Low Efficiency Research Articles

A reliability calculation method based on ISSA-BP neural network

PurposeTo address the shortcomings of the traditional back propagation (BP) neural network agent model, such as insufficient fitting accuracy and low computational efficiency, an improved method is proposed.Design/methodology/approachIn this study, an improved sparrow search algorithm (ISSA) is developed to optimize the reliability calculation of the BP neural network (ISSA-BP) using an enhanced BP neural network model. The traditional sparrow search algorithm is enhanced by incorporating a golden sine strategy to improve its position-updating mechanism, thereby overcoming its tendency to converge prematurely to local optima. Additionally, an opposition-based learning strategy is integrated to explore the reverse solution around the optimal solution of the sparrow search algorithm, mitigating the risk of local optima.FindingsThe results of the test function demonstrate that the proposed method significantly enhances fitting accuracy while maintaining computational efficiency. Finally, by applying this approach to the metro bogie frame as a case study, the structural reliability of the bogie frame is evaluated using the Monte Carlo method, providing valuable insights for subsequent analysis and structural optimization.Originality/valueThe use of the surrogate model approach for structural reliability analysis significantly improves solution efficiency. Furthermore, the integration of ISSA with the BP neural network enhances both fitting accuracy and computational efficiency, demonstrating the superiority and practicality of the proposed method.

Improved hole injection for AlGaN-based DUV LEDs with graded-composition multiple quantum barrier insertion layers

The primary impediments to achieving high external quantum efficiency (EQE) and light output power (LOP) in AlGaN-based deep-ultraviolet light-emitting diodes (DUV LEDs) are inadequate hole injection efficiency and pronounced electron leakage. The significant polarization-induced positive charges, originating from the discontinuity in the Al composition between the last quantum barrier (LQB) and electron-blocking layer (EBL), attract electrons, consume holes, and reflect holes back into the p-type region, leading to severe electron leakage and low hole injection efficiency. In this paper, we introduce a graded-composition multiple quantum barrier (GQB) structure at the LQB/EBL interface. We adjust the Al composition in the insertion layer to alter the electrical polarity of the polarization-induced sheet charges, thereby modifying the electric field distribution in the EBL, LQB, and inserted GQB structure. Consequently, holes acquire boosted energy during their migration towards the active region. In addition, we enhance the hole injection and electron confinement ability via reducing the effective valence band barrier height and increasing the effective conduction band barrier height, thus diminishing the possibility of electron leakage from the active region into the p-type region. Therefore, the GQB structure proposed in this study provides a promising approach to improving the optical and electrical performance of DUV LEDs.

Dye-Sensitized Solar Cells: Unveiling Barriers to Enhanced Performance

Global energy consumption is steadily increasing, and the world's reliance on non-renewable energy sources such as hydroelectric and thermoelectric power is unsustainable due to their diminishing availability. The photovoltaic (PV) devices have been developed through various methods for various applications, and among these, Dye- Sensitized Solar Cells (DSSCs) have emerged as a cost-effective and easily implementable technology. This comprehensive review paper offers an in-depth overview of DSSCs, aiming to provide insights into their construction, working principles, applications, and the significant challenges they face, primarily related to their low efficiency and stability. To fully commercialize DSSCs and compete with existing energy technologies, it is imperative to continue addressing and overcoming the efficiency challenges outlined in this review. KEYWORDS: TiO2, Dye Sensitized Solar Cell, Electrolyte, Photoanode, Counter Electrode

Influence of Chloride and Electrolyte Stability on Passivation Layer Evolution at the Negative Electrode of Mg Batteries Revealed by operando EQCM‐D

Rechargeable magnesium batteries are promising for future energy storage. However, among other challenges, their practical application is hindered by low coulombic efficiencies of magnesium plating and stripping. Fundamental processes such as the formation, structure, and stability of passivation layers and the influence of different electrolyte components on them are still not fully understood. In this work, we gain unique insights into the initial Mg plating and stripping cycles by comparing Mg bis(trifluoromethanesulfonyl)imide (Mg(TFSI)2)‐ and Mg tetrakis(hexafluoroisopropyloxy)borate (Mg[B(hfip)4]2)‐based electrolytes, each with and without MgCl2, on gold electrodes by highly sensitive operando electrochemical quartz crystal microbalance with dissipation monitoring (EQCM‐D) applying hydrodynamic spectroscopy. With the stable Mg[B(hfip)4]2‐based electrolytes, highly efficient and interphase‐free cycling is possible and passivation layers are attributed to electrolyte contaminants. These are forming and degrading during the so‐called initial conditioning process. With the more reactive Mg(TFSI)2‐based electrolyte, thick passivation layers with small pores are growing during cycling. We demonstrate that the addition of chloride lowers the amount of passivated Mg deposits in these electrolytes and accelerates the currentless dissolution of the passivation layer. This has a positive effect since we observe the most efficient cycling and uniform deposition when no interphase is present on the electrode.

High‐Performance Infrared Scene Generation Using a Double‐S Microbridge Photothermal Film Emitter With Ultralarge Array

AbstractInfrared emitters are highly desirable for applications in infrared imaging and stealth technology. Photothermal film emitters, which are driven by light, have garnered considerable interest due to their excellent photothermal properties and ease of fabrication. However, existing photothermal films often suffer from low photothermal conversion efficiency (PCE) and limited array scale. Here, a photothermal film emitter featuring a double‐S microbridge structure is presented, which comprehensively considering the PCE and frame rate. Initially, Si microbridges are fabricated within each microstructure to support the photothermal film. The pattern structure is then arranged into a double‐S configuration to manipulate the thermal conductivity. By optimizing the length and width of the double‐S pattern, high PCE and fast frame rates are achieved. The double‐S microbridge structure photothermal film emitter is fabricated with a 4‐inch diameter, forming an ultra‐large array with over 3000 × 3000 pixels. The absorption and photothermal conversion characteristics are studied, revealing a maximum temperature of 582.70 K and a highest PCE of 16.32%. Time‐dependent photothermal response demonstrated the emitter's rapid heat storage and release capabilities. Additionally, an infrared scene generator is realized. These results position the photothermal film emitter as a promising solution for infrared imaging and dynamic scene generation.

Enhanced TomoSAR imaging method with complex least squares for 3D building reconstruction

ABSTRACT Synthetic aperture radar tomography (TomoSAR) has emerged as an advanced technology for the rapid acquisition of three-dimensional information, with model solutions dependent on a specific complex least squares adjustment criterion. We design two TomoSAR imaging algorithms based on two adjustment criterions minimizing the square sum of the real and imaginary components of observation vector residual, and minimizing the square sum of the L2-norm of observation vector residual. Additionally, we propose a strong scatterer recognition method that combines amplitude thresholding and density-based spatial clustering of applications with noise to alleviate the low efficiency and excessive noise in real images. The simulated and practical experiments are conducted to evaluate the performance of algorithms. Results suggested that two algorithms perform similarly in parameter estimation accuracy and noise immunity for buildings with simple structures and single scatterer. However, for buildings with multiple scatterers, the algorithm derived by minimizing the square sum of the L2-norm from the observation vector residual exhibits more robustly than the other algorithm, accurately distinguishing multiple scatterers within pixels and reconstructing 3D scenes mirroring the actual ones. The results verify the effectiveness of the proposed strong scatterer recognition method and the importance of the adjustment criterion in TomoSAR imaging.

A comparative study for optimizing photocatalytic activity of TiO2-based composites with ZrO2, ZnO, Ta2O5, SnO, Fe2O3, and CuO additives

Despite the widespread use of titanium dioxide (TiO2) in photocatalytic applications, its inherent limitations, such as low efficiency under visible light and rapid recombination of electron-hole pairs, hinder its effectiveness in environmental remediation. This study presents a comparative investigation of TiO2-based composites, including TiO2/ZrO2, ZnO, Ta2O3, SnO, Fe2O3, and CuO, aiming to assess their potential for enhancing photocatalytic applications. Photocatalysis holds promise in environmental remediation, water purification, and energy conversion, with TiO2 being a prominent photocatalyst. To improve efficiency and broaden applicability, various metal oxide composites have been explored. Composites were synthesized and characterized using techniques such as XRD, SEM, TEM, and zeta potential analysis to evaluate their structural and morphological properties. Photocatalytic performance was assessed by degrading herbicide Imazapyr under UV illumination. Results revealed that, the photo-activity of all prepared composites were more effective than the photo-activity of commercial hombikat UV-100. The photonic-efficiency is arranged according to the order TiO2/CuO > TiO2/SnO > TiO2/ZnO > TiO2/Ta2O3 > TiO2/ZrO2 > TiO2/Fe2O3 > Hombikat TiO2-UV100. All composites exhibited superior performance, attributed to enhanced light absorption and charge separation. The study underscores the potential of these composites for environmental remediation and energy conservation, offering valuable insights for the development of advanced photocatalysts.

Enhanced Anti‐inflammatory Effects of Diclofenac Delivered Orally via Polyvinylpyrrolidone K30/Silk Fibroin Nanoparticles in a Murine Model of Carrageenan‐Induced Paw Edema

Diclofenac has a relatively low oral bioavailability (50‐60%) and is quickly metabolized with a half‐life of less than 1 h. Therefore, the oral therapeutic effect of diclofenac is not optimal. This research developed polyvinylpyrrolidone K30‐functionalized silk fibroin nanoparticles as an effective delivery system for diclofenac (FNPs‐PVP‐DC). The FNPs‐DC and FNPs‐PVP‐DC were formulated by two methods of adsorption and solvent exchange. Depending on the formulation factors, the obtained particles exhibited different properties of nano‐scale sizes (400‐800 nm), narrow size distribution, negatively charged surfaces (‐17 to ‐19 mV), high PVP K30 incorporation (23%‐50%), pHpzc of ~6.6, and appropriate chemical interactions. Interestingly, particles formulated by the adsorption method showed low drug encapsulation efficiencies of < 15%, whereas the solvent exchange method yielded moderate results of ~40%. The FNPs‐DC possessed aggregated patterns, while the FNPs‐PVP‐DC were more uniformly distributed. All formulations limited diclofenac release (< 20%) under gastric conditions and sustained its release in the intestinal environment. In in‐vivo carrageenan‐induced paw edema mice model, the FNPs‐PVP‐DC demonstrated a 20‐30% higher anti‐inflammatory effect and a faster onset of action (within 1 h) compared to pure diclofenac at the same dose (5 mg/kg). These findings suggest that FNPs‐PVP‐DC have promising potential as novel oral anti‐inflammatory products.

Design, perspectives, and challenges of modification strategies for alkali metal anodes

Abstract. The alkali metal anode has emerged as a focal point of research due to its extremely low oxidation-reduction potential and high theoretical specific capacity. However, challenges such as unstable solid electrolyte interphase (SEI), infinite volume expansion, and uncontrollable dendrite growth result in low coulombic efficiency and irreversible losses during the deposition and stripping processes. To address these issues, various effective strategies have been proposed to protect the alkali metal anode and achieve dendrite-free growth. In this review, we summarize recent advancements in enhancement strategies for alkali metal anodes, including the construction of three-dimensional current collectors and interface engineering. Specifically, we delve into the development of carbon-based current collectors with various dimensions and structures and the application of interface engineering techniques to tackle the challenges of unstable SEI, volume changes, and dendrite growth. Furthermore, we explore advanced characterization techniques that provide deeper insights into the reaction mechanisms and behavior of these enhancement strategies. Finally, we discuss the current limitations and future research directions in protecting alkali metal anodes, aiming to provide valuable insights into the study of dendrite growth and the development of effective protection strategies for alkali metal anodes.

Integrated organic and mineral fertilizer strategies for achieving sustainable maize yield and soil quality in dry sub-humid inceptisols

Maize is one of the important cereal crops grown in rainfed regions of northwestern Himalayas, however, persistent use of chemical fertilizers coupled with poor soil nutrients and water holding capacity due to coarse textured soils poses serious threat to sustaining maize yield and soil health. To address these bottlenecks, a long-term experiment with application of organic manures and mineral fertilizer provides insights to quantify changes in soil organic carbon (SOC), crop yield and rain water use efficiency (RWUE) in rainfed area having low water use efficiency. A twelve years field experiment was conducted under dry sub-humid Inceptisols in northern India to study the potential impacts of organic and mineral fertilization on maize (Zea mays L.) productivity, water use efficiency and soil quality. Ten treatments were assessed, involving different nitrogen levels (20, 30, and 40 kg N ha⁻¹) combined with 10 tha⁻¹ year⁻¹ of farmyard manure (FYM), in-situ green manure from sunhemp, and the incorporation of Leucaena leucocephala leaves at 5 tha⁻¹ year⁻¹, including an unfertilized control. Maize yield increased linearly with increasing nitrogen application rates. The combination of FYM @ 10t ha−1 and 40 kg N ha−1(T4) yielded the highest maize production. Manure addition improved soil organic carbon (SOC) and major soil nutrients (N, P and K) while unfertilized control showed decline in soil nutrients compared to their initial values. Compared with control, incorporation of 10 t ha−1 FYM increased SOC by 1.3, 1.41, 1.44 times at application rate of 20, 30, 40 kg N ha−1, respectively. Application of N@40 kg ha−1 + 10t FYM ha−1 showed highest rain water use efficiency (RWUE) and relative production efficiency index (RPEI) (2.74 kg ha−1 mm−1 and 82, respectively) and the lowest rank sum of 6. Highly significant positive relationship existed between RPEI and RWUE, RPEI and sustainability yield index (SYI), RWUE and SYI indicated the superiority of FYM in combination with mineral fertilizer. Regression models, correlating yield with monthly rainfall and crop growing periods, indicated that the integration of FYM (10 tha⁻¹) with 40 kg N ha⁻¹ was most effective in achieving the highest relative soil quality index (RSQI) of 76 and the greatest sustainability yield index (SYI) of 49.3%. Based on results, we recommend balanced fertilization (N@40 kg ha−1 +10t FYM ha−1) which is easily manageable by farmers as the optimal strategy for improving soil quality and achieving sustainable maize productivity in nutrient depleted Inceptisols of northern India.

Method for Rail Surface Defect Detection Based on Neural Network Architecture Search

Abstract This study addresses the inherent limitations of implementing neural network architecture search algorithms for rail surface defect detection, including low search efficiency and the oversight of edge features on the rail surface. A sophisticated multi-level neural network architecture search framework is proposed that integrates and emphasizes rail surface edge features. The framework utilizes the Z-Score normalization method to quantify the edge concern of rail surface defect samples, combined with an Edge-Loss function to enhance edge feature recognition capabilities. Furthermore, acknowledging the sensitivity of defect features to spatial resolution changes, a multi-level neural network architecture search space is meticulously designed. In the cell-level search space, a method combining partial channel sampling with operation pruning is employed to enhance model search efficiency and regularization. In the network-level search space, optimal paths for resolution change are established, allowing for the screening and aggregation of defect features at various levels to facilitate the adaptive extraction of multi-scale edge defect features. Experimental outcomes indicate that this method significantly reduces computational resource usage by approximately 75% and increases mIOU by 2.6% relative to traditional architecture search methods. Moreover, it demonstrates robust capability in accurately recognizing defective edges on rail surfaces, thereby substantiating the method's effectiveness.

Structural Design on Porous Aromatic Frameworks for Photocatalysis

Photocatalytic technology has shown great potential in various fields such as environmental purification, energy conversion, and chemical transformations due to its green, sustainable, and low‐cost characteristics. Porous aromatic frameworks (PAFs) with high specific surface areas, designable local structures, and abundant active sites could potentially serve as efficient photocatalysts for various catalytic reactions. This makes PAFs have a wide range of application prospects and significant advantages in the field of photocatalysis. This concept discusses the recent progress of photocatalysis over PAFs. Various strategies are used to solve the general problems of photocatalyst, such as poor light absorption, low carrier separation efficiency and poor stability, which further reveal the relationship between their structure and performance.

Differential Game Analysis of Carbon Emission Reduction Effect and Price Strategy Considering Government Intervention and Manufacturer Competition

ABSTRACTGovernments and enterprises are paying more and more attention to carbon emissions. Considering the dynamic of carbon emissions reduction (CER) and the government intervention, this study discusses the optimal CER effort level, price, and government intervention intensity in a two‐echelon supply chain consisting of a government and two manufacturers. The two manufacturers have two competitive behaviors: Cournot and Stackelberg. Two differential game models are constructed for the two different behaviors, and the optimal decisions under the two models are obtained. The comparisons of these optimal solutions are analyzed, and the influence of some parameters on the optimal solution in the two models is investigated under two scenarios. Furthermore, the optimal government intervention intensity is obtained with the goal of maximizing government utility. The results show that the Stackelberg game allows manufacturers to achieve higher profits and CER but is disadvantageous to consumers, and the manufacturer as the leader has a first‐mover advantage. Fierce market competition leads to greater CER and profits, but higher prices reduce consumer surplus. Larger penalties can promote enterprises to reduce carbon emissions when carbon emissions are large. Compared with the Cournot behavior game, the Stackelberg allows manufacturers to obtain higher profits and CER, but the prices are higher that are detrimental for consumers. The fierce market competition is good for manufacturers, the environment, and the society, but it reduces the consumer surplus. The low CER efficiency causes high costs and reduces the manufacturer's motivation to CER, which harm the environment and reduce profits. The government intervention is negatively correlated with the intensity of market competition and the sensitivity of manufacturers to policies.

Whole Genome Sequencing and Comparative Genomic Analysis of Pseudomonas aeruginosa SF416, a Potential Broad-Spectrum Biocontrol Agent Against Xanthomonas oryzae pv. oryzae

Rice is one of the most important staple crops worldwide. However, the bacterial blight of rice caused by Xanthomonas oryzae pv. oryzae (Xoo) poses a major threat to the production of rice. In this study, we isolated and identified the strain Pseudomonas aeruginosa SF416, which exhibited significant antagonistic activity against Xoo, from a soil sample collected in a winter wheat field in Shannanzhalang County, Tibet, China. The bacterial solution (BS) and cell-free supernatant (CFS) of SF416 had significant prevention effects for the bacterial blight of rice, with an efficacy of 45.1% and 34.18%, respectively, while they exhibited a slightly lower therapeutic efficiency of 31.64% and 25.09%. The genomic analysis showed that P. aeruginosa SF416 contains genes involved in cell motility, colonization, cold and hot shock proteins, antibiotic resistance, and plant growth promotion. SF416 also harbors two sets of phenazine-1-carboxylic acid (PCA) synthesis gene clusters, phz1 (phzA1-G1) and phz2 (phzA2-G2), and other phenozine product-synthesis--related genes phzS, phzM, and phzH, as well as genes in the SF416 genome that share high similarity with the ones in the genomes of P. aeruginosa M18, suggesting that the two sets of PCA synthesis gene clusters are responsible for the antagonistic effect of SF416 against Xoo. A comparative antiSMASH analysis revealed that P. aeruginosa SF416 contains 17 gene clusters related to secondary metabolite synthesis, 7 of which, encoding for pyochelin, azetidomonamide A/B, L-2-amino-4-methoxy-trans-3-butenoic acid, hydrogen cyanide, pyocyanine, pseudopaline, and bicyclomycin, are conserved in strains of P. aeruginosa. Moreover, SF416 can produce protease and siderophores and display a broad-spectrum antagonistic activity against various major plant pathogenic bacteria and fungi. The results suggest that P. aeruginosa SF416 could be a potential candidate agent for the bacterial blight of rice.

An Efficient and Stable Registration Framework for Large Point Clouds at Two Different Moments

Point cloud registration plays a great role in many application scenarios; however, the registration of large-scale point clouds for actual different moments suffers from the problems of low efficiency, low accuracy, and a lack of stability. In this paper, we propose a registration framework for large-scale point clouds at different moments, which firstly downsamples large-scale point clouds using a random sampling method, then performs a random expansion strategy to make up for the loss of information caused by the random sampling, then completes the first registration by a deep learning network based on the extraction of keypoints and feature descriptors in combination with RANSAC, and finally completes the registration using the point-to-point ICP method. We conducted validation experiments and application experiments on large-scale point clouds of key train components, and the experimental results are much higher in accuracy or efficiency than other methods, which proves the effectiveness of our framework, which can be applied to actual large-scale point clouds.

The Study of Water Content on the Coal Loading Performance of Thin Coal Seam Shearer Drum by Discrete Element Method (DEM)

ABSTRACTAs the main component of thin coal seam shearers, the drum bears the functions of loading and cutting, and its performance has become an important factor restricting mining efficiency and production safety. In response to the problem of low efficiency in installing thin coal seam shearers, this paper uses the Discrete Element Method (DEM) to study the effects of loading methods, helical angle of drum, drum rotation speed, and particle water content on coal loading rate. Research has found that the coal loading performance of the ejection loading method is much higher than that of the pushing loading method. As the helical angle increases, the average loading rate increases. As the rotation speed increases, the loading rate of wet coal particles gradually decreases. During production and thin coal seam mining, special attentions should be paid to the control of helical angle of drum and drum rotation speed. This study has guiding importance for improving the efficiency of thin coal seam mining.

A Magnetic Climbing Robot for Steel Bridge Inspection

Abstract. The maintenance of traditional steel bridges presents many significant challenges due to the fact that bridges of different ages and standards vary in design, structural complexity and technical difficulty. In light of these considerations, it is clear that maintenance personnel must possess a wealth of professional expertise and experience in order to effectively address the diverse and intricate maintenance challenges that arise. Moreover, the maintenance process entails high-risk operations such as high-altitude work and welding, which pose a threat to the safety of construction personnel. Therefore, this study introduces a magnetic adsorption robot designed to address the low efficiency and high costs of traditional maintenance methods. This robot features a dual robotic arm mechanism and modeled using the Denavit Hartenberg (D-H) parameter method. Electromagnetic adsorption is utilized to achieve wall adhesion, and direct power supply is provided through DC power to control weight. The robot can perform flexible remote control operations through the HC-05 Bluetooth module. The experimental results show that the robot exhibits robust adhesion and obstacle crossing ability on steel surfaces, thereby enabling unimpeded movement within the steel structure. In addition, the robot is now capable of performing overhaul procedures via remote control.

Recurrent Aphthous Stomatitis and Sleep Quality Factors: A Comprehensive Analysis

ABSTRACTBackgroundDue to the unclear etiology of recurrent aphthous stomatitis (RAS), a painful and distressing condition with a high prevalence, the researchers have hypothesized a connection between sleep quality and RAS.MethodsThe cross‐sectional study enrolled 10,138 Fasa Cohort Study participants aged 35–70 years. Various sleep quality factors were calculated and categorized based on the Pittsburgh Sleep Questionnaire.ResultsAmong 9030 subjects finally included with RAS prevalence of 20.2%, adjusted logistic regression showed significant odds ratios (ORs) in subjects who sleep < 5 h (OR = 1.44, 95%CI 1.25, 1.66), have sleep latencies of more than 60 min (OR = 1.37, 95%CI 1.11, 1.69), have sleep efficiencies of 65%–75% (OR = 1.55, 95%CI 1.21, 1.98), or regularly go to bed after 11 p.m. (OR = 1.23, 95%CI 1.11, 1.37). Subgroup analyses indicated no significant associations between RAS and various sleep factors in individuals who worked night shifts, and stronger associations were observed in men than women.ConclusionThe study found a significant positive association between RAS and sleep quality factors such as shorter duration, lower efficiency, longer latency, later bedtime, and regular sleeping pill use. Establishing early and sufficient sleep and addressing sleep onset disturbances by adhering to sleep hygiene principles should be prioritized in individuals with RAS.

Prediction of Syngas Composition During Gasification of Lignocellulosic Waste Mixtures

Avoiding global dependence on fossil oils and improving the environmental impact of energy production are factors that drive research into renewable energies. Considering lignocellulosic biomass residues as a raw material for gasification, a thermochemical process that converts lignocellulosic resources into synthesis gas (H2, CO, CH4, and CO2) is an alternative under study due to its low costs, high efficiency, and wide variety of applications. Fortunately, there are still areas for its improvement and technological development. For example, this can be achieved by gasification. Distinct types of lignocellulosic biomass, such as sugarcane bagasse, wheat straw, pine sawdust, or corn cob, differ in their physical, chemical, and morphological properties, which can affect the characteristics of the gasification process. This work uses the generalized stoichiometry and mass and atomic balances in the gasification reactor to predict the composition of syngas produced via the gasification of both individual substrates and mixtures. The results provide useful information for the design and operation of gasification reactors with an operating region between 2.0 bar and 4.5 bar and between 1023.15 K and 1223.15 K, particularly with regard to understanding the effects of distinct types of biomasses in terms of their humidity and molecular weight on the operation and performance of the process. One important conclusion reached after simulating the addition of more vapor is that the (H2/CO) ratio cannot be increased indefinitely: it is limited by the thermodynamic equilibrium reached by the system.

Recent Progress on Air, Liquid, PCM, Heat Pipe, and Hybrid Modes of Thermal Management in Lithium-Ion Batteries

This study emphasises lithium-ion batteries, which have been the subject of extensive research due to their wide range of benefits, including extended life cycle, minimal discharge, and high energy density. However, the temperature sensitivity of the batteries presents a notable obstacle that can negatively impact their performance and longevity when operating under extreme conditions. To overcome this challenge, implementing an effective battery thermal management system (BTMS) is imperative. Battery thermal management is crucial for ensuring the safety and longevity of lithium-ion batteries, especially in high-demand applications like electric vehicles. This comprehensive review explores a variety of BTMS technologies, including air-cooling methods, liquid-cooling techniques, heat pipes, and PCM materials. While air-cooled BTMS is a safe and straightforward design, its lower heat capacity and thermal efficiency limit its use to low-capacity batteries. However, forced air-cooled BTMS is an excellent solution for high charging/discharging rates, as air flows through channels within the battery packs to optimize cooling. Liquid-cooled BTMS also shows promise, although designers must ensure the sealing cover is secure to prevent leaks. Heat pipes (HP) offer a unique approach to controlling battery temperature, while Phase change materials (PCM) thermal management is notable for its ability to absorb significant heat by latent heat. Hybrid cooling combines fins, nanofluids, PCM, and microchannels-based cooling and can significantly enhance battery performance under high charging/discharging rates. Furthermore, lithium-ion batteries are extensively used in various applications, including the Electric vehicle industry. Keeping the lithium-ion battery temperature within the optimal range is important and is accomplished by a suitable BTMS. Different methods, such as air cooling, Liquid cooling, Heat pipe, and PCM materials, are used in BTMS. An effective thermal management system and efficient battery model are absolutely necessary. Each of the techniques in BTMS has its own benefits and drawbacks. The effectiveness of thermal management configurations and methods can vary. Thus, evaluating performance and optimal configuration is crucial before implementation.