Energy Utilization Efficiency Research Articles

Enhanced reaction extraction distillation via multi-objective optimization and 4E analysis for sustainable recovery of organic compounds from wastewater

Resource utilization and sustainable treatment of wastewater, which can achieve efficient energy utilization and environmental protection, have received hot social attention. Tetrahydrofuran and methanol are the two most common substances in pharmaceutical wastewater. It is very necessary to explore the wastewater treatment process containing these two substances. In this study, extractive distillation and reactive distillation were proposed to effectively separate the tetrahydrofuran-methanol-water component of pharmaceutical wastewater. To further reduce energy consumption, two strengthening processes, double-column reactive-extractive distillation and reactive-extractive dividing wall column distillation were designed. Taking the minimum operating and equipment cost as the objective function, the processes were optimized by using the multi-objective genetic optimization algorithm to obtain the best process parameters. Four processes were evaluated in terms of total annual cost, energy consumption, gas emissions and thermodynamic efficiency. Compared to the traditional three-column extractive distillation process, the above-mentioned four aspects of the reactive-extractive dividing wall column process was reduced by 40.63%, 43.13%, 43.14% and 17.71%, respectively. The reactive-extractive dividing wall column distillation process is of great significance for the efficient purification of valuable organic matter in wastewater and environmental protection.

Fluorescence spectra as an indicator of the influence of environmental conditions on fruit trees

Molecular fluorescence spectra determine possible structural changes of these molecules and provide data (by comparing them with absorption ones) on the efficiency of solar energy utilization. Fluorescence emission spectra provide information on the functionality of the photosynthetic apparatus by means of two bands red F690 and beyond red F735. The objective of the study is to highlight possible changes in the organization and operation of the photosynthetic apparatus, induced by different radiations, in the leaves, for a variety of pear (Santa Maria), based on the characteristics of the two bands of emitted fluorescence. The Santa Maria variety was studied in the period of June.

Investigation of ultrafast intermediate states during singlet fission in lycopene H-aggregate using femtosecond stimulated Raman spectroscopy.

The singlet fission process involves the conversion of one singlet excited state into two triplet states, which has significant potential for enhancing the energy utilization efficiency of solar cells. Carotenoid, a typical π conjugated chromophore, exhibits specific aggregate morphologies known to display singlet fission behavior. In this study, we investigate the singlet fission process in lycopene H-aggregates using femtosecond stimulated Raman spectroscopy aided by quantum chemical calculation. The experimental results reveal two reaction pathways that effectively relax the S2 (11Bu+) state populations in lycopene H-aggregates: a monomer-like singlet excited state relaxation pathway through S2 (11Bu+) → 11Bu- → S1 (21Ag-) and a dominant sequential singlet fission reaction pathway involving the S2 (11Bu+) state, followed by S* state, a triplet pair state [1(TT)], eventually leading to a long lifetime triplet state T1. Importantly, the presence of both anionic and cationic fingerprint Raman peaks in the S* state is indicative of a substantial charge-transfer character.

Energy Bus-Based Matrix Modeling and Optimal Scheduling for Integrated Energy Systems

Integrated energy systems (IESs) can easily accommodate renewable energy resources (RESs) and improve the utilization efficiency of fossil energy by integrating various energy production, conversion, and storage technologies. However, the coupled multi-energy flows and the uncertainty of RESs bring challenges regarding optimal scheduling. Therefore, this study proposes an energy bus-based matrix-modeling method and a coordinated scheduling strategy for the IES. The matrix-modeling method can be used to formulate the steady- and transient-state balances of the multi-energy flows, and the transient model can clearly express the multi-time-scale characteristics of the different energy flows. The model parameters are fitted with data from experiments and the literature. To address the inherent randomness of the RESs and loads, a coordinated scheduling strategy is designed that contains two components: day-ahead optimization and rolling optimization. Day-ahead optimization uses the system steady-state model and multiple scenarios from the RES and load forecast data to minimize the operation cost while rolling optimization is based on the system’s transient-state model and aims to achieve the optimal real-time scheduling of the energy flows. Finally, a case study is conducted to verify the advantages and effectiveness of the proposed model and optimization method. The results show that stochastic optimization reduces the total daily cost by 1.48% compared to deterministic optimization when considering the prediction errors associated with the RESs and loads, highlighting the stronger adaptability of stochastic optimization to prediction errors. Moreover, rolling optimization based on the system’s transient-state model can reduce the errors between day-ahead scheduling and rolling correction.

Schottky junction-mediated carrier separation in BiOBr/Ti3C2Tx van der Waals heterojunction photocatalyst for increased removal of Cr(VI) under visible-light

The photocatalytic removal of pollutants can integrate efficient solar energy utilization with wastewater treatment. Herein, we report a simple strategy to construct BiOBr/Ti3C2Tx composite photocatalysts consisting of self-assembled van der Waals (vdw) heterojunction structures containing Schottky junctions. The vdW interaction between BiOBr and Ti3C2Tx and the structural stability of the catalysts were validated by density functional theory (DFT) calculations and an ab initio molecular dynamic simulation (AIMD). Compared to BiOBr, the BiOBr/Ti3C2Tx composites exhibited an enhanced light absorption capability and photocurrent response, along with a lower carrier recombination rate and charge-transfer resistance. The BiOBr/Ti3C2Tx activity for the photoreduction of hexavalent chromium (Cr(VI)) under visible-light irradiation considerably surpassed that of the original BiOBr (53.9%). Using the BTC-0.8 catalyst (with a Ti3C2Tx: BiOBr mass ratio of 0.8%) optimal reduction efficiency (94.0%) for Cr(VI) with a reaction rate approximately 3.5 times that of pure BiOBr. The BTC-0.8 catalyst was viable over a wide pH range and maintained an 83.9% photoreduction rate after four cycling experiments. The exceptional photocatalytic ability of BiOBr/Ti3C2Tx was achieved because Ti3C2Tx served as an electron injection layer that separated photogenerated carriers. The Schottky junction constructed within the BiOBr/Ti3C2Tx vdW heterojunctions suppressed electron backflow, promoting carrier separation. The excellent photocatalytic performance and strong cyclic stability of BiOBr/Ti3C2Tx demonstrated the considerable application potential of this photocatalyst.

New Advances in Materials, Applications, and Design Optimization of Thermocline Heat Storage: Comprehensive Review

To achieve sustainable development goals and meet the demand for clean and efficient energy utilization, it is imperative to advance the penetration of renewable energy in various sectors. Energy storage systems can mitigate the intermittent issues of renewable energy and enhance the efficiency and economic viability of existing energy facilities. Among various energy storage technologies, thermocline heat storage (THS) has garnered widespread attention from researchers due to its stability and economic advantages. Currently, there are only a few review articles focusing on THS, and there is a gap in the literature regarding the optimization design of THS systems. Therefore, this paper provides a comprehensive review of the recent research progress in THS, elucidating its principles, thermal storage materials, applications, and optimization designs. The novelty of this work lies in the detailed classification and analysis of various optimization designs for THS, including tank shape, aspect ratio, inlet/outlet configuration, thermal energy storage materials arrangement, operating strategies, and numerical model optimization approaches. The limitations of existing research are also identified, and future perspectives are proposed, aiming to provide recommendations for THS research and contribute to the development and promotion of THS technology.

Climate Change Effect in Nigeria Mitigation, Adaptation, Strategies and Way Forward in the World of Internet of Things

This paper delves into the comprehensive impact of climate change in Nigeria, emphasising the critical role of Internet of Things (IoT) technology in formulating mitigation and adaptation strategies. It highlights the significant threats climate change poses to Nigeria's ecological balance, economy, and societal structure, including altered temperature patterns, more frequent extreme weather events, and ramifications for agriculture, water supply, and health. It underscores the urgency for effective responses to protect the nation's welfare and economic integrity. The study showcases the potential of IoT technology as a pivotal tool in crafting innovative responses to climate change challenges. It demonstrates how IoT can bolster Nigeria's resilience through enhanced agricultural methods, better management of water resources, and more efficient energy utilisation. IoT devices' real-time data gathering and analytical prowess facilitate precise environmental monitoring, timely disaster warnings, and resource optimisation. The discussion extends to mitigation tactics like shifting towards renewable energy, improving energy efficiency, and sustainable land use, alongside adaptation strategies that include building climate- resilient structures, advocating for water conservation, and applying climate-smart agricultural practices to safeguard food security. Advocating for a cooperative strategy that integrates efforts from the government, private sector, academia, and communities, the paper stresses the importance of incorporating IoT solutions into national climate action and development strategies for a unified and robust approach to climate-related challenges. It concludes with a roadmap for the future, proposing policy reforms, investments in IoT infrastructure, skill development, and heightened public awareness as essential moves towards a sustainable, climate-resilient Nigeria. By strategically deploying IoT technologies, Nigeria can mitigate the detrimental impacts of climate change and tap into new avenues for economic and environmental prosperity.

Investigation of the influence of different types of electrolytes on the performance of the Electrochemical Discharge Machining process during micromachining of molybdenum

Electrochemical Discharge Machining (ECDM) is a hybrid process that integrates the principles of Electrochemical Machining (ECM) and Electrical Discharge Machining (EDM) to create micro-holes in both conductive and non-conductive materials that are typically difficult to machine. Given the unpredictable nature of this hybrid method, the composition of the electrolyte emerges as a critical factor influencing the accuracy and performance of the machining process. Consequently, the optimization and analysis of electrolytes are pivotal for the efficient utilization of energy during ECDM and for ensuring machining precision. This study aims to experimentally investigate the impact of various types of electrolytes and their concentrations. These are divided into two categories: neutral solutions, which include sodium nitrate (NaNO₃) and sodium chloride (NaCl), and alkaline solutions, comprising sodium hydroxide (NaOH) and potassium hydroxide (KOH), as well as a mixture of both NaOH and KOH. The evaluation metrics considered include the Material Removal Rate (MRR), Tool Wear Rate (TWR), overcut (OC), Heat Affected Zone (HAZ) and surface quality. It was observed that alkaline solutions, particularly the mixed electrolyte, resulted in higher MRR and HAZ, reduced TWR, and the production of micro-holes with minimized overcut compared to using KOH and NaOH separately or neutral solutions, while also enhancing surface quality. Further analysis using Scanning Electron Microscopy (SEM) images and Energy-Dispersive Spectroscopy (EDS) of the brass tools used with different electrolytes revealed that tools used in KOH and mixed electrolytes exhibited less wear and material erosion compared to those used in NaOH and neutral solutions.

Forecasting of blast furnace gas utilisation rate via convolutional autoencoders and K-nearest neighbour methods

Gas utilisation rate (GUR) is an essential parameter to characterise the level of energy utilisation efficiency and operation status of blast furnaces (BFs). In the present study, data collected from a BF plant with vanadium–titanium magnetite were subjected to correlation and distribution analyses. Based on the operation cycle of the BF, production parameters from the preceding eight consecutive hours were selected as input parameters for the model. Convolutional autoencoders (CAEs) were employed to extract coded features from the selected data, serving as indirect inputs to the prediction model. Subsequently, K-nearest neighbour (KNN) was utilised to establish a mapping relationship between the coded features and GUR, facilitating forecasting for the subsequent 3 hours. Additionally, a hybrid approach incorporating both supervised and unsupervised training methods was utilised to facilitate GUR prediction, and the performance of the CAE–KNN model was re-validated using data from the remaining sections of the plant. The hit rate of predictions is no less than 96% as the permissible error was within 1.5%.

Impact of Enterprise Digital Transformation on the Efficiency of Total Factor Energy Utilization

With the advent of the information age and the rapid progress of technology, it has become inevitable for enterprises to move towards digital transformation. Energy is one of the most vital material bases for national economic and social development, which plays a vital role in national economic growth. How to use energy efficiently has been the core factor to measure the sustainable development potential of an enterprise. Based on the data of listed companies in China, this paper empirically analyzes the impact of enterprise informatization on energy efficiency from different perspectives. Studies have shown that the degree of enterprise informatization has a direct relationship with its energy efficiency. At present, the overall informatization of enterprises in various regions of China is low. However, with the continuous popularization of digital technology and applications, it has a certain inhibitory effect on enterprise energy consumption, with the effect becoming more and more apparent. Especially during the digital transformation, the role of state-owned enterprises in promoting total factor energy consumption has been more significant. Therefore, from the perspective of digital transformation, it is of great significance to study the energy efficiency of state-owned enterprises. This research explores the significant differences in energy efficiency among various industries, and the adoption of digital transformation strategies will help narrow these differences and further promote energy efficiency improvement across the industry. In addition, through the analysis of typical cases, this topic reveals the main problems faced by enterprises in the process of digital transformation and their causes, which puts forward corresponding countermeasures and suggestions. This study can provide a solid theoretical basis for the positive role played by Chinese enterprises and related departments during the digital transformation.

Tailored Phototherapy Agent by Infection Site In Situ Activated Against Methicillin-Resistant S. aureus.

Phototherapy, including photodynamic therapy (PDT) and photothermal therapy (PTT), is a promising treatment approach for multidrug resistant infections. PDT/PTT combination therapy can more efficiently eliminate pathogens without drug resistance. The key to improve the efficacy of photochemotherapy is the utilization efficiency of non-radiation energy of phototherapy agents. Herein, a facile phototherapy molecule (SCy-Le) with the enhancement of non-radiative energy transfer is designed by an acid stimulation under a single laser. Introduction of the protonated receptor into SCy-Le results in a distorted intramolecular charge in the infected acidic microenvironment, pH ≈ 5.5, which in turn, enhances light capture, reduces the singlet-triplet transition energies (ΔES1-T1), promotes electron system crossing, enhances capacity of reactive oxygen speciesgeneration, and causes a significant increase in temperature by improving vibrational relaxation. SCy-Le shows more than 99% bacterial killing rate against both methicillin-resistant Staphylococcus aureus and its biofilms in vitro and causes bacteria-induced wound healing in mice. This work will provide a new perspective for the design of phototherapy agents, and the emerging photochemotherapy will be a promising approach to combat the problem of antibiotic resistance.

Stable Photo-Rechargeable Al Battery for Enhancing Energy Utilization.

The photovoltaic cells (PVs) are able to convert solar energy to electric energy, while energy storage devices are required to be equipped due to the fluctuations of sunlight. However, the electrical connection of PVs and energy storage devices leads to increased energy consumption, and thus energy storage ability and utilization efficiency are decreased. One of the solutions is to explore an integrated photoelectrochemical energy conversion-storage device. Up to date, the integrated photo-rechargeable Li-ion batteries often suffer from unstable photo-active materials and flammable electrolytes under illumination, with concerns in safety risk and limited lifetime. To address the critical issues, here a novel photo-rechargeable aluminum battery (PRAB) is designed with safe ionic liquid electrolytes and stable polyaniline photo-electrodes. The integrated PRAB presents stable operation with enhanced reversible specific capacity ∼191% under illumination. Meanwhile, a simplified continuum model is established to provide rational guidance for designing electrode structures along with charging/discharging strategy to meet the practical operation conditions. The as-designed PRAB presents energy saving efficiency ∼61.92% upon charging and energy output increment ∼31.25% during discharging under illumination. The strategy of designing and fabricating stable and safe photo-rechargeable non-aqueous Al battery highlights the pathway for substantially promoting the utilization efficiency of solar energy. This article is protected by copyright. All rights reserved.

Energy Performance in Residential Buildings as a Property Market Efficiency Driver

Energy consumption plays an important role in contemporary economies. Its significance extends beyond utilitarian value, impacting economic robustness, environmental protection, and residents’ well-being. The escalating global energy requisites necessitate efficient energy utilization and a shift towards renewable sources to address climate change and strengthen energy independence. Developing accurate predictive models to forecast long-term energy costs and savings remains a complex problem. This paper aims to provide a methodology to identify the influence of building energy performance on real estate market efficiency, focusing on property maintenance costs. Real estate plays a crucial role in human life, serving both as a fundamental need and as a vehicle for achieving personal aspirations and secure financial investments, particularly during times of economic and social instability. Through interdisciplinary methodological architecture, this study addresses three key issues: the impact of rising energy costs on market efficiency, the responsiveness of the real estate market to energy price fluctuations, and the significance of property maintenance costs on market value. The research approach includes creating and applying AI algorithms capable of evaluating extensive datasets pertaining to real estate features. Utilizing machine learning methods, the algorithm determines the importance of energy efficiency measures as well as various other inherent and external attributes of properties. The suggested methodology provides a novel approach to improve the effectiveness of market efficiency analysis.

Boosted Mutated Corona Virus Optimization Routing Protocol (BMCVORP) for Reliable Data Transmission with Efficient Energy Utilization

Boosted Mutated Corona Virus Optimization Routing Protocol (BMCVORP) for Reliable Data Transmission with Efficient Energy Utilization

Multi-market P2P trading of cooling–heating-power-hydrogen integrated energy systems: An equilibrium-heuristic online prediction optimization approach

In this paper, an equilibrium-heuristic online prediction optimization approach is proposed for multi-market peer-to-peer (P2P) electricity–hydrogen trading of integrated energy systems (IESs) with uncertainties. First, the IES, consisting of a hydrogen energy storage subsystem and a combined cooling, heating, and power subsystem, is constructed in the distribution network to improve energy utilization and market efficiency. Then, a bi-level optimization model for IESs, participating in the P2P electricity–hydrogen energy trading, the real-time electricity, and the ancillary service markets, is proposed, in which the top-level model can be formulated as a P2P electricity–hydrogen trading pricing model through the social welfare maximization problem, and the lower-level model is used to maximize the IES operating profit. To effectively solve the bi-level model, the game equilibrium-based ADMM distributed algorithm is used to obtain the P2P trading volume and prices of the top-level model, and a new hybrid heuristic algorithm, called hybrid sand cat swarm optimization and improved honey badger algorithm (SCIHB), is proposed to solve the lower level model. SCIHB utilizes a hybrid mechanism and an adaptive learning rate parameter to balance local exploitation and global exploration. Furthermore, a new online learning probabilistic prediction method based on the hidden Markov model and wavelet transform is introduced to describe the uncertainties of wind power, electricity prices, and frequency regulation prices. Finally, case studies are conducted on an IEEE 33-bus test system, and the numerical results verify the effectiveness of the proposed P2P trading model and solution approach.

A novel green methanol – heat cogeneration system based on municipal solid waste plasma gasification and coke oven gas: Energy, exergy, economic, and environmental assessment

Burning municipal solid waste for disposal contributes significantly to atmospheric pollution. Utilizing municipal solid waste for green methanol production can alleviate environmental burdens. This study proposes a novel approach based on municipal solid waste plasma gasification, integrating coke oven gas catalytic reforming for green methanol synthesis. A comparative analysis is conducted against a conventional scheme involving water gas shift for syngas production. Simulation models of both approaches are constructed, revealing that the newly proposed system achieves higher methanol synthesis yield and energy utilization efficiency at 90.57 % and 61.28 %, respectively, with an exergy efficiency of 63.74 %. The project incurs an investment cost of 11,448.70 k$, with a dynamic payback period of 4.18 years after a 1-year construction cycle. The net present value over a 25-year operational span is 21,899.16 k$. Additionally, the proposed system emits less than 0.06 tons of carbon dioxide per ton of green methanol, significantly lower than the 0.72 tons emitted by the water gas shift-adjusted syngas synthesis scheme. It makes the proposed approach a potential negative carbon emitter compared to municipal solid waste incineration. Therefore, the system demonstrates favorable thermodynamic performance, coupling with substantial economic and environmental benefits.

Experiment investigation for interconnected effects of driving cycle and ambient temperature on bidirectional energy flows in an electric sport utility vehicle

The constrained driving range has emerged as a pivotal quandary impeding the advancement of electric sport utility vehicles (ESUVs). In this study, energy flow tests were executed on an ESUV to investigate interconnected effects of driving cycle and ambient temperature on bidirectional energy flows throughout the entire driving range. The results reveal that air conditioner singularly imposes a substantial surge in energy consumption at high-temperature settings. Notably, energy utilization efficiency (ηuti) reaches its zenith under Fixed speed cycle at room temperature (FSR_R) and energy recovery efficiency (ηrec) attains its peak under World Light Vehicle Test Cycle at room temperature (WLTC_R). Nevertheless, ηuti and ηrec attain their acme at room temperature and reach their nadir under low-temperature conditions, regardless of the specific driving cycle employed. Battery average temperature exhibits an ascending trajectory at room temperature and displays cyclic fluctuations at high temperature, while first increasing rapidly and then decreasing gradually in low-temperature ambient. Battery output energy per cycle initially decreases and eventually stabilizes with increasing the cycle count, and the battery recovery energy shows an initial upward trend followed by a stabilization phase. These findings provide empirical substantiation and prescriptive insights for mitigating energy consumption and enhancing driving range of ESUVs.

Reinforcing the efficiency of photocatalytic CO2 conversion with H2O vapor through the integration of photothermal Cu/C@Bi/C supported on 3D g-C3N4 under full-spectrum solar irradiation

Developing an efficient photocatalyst for CO2 conversion to chemical fuels that maximizes the utilization of solar energy, particularly near-infrared light, remains a persistent challenge. Meanwhile, it is difficult to suppress the H2 evolution during the photocatalytic process. Herein, Cu/C@Bi/C grafted on the surface of 3D g-C3N4 (NCN) can serve as a highly durable and active catalyst for photothermal synergistic catalytic CO2 reduction under full-spectrum solar irradiation in solid-liquid-gas three-phase interfaces, wherein the Cu/C@Bi/C serves as a harvesting-near-infrared light nanoreactor and an electron transport bridge for the enhancement of the interface local temperature and the efficient transfer of photoinduced electrons. As a result, the hybrid catalyst shows excellent photothermal catalytic activity of CO2 to CO (169.26 μmol·g−1·h−1) and CO2 to CH4 (1.94 μmol·g−1·h−1), outperforming the majority of the conventional photocatalysts, whereas the competitive reaction of H2 evolution can be inhibited. This study presents a feasible approach for the efficient utilization of solar energy by harnessing near-infrared light through nano-reactors, thereby providing a viable strategy for photothermal catalytic CO2 reduction.

Performance study on an energy-efficient TSA air-purification process utilizing compression heat regeneration

A novel compression heat regeneration TSA process is disclosed in this paper, which aims to reduce the regeneration energy consumption of the raw air purifier in the air separation process. Since air separation is an energy-intensive process accounting for a significant proportion (about 5 %) of China's total electricity consumption, this new process holds great significance in energy conservation. Distinguishing from traditional processes, the new one integrates components such as a compressor, a regenerator, and an expander to meet the regeneration heat requirements of the purifier with minimal electrical energy consumption. It also recovers the waste heat from the tail gas to enhance the expander’s power generation, thereby realizing efficient and comprehensive energy utilization. Mathematical models have been established for components such as the adsorber, compressor, and expander, and simulations have been conducted based on actual data from an industrial-grade purifier. Consequently, historical parameter curves and bed profiles at the inlet and outlet of the adsorber have been obtained, providing insights into the purification performance and regeneration effectiveness of the new process. Furthermore, the inlet and outlet parameters, as well as the power consumption of the compressor and expander, have been determined. The temperature bed profiles and temperature history curves at the inlet and outlet of the regenerator have also been obtained. Subsequently, a comparison has been made between the new and traditional processes regarding energy consumption, and an economic assessment of the new process has been conducted based on its energy-saving potential. The following conclusions have been drawn through comparative analysis: (1) Compared to the traditional process, the new process can save approximately 51.6 % of electrical energy; (2) The payback period for retrofitting the traditional process to the new one is approximately 1.93 years.

Preparation and characterization of phase change material emulsions and their applications in liquid cooling systems for wind turbines

In order to improve the effect of liquid cooling system for wind turbine, this study used ultrasonic preparation method, stearic acid as phase change material, sorbitan trioleate and sodium lauryl sulfate as compound surfactants successfully prepared stearic acid phase change material emulsion as a cooling medium for investigation. The characterization, thermophysical properties, and fluidity of stearic acid phase change material emulsions at varying concentrations were examined through differential scanning calorimetry, thermal constant analysis, and viscometry. To investigate the cooling effects, a stator axial liquid cooling model was developed for both water and a 14 % stearic acid phase change material emulsion. Findings revealed that the 14 % stearic acid phase change material emulsion exhibited a latent heat of phase change of 22.5 J/g, reaching a peak melting temperature of 68.7 °C. Additionally, the latent heat of solidification was measured at 21.08 J/g, accompanied by a peak solidification temperature of 60.3 °C. The maximum thermal conductivity reached 0.5801 W/(m·K), and the specific heat capacity peaked at 5219.8 J/(K·mol), marking a notable improvement of 1.26 times. Under an inlet temperature of 30 °C and a flow rate of 1 L/min, stearic acid phase change material emulsion effectively lowered the temperatures of the windings, stator, rotor, and casing by 19.2 °C, 23.6 °C, 19.2 °C, and 9.6 °C, respectively. stearic acid phase change material emulsion demonstrates excellent temperature control effectiveness at 3600 r/min and a low flow rate of 1 L/min, showcasing efficient energy utilization efficiency.