Energy-efficient Applications Research Articles

Application of Triple Glazing Thickness Optimization Based on Artificial Fish Swarm Algorithm

In response to the growing demand for energy-efficient building designs in cold northern regions, this study explores the optimization of triple glazing thickness to maximize the transmission of solar energy within the wavelength range of 300-2000 nm. The optimization employs the Artificial Fish Swarm Algorithm (AFSA), which is used to iteratively determine the optimal combination of glass thicknesses. A transmittance model of solar radiation through triple glazing is established, where the thicknesses of the three glass layers are treated as variables. The study shows that the optimized thickness combination significantly enhances the indoor heating effect by maximizing solar energy incidence, offering theoretical support and practical guidance for energy-saving building designs in cold climates. Parameter settings of the AFSA, including perception range, step size, and crowding factor, are analyzed to understand their influence on optimization performance. The results suggest that AFSA efficiently addresses complex optimization problems, demonstrating its potential in optimizing material properties for energy-efficient applications. Future directions include multi-objective optimization considering additional factors such as thermal insulation and cost, algorithmic improvements to enhance search accuracy, and experimental validation of the results in real-world conditions. This research provides a scientific foundation for integrating advanced optimization algorithms into the sustainable design of building materials.

Recent advances in nanomaterial-enabled chemiresistive hydrogen sensors.

With the growing adoption of hydrogen energy and the rapid advancement of Internet of Things (IoT) technologies, there is an increasing demand for high-performance hydrogen gas (H2) sensors. Among various sensor types, chemiresistive H2 sensors have emerged as particularly promising due to their excellent sensitivity, fast response times, cost-effectiveness, and portability. This review comprehensively examines the recent progress in chemiresistive H2 sensors, focusing on developments over the past five years in nanostructured materials such as metals, metal oxide semiconductors, and emerging alternatives. This review delves into the underlying sensing mechanisms, highlighting the enhancement strategies that have been employed to improve sensing performance. Finally, current challenges are identified, and future research directions are proposed to address the limitations of existing chemiresistive H2 sensor technologies. This work provides a critical synthesis of the most recent advancements, offering valuable insights into both current challenges and future directions. Its emphasis on innovative material designs and sensing strategies will significantly contribute to the ongoing development of next-generation H2 sensors, fostering safer and more efficient energy applications.

Ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales

ABSTRACTAs we enter the exascale computing era, efficiently utilizing power and optimizing the performance of scientific applications under power and energy constraints has become critical and challenging. We propose a low‐overhead autotuning framework to autotune performance and energy for various hybrid MPI/OpenMP scientific applications at large scales and to explore the tradeoffs between application runtime and power/energy for energy efficient application execution, then use this framework to autotune four ECP proxy applications—XSBench, AMG, SWFFT, and SW4lite. Our approach uses Bayesian optimization with a Random Forest surrogate model to effectively search parameter spaces with up to 6 million different configurations on two large‐scale HPC production systems, Theta at Argonne National Laboratory and Summit at Oak Ridge National Laboratory. The experimental results show that our autotuning framework at large scales has low overhead and achieves good scalability. Using the proposed autotuning framework to identify the best configurations, we achieve up to 91.59% performance improvement, up to 21.2% energy savings, and up to 37.84% EDP (energy delay product) improvement on up to 4096 nodes.

Thermoelectric Materials: A Scientometric Analysis of Recent Advancements and Future Research Directions

This scientometric study looks at the current trend in thermoelectric materials research and explores the evolving domain of thermoelectric materials research using a combination of bibliometric and scientometric methodologies. The analysis examines global research trends from a dataset of over 37,739 research articles, focusing on thematic evolution, annual growth rates, and significant contributions. Six principal research clusters were identified, encompassing energy conversion, material synthesis and nanostructures (the most prominent cluster), computational modeling and material properties, measurement and characterization, material performance enhancement, and material processing and microstructure. Each cluster highlights a critical aspect of the field, reflecting its broad scope and depth. The key findings reveal a marked annual increase in research output, highlighting the growing global importance of thermoelectric materials in sustainable energy solutions. This is especially evident in the significant contributions from China and the USA, emphasizing their leadership in the field. The study also highlights the collaborative nature of thermoelectric research, showing the impact of global partnerships and the synergistic effects of international collaboration in advancing the field. Overall, this analysis provides a comprehensive overview of the thermoelectric materials research landscape over the past decade, offering insights into trends, geographic contributions, collaborative networks, and research growth. The findings underscore thermoelectric materials’ vital role in addressing global energy challenges, highlighting recent advancements and industrial applications for energy efficiency and sustainability.

Impact of employing phase change material in building wall on energy consumption and thermal comfort level

Energy crises are becoming a problem for many, most of the energy being produced is utilized in buildings. Building design and materials that are used in buildings play a vital role in saving electricity. Sustainable cities are one of the eleventh goal of Sustainable Development Goals to be achieved and this study is in context of SDGs for developing tools to create this globe sustainable and efficient society for humans. Phase change material is a type of material that can absorb and release heat energy as it changes between solid and liquid states. This ability to store and release thermal energy makes PCM a promising material for use in building insulation, Heating Ventilation Air Conditioning Systems, and other energy efficient applications. The use of PCM in buildings has the potential to significantly reduce energy consumption and improve thermal comfort levels. By incorporating PCM into building envelopes, such as walls, roofs, and floors, the material can absorb excess heat during the day and release it at night, helping to regulate indoor temperatures and reduce the need for heating and cooling systems. This study investigates the impact of using PCM in building envelopes. In this regard office building rooms are modelled in CAD software and are simulated in energy plus software. The simulation results are validated by considering the experiment and numerical study as a reference from paper. Model room is simulated for Hyderabad, Pakistan. Building envelopes without PCM have conduction rate of around 106.6 W/m2, whereas building envelopes with PCM have conduction rate around 42 W/m2. This shows that utilization of PCM reduced heat conduction up to around 40%. PCM reduced energy consumption of around 33.25 kWh/year/m2. Results show that without PCM air temperature was above the thermal comfort value. it reached 300C in hot months, it reduced up to 270C with the incorporation of PCM.

Tailoring Light-Harvesting in Zn-Porphyrin and Carbon Fullerene based Donor-Acceptor Complex through Ethynyl-Extended Donor π-Conjugation.

Organic photovoltaic efficiency though currently limited for practical applications, can be improved by means of various molecular-level modifications. Herein the role of extended donor -conjugation through ethynyl-bridged meso-phenyl/pyridyl on the photoinduced charge-transfer kinetics is studied in noncovalently bound Zn-Porphyrin and carbon-fullerene based donor-acceptor complex using time-dependent optimally tuned range-separated hybrid combined with the kinetic rate theory in polar solvent. Noncovalent dispersive interaction is identified to primarily govern the complex stability. Ethynyl-extended -conjugation results in red-shifted donor-localized Q-band with substantially increased dipole oscillator strength and smaller exciton binding energy, suggesting greater light-harvesting efficiency. However, the low-lying charge-transfer state below to the Q-band is relatively less affected by the ethynyl-extended -conjugation, yielding reduced driving forces for the charge-transfer. Detailed kinetics analysis reveals similar order of charge-transfer rate constants (~1012 s-1) for all donor-acceptor composites studied. Importantly, enhanced light-absorption, smaller exciton binding energy and similar charge-transfer rates together with reduced charge-recombination make these complexes suitable for efficient photoinduced charge-separation. These findings will be helpful to molecularly design the advanced organic donor-acceptor blends for energy efficient photovoltaic applications.

The Impact of 3D Printing Technology on the Improvement of External Wall Thermal Efficiency—An Experimental Study

Three-dimensional printing technology continues to evolve, enabling new applications in manufacturing. Extensive research in the field of biomimetics underscores the significant impact of the internal geometry of building envelopes on their thermal performance. Although 3D printing holds great promise for improving thermal efficiency in construction, its full potential has yet to be realized, and the thermal performance of printed building components remains unexplored. The aim of this paper is to experimentally examine the thermal insulation characteristics of prototype cellular materials created using 3D additive manufacturing technologies (SLS and DLP). This study concentrates on exploring advanced thermal insulation solutions that could enhance the energy efficiency of buildings, cooling systems, appliances, or equipment. To this end, virtual models of sandwich composites with an open-cell foam core modeled after a Kelvin cell were created. They were characterized by a constant porosity of 0.95 and a pore diameter of the inner core of the composites of 6 mm. The independent variables included the different material from which the composites were made, the non-uniform number of layers in the composite (one, two, three, and five layers) and the total thickness of the composite (20, 40, 60, 80, and 100 mm). The impact of three independent parameters defining the prototype composite on its thermal insulation properties was assessed, including the heat flux (q) and the heat transfer coefficient (U). According to the experimental tests, a five-layer composite with a thickness of 100 mm made of soybean oil-based resin obtained the lowest coefficient with a value of U = 0.147 W/m2·K.

MXene quantum dots modified pitaya peel-based composite phase change material with excellent thermal properties for building energy efficiency applications

Bio-based materials have attracted much attention because their application in the construction field is conducive to energy saving and emission reduction. In this paper, a bio-based composite phase change material (CPCM) was prepared by utilizing pitaya peel as a bio-based material, MXene quantum dots (MQDs) as a modified material, and polyethylene glycol (PEG) as a phase change medium. MXene quantum dots dispersed in the pitaya peel-based porous carbon skeleton enhanced the three-dimensional thermal conductivity network of the porous carbon skeleton somewhat improved the thermal conductivity (0.676 W/mK) of the polyethylene glycol/MXene quantum dots-modified pitaya peel-based porous carbon foam (PPF) composite phase change material (PEG/PPF@M). It is worth noting that PEG/PPF@M has excellent thermal stability and its enthalpy is basically unchanged after 100 cycles, which proves the recyclable stability of PEG/PPF@M in practical applications. PEG/PPF@M has great potential for thermal management of buildings and electronic components. Overall, a novel multifunctional CPCM was prepared in this study using a simple process method, which can not only be applied in electronic products to improve the service life of electronic components, but also in the field of construction to realize energy saving and emission reduction, as well as the recycling and reuse of waste.

Numerical and Experimental Study on the Performance of Photovoltaic—Trombe Wall in Hot Summer and Warm Winter Regions: Energy Efficiency Matching and Application Potential

Enhancing the energy efficiency of building envelopes is one of the key strategies for energy conservation and reducing consumption in buildings. This study employs numerical research methods to explore the impact of crucial factors such as solar cell coverage, air channel height, indoor relative humidity, and indoor wind speed on the power generation performance and thermal comfort of a photovoltaic (PV)—Trombe wall. The dynamic changes in optical and thermal performance and energy efficiency matching mechanisms of this system are also discussed in hot summer and warm winter regions. The research findings indicate that the periods of good thermal comfort and power generation efficiency for humans are from 9:00 to 17:00 in winter. In summer, these periods are from 5:00 to 8:00 as well as from 17:00 to 20:00. When the system height is 2 m, the electricity price for power supplied by the PV—Trombe wall system is 25% lower than the residential price, with an annual energy generation of 322.5 kWh/m2 of solar panel, which can save USD 6.35 in costs. Moreover, an experiment is conducted to investigate the thermoelectric correlation by constructing a traditional Trombe wall and an external PV—Trombe wall. When the coverage reached 52.08%, the overall system efficiency was maximized. At a coverage of 78.12%, the system’s thermal efficiency was at its lowest, while the maximum power generation was 510.3 W. It can be seen that the PV—Trombe wall possesses good economic benefits and energy saving as well as emission reduction potential in hot summers and warm winters regions, and the smooth implementation of related works will effectively promote its applications and promotions.

Energy-Efficient Application of CrN Coating on Low-Alloy Tool Steel: Comparative Analysis of Technological Processes

Abstract This research examines the technological processes of applying CrN coating on low-alloy tool steel, focusing on the comparison between hardening-tempering-coating (HTC) and hardening-coating (HC) processes, with an emphasis on energy savings. The study investigates the chemical composition, microstructure, mechanical properties, fractography, residual stress, and corrosion resistance of the coated tool steel. Notably, the results indicate no significant differences in the microstructural, mechanical, and corrosion properties between the HTC and HC processes, suggesting that tempering may be excluded without compromising the quality. This study introduces a novel approach to tool steel coating, which improves energy efficiency while maintaining high-quality outcomes. The findings highlight potential improvements in industrial applications, offering an energy-efficient alternative that does not sacrifice the performance or durability of the tool steel. This advancement could lead to significant improvements in manufacturing efficiency and sustainability.

Automated model order reduction for building thermal load prediction using smart thermostats data

This paper presents a methodology to automatically determine the structure of sufficiently accurate grey-box models for model predictive control, energy efficiency and flexibility applications in buildings. The methodology is based on model reduction and system identification techniques, with a path that enhances data pre-processing, a multistage order reduction, and parameter estimation. The model structure is determined with a cascade approach that either neglects, keeps, or aggregates thermal zones by using discrete and continuous frequency domain techniques. Once the optimal structure is identified, the parameters are calibrated with the measured data from smart thermostats, using the model predictive control relevant identification method. The methodology is applied to a monitored house located in Québec, Canada. The developed algorithm identifies adjacent zones, even when the building layout is unknown, by studying indoor temperature fluctuations. The results concerning the model creation suggest that, for this specific building, the aggregation by floor is the most efficient way for creating reduced order thermal models, limiting uncertainty due to thermal zone interaction. This methodology provides control-oriented models that accurately predict response up to 24-h ahead with Root Mean Square Error less than 0.5 °C and acceptable Fitness Function values for the minimum number of selected parameters. Finally, several scenarios demonstrate the insights gained from using grey-box building thermal models for design, control, and retrofitting applications.

Ultrafast Conversion of Water and Oxygen Molecules With Dissociation of Hydrogen Bonding Effect to Achieve Extra-High Energy Efficiency of Secondary Metal-Air Batteries.

Metal-air secondary batteries with ultrahigh specific energies have received vast attention and are considered new promising energy storage. The slow redox reactions between oxygen-water molecules lead to low energy efficiency (55-71%) and limited applications. Herein, it is proposed that the MIL-68(In)-derived porous carbon nanotube supports the CoNiFeP heteroconjugated alloy catalyst with an overboiling point electrolyte to achieve the ultrahigh oxidation rate of water molecules. Structural characterization and density functional theorycalculations reveal that the new catalyst greatly reduces the free energy of the process, and the overboiling point further accelerates the dissociation of O─H and hydrogen bonds, and the release of O2 molecules, achieving an extra-low overpotential of 110mV@10mAcm-2 far lower than commercial Ir/C catalysts of 192mV at 125°C and state-of-the-art. Furthermore, the energy efficiency of assembled rechargeable zinc-air batteries begins to break through at 85°C, jumps at 100°C, and reaches ultrahigh energy efficiency of 88.1% at 125°C with an ultralow decay rate of 0.0068% after 150 cycles far superior to those of reported metal-air batteries. This work provides a new catalyst and electrolyte joint-design strategy and reexamines the battery operating temperature to construct higher energy efficiency for secondary fuel cells.

Effect of Ca, Ba, Be, Mg, and Sr Substitution on Electronic and Optical Properties of XNb2Bi2O9 for Energy Conversion Application Using Generalized Gradient Approximation–Perdew–Burke–Ernzerhof

Bismuth layered structure ferroelectrics (BLSFs), also known as Aurivillius phase materials, are ideal for energy-efficient applications, particularly for solar cells. This work reports the first comprehensive detailed theoretical study on the fascinating structural, electronic, and optical properties of XNb2Bi2O9 (X = Ca, Ba, Be, Mg, Sr). The Perdew–Burke–Ernzerhof approach and generalized gradient approximation (GGA) are implemented to thoroughly investigate the structural, bandgap, optical, and electronic properties of the compounds. The optical conductivity, band topologies, dielectric function, bandgap values, absorption coefficient, reflectivity, extinction coefficient, refractive index, and partial and total densities of states are thoroughly investigated from a photovoltaics standpoint. The material exhibits distinct behaviors, including significant optical anisotropy and an elevated absorption coefficient > 105 cm−1 in the region of visible; ultraviolet energy is observed, the elevated transparency lies in the visible and infrared regions for the imaginary portion of the dielectric function, and peaks in the optical spectra caused by inter-band transitions are detected. According to the data reported, it becomes obvious that XNb2Bi2O9 (X = Ca, Ba, Be, Mg, and Sr) is a suitable candidate for implementation in solar energy conversion applications.

Short and sweet: balancing energy savings and cleaning performance to identify efficient short-cycles for domestic dishwashers

Abstract Optimizing the energy efficiency of household appliances is crucial to appliance manufacturers, energy suppliers, governments and, almost importantly, consumers. For the reliable cleaning of normally soiled dishes, consumers can save energy by using Eco-programs instead of Intensive- or Auto-programs, but this means that they have to accept cleaning times of up to 4 h. Consequently, the acceptance for these programs is not very high, despite consumers’ high willingness to save energy and water. Short-cycles that run for less than 55 min and use equal to less energy on average than Eco-programs have a high consumer potential. However, according to manufacturers, these are rather designed for lightly soiled or pre-treated dishes. Considering the Sinner’s circle, the cleaning result depends on the interaction of temperature, time, mechanics and chemistry, so we investigated the extent to which using a commercially available detergent, thus fully exploiting the “chemistry” component of the Sinner’s circle, can save time, temperature, water and, most importantly, energy in the end. Our results show that there are Short-program combinations using a commercially available detergent that reliably clean normally soiled dishes in less than 55 min and typically 30–40 min with significantly lower energy consumption than average Eco-cycles.

Green I.T and Datacenter: a Study of Environmental Management Indicators

Objective: Identify the environmental indicators from the ABNT ISO NBR 14031 standard applicable to data centers to improve energy efficiency and environmental management. Theoretical Framework: The study addresses concepts of Green IT, practices for data center efficiency, and the indicators from the ABNT NBR ISO 14031 standard, including environmental, managerial, operational, and condition performance indicators. Method: Bibliometric research to support the theme, through searches on the Scopus and IEEE platforms, with content analysis of the main references, including the NBR ISO 14031 standards. Results and Discussion: Operational indicators from the NBR ISO 14031 standard were identified and adapted for data centers, such as the quantity of reused materials, energy used and saved, and specific emissions. The practical application of these indicators was detailed. Research Implications: The research contributes to the application of Green IT practices and energy efficiency in data centers, providing a basis for the adoption of environmental management indicators. Originality/Value: Although there are various individual studies related to Green IT or data centers, there are few studies relating these themes together. Thus, this study fills this gap by promoting an integrated approach to Green IT and environmental management, and providing support for data center managers towards Green IT.

An Area and Power Optimization for Level Shifters using 45nm CMOS Technology

Abstract: Modern integrated circuits require level shifters as essential parts to enable communication between circuits running at various voltage levels. Design-wise, the Level Shifter has a minimal silicon footprint due to its limited component count and operates with minimal power usage, making it well-suited for energy-efficient applications. This work implements CMOS voltage level shifter, also known as conventional CMOS level shifter. The level shifter's overall power and area usage are compared. CMOS level shifters simulations are carried out using CADENCE tool. The simulation's outcomes are implemented in conventional 45-µm CMOS technology. Index Terms: Level shifters, - Very Large-Scale Integrated Circuits (VLSI), level shifter, low power

Do Opportunity Costs of Regulations Appropriately Benefit or Inappropriately Burden Disadvantaged Consumers?

Abstract President Biden’s first-day memo “Modernizing Regulatory Review” directs the Office of Management and Budget to “propose procedures that take into account the distributional consequences of regulations… to ensure that regulatory initiatives appropriately benefit and do not inappropriately burden disadvantaged, vulnerable, or marginalized communities.” This paper makes two contributions. First, it discusses how economic analysis can transparently provide the information needed to make value-judgments about what distributional effects are appropriate and inappropriate. Second, it discusses the distributional consequences of regulations that are either designed to reduce internalities or might have the additional benefit of reducing internalities. Examples include tobacco product regulations, appliance energy efficiency standards, and automobile fuel efficiency standards. In many cases, the regulations will increase the prices or decrease the availability of goods that disadvantaged consumers prefer. This paper discussed how to determine whether restricting their consumption opportunities creates net benefits or net costs for disadvantaged consumers. Inframarginal consumers who do not change their consumption face higher opportunity costs but do not receive any benefits from reduced internalities. Empirical challenges include the need to quantify the fraction of inframarginal consumers and the size of the internalities.

Enhancing thermal performance in enclosures filled with nanofluids subjected to sinusoidal heating: a numerical study

ABSTRACT This study conducts a comprehensive numerical investigation into enhancing thermal transfer within square enclosures filled with water-based oxide nanoparticle suspensions, subjected to central sinusoidal heating. Further flow configuration, influenced by an inclined magnetic field, is designed with a focus on enhancing thermal efficiency for engineering applications. Key innovations include the application of sinusoidal heating elements to enhance thermal performance significantly. Computational analysis supported by finite element analysis, quantifies the impact of these parameters on flow dynamics and thermal transmission, presenting a substantial advance in the understanding of nanofluid-filled enclosure thermal management. The study reveals that the undulation of the heating element plays a crucial role in the heat transfer rate, with improvements observed as undulation increases. The introduction of magnetic fields further controls flow distribution and buoyancy effects, as demonstrated by our findings that an increase in the Rayleigh number correlates with enhanced convection, dominating the cavity's thermal dynamics. Additionally, the report outlines the conditions under which the Nusselt number increases, indicating enhanced thermal performance. These insights are pivotal for designing optimized heat transfer systems and energy-efficient applications, setting a new benchmark for thermal management strategies in practical engineering contexts.

Achieving net negative sensible heat release from buildings

Heat is added to the surroundings as a result of replacing natural landscapes with buildings. This includes waste heat from air conditioning systems and heat transferred into the environment from exterior surfaces. Here, we propose a new concept of “negative sensible heat release” from buildings—that is, buildings that put less sensible heat into the environment than that released from the unbuilt terrain upon which the building was constructed. We explore the potential for net negative sensible heat releasing buildings through simulation studies in hot arid and humid cities—Phoenix, and Houston. Results show that it is possible to achieve net negative sensible heat release from low-rise office buildings by simply increasing roof and wall solar reflectance using existing technologies. While typical 2-story office buildings can generate average heat fluxes of around 100 W/m2 (based on building footprint area), by increasing solar reflectance of the roof from 0.2 to 0.9 and solar reflectance of the walls from 0.2 to 0.65, the same building can generate net negative sensible heating of 20 to 40 W/m2. Increasing building insulation and energy efficiency of appliances and air conditioning equipment can further reduce the heat release from buildings. This points to a compelling mechanism whereby buildings can be designed or retrofitted to have a beneficial impact on the local thermal environment.

A study on creating energy efficient cloud-connected user applications using the RMVRVM paradigm

Many applications that run on smartphones are heavy on User Interface (UI) and depend on back-end services deployed on the cloud to fetch the required data through REST-based API. Because of the large number of devices actively being used, their collective energy consumption is very significant. Saving energy on these devices is beneficial not only for reducing the carbon footprint but also for the end users as it results in longer battery life. The data fetched by these applications using the REST API is generally processed, filtered and made compliant with the user interface through a paradigm called the Model View View-Model (MVVM).In our previous work Singh (2022a), we proposed a novel Remote-Model View Remote-View-Model (RMVRVM) paradigm to reduce battery consumption by MVVM-based UI-centric cloud-connected applications. In this paper, we present new results and details of the architecture and properties of the RMVRVM paradigm, discuss the complexity shift, provide a migration framework to help practitioners migrate the existing MVVM-based applications and also discuss the possibility of RMVRVM replacing MVVM. We apply the migration framework on an open-source MVVM application and run the experiment to prove the efficacy of RMVRVM. We also expanded the experiments to include the iOS platform and 4G network. To cover the complexity shift to server-side, we discuss the energy consumption on the cloud and how energy-saving practices in cloud data centers help save overall energy consumption.