Improve Energy Conversion Efficiency Research Articles

Clustering First-order reversal curve diagram using the Gaussian mixture model and the Davies Bouldin index

Abstract In our energy-consuming society, understanding magnetization reversal in permanent magnets is crucial for improving energy conversion efficiency between electric energy and mechanical energy. First-order reversal curves (FORCs) have enabled qualitative studies of reversal mechanisms, however, further understanding based on quantitative analysis is still difficult due to the complexity of FORC diagrams. We introduce a machine-learning based approach combining the Gaussian mixture model and the Davies-Bouldin index to separate characteristic features in FORC diagrams of Nd-Fe-B magnets. The clustering method is evaluated using several FORC diagrams obtained at different temperatures, and we also demonstrated hysteresis loop reconstruction using the clustered FORC diagrams.

Design and Modeling of Coreless Magnetoelectric Transducers for Snake-like Wave Energy Converters

With the development of the economy, people’s demand for energy is increasing, which has led to a shortage of fossil fuels. Wave energy is a widely distributed renewable energy source, and the development of wave energy generation technology can greatly alleviate the energy shortage problem. This study takes the snake-like wave energy converter (WEC) as an example and designs a coreless magnetoelectric transducer for it. The structure of the coreless magnetoelectric transducer is relatively simple, eliminating the iron core in the transducer, which can eliminate its own damping. At the same time, this structure can minimize the gap between the magnet and the coil, improve energy conversion efficiency, and work continuously under complex working conditions. This study takes two types of coreless magnetoelectric transducers as examples to analyze. This study aims to establish equivalent magnetic circuit models for the coreless magnetoelectric transducers, explore the effects of different magnets on the performance of the transducers, and optimize the parameters in the transducers. We used simulation software to analyze the transducer and verify the accuracy of the models. Finally, prototypes of the coreless magnetoelectric transducers were made, and a testing system for the transducer was established to test its energy conversion capability. Our experiments show that coreless magnetoelectric transducers have good energy conversion capabilities and can be used as transducers for snake-like WECs. At the same time, this type of transducer can also be applied to other types of WECs, providing a new approach for the research of WECs.

Experimental Analysis and CFD Simulation of Photovoltaic/Thermal System with Nanofluids for Sustainable Energy Solution

The integration of photovoltaic/thermal (PV/T) systems with nanofluids presents a promising avenue for enhancing sustainable energy solution. This study investigates the performance of such systems through experimental analysis and computational fluid dynamics (CFD) simulations. Nanofluids, engineered colloidal suspensions of nanoparticles in base fluids, are employed to enhance heat transfer within the PV/T system. The experimental setup involves measuring electrical output, thermal efficiency, and overall system performance under varying conditions. Additionally, CFD simulations are conducted to model fluid flow and heat transfer dynamics within the PV/T collector integrated with nanofluids. The results from both experimental and simulation studies provide insights into the synergitic effects of nanofluids on enhancing energy conversion efficiency and thermal management of the PV/T system. The research contributes to the development of sustainable energy solutions by demonstrating the potential of nanofluid-enhanced PV/T systems in improving energy conversion efficiency and thermal management for various environmental conditions.

Deciphering the Underlying Mechanism of the Fourth Entity in Medium-Entropy NiCoFeMP toward Boosting Oxygen Evolution Electrocatalysis.

High-/medium-entropy materials have been explored as promising electrocatalysts for water splitting due to their unique physical and chemical properties. Unfortunately, state-of-the-art materials face the dilemma of explaining the enhancement mechanism, which is now limited to theoretical models or an unclear cocktail effect. Herein, a medium-entropy NiCoFeMnP with an advanced hierarchical particle-nanosheet-tumbleweed nanostructure has been synthesized via simple precursor preparation and subsequent phosphorization. Evaluated as the electrocatalyst for oxygen evolution reaction (OER), the medium-entropy NiCoFeMnP displays a lower overpotential of 272 mV at a current density of 10 mA cm-2, and more favorable kinetics than the binary NiFeP, ternary NiCoFeP, quaternary NiCoFeCuP and NiCoFeCrP counterparts, and other reported high-/medium-entropy electrocatalysts. Careful experimental analyses reveal that the incorporation of Mn can significantly regulate the electronic structure of Ni, Co, and Fe sites. More importantly, the Mn introduction and entropy stabilization effect in the reconstructed metal (oxy)hydroxide simultaneously promote the lattice oxygen mechanism, improving the activity. This work sheds new light on the design of high-/medium-entropy materials from an in-depth understanding of the underlying mechanism for improving energy conversion efficiency.

Surface functionalized porous MXene (Ti3C2Tx)/Polyethyleneimine membrane for efficient osmotic energy conversion

The development of ion-selective membranes is crucial for achieving efficient osmotic power conversion in reverse electrodialysis system. However, balancing ion selectivity and ion permeability in membranes remains a challenge, limiting improvements in energy conversion efficiency for practical applications. In this study, we develop efficient cation exchange membranes by integrating versatile aromatic hydroxyl groups with MXene nanosheets and polyethyleneimine (PEI) into their lamellar structure. This approach holds promise for achieving non-swelling, high selectivity, and enhanced power density for osmotic energy conversion. The abundance positive surface charge within PEI molecules, combined with the 2D sub-nanochannels of MXene nanosheets, facilitates the biomimetic replication of channel size, chemical groups, and adjustable charge density in the resulting membranes. The fabrication of these membranes is easily achieved through simple hydrothermal, functionalization, and surface-charged techniques, suggesting promising scalability. These membranes exhibit remarkable stability against swelling in aqueous solutions for up to 25 days and demonstrate a high selectivity of 0.95 and a superior output power density of 18.3 W/m2 in artificial river water and seawater.

Enhanced Antireflection and Absorption in Thin Film GaAs Solar Cells Using Dielectric Composite Nanostructures

This study investigates the application of dielectric composite nanostructures (DCNs) to enhance both antireflection and absorption properties in thin film GaAs solar cells, which are crucial for reducing production costs and improving energy conversion efficiency in photovoltaic devices. Building upon previous experimental validations, this work systematically explores the underlying theoretical mechanisms using the finite difference time domain (FDTD) method to analyze the light interaction with the proposed DCNs. The results show that the combination of Mie resonance, Fabry–Perot resonance, and guided resonance, induced by the surface structuring of the DCNs, significantly enhances light absorption in the active layer, particularly at longer wavelengths. For solar cells featuring a 500-nm-thick absorber layer, SARL-decorated solar cells demonstrated an average reflectivity of 12.18%, whereas those incorporating DCNs exhibited a significantly reduced average reflectivity of 4.52%. These findings indicate that DCNs structures are highly effective in enhancing the performance of thin and ultra-thin GaAs solar cells by minimizing surface reflection and increasing photon utilization, offering a promising solution for high efficiency, cost effective photovoltaic devices.

Visualizing the structure and dynamics of transition metal-based electrocatalysts using synchrotron X-ray absorption spectroscopy.

As the global energy structure evolves and clean energy technologies advance, electrocatalysis has become a focal point as a critical conversion pathway in the new energy sector. Transitional metal electrocatalysts (TMEs) with their distinctive electronic structures and redox properties show great potential in electrocatalytic reactions. However, complex reaction mechanisms and kinetic limitations hinder the improvement of energy conversion efficiency, highlighting the necessity for comprehensive studies on structure and performance of electrocatalysts. X-ray Absorption Fine Structure (XAFS) spectra stand out as a robust tool for examining the electrocatalyst's structures and performance due to its atomic selectivity and sensitivity to local environments. This review delves into the application of XAFS technology in characterizing TMEs, providing in-depth analyses of X-ray Absorption Near-Edge Structure (XANES) spectra, and Extended XAFS (EXAFS) spectra in both R-space and k-space. These analyses reveal intrinsic structural information, electronic interactions, catalyst stability, and aggregation morphology. Furthermore, the paper examines advancements in in-situ XAFS techniques for real-time monitoring of active site changes, capturing critical intermediate and transitional states, and elucidating the evolution of active species during electrocatalytic reactions. These insights deepen our understanding on structure-activity relationship of electrocatalysts and offer valuable guidance for designing and developing highly active and stable electrocatalysts.

Pressure-Promoted Triplet-Pair Separation in Singlet-Fission TIPS-Pentacene Nanofilms Revealed by Ultrafast Spectroscopy.

Singlet fission (SF), as an effective way to break through the Shockley-Queisser limit, can dramatically improve energy conversion efficiency in solar cell areas. The formation, separation, and relaxation of triplet-pair excitons directly affect the triplet yield, especially triplet-pair separation; thus, how to enhance the triplet-pair separation rate becomes one of the key points to improve SF efficiency; the decay mechanism where the singlet state is converted into two triplet states is significant for the study of the SF mechanism. Herein, we employ ultrafast transient absorption spectroscopy to study the singlet-fission process of nano-amorphous 6, 13-bis(triisopropylsilylethynyl)-Pentacene (TIPS-pentacene) films in a diamond anvil cell (DAC). A kinetics model related to the structural geometric details, as well as an evaluation of the pressure manipulation impacts, is demonstrated based on the experimental results. The results indicate that pressure manipulation enhanced the triplet-pair separation rates of SF-based materials according to their structural micro-environmental improvement when compressed in DAC, while the triplet-exciton transportation lifetime is prolonged. This work shows that pressure may effectively optimize the structural disorder of SF materials, which were found to improve triplet-pair separation efficiency and potentially offer an effective way to further improve SF efficiency.

Experimental and process simulation on solid fuel chemical looping cascade utilization conversion technology aiming hydrogen generation

In this work, a novel chemical looping process towards hydrogen generation based on the cascade utilization of components in solid fuels (like biomass and coal) with different reactivity (pyrolysis gas and char) was proposed, aiming for energy conversion from carbon-intensive fuels to carbon-free renewable hydrogen via the material migration of iron oxides. Biomass, represented by sawdust, is an important part among various renewable energy sources and a typical solid fuel with great potential. Therefore, in the most concerned reduction stage, experiments were conducted mainly using sawdust to investigate the effects of various parameters (temperature, oxygen/fuel ratio, residence time) on the carbon conversion involved in char in the primary reduction stage, gas/solid spatiotemporal distribution in the deep reduction stage and subsequent H2 generation performance, and kinetic parameters were fitted for different reduction stages. Process simulation was further conducted based on the actual experimental results. The proposed process demonstrated satisfactory applicability to solid fuels with different characteristics, and biomass was more suitable for hydrogen production. Compared with chemical looping combustion process, a significant improvement of sawdust-fueled energy conversion efficiency from 33.26 % to 51.76 % and a decrease of OCs theoretical circulation rate (27.77 %) were achieved under the chemical looping process aiming hydrogen generation.

Optimizing the photovoltaic-assisted electric bus network with rooftop energy supply

As a clean and renewable resource, solar energy has demonstrated its potential to alleviate the energy vulnerability and grid strain for electric bus systems. In this study, we investigate the optimal design of an electric bus network in which rooftop solar panels are equipped to provide en-route photovoltaic assistance. A continuous-based model is proposed to optimize critical network design variables, including time-varying headway, stop spacing, and deployment of depot chargers. Introducing rooftop solar photovoltaics can significantly reduce range anxiety for electric buses. Compared with conventional electric bus systems, 4.2%–7.8 % daily in-operation time can be extended, while at most 5.7 % fleet size can also be saved per day. The proposed system demonstrates much more advantages in regions where hourly solar irradiance exceeds 1000 W/m2. Sensitivity tests indicate that (1) with a 10 % improvement in energy conversion efficiency, 1.2 % daily fleet size and 7.5 % depot chargers can be reduced; (2) every 50-kWh increase in bus battery capacity would bring a 1.8 % increment in system cost. Increasing the installation area of solar panels can help reduce battery capacity and lower the system cost. A real-world-based case in Panjin City, China is further designed to validate the application of the proposed system.

Application and prospect analysis of microbial fuel cell technology

As global energy demand grows and environmental problems intensify, the search for clean, renewable energy solutions becomes especially urgent. This article reviews microbial fuel cell (MFCs) technology, a new type of clean energy technology that uses microbial metabolic activity to convert organic matter into electricity. Compared with traditional fossil fuel power generation methods, MFCs have significant advantages such as low pollution, low noise, and renewable. The working principle of MFCs, including the reaction process of anode and cathode, as well as the key factors affecting the performance of MFCs, such as the choice of anode and cathode materials, are discussed. In addition, the coupling applications of MFCs with other technologies, such as photocatalysis, electrofenton technology, microbial electrolysis (MEC) and constructed wetland technology, are discussed, which provide new possibilities for improving wastewater treatment efficiency and expanding the application field of MFC. Finally, the challenges and future development direction of MFCs technology are prospected, and key research directions such as improving energy conversion efficiency, reducing cost and enhancing system stability are pointed out.

Designing copper-doped zinc oxide nanoparticle by tobacco stem extract-mediated green synthesis for solar cell efficiency and photocatalytic degradation of methylene blue

This study presents the green synthesis of copper-doped zinc oxide (Cu-doped ZnO) nanoparticles using tobacco stem (TS) extract. The environmentally friendly synthesis method ensures distinct features, high efficiency, and applicability in various fields, particularly in solar cell technology and photocatalytic applications. ZnO nanostructures are investigated due to their unique properties, cost-effectiveness, and broad range of applications. The nanoparticles are synthesized with varying Cu concentrations, and their structural, morphological, and compositional characteristics are thoroughly analyzed. The Cu-doped ZnO nanoparticles exhibit improved properties, such as increased surface area and reduced particle size, attributed to the incorporation of Cu dopants. The green synthesis approach using TS extract serves as a stabilizing agent and avoids the toxicity associated with chemical methods. Characterization techniques including SEM, TEM, EDX, FTIR, and XRD confirm the successful synthesis of the nanoparticles. Photocatalytic degradation studies reveal that the 5% Cu-doped ZnO exhibits the highest photocatalytic activity against methylene blue, attributed to synergistic effects between Cu and ZnO, including oxygen vacancy and electron–hole pair recombination rate suppression. The photocatalytic mechanism involves the generation of superoxide and hydroxyl radicals, leading to methylene blue degradation. Furthermore, the Cu-doped ZnO nanoparticles demonstrate promising photovoltaic performance, with the optimal efficiency observed at a 5% Cu concentration. The study suggests that Cu-doped ZnO has the potential to enhance solar cell efficiency and could serve as an alternative material in solar cell applications. Future research should focus on refining Cu-doped ZnO for further improvements in solar energy conversion efficiency

Improved energy harvesting by enhanced nonlinearities: New phenomena and experimental demonstration

This paper investigates a nonlinear piezoelectric energy harvesting system that enhances conversion of mechanical energy to electrical energy by integrating piezoelectric materials with a nonlinear system. The research simplifies a flexible beam with macro fiber composite (MFC) piezoelectric patches using a lumped-parameter approach and derives the dynamic equations of the system using the Lagrange equations. The incremental harmonic balance method (IHBM) is then employed to solve these equations, simulating the nonlinear dynamics involved in the harvested voltage. Key findings include the initial discovery of multiple voltage islands which are voltage jumps that improve energy conversion efficiency, confirmed by experimental data validating the IHBM simulations. The study reveals that these phenomena are due to the enhanced nonlinearities of the system, particularly the geometric nonlinearity caused by the spring k1 and the nonlinear magnetic force between magnets. Adjusting k1 allows the observation of multiple voltage islands, and increasing d0 results in a broad-frequency constant voltage, offering new insights. The research concludes that the nonlinear piezoelectric energy harvester can effectively convert vibration energy into electrical one, as demonstrated by successfully powering multiple light-emitting diodes (LEDs). Bifurcation diagrams illustrate the adaptability of the system, showing transitions among periodic, quasi-periodic, and chaotic states for different parameters.

Boosting quantum-structured solar cell light absorption through compressively strained superlattices

The escalating demand for improved energy conversion efficiency in vehicular applications of solar cells underscores the need for innovative solutions. This study focuses on enhancing the current density of GaAs middle cells within conventional Ge-based triple-junction solar cells to realize unprecedented levels of energy conversion efficiency. We introduced a novel superlattice configuration termed a compressively strained superlattice (CSSL) and demonstrated its integration into a p-i-n junction GaAs solar cell, achieving a current density increase of 1.03 mA cm−2 over conventional GaAs solar cells. Prior investigations have explored a strain-balanced superlattice (SBSL) to enhance GaAs middle cell current density. However, our findings establish the superiority of the CSSL over the SBSL in terms of current density improvement, with the CSSL featuring 1.59 times more quantum wells per unit length than the SBSL. This increase in quantum well quantity significantly enhances light absorption efficiency and consequently, the current density.

Dependent Task Offloading and Resource Allocation via Deep Reinforcement Learning for Extended Reality in Mobile Edge Networks

Extended reality (XR) is an immersive technology widely applied in various fields. Due to the real-time interaction required between users and virtual environments, XR applications are highly sensitive to latency. Furthermore, handling computationally intensive tasks on wireless XR devices leads to energy consumption, which is a critical performance constraint for XR applications. It has been noted that the XR task can be decoupled to several subtasks with mixed serial–parallel relationships. Furthermore, the evaluation of XR application performance involves both subjective assessments from users and objective evaluations, such as of energy consumption. Therefore, in edge computing environments, ways to integrate task offloading for XR subtasks to meet users’ demands for XR applications is a complex and challenging issue. To address this issue, this paper constructs a wireless XR system based on mobile edge computing (MEC) and conducts research on the joint optimization of multi-user communication channel access and task offloading. Specifically, we consider the migration of partitioned XR tasks to MEC servers and formulate a joint optimization problem for communication channel access and task offloading. The objective is to maximize the ratio of quality of experience (QoE) to energy consumption while meeting the user QoE requirements. Subsequently, we introduce a deep reinforcement learning-based algorithm to address this optimization problem. The simulation results demonstrate the effectiveness of this algorithm in meeting user QoE demands and improving energy conversion efficiency, regardless of the XR task partitioning strategies employed.

Performance improvement of a Stirling-type two-stage pulse tube cooler by using stepped displacer plus bypasses phase shifter

Stirling-type pulse tube cooler (SPTC) is the most prospective thermoacoustic refrigerator due to its long lifetime, high reliability and low vibration, and the phase shifter significantly affects the energy conversion efficiency of SPTC. A novel phase shifter of the stepped displacer plus bypasses (SD-B) is proposed in this paper. Thermoacoustic impedance characteristics of the stepped displacer (SD) and the stepped displacer plus bypasses (SD-B) are analyzed. Based on a two-stage SPTC, the effect of additional combined DC flows in the system is first investigated. Results indicate that the cooling capacity could be improved through introducing additional DC flows in the positive direction from the hot end of regenerator to pulse tube. While for SD, negative DC flows are induced due to the clearance seal gaps between the displacer piston and cylinder shell. Thus, SD-B is explored to improve energy conversion efficiency through naturally introducing DC flows by bypasses. The influence of the opening diameter of two bypasses is investigated, and comparisons between the SD and SD-B are performed. Results indicate that with SD-B, the cooling capacity at 20 K achieves a maximum of 2.04 W with a relative Carnot efficiency of 13.0 %, 56.9 % higher than that of SD.

A developed convolutional neural network model for accurately and stably predicting effective thermal conductivity of gradient porous ceramic materials

Accurate and stable prediction of the effective thermal conductivity (ETC) of porous ceramic materials is of great significance for their application in areas such as optimizing the design of thermal barrier coatings and improving energy conversion efficiency. Porous ceramic materials exhibit complex porous structures with gradient porosity distributions that pose a great challenge for effective medium theory (EMT) and conventional convolutional neural networks (CNN) in attempting to accurately and stably predict the ETC of porous media. In this study, a CNN model that integrates self-attention and a multiscale feature-fusion mechanism is proposed to predict the ETC of porous media with greater accuracy and stability. The integration of the self-attention and multiscale feature-fusion mechanisms enhances the CNN's ability to learn long-range dependencies and preserve detailed information. The optimization of the CNN's accuracy and stability is visually illustrated using gradient-weighted class activation mapping (Grad-CAM) for ETC. Additionally, by employing the proposed gradient quartet structure generation set (QSGS), a gradient porous ceramic media dataset comprising 10 000 images was built to train the CNN model. Finally, the prediction results and relative error distribution of the ETC were compared across different models. Our model demonstrated improvements in statistical metrics, including a 33.7 % decrease in mean error, 25.2 % decrease in median error, and 59.6 % decrease in maximum error. The decreases in these metrics and Grad-CAM for the ETC strongly demonstrates that the model proposed in this work greatly improved the accuracy and stability of predicting the ETC of ceramic materials with gradient porosity distributions.

Reaction kinetics of CCLC process based on molecular simulation

Abstract In China, coal-fired power generation is still the main mode of electricity supply. However, the large amount of coal use exacerbates environmental and sustainability issues. To achieve the “dual-carbon” goal, significant reductions in carbon dioxide (CO2) emissions from fossil-fueled power generation will be necessary before a transition to cleaner energy can occur. Therefore, the reaction kinetics of the CCLC process was researched by molecular dynamics (MD) simulations, which led to the activation energies of 57.58 kJ/mol and -34.26 kJ/mol for the FR and AR reactions. This is of great significance for reducing CO2 emissions and improving energy conversion efficiency.

Simulation and optimization of 30.17% high performance N-type TCO-free inverted perovskite solar cell using inorganic transport materials

Perovskite solar cells (PSCs) have gained much attention in recent years because of their improved energy conversion efficiency, simple fabrication process, low processing temperature, flexibility, light weight, and low cost of constituent materials when compared with their counterpart silicon based solar cells. Besides, stability and toxicity of PSCs and low power conversion efficiency have been an obstacle towards commercialization of PSCs which has attracted intense research attention. In this research paper, a Glass/Cu2O/CH3NH3SnI3/ZnO/Al inverted device structure which is made of cheap inorganic materials, n-type transparent conducting oxide (TCO)-free, stable, photoexcited toxic-free perovskite have been carefully designed, simulated and optimized using a one-dimensional solar cell capacitance simulator (SCAPS-1D) software. The effects of layers’ thickness, perovskite’s doping concentration and back contact electrodes have been investigated, and the optimized structure produced an open circuit voltage (Voc) of 1.0867 V, short circuit current density (JSC) of 33.4942 mA/cm2, fill factor (FF) of 82.88% and power conversion efficiency (PCE) of 30.17%. This paper presents a model that is first of its kind where the highest PCE performance and eco-friendly n-type TCO-free inverted CH3NH3SnI3 based perovskite solar cell is achieved using all-inorganic transport materials.

Study on Rock Interface Stability in the Heat Exchange Channel of the Horizontal Section of U-Shaped Wells in Hot Dry Rock

Enhanced Geothermal Systems (EGS) represent a promising direction for sustainable energy development, yet their efficiency and feasibility often suffer due to suboptimal heat extraction methods and interface instability in U-shaped wells. This study introduces an innovative volume encapsulation technology that aims to address these challenges. The proposed technology employs a combination of hydraulic fracturing and acidification to prepare the rock interface, followed by encapsulation using high-temperature liquid metal. Low-melting-point alloys are utilized as a heat exchange medium between the horizontal sections of the wells. This study meticulously analyzes the impact of formation stress, thermal shock stress, and liquid metal properties on rock interface stability. Advanced simulation tools and experimental setups were used to test the encapsulation process under various conditions. The application of liquid metal encapsulation demonstrated significant improvements in energy conversion efficiency and rock interface stability. In conditions simulating a dry and hot rock reservoir at depths up to 3000 m and temperature gradients reaching 2200 °C/m, the adjusted depth of horizontal sections and increased pumping pressure contributed to maintaining interface stability. The established failure criteria provide a robust theoretical foundation for the encapsulation process. Volume encapsulation technology using liquid metal not only enhances the operational efficiency of EGS but also stabilizes the rock interface, thereby increasing the feasibility of continuous geothermal energy extraction. This study offers valuable theoretical insights and practical guidance for future research and applications in geothermal energy technologies, creating new pathways for the efficient exploitation of geothermal resources.