impact on the transmission rate. The sample demonstrates self-cleaning, resistance to dust and pollution, and efficient electrical heating properties. Testing on fogging and freezing validates the practicality and effectiveness of these substances for applications in anti-fogging and de-icing.

Observation of alpha-particles in recent D–T experiments on JET

The fusion reaction between deuterium and tritium, D(T,n)4 He is the main source of energy in future thermonuclear reactors. Alpha-particles (4 He-ions) born with an average energy of 3.5 MeV transferring energy to the thermal plasma during their slowing down, should provide the self-sustained D–T plasma burn. The adequate confinement of α-particles is essential to provide efficient heating of the bulk plasma and steady burning of a reactor plasma. That is why the fusion-born α-particle studies have been a priority task in the second D–T experiments (DTE2) on the Joint European Torus (JET) to understand the main mechanisms of their slowing down, redistribution and losses and to develop optimal plasma scenarios. JET with Be-wall and W-divertor, enhanced auxiliary heating systems and improved energetic-particle diagnostic capabilities, producing significant population of α-particles, provided the possibility for comprehensive studying of the α-particle behaviour. Selected results of the confined and lost α-particle measurements, evidence of α-particle self-heating and assessments of the fusion performance are presented in this paper giving an opportunity for further modelling and extrapolation to the International Thermonuclear Experimental Reactor and burning plasma reactors.

Characterizing multi-pollutant emission impacts of sulfur reduction strategies from coal power plants

Fuel combustion for electricity generation emits a mix of health- and climate-relevant air emissions, with the potential for technology or fuel switching to impact multiple emissions together. While there has been extensive research on the co-benefits of climate policies on air quality improvements, few studies have quantified the effect of air pollution controls on carbon emissions. Here we evaluate three multi-pollutant emission reduction strategies, focused on sulfur dioxide (SO2) controls in the electricity sector. Traditional ‘add-on’ pollution controls like flue gas desulfurization (FGD) reduce SO2 emissions from coal combustion but increase emissions of nitrogen oxides (NO X ), volatile organic compounds (VOCs), fine particulate matter (PM2.5), and carbon dioxide (CO2) due to heat efficiency loss. Fuel switching from coal to natural gas and renewables potentially reduces all pollutants. We identified 135 electricity generation units (EGUs) without SO2 controls in the contiguous US in 2017 and quantified the unit-level emission changes using pollution control efficiencies, emission rates, fuel heat input, and electricity load. A cost-benefit analysis is conducted, considering pollution control costs, fuel costs, capital and operation and maintenance (O&M) costs, the monetized health benefits from avoided multi-pollutant, and the social cost of carbon as the benefit for carbon reduction. We find that add-on SO2 controls result in an average annual net benefit of $179.3 million (95% CI: $137.5-$221.0 million) per EGU, fuel switching from coal to natural gas, $432.7 million (95% CI: $366.4-$498.9 million) per EGU; and fuel switching from coal to renewable energy sources, $537.9 million (95% CI: $457.1-$618.9 million) per EGU. Our results highlight multi-pollutant emission reduction strategy as a cost-effective way to synergistically control air pollution and mitigate climate change.

Superspreading Surface with Hierarchical Porous Structure for Highly Efficient Vapor-Liquid Phase Change Heat Dissipation.

Superspreading surfaces with excellent water transport efficiency are highly desirable for addressing thermal failures through the liquid-vapor phase change of water in electronics thermal management applications. However, the trade-off between capillary pressure and viscous resistance in traditional superspreading surfaces with micro/ nanostructures poses a longstanding challenge in the development of superspreading surfaces with high cooling efficiency in confined spaces. Herein, a heat-treated hierarchical porous enhanced superspreading surface (HTHP) for highly efficient electronic cooling is proposed. Compared with the single porous structures in nanograss, nanosheets, and copper foam, HTHP with hierarchical honeycomb pores effectively resolves the trade-off effect by introducing large vertical through-pores to reduce viscous resistance, and connected small pores to provide sufficient capillary pressure synergistically. HTHP exhibits excellent capillary performance in both horizontal spreading and vertical rising. Despite a thickness of only 0.33mm, the as-prepared ultrathin vapor chamber (UTVC) fabricated to exploit the superior capillary performance of HTHP achieved effective heat dissipation with outstanding thermal conductivity (12121 Wm-1K-1), and low thermal resistance (0.1 KW-1) at a power of 5W. This regulation strategy based on hierarchical honeycomb porous structures is expected to promote the development of high-performance superspreading surfaces with a wide range of applications in thermal management.

Development of a novel Al-Si microcapsules with heat-resistant, high latent heat, and efficient solar heat absorption

Aluminum-silicon (Al-Si) alloys are prominent in high-temperature thermal storage due to their high thermal storage density, thermal conductivity, and low cost. Despite their potential, the corrosivity and chemical activity from their liquid phase leakage limit broader applications. The hydrothermal method, often used for encapsulating Al-Si into microencapsulated phase change materials (MEPCMs), consumes the core material, reducing latent heat values. Additionally, the inability to modify the shell material fails to meet multifunctional demands. Addressing solar thermal application needs, we developed a novel heat-resistant, high-latent-heat Al-Si MEPCMs using a “double-layer coating, sacrificial inner layer” approach. This method, originally proposed by our research group and first extended to the microencapsulation of high-temperature phase change materials (PCM), uses Al-12Si as the core, PMMA as the sacrificial layer, and SiO2 as the outer shell.The MEPCMs demonstrated an encapsulation efficiency of 90.7 % and a latent heat value of 454.9 J/g. By adjusting the core–shell ratio, the size of the internal void was optimized to enhance thermal performance and cyclic stability, with MEPCM-S3 maintaining 98.6 % of its latent heat (439.5 J/g) after 10 thermal shocks and 300 thermal cycles. Furthermore, surface loading of carbon black (CB) enhanced the spectral absorption rate to 87.72 % in the 200–2500 nm range, marking an 11 % increase. These modifiable, high-latent heat, and cycle-resistant Al-Si MEPCMs hold broad prospects for applications in high-temperature thermal storage and as next-generation efficient solar energy storage media.

Thermodynamic performance evaluation and optimization of a hybrid system integrating vacuum graphene-anode thermionic converters with direct carbon fuel cells

An efficient hybrid system integrating a direct carbon fuel cell (DCFC) with a vacuum graphene-anode thermionic converter (VGTC) is proposed for cogeneration. The VGTC efficiently recycles waste heat released from the DCFC and generate additional electricity, significantly improving energy utilization efficiency and economic performance. A comprehensive mathematical model is developed to quantitatively assess the thermodynamic performance of the hybrid system, taking into account the overpotential losses of the DCFC and the irreversible energy losses occurring within the system. The results show that at an operating temperature of 923 K, the hybrid system can achieve a maximum power density of 466 W/m2, which is approximately 1.34 times that of a single DCFC, indicating a significant improvement in output performance. Besides, the optimal operating region and parameter selection criteria for the hybrid system are determined using finite-time thermodynamic optimization theory. Furthermore, the effects of essential parameters on the output performance of the hybrid system, such as the operating temperature of the DCFC, the heat transfer coefficient, the Fermi level of graphene, the work function of the cathode, the thermal emissivity, and the reflectivity of the back mirror, are investigated. Finally, the comparative study shows that the proposed hybrid system outperforms other previously reported hybrid systems regarding output electric power and conversion efficiency due to the efficient high-grade waste heat recovery and energy conversion by the VGTC.

Hybrid Nanofluid Flow over a Shrinking Rotating Disk: Response Surface Methodology

For efficient heating and cooling applications, minimum wall shear stress and maximum heat transfer rate are desired. The current study optimized the local skin friction coefficient and Nusselt number in Al2O3-Cu/water hybrid nanofluid flow over a permeable shrinking rotating disk. First, the governing equations and boundary conditions are solved numerically using the bvp4c solver in MATLAB. Von Kármán’s transformations are used to reduce the partial differential equations into solvable non-linear ordinary differential equations. The augmentation of the mass transfer parameter is found to reduce the local skin friction coefficient and Nusselt number. Higher values of these physical quantities of interest are observed in the injection case than in the suction case. Meanwhile, the increase in the magnitude of the shrinking parameter improved and reduced the local skin friction coefficient and Nusselt number, respectively. Then, response surface methodology (RSM) is conducted to understand the interactive impacts of the controlling parameters in optimizing the physical quantities of interest. With a desirability of 66%, the local skin friction coefficient and Nusselt number are optimized at 1.528780016 and 0.888353037 when the shrinking parameter (λ) and mass transfer parameter (S) are −0.8 and −0.6, respectively.

Topology reduction through machine learning to accelerate dynamic simulation of district heating

District heating networks (DHNs) provide an efficient heat distribution solution in urban areas, accomplished through interconnected and insulated pipes linking local heat sources to local consumers. This efficiency is further enhanced by the capacity of these networks to integrate renewable heat sources and thermal storage systems. However, integration of these systems adds complexity to the physical dynamics of the network, necessitating complex dynamic simulation models. These dynamic physical simulations are computationally expensive, limiting their adoption, particularly in large-scale networks. To address this challenge, we propose a methodology utilizing Artificial Neural Networks (ANNs) to reduce the computational time associated with the DHNs dynamic simulations. Our approach consists in replacing predefined clusters of substations within the DHNs with trained surrogate ANNs models, effectively transforming these clusters into single nodes. This creates a hybrid simulation framework combining the predictions of the ANNs models with the accurate physical simulations of remaining substation nodes and pipes. We evaluate different architectures of Artificial Neural Network on diverse clusters from four synthetic DHNs with realistic heating demands. Results demonstrate that ANNs effectively learn cluster dynamics irrespective of topology or heating demand levels. Through our experiments, we achieved a 27% reduction in simulation time by replacing 39% of consumer nodes while maintaining acceptable accuracy in preserving the generated heat powers by sources.

Investigation of sawdust microwave-assisted pyrolysis by machine learning, Part I: Optimization insights by large language models

Microwave-assisted catalytic pyrolysis shows promise for efficiently converting waste biomass, such as sawdust, into valuable bio-oil. However, current research on pyrolysis characteristics predominantly relies on conventional trial-and-error experimentation. This work pioneers the first use of large language models (LLMs) to gain insights into optimizing bio-oil yield by analyzing the effects of catalyst loading and pretreatment temperature on product distribution. Additionally, we encode the textual LLM outputs into distributed vectors via Word2Vec and concatenate them with artificial neural network (ANN) embeddings, capitalizing on the complementary strengths of data-driven and language models. Our results demonstrate superior accuracy and interpretability, providing better optimization insights on heating dynamics and energy efficiency while avoiding extensive experimental costs. This research establishes the prospects of LLMs as supplementary tools for thermochemical conversion studies, potentially reducing resource-intensive lab trials through reliable data-driven predictions.

Unraveling interfacial thermal transport in β-Ga2O3/h-BN van der Waals heterostructures

As global power consumption rapidly increases with generation of significant amount of heat, efficient thermal management in electronic equipments becomes an urgent task, which requires a comprehensive understanding on thermal transport in heterostructures within devices. Here, we present detailed examination on the interfacial thermal transport of van der Waals (vdW) heterostructures, composed of β-Ga2O3 and hexagonal boron nitride (h-BN) multilayers. Through extensive molecular dynamics simulations, we show that the interfacial thermal conductance (ITC) of β-Ga2O3/h-BN system becomes as high as 136.8MWm−2K−1, and the high ITC value results from substantial phonon interaction across the interface. In addition to the pristine interface, the effect of structural modulation including strain, vacancies and substitutional defects in h-BN multilayers on the ITC is also analyzed, and it is demonstrated that there exists ranges of strain values and defect concentrations which increase the ITC, and that the enhanced ITC is the result of the interplay among the interfacial distance, the overlap in the phonon density of states and elastic mismatch between β-Ga2O3 and h-BN multilayers. These results not only provide insights into understanding interfacial phonon transport in vdW systems but also offer guiding principles for designing efficient heat dissipators in device applications.

Sn99Ag0.3Cu0.7–TiO2 composite solder joints and their influence on thermal parameters of power components

PurposeThis paper aims to investigate the influence of composite solder joint preparation on the thermal properties of metal-oxide-semiconductor field-effect transistors (MOSFETs) and the mechanical strength of the soldered joint.Design/methodology/approachReinforced composite solder joints with the addition of titanium oxide nanopowder (TiO2) were prepared. The reference alloy was Sn99Ag0.3Cu0.7. Reinforced joints differed in the weight percentage of TiO2, ranging from 0.125 to 1.0 Wt.%. Two types of components were used for the tests. The resistor in the 0805 package was used for mechanical strength tests, where the component was soldered to the FR4 substrate. For thermal parameters measurements, a power element MOSFET in a TO-263 package was used, which was soldered to a metal core printed circuit board (PCB) substrate. Components were soldered in batch IR oven.FindingsShear tests showed that the addition of titanium oxide does not significantly increase the resistance of the solder joint to mechanical damage. Titanium oxide addition was shown to not considerably influence the soldered joint’s mechanical strength compared to reference samples when soldered in batch ovens. Thermal resistance Rthj-a of MOSFETs depends on TiO2 concentration in the composite solder joint reaching the minimum Rthj at 0.25 Wt.% of TiO2.Research limitations/implicationsMechanical strength: TiO2 reinforcement shows minimal impact on mechanical strength, suggesting altered liquidus temperature and microstructure, requiring further investigation. Thermal performance: thermal parameters vary with TiO2 concentration, with optimal performance at 0.25 Wt.%. Experimental validation is crucial for practical application. Experimental confirmation: validation of optimal concentrations is essential for accurate assessment and real-world application. Soldering method influence: batch oven soldering may affect mechanical strength, necessitating exploration of alternative methods. Thermal vs mechanical enhancement: while TiO2 does not notably enhance mechanical strength, it improves thermal properties, highlighting the need for balanced design in power semiconductor assembly.Practical implicationsIncorporating TiO2 enhances thermal properties in power semiconductor assembly. Optimal concentration balancing thermal performance and mechanical strength must be determined experimentally. Batch oven soldering may influence mechanical strength, requiring evaluation of alternative techniques. TiO2 composite solder joints offer promise in power electronics for efficient heat dissipation. Microstructural analysis can optimize solder joint design and performance. Rigorous quality control during soldering ensures consistent thermal performance and mitigates negative effects on mechanical strength.Social implicationsThe integration of TiO2 reinforcement in solder joints impacts thermal properties crucial for power semiconductor assembly. However, its influence on mechanical strength is limited, potentially affecting product reliability. Understanding these effects necessitates collaborative efforts between researchers and industry stakeholders to develop robust soldering techniques. Ensuring optimal TiO2 concentration through experimental validation is essential to maintain product integrity and safety standards. Additionally, dissemination of research findings and best practices can empower manufacturers to make informed decisions, fostering innovation and sustainability in electronic manufacturing processes. Ultimately, addressing these social implications promotes technological advancement while prioritizing consumer trust and product quality in the electronics industry.Originality/valueThe research shows the importance of the soldering technology used to assemble MOSFET devices.

Atmospheric alchemy: The energy and cost dynamics of direct air carbon capture

Abstract Amid a relentless global climate crisis, the 28th Conference of the Parties (COP28) spotlighted Direct Air Carbon Capture (DACC) as a key intervention to mitigate escalating temperatures and CO2 levels. The Intergovernmental Panel on Climate Change (IPCC) underscores the urgency of this challenge, stipulating the need for robust CO2 removal strategies. It sets a daunting yet crucial target: capture 85 million metric tons of CO2 by 2030, escalating to 980 million metric tons by 2050, to achieve net-zero emissions (IEA, Executive Summary—Direct Air Capture 2022—Analysis. https://www.iea.org/reports/direct-air-capture-2022/executive-summary). Despite this imperative, the existing 19 operational DAC facilities globally face significant barriers, including prohibitive costs and stringent regulations, which impede their large-scale application (Ozkan et al.). Current status and pillars of direct air capture technologies. Iscience (2022). While COP28 stopped short of delineating a definitive roadmap for DAC, this article addresses a vital aspect of this technology: DAC processes’ substantial energy and heat requirements, which are integral to their operational efficiency and economic viability. This article illuminates pathways for future technological evolution and cost optimization through an in-depth analysis of these requirements, thereby charting a course toward a more effective and scalable DAC infrastructure. Graphical abstract Highlights With atmospheric CO2 exceeding 420 ppm, the clock is ticking on the climate crisis. DAC offers a revolutionary approach to directly remove this excess CO2, acting as a critical tool in our fight for a sustainable future. However, current DAC systems face the challenge of high energy consumption. Continuous fan operation for air intake and sorbent material regeneration, consuming nearly 2000–3000 kWh per ton of CO2 captured, are major contributors. Optimizing these processes is crucial. Advancements in sorbent efficiency, system design that minimizes parasitic energy losses, and seamless integration with renewable energy sources are key to slashing DAC’s energy demands. By reducing its carbon footprint and enhancing economic viability, these advancements can unlock the full potential of DAC to become a game-changer in combating climate change and securing a cleaner future for our planet. Discussion Given the significant energy and heat requirements of DACC processes, what technological innovations are necessary to make these systems more energy efficient and economically viable? Considering the substantial energy demands of DACC processes, what are the most promising avenues for reducing these requirements to enhance the technology's scalability and cost-effectiveness? How can current technological limitations be overcome to scale up DACC effectively? What role could renewable energy sources play in meeting the energy and heat demands of DACC facilities, and how might this integration impact the overall carbon footprint of the carbon capture process? How do the energy and heat requirements of DACC technologies influence their location and infrastructure needs, particularly in relation to energy sources and heat sinks? What technological innovations or advancements are currently being explored to optimize the energy and heat efficiency of DACC processes, and what challenges do they face in terms of implementation and scaling? Given the significant role of DACC in achieving net-zero emissions targets, how can policy and regulatory frameworks be designed to support the development and deployment of energy-efficient DACC solutions?

Analytical and numerical examinations on the stability investigation of Casson nanofluid flow in a permeable layer controlled by vertical throughflow

Purpose The purpose of the study is to analytically as well as numerically investigate the weight of throughflow on the onset of Casson nanofluid layer in a permeable matrix. This study examines both the marginal and over stable kind of convective movement in the system. Design/methodology/approach A double-phase model is used for Casson nanofluid, which integrates the impacts of thermophoresis and Brownian wave, whereas for flow in the porous matrix the altered Darcy model is occupied under the statement that nanoparticle flux is disappear on the boundaries. The resultant eigenvalue problem is resolved analytically as well as numerically with the help of Galerkin process with the Casson nanofluid Rayleigh–Darcy number as the eigenvalue. Findings The findings revealed that the throughflow factor postpones the arrival of convective flow and reduces the extent of convective cells, whereas the Casson factor, the Casson nanoparticle Rayleigh–Darcy number and the reformed diffusivity ratio promote convective motion and also decrease the extent of convective cells. Originality/value Controlling the convective movement in heat transfer systems that generate high heat flux is a real mechanical challenge. The proposed framework proved that the use of throughflow is one of the most important ways to control the convective movement in Casson nanofluid. To the best of the authors’ knowledge, no inspection has been established in the literature that studies the outcome of throughflow on the Casson nanofluid convective flow in a porous medium layer. However, the convective flow of Casson nanofluid finds many applications in improving heat transmission and energy efficiency in a range of thermal systems, such as the cooling of heat-generating elements in electronic devices, heat exchangers, pharmaceutical practices and hybrid-powered engines, where throughflow can play a significant role in controlling the convective motion.