Uniform Distribution Research Articles

Effect of stigmasterol and polyglycerol polyricinoleate concentrations on the preparation and properties of rapeseed oil-based gel emulsions

Emulsion gels mimic the rheological properties of solid and semi-solid fats, offering a viable solution to replace conventional fats in low-fat food formulations. In this study, gel emulsions stabilized with stigmasterol (ST) and polyglycerol polyricinoleate (PGPR) complexes were prepared. Initially, we examined the effect of the ST/PGPR complex on the mechanism of gel emulsion stabilization. Our findings revealed that the gel emulsion formulated with 3% PGPR and ST exhibited a robust structure, effectively stabilizing the entire system and ensuring uniform distribution, and increasing ST concentration led to greater stability of the gel emulsion system. Stability assessments demonstrated that gel emulsions containing 3% PGPR and varying ST concentrations exhibited remarkable thermal stability and effectively delayed oil oxidation. These results underscore the high stability of gel emulsions stabilized with the ST/PGPR complex, highlighting their potential as a margarine substitute.

On the Generalisation Performance of Geometric Semantic Genetic Programming for Boolean Functions: Learning Block Mutations

In this paper we present the first rigorous theoretical analysis of the generalisation performance of a Geometric Semantic Genetic Programming (GSGP) system. More specifically, we consider a hill-climber using the GSGP Fixed Block Mutation (FBM) operator for the domain of Boolean functions. We prove that the algorithm cannot evolve Boolean conjunctions of arbitrary size that are correct on unseen inputs chosen uniformly at random from the complete truth table i.e., it generalises poorly. Two algorithms based on the Varying Block Mutation (VBM) operator are proposed and analysed to address the issue. We rigorously prove that under the uniform distribution the first one can efficiently evolve any Boolean function of constant size with respect to the number of available variables, while the second one can efficiently evolve general conjunctions or disjunctions of any size without requiring prior knowledge of the target function class. An experimental analysis confirms the theoretical insights for realistic problem sizes and indicates the superiority of the proposed operators also for small parity functions not explicitly covered by the theory.

Cobalt-Doped Ceria Sensitizer Effects on Metal Oxide Nanofibers: Heightened Surface Reactivity for High-Performing Chemiresistive Sensors.

Chemiresistive gas sensors based on semiconducting metal oxides typically rely on noble metal catalysts to enhance their sensitivity and selectivity. However, noble metal catalysts have several drawbacks for practical utilization, including their high cost, their propensity for spontaneous agglomeration, and poisoning effects with certain types of gases. As such, in the interest of commercializing the chemiresistive gas sensor technology, we propose an alternative design for a noble-metal-free sensing material through the case study of Co-doped ceria (Co-CeO2) catalysts embedded in a SnO2 matrix. In this investigation, we utilized electrospinning and subsequent calcination to prepare Co-CeO2 catalyst nanoparticles integrated with SnO2 nanofibers (NFs) with uniform particle distribution and particle size regulation down to the sub-2 nm regime. The resulting Co-CeO2@SnO2 NFs exhibited superior gas sensing characteristics toward isoprene (C5H8) gas, a significant biomarker for monitoring the onset of various diseases through breath diagnostics. In particular, we identified that the Co-CeO2 catalysts, owing to the transition metal doping, facilitated the spillover of chemisorbed oxygen species to the SnO2 sensing body. This resulting in the sensor having a 27.4-fold higher response toward 5 ppm of C5H8 (compared to pristine SnO2), exceptionally high selectivity, and a low detection limit of 100 ppb. The sensor also exhibited high stability for prolonged response-recovery cycles, attesting to the strong anchoring of Co-CeO2 catalysts in the SnO2 matrix. Based on our findings, the transition metal-doped metal oxide catalysts, such as Co-CeO2, demonstrate strong potential to completely replace noble metal catalysts, thereby advancing the development of the commercially viable chemiresistive gas sensors free from noble metals, capable of detecting target gases at sub-ppm levels.

Simulation analysis and optimization of containerized energy storage battery thermal management system

The air-cooling system is of great significance in the battery thermal management system because of its simple structure and low cost. This study analyses the thermal performance and optimizes the thermal management system of a 1540 kWh containerized energy storage battery system using CFD techniques. The study first explores the effects of different air supply angles on the heat transfer characteristics. Second, the evaluation indexes of heat removal efficiency, air exchange efficiency, temperature and velocity uniformity coefficient are used to select the optimal air supply angle by the Topsis method. Then, the return air vent position is optimized based on the optimal air supply angle, and the optimal solution is obtained. Research indicates that increasing the air supply angle enhances air mixing within the container and simultaneously decreases the battery pack surface temperature. With a 90° air supply angle, the maximum temperature reduces to 33.58 °C, a 19.52 % reduction compared to 30°. The temperature difference across each battery surface also drops by 16.02 % to 3.46 °C. Adjusting the position of the return air vent further improves temperature uniformity and air flow distribution within the battery compartment. When the air supply angle is 90° and the return air vent evenly distributed at Z = 0.85 m next to the fire door, an optimal uniform temperature distribution is achieved. This reduces the maximum surface temperature by 16.47 %, from 36.67 °C to 30.63 °C and decreases the average temperature difference to 3.0 °C, 21.4 % lower. Thus, the present method effectively enhances the performance of the containerized energy storage battery thermal management system.

Novel TiO2-Supported Gold Nanoflowers for Efficient Photocatalytic NOx Abatement

In this study, we pioneered the synthesis of nanoflower-shaped TiO2-supported Au photocatalysts and investigated their properties. Au nanoflowers (Au NFs) were prepared by a Na-citrate and hydroquinone-based preparation method, followed by wet impregnation of the derived Au NFs on the surface of TiO2 nanorods (TNR). A uniform and homogeneous distribution of Au NFs was observed in the TNR + NF(0.7) sample (lower Na-citrate concentration), while their distribution was heterogeneous in the TNR + NF(1.4) sample (higher Na-citrate concentration). The UV-Vis DR spectra revealed the size- and shape-dependent optical properties of the Au NFs, with the LSPR effect observed in the visible region. The solid-state EPR spectra showed the presence of Ti3+, oxygen vacancies and electron interactions with organic compounds on the catalyst surface. In the case of the TNR + NF(0.7) sample, high photocatalytic activity was observed in the H2-assisted reduction of NO2 to N2 at room temperature under visible-light illumination. In contrast, the TNR + NF(1.4) catalyst as well as the heat-treated samples showed no ability to reduce NO2 under visible light, indicating the presence of deformed Au NFs limiting the LSPR effect. These results emphasized the importance of the choice of synthesis method, as this could strongly influence the photocatalytic activity of the Au NFs.

Multifunctional CoCe/silica and CoMnCe/silica spinel ferrite nanocomposite: in vitro and in vivo evaluation for cancer therapy

Multifunctional magnetic spinel ferrite based on CoCe and CoMnCe/silica nanocomposites (NCs) were developed for targeted cancer therapeutics. The formation of spinel ferrite and co-existence of spinel ferrite/silica/chemo-drug, surface/pore size distribution, morphological features and magnetic properties were investigated using different characterization techniques. XRD pattern confirmed the pure phase of CoCe and CoMnCe spinel ferrite with estimated crystal size of 27.9 nm. After silica coating and pegylation, the crystal size of CoCe and CoMnCe increases to 36.3 nm and 76.2 nm. Nitrogen adsorption isotherm confirm an effective embedment of both spinel ferrites into silica with large surface area (653 m2/g and 718 m2/g) and uniform pore size distributions (6.1 nm and 6.9 nm). FT-IR spectra confirm the magnetic spinel ferrite/silica interactions (977, 1705 and 3410 cm−1), cisplatin functionalization (1645 cm−1) and PEG (1275–2900 cm−1). Coating SFNPswith Si and/or Cp and/or PEG, tunes the magnetic characteristics of the NCs system. For both CoCe and CoMnCe SFNPs, saturation magnetization (Ms) of 14.96 and 10.91 emu/g, residual magnetization (Mr) of 4.40 and 2.42 emu/g, Hc (coercivity) of 1072.1 and 719.3 Oe gradually diminish upon Si, respectively. The chemical state of CoMnCe SFNPs, CoCe SFNPs, their silica and active cisplatin NCs (Pt0 and Pt2+) were investigated using X-ray Photoelectron Spectroscopy (XPS). The anti-cancer efficacy of pegylated nanoformulations were tested in in vitro cells (HeLa, HCT-116 and HEK-293) and Hemolysis assay. The toxicity of different nanoformulations administered in different concentrations (20–2000 mg/kg) in in vivo was estimated based on LD50 value.

Dynamic Directional Ultrasonically In Situ-Generated N,S-Codoped Carbon Dots in Poly(ethylene glycol) for Improved Tribological Performance.

The dispersion stability of nanomaterials in lubricants significantly influences tribological performance, yet their addition as lubricant additives often presents challenges in secondary dispersion. Here, we present a straightforward method for in situ preparation of N,S-codoped CDs (N,S-CDs)-based lubricants using heterocyclic aromatic hydrocarbons containing N/S elements in poly(ethylene glycol) (PEG) base oil by a directional ultrasound strategy. Two types of N,S-CDs were successfully prepared via the directional ultrasound treatment of PEG with benzothiazole (BTA) and benzothiadiazole (BTH) separately. The resultant N,S-CDs have a uniform distribution of N and S elements and maintain good colloidal dispersion stability in PEG even after 9 months of storage. The N,S-CDs can enter the surface gap of the friction pairs and then induce a tribochemical reaction. Benefiting from the synergistic effect of N and S activating elements, a robust and stable protective film consisting of iron sulfides, iron oxides, carbon nitrides, and amorphous carbonaceous compounds is formed, thus endowing N,S-CDs-based lubricants with improved antiwear and friction-reducing performance. Compared with pure PEG, the coefficient of friction (COF) of the N,S-CDs(BTH)-based lubricant decreased to 0.108 from 0.292, accompanied by a 91.2% reduction in wear volume, and the maximum load carrying capacity increased to 450 from 150 N.

Elastic Foundation Solution for the End Notched Flexure (ENF) Mode II Sandwich Configuration

Abstract This paper presents a closed form solution for the energy release rate of face/core debonds in the Mode II end notched flexure (ENF) sandwich configuration. The finite-length sandwich specimen is considered to have a “debonded” region and a “joined” region. In the later, the interface between the top face and the substrate (core and bottom face) is modeled by an elastic foundation, which is a uniform distribution of shear and normal springs. Based on the Timoshenko beam theory, the solution for a general asymmetric sandwich construction is derived. The energy release rate expression is derived via the J-integral. Another closed form expression for the energy release rate is derived from the energy released by a differential spring as the debond propagates. In this closed form solution there is no fitting and everything, including the foundation constants, are given in closed form. Results are produced for a range of face/core stiffness ratios and debond length/core thickness ratios, and are compared with the corresponding ones from a finite element solution. A very good agreement is observed except for small debond lengths vs specimen thickness.

Green synthesis of Vitis vinifera extract-appended magnesium oxide NPs for biomedical applications

Abstract Biologically active magnesium oxide (MgO) nanoparticles were synthesised using green reduction with an extract derived from the Vitis vinifera plant. The investigation focused on examining the structure and carbon abundance resulting from the thermal degradation of adsorbed biomolecules. It was accomplished using powder X-ray diffraction, Raman spectroscopy, and FT-IR analysis techniques. X-ray photoelectron spectroscopy studies conducted on MgO nanoparticles indicate the absence of any supplementary peaks, thereby indicating the purity of the material. The morphological characteristics, which have been examined using field emission scanning electron microscopy and TEM methodologies, demonstrate the presence of particles with a spherical shape, exhibiting minimal agglomeration and a uniform distribution across the surfaces of MgO. The porous structure, porosity, and pore volume of the MgO particles were evaluated using Brunauer-Emmett-Teller surface analysis. The experimental findings reveal that the surface area of the MgO nanoparticles is 23.8742 m2/g, while the total pore volume is 0.12528 cm3/g. Additionally, the average pore diameter is determined to be 1.7 nm. These observations collectively suggest the presence of microporous structures within the MgO nanoparticles. This article discusses the biological studies to assess the antibacterial, antifungal, anti-inflammatory, and anti-diabetic activities of the synthesised MgO nanoparticles.

Multi-Objective Evolutionary Neural Architecture Search with Weight-Sharing Supernet

Deep neural networks have played a crucial role in the field of deep learning, achieving significant success in practical applications. The architecture of neural networks is key to their performance. In the past few years, these architectures have been manually designed by experts with rich domain knowledge. Additionally, the optimal neural network architecture can vary depending on specific tasks and data distributions. Neural Architecture Search (NAS) is a class of techniques aimed at automatically searching for and designing neural network architectures according to the given tasks and data. Specifically, evolutionary-computation-based NAS methods are known for their strong global search capability and have aroused widespread interest in recent years. Although evolutionary-computation-based NAS has achieved success in a wide range of research and applications, it still faces bottlenecks in training and evaluating a large number of individuals during optimization. In this study, we first devise a multi-objective evolutionary NAS framework based on a weight-sharing supernet to improve the search efficiency of traditional evolutionary-computation-based NAS. This framework combines the population optimization characteristic of evolutionary algorithms with the weight-sharing ideas in one-shot models. We then design a bi-population MOEA/D algorithm based on the proposed framework to effectively solve the NAS problem. By constructing two sub-populations with different optimization objectives, the algorithm can effectively explore network architectures of various sizes in complex search spaces. An inter-population communication mechanism further enhances the algorithm’s exploratory capability, enabling it to find network architectures with uniform distribution and high diversity. Finally, we conduct performance comparison experiments on image classification datasets of different scales and complexities. Experimental results demonstrate the effectiveness of the proposed multi-objective evolutionary NAS framework and the practicality and transferability of the introduced bi-population MOEA/D-based NAS method compared to existing state-of-the-art NAS methods.

Bayesian parameter estimation using truncated normal distributions as priors for parameters in fundamental models of chemical processes

AbstractModellers of chemical processes with knowledge about plausible parameter values use Bayesian parameter estimation methods to account for their prior beliefs. Some modellers specify prior distributions with finite parameter ranges, such as uniform distributions and truncated normal distributions, because they better account for knowledge about realistic parameter ranges than normal prior distributions with parameter values ranging between and . We derive closed‐form objective functions for Bayesian parameter estimation with truncated normal priors and uniform priors, for the first time, so that parameter estimation can be performed by solving simple optimization problems rather than using complex sampling‐based techniques. A parametric bootstrapping method that considers truncated normal priors and model nonlinearity is proposed to determine 95% confidence intervals and joint confidence regions. A pharmaceutical case study is used to show the effectiveness of the proposed objective functions and bootstrapping methodology. Confidence regions from bootstrapping are similar to linearization‐based confidence regions that do not account for truncation when truncated areas in normal prior distributions are relatively small. More truncation, which corresponds to more‐precise prior knowledge about the parameters, results in smaller joint confidence regions. The proposed methods will be attractive for parameter estimation in complex process models because they can be less computationally intensive than Markov chain Monte Carlo methods that provide similar results.

Numerical simulation analysis of composite flow field design on mass transfer in proton exchange membrane fuel cell

Bipolar plate flow field design is crucial for optimizing Proton Exchange Membrane Fuel Cell (PEMFC) performance. This study employs three-dimensional simulations and Computational Fluid Dynamics (CFD) methods to analyze and compare traditional Straight Parallel Flow Field (SPFF), Block Incorporated Flow Field (BIFF), Sub-channel Ribbed Flow Field (SRFF), and Combined Block and Sub-channel Flow Field (CBSFF). The findings indicate that CBSFF not only demonstrates superior oxygen distribution characteristics at high current densities but also shows improved uniformity in moisture and temperature distribution. In addition, the effect of the structural parameters of the CBSFF flow field on its performance has been investigated. In particular, at a voltage of 0.5 V, the net power of the CBSFF is increased by 18 percent compared with that of the SPFF when the height of the block, hb=0.5, and the height of the subchannel, hs=0.3, are used.

Approximation of the Pressure-discharge Curve in Inline Drip Irrigation System

The efficiency of drip irrigation systems depends directly on the uniformity of water discharge from emission devices. Ideally, all emitters should discharge equal amounts of water, but variations occur due to hydraulic and manufacturing factors. This study established the pressure-discharge relationship curve and determined emitter flow variation caused by the hydraulic and the manufacturer’s coefficients of variation for 2 and 4 lph inline emitters. The power exponent and constant of the pressure-discharge curve were determined by measuring the emitter flow rates at operating pressures ranging from 0.2 to 3.0 kg/cm². The emitter flow rates of 100 emitters were measured at an operating pressure of 1.0 kg/cm² to determine the manufacturing coefficient (Vm) and emitter flow variation (qvar(m)). The discharge exponent was found to be 0.46 for both emitter flow rates, with proportionality constants of 0.692 for 2 lph and 1.387 for 4 lph emitters respectively. The results showed a strong correlation between pressure and flow rate, with RMSE values of 0.51 and 0.34 lph, and coefficients of determination of 0.988 and 0.991 for 2 and 4 lph emitters, respectively. High manufacturing precision was indicated by low Vm values of 0.0491 for 2 lph and 0.055 for 4 lph emitters, while qvar(m) values were 0.261 for 2 lph and 0.283 for 4 lph emitters. Total coefficient of variation (Vq) values were 0.1 for 2 lph and 0.14 for 4 lph emitters, with total emitter flow variations (qvar) of 0.29 for 2 lph and 0.39 for 4 lph emitters. The study established the pressure-discharge curve for inline drip irrigation systems, emphasizing the critical relationship between pressure and flow rate. The derived chart from pressure discharge relationship is a valuable tool for estimating emitter flow variation due to hydraulic variation within the same subunit. Precise manufacturing and effective management of hydraulic variations are essential for ensuring uniform water distribution, optimizing drip irrigation systems, and ultimately enhancing crop yield and resource utilization.

Approximation of the Pressure-discharge Curve in Inline Drip Irrigation System

The efficiency of drip irrigation systems depends directly on the uniformity of water discharge from emission devices. Ideally, all emitters should discharge equal amounts of water, but variations occur due to hydraulic and manufacturing factors. This study established the pressure-discharge relationship curve and determined emitter flow variation caused by the hydraulic and the manufacturer’s coefficients of variation for 2 and 4 lph inline emitters. The power exponent and constant of the pressure-discharge curve were determined by measuring the emitter flow rates at operating pressures ranging from 0.2 to 3.0 kg/cm². The emitter flow rates of 100 emitters were measured at an operating pressure of 1.0 kg/cm² to determine the manufacturing coefficient (Vm) and emitter flow variation (qvar(m)). The discharge exponent was found to be 0.46 for both emitter flow rates, with proportionality constants of 0.692 for 2 lph and 1.387 for 4 lph emitters respectively. The results showed a strong correlation between pressure and flow rate, with RMSE values of 0.51 and 0.34 lph, and coefficients of determination of 0.988 and 0.991 for 2 and 4 lph emitters, respectively. High manufacturing precision was indicated by low Vm values of 0.0491 for 2 lph and 0.055 for 4 lph emitters, while qvar(m) values were 0.261 for 2 lph and 0.283 for 4 lph emitters. Total coefficient of variation (Vq) values were 0.1 for 2 lph and 0.14 for 4 lph emitters, with total emitter flow variations (qvar) of 0.29 for 2 lph and 0.39 for 4 lph emitters. The study established the pressure-discharge curve for inline drip irrigation systems, emphasizing the critical relationship between pressure and flow rate. The derived chart from pressure discharge relationship is a valuable tool for estimating emitter flow variation due to hydraulic variation within the same subunit. Precise manufacturing and effective management of hydraulic variations are essential for ensuring uniform water distribution, optimizing drip irrigation systems, and ultimately enhancing crop yield and resource utilization.

Biomass Pellet Processing from Sugar Industry Byproducts: A Study on Pelletizing Behavior and Energy Usage

As global energy demand has increased, bioenergy has emerged as a viable option for reducing greenhouse gas emissions. This study focuses on using waste materials from the sugar industry, such as sugarcane straw, bagasse, and filter cake, to compress into pellets to investigate pelletizing behavior and energy usage. Raw material preparation was a critical phase influencing pelletizing efficiency. Biomass pellet quality depended on a uniform particle size distribution and adequate moisture content. A moisture content of 20% (wb) was found to be suitable for biomass pelletization from the sugar sector. Specific energy in the pelletizing process ranged from 144.28 to 197.85 Wh/kg. The suggested mixing ingredients (sugarcane leaves: bagasse: filter cake) of 0% sugarcane leaves, 90% bagasse, 10% filter cake, and 5% sugarcane leaves, 93.5% bagasse, and 1.5% filter cake resulted in pellets with a bulk density of over 600 kg/m3 and a durability of at least 97.5%. All aspects were assessed according to standardized criteria for developing biomass pellet processing technology from sugar industry byproducts. This method could improve efficiency, boost production volume, lower production costs, and promote the efficient and cost-effective use of renewable energy.

Research on Improving Moisture Resistance of Asphalt Mixture with Compounded Recycled Metallurgical Slag Powders

The utilization of steel slag as an alternative material in asphalt mixtures is considered the solution to the problem of the shortage of natural aggregates. However, asphalt mixtures with steel slag show susceptibility to damage caused by moisture, especially in powder form. Therefore, blast furnace slag powders were used to compound with steel slag powders as fillers to improve the moisture resistance of asphalt mixtures. The characteristics of the steel slag powders and blast furnace slag powders were investigated initially. Subsequently, the adhesion properties of the asphalt mastics with the powders to the aggregates were evaluated. Finally, the moisture resistances of the asphalt mixtures were identified. The results indicate that the steel slag powder exhibited a notable prevalence of surface pores, which had a more uniform size distribution. In contrast, the blast furnace slag powder exhibited a greater average pore size. The larger specific surface area of the steel slag powder was over 30% larger than that of the blast furnace slag powder, and the superior gelling activity of the blast furnace powder enhanced the adhesion property. Both the steel slag powder and blast furnace slag powder were found to enhance the adhesion properties of the asphalt mastics, while the effect of the steel slag powder was more pronounced, the maximum force difference of which exceeded 200 N. The antagonistic effect of the steel slag powder and blast furnace slag powder on the resistance of the adhesive interface to moisture damage was confirmed by the contact angle test. The incorporation of the blast furnace slag powder markedly enhanced the moisture resistances of the asphalt mixtures. The phenomenon of dynamic moisture damage to the asphalt mixtures was more pronounced under the multicycle times, obviously severer than that in a stable water environment. As the dynamic moisture cycles increased, the degree of destruction gradually approached a steady state.

Analysis of flow field characteristics and factors influencing the excavation chamber in large-diameter slurry shield

The study aims to improve the flow field characteristics in the excavation chamber of the slurry shield to mitigate cutterhead clogging under cohesive strata. The Computational Fluid Dynamics (CFD) method is employed to quantitatively investigate the impact of scouring flux, cutterhead rotational speed, adding nozzles, and excavation methods on the flow field characteristics. Results show that increasing the existing scouring system flux even to 2000 m3/h couldn’t improve the slurry flowability at the cutterhead periphery. However, increasing the cutterhead rotational speed can significantly improve the slurry flowability at the cutterhead periphery and opening, resulting in a more uniform distribution of the flow field. Similarly, adding nozzles at the cutterhead periphery has positive effects. When the total scouring flux of 6 additional nozzles reached 800 m3/h, a favorable scour effect is achieved near the excavating face. Furthermore, adopting the air pressure assisted mode, the flowability of slurry at the cutterhead opening shows a significant enhancement compared to the full-chamber, and upper-half nozzles are transformed into non-submerged jets achieving a better scouring effect. Based on the analysis, it is recommended to add nozzles at the cutterhead periphery. If geological conditions permit, the “high-speed, low-penetration” or air pressure assisted excavation mode can be attempted.

Synthetic ester-based forced flow immersion cooling technique for fast discharging lithium-ion battery packs

Rapid advancements in Li-ion battery technology are being made to meet the growing demand for efficient energy storage solutions in electric vehicles and portable electronics. However, heat generation during rapid charging and discharging remains a significant challenge, as it can lead to overheating, fire, and explosion. To address this issue, battery thermal management systems require improvements in cooling strategies. This study aims to optimize the thermal performance of Li-ion battery packs during fast discharge operation by single-phase synthetic ester oil-based forced flow immersion cooling (FFIC) technique. The study analyzes the thermal performance of the FFIC of a 4S2P LIB pack based on various flow rates, pressure drops, and pump power consumption and compares it with various conventional cooling methods and dielectric fluids. The MSMD-based NTGK battery modeling approach is used to analyze the electrical and thermal characteristics of the battery pack at 3C discharge and environmental temperature of 25 °C. The simulation findings revealed that the synthetic ester oil has a superior cooling effect than mineral oil in the 4S2P Li-ion battery pack. The experimental results showed that the synthetic ester-based FFIC Li-ion battery pack achieves an optimal pack temperature of 31.3 °C and uniform temperature distribution at the flow rate of 5 L/min and pressure drop of 228.44 Pa. Moreover, FFIC reduces temperature rise by 51 % compared with natural air convection and 35 % compared with static flow immersion cooling (SFIC) in the 4S2P lithium-ion battery pack. Also, the practical significance of the SEO-based FFIC immersion cooling technique is assessed across extreme climate zones such as −10 °C and 40 °C and determined its superior performance in Li-ion batteries. Hence, this study proved that the FFIC technique is suitable for Li-ion batteries in electric vehicle applications in terms of optimal performance, reliability, and safety during high-current discharge operations.

Current and Future Perspectives of Bioactive Glasses as Injectable Material

This review covers recent compositions of bioactive glass, with a specific emphasis on both inorganic and organic materials commonly utilized as matrices for injectable materials. The major objective is to highlight the predominant bioactive glass formulations and their clinical applications in the biomedical field. Previous studies have highlighted the growing interest among researchers in bioactive glasses, acknowledging their potential to yield promising outcomes in this field. As a result of this increased interest, investigations into bioactive glass have prompted the creation of composite materials and, notably, the development of injectable composites as a minimally invasive method for administering the material within the human body. Injectable materials have emerged as a promising avenue to mitigate various challenges. They offer several advantages, including minimizing invasive surgical procedures, reducing patient discomfort, lowering the risk of postoperative infection and decreasing treatment expenses. Additionally, injectable materials facilitate uniform distribution, allowing for the filling of defects of any shape.

Across Interfacial Li+ Conduction Accelerated by a Single-Ion Conducting Polymer in Ceramic-Rich Composite Electrolytes for Solid-State Batteries.

Composite electrolytes have been accepted as the most promising species for solid-state batteries, exhibiting the synergistic advantages of solid polymer electrolytes (SPEs) and solid ceramic electrolytes (SCEs). Unfortunately, the interrupted Li+ conduction across the SPE and SCE interface hinders the ionic conductivity improvement of composite electrolytes. In our study on a ceramic-rich composite electrolyte (CRCE) membrane composed of borate polyanion-based lithiated poly(vinyl formal) (LiPVFM) and Li1.3Al0.3Ti1.7(PO4)3 (LATP) particles, it is found that the strong interaction between the polyanions in LiPVFM and LATP particles results in a uniform distribution of ceramic particles at a high proportion of 50 wt % and good robustness of the electrolyte membrane with a Young's modulus of 9.20 GPa. More importantly, ab initio molecular dynamics simulation and experimental results demonstrate that Li+ conduction across the SPE and SCE interface is induced by the polyanion-based polymer due to its high lithium-ion transference number and similar Li+ diffusion coefficient with the SCE. Therefore, the unblocked Li+ conduction among ceramic particles dominates in the CRCE membrane with a high ionic conductivity of 6.60 × 10-4 S cm-1 at 25 °C, a lithium-ion transference number of 0.84, and a wide electrochemical stable window of 5.0 V (vs Li/Li+). Consequently, the high nickel ternary cathode LiNi0.8Mn0.1Co0.1O2-based batteries with CRCE deliver a high-rate capability of 135.08 mAh g-1 at 1.0 C and a prolonged cycle life of 100 cycles at 0.2 C between 3.0 and 4.3 V. The polyanion-induced Li+ conduction across the interface sheds new light on solving composite electrolyte problems for solid-state batteries.