Cell Structure Research Articles

Effects of Saikosaponin D on Apoptosis, Autophagy, and Morphological Structure of Intestinal Cells of Cajal with Functional Dyspepsia.

Functional dyspepsia (FD) is one of the most common gastrointestinal diseases, with a global prevalence of 10%-30%. However, the specific pathogenesis of FD has not yet been determined. As such, the aim of this study was to investigate the effects of saikosaponin D (SSD) administration on the apoptosis, autophagy, and morphological structure of the intestinal cells of Cajal (ICCs) in FD. Methods：A rat model of FD was constructed by stimulating the rat tail with a sponge clamp at one-third of the distal tail length. An autophagy model was constructed for ICCs using glutamate. The apoptosis rate in each group of cells was determined using flow cytometry. The expressions of ghrelin and substance P (SP) were detected using ELISA. The body weight and food intake of male and female rats in the SSD group were consistently higher than those in the model group. The SSD group showed substantial improvement compared with the model group, with no inflammatory cell infiltration and normal gastric mucosal structures. After intervention with SSD, the ultrastructure of the ICCs considerably improved and was clear. Compared with the model group, the expressions of LC3 I/II, ghrelin, and SP proteins in the SSD group were significantly upregulated, and the apoptosis rate was significantly reduced. The administration of SSD improved ICC morphology and structure, inhibited excessive autophagy, and improved FD, a gastrointestinal motility disorder, by regulating ghrelin and SP levels.

Enhanced Thermal Conductivity in Thermoplastic Polyether Ester Elastomer Vitrimer Composite Foams via Cell Growth-Induced Orientation and Lap of Hybrid Fillers

Lightweight thermal conductive polymer foams own a great potential application in some weight sensitive fields such as aerospace and encapsulation. Herein, the enhancement of thermal conductivity of thermoplastic polyether ester elastomer (TPEE) vitrimer composites foams caused by cell growth inducing fillers orientation and lap was investigated with hybrid fillers of fixed 15 vol.% h-BN and various SiC nanowires. First, the hybrid fillers orientation in TPEE vitrimer composites (TVC) characterized by SEM and XRD patterns showed that the hybrid fillers were induced to be through-plane orientation and no interfacial defects were observed owing to the increasing contact area among fillers caused by large specific area and length of SiC nanowires. Based on that, cells were generated into TVC through scCO2 foaming. The effect of through-plane orientation and lap of hybrid fillers caused by cell growth of different cell structures on the thermal conductivity of TVC foams was investigated using extended Hashin-Shtrikman model and Maxwell-Eucken I model. The results showed that the thermal conductivity of TVC foams could greatly be enhanced to be higher than that of TVC by cell growth of continuous cell structures as it contributed to the through-plane orientation and lap of hybrid fillers to increase the contact and lap ratio among fillers. Thereby, the thermal conductive networks favorable to heat transfer were constructed in TVC foams to enhance the thermal conductivity as well as merit of lightweight.

Analysis of nickel oxide as a counter electrode for dye-sensitized solar cells using OghmaNano software

Dye-sensitized solar cells (DSSCs), a promising green technology, convert solar energy into electricity more cost-effectively than traditional solar cells. While platinum (Pt) is commonly used in DSSCs, its high cost and toxicity limit practical applications. Recent research aims to develop low-cost counter electrodes with high efficiency. Nickel oxide (NiO), a p-type semiconductor with a wide bandgap, good transmittance, and suitable work function, emerges as a potential alternative for counter electrode of DSSCs. In this work, DSSCs with NiO of thicknesses varying from 100 nm to 1000 nm were simulated to determine its influence on photovoltaic performance using OghmaNano software. The structure of simulated solar cells consists of NiO as counter electrode, zinc oxide (ZnO) as photoanode, N719 as dyes, electrolyte as charge carrier transport, and fluorine-doped tin oxide (FTO) as a contact layer. There are five data of NiO used as an active layer. From the simulation results, NiO-doped gold exhibits the highest power conversion efficiency (PCE) of 15.95% at a thickness of 700 nm, while pure NiO shows the lowest PCE with 4.53% at a thickness of 600 nm. These results have demonstrated that NiO can replace Pt as a counter electrode for DSSCs and doping plays a vital role in increasing efficiency.

Microstructure evolution of dendrite and eutectic in undercooled Al70Ge30 alloy

Al-Ge eutectic alloy, as a desirable bonding material, has been widely used in microelectromechanical systems (MEMS) packaging. The bonding property of Al-Ge eutectic alloy is closely related to their microstructures. However, the microstructure evolution and underlying mechanisms in undercooled eutectic Al-Ge alloy remain unclear. In this work, Al70Ge30 alloy was prepared and subjected to undercooling using a cycled superheating purification technology. The maximum undercooling can reach 90K (0.13TL). The solidified Al70Ge30 alloy exhibits concomitant dendrites and eutectic microstructures. The dendrites undergo rapid refinement at low undercooling and subsequently maintain nearly constant size as undercooling increases. Intriguingly, undercooling has a significant influence on eutectic microstructures. The eutectic microstructure transformed from feather structures to fishbone structures as undercooling increases then transformed into a line-like structure in eutectic cells. The evolution mechanisms of dendrites and eutectic structures are further elucidated based on several classical thermodynamic models. This study can provide theoretical and experimental guidance for the microstructure evolution of undercooled eutectic alloys with similar eutectic structures.

Mitochondria of T Lymphocytes Promote Anti-Pulmonary Tumor Immune Response.

B-cell lymphoma 2 (Bcl-2), a protein involved in apoptosis, has been proven to have carcinogenic potential and is well documented. With the recent advancement in optical technology, it has become possible to observe subcellular organelles such as mitochondria in real-time without the need for staining. Consequently, we have examined the movement of mitochondria in cancer cells, correlating it with the regulation of Bcl-2. Using a tomographic microscope, which can detect the internal structure of cells, we observed lung tumor cells. Cells were exposed to a laser beam (λ = 520 nm) inclined at 45°, and holographic images were recorded up to a depth of 30 µm of reconstruction. Intriguingly, lung tumor cells rapidly expelled mitochondria upon the attachment of Bcl-2 or B-cell lymphoma extra-large (Bcl-xL) inhibitors. On the other hand, we observed that tumor cells hijack mitochondria from T cells. The hijacked mitochondria were not immediately linked to tumor cell death, but they played a role in assisting granzyme B-induced tumor cell death. Due to lower levels of Bcl-2 and Bcl-xL on the mitochondria of T cells compared to lung tumor cells, immune cells depleted of Bcl-2 and Bcl-xL were co-cultured with the tumor cells. As a result, a more effective tumor cell death induced by granzyme B was observed. Additionally, further enhanced anticancer immune response was observed in vivo. Together, we show that modified mitochondria of T cells can provide potential novel strategies towards tumor cell death.

Physiology and transcriptome analysis of Artemisia argyi adaptation and accumulation to soil cadmium

The soil pollution caused by cadmium (Cd) poses a significant threat to the environment. Therefore, identifying plants that can effectively remediate Cd-contaminated soils is urgently needed. In this study, physiological, cytological, and transcriptome analyses were performed to comprehensively understand the changes in Artemisia argyi under Cd stress. Physiological and cytological analyses indicated that A. argyi maintained normal growth with intact cell structure under Cd stress levels up to 10 mg/kg. Cytological analysis showed that Cd precipitation in leaf cells occurred in the cytoplasm and intercellular spaces. As the levels of Cd stress increased, proline accumulation in leaves increased, whereas soluble protein and soluble sugar initially increased, followed by a subsequent decline. The translocation factor was above 1 under 0.6 mg/kg Cd stress but decreased when it exceeded this concentration. Transcriptome analyses revealed several crucial Cd-influenced pathways, including amino acid, terpenoid, flavonoid, and sugar metabolisms. This study not only proved that A. argyi could enrich Cd in soil but also revealed the response of A. argyi to Cd and its resistance mechanisms, which provided insight into the cleaner production of A. argyi and the remediation of Cd-contaminated soil.

Parametric optimization of bio-inspired engineered sandwich core

The present study aims to design an efficient honeycomb cell structure for enhanced energy absorption. Elytra and bamboo bio-inspired parts were compared using a multi-criteria decision-making methodology (COPRAS) and finite element analysis (through Abaqus/CAE) to select the optimal candidate geometry for the study. A circular elytra-inspired geometry featuring four reinforcing cylinders was selected, demonstrating an increase in Specific Energy Absorption (SEA) of over 68% compared to a baseline geometry of the same mass. Structure optimization, aided by a genetic algorithm (NSGA-II), significantly improved crashworthiness parameters, presenting optimized values for design variables, This resulted in an increase in SEA by up to 94% and a 34% improvement in Crushing Force Efficiency (CFE) compared to a baseline geometry. The robust correlation between the algorithm and Finite Element Method (FEM) results highlights its usefulness for initial design, reducing computational demands. The research selects a circular elytra-inspired geometry featuring four reinforcing cylinders and showcasing the potential of multi-objective optimization algorithm in conjunction with FEM analysis in creating high-performance, lightweight structures for passive safety in aeronautics.

CellSNAP: a fast, accurate algorithm for 3D cell segmentation in quantitative phase imaging.

Three-dimensional quantitative phase imaging (QPI) has rapidly emerged as a complementary tool to fluorescence imaging, as it provides an objective measure of cell morphology and dynamics, free of variability due to contrast agents. It has opened up new directions of investigation by providing systematic and correlative analysis of various cellular parameters without limitations of photobleaching and phototoxicity. While current QPI systems allow the rapid acquisition of tomographic images, the pipeline to analyze these raw three-dimensional (3D) tomograms is not well-developed. We focus on a critical, yet often underappreciated, step of the analysis pipeline that of 3D cell segmentation from the acquired tomograms. We report the CellSNAP (Cell Segmentation via Novel Algorithm for Phase Imaging) algorithm for the 3D segmentation of QPI images. The cell segmentation algorithm mimics the gemstone extraction process, initiating with a coarse 3D extrusion from a two-dimensional (2D) segmented mask to outline the cell structure. A 2D image is generated, and a segmentation algorithm identifies the boundary in the plane. Leveraging cell continuity in consecutive -stacks, a refined 3D segmentation, akin to fine chiseling in gemstone carving, completes the process. The CellSNAP algorithm outstrips the current gold standard in terms of speed, robustness, and implementation, achieving cell segmentation under 2s per cell on a single-core processor. The implementation of CellSNAP can easily be parallelized on a multi-core system for further speed improvements. For the cases where segmentation is possible with the existing standard method, our algorithm displays an average difference of 5% for dry mass and 8% for volume measurements. We also show that CellSNAP can handle challenging image datasets where cells are clumped and marred by interferogram drifts, which pose major difficulties for all QPI-focused AI-based segmentation tools. Our proposed method is less memory intensive and significantly faster than existing methods. The method can be easily implemented on a student laptop. Since the approach is rule-based, there is no need to collect a lot of imaging data and manually annotate them to perform machine learning based training of the model. We envision our work will lead to broader adoption of QPI imaging for high-throughput analysis, which has, in part, been stymied by a lack of suitable image segmentation tools.

Effects of Liquid Nitrogen Freezing, Immersion Freezing, and Air Freezing on Properties of Perca fluviatilis Fillets and Analysis of Potential Protein Markers Based on Label-Free Proteomics

The effects of liquid nitrogen freezing (LNF), immersion freezing (IF), and air freezing (AF) combined with thawing in running water at 20°C on the quality of Perca fluviatilis fillets were investigated using label-free proteomics technology. The ice crystal equivalent diameter (12.30±0.33 μm) and ice crystal area ratio (7.61±2.81%) of LNF were significantly lower than IF and AF (P < 0.05). The ice crystals of LNF were small and evenly distributed, and the mechanical damage to the cell structure is small. LNF samples were closer to fresh samples regarding texture. Proteomic analysis identified a total of 11 differentially abundant proteins (DAPs) associated with LNF, IF, and AF. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that these DAPs were primarily catalytic proteins, metabolic enzymes, and structural proteins involved in metabolic pathways such as pyruvate metabolism, glycolysis, and arginine and proline metabolism. Among them, tubulin beta chain (A0A8C3G6F1), carbonic anhydrase (A0A2P1JP97), immunoglobulin-like and fibronectin type III domain-containing protein 1 (A0A484DE91), and tubulin are predicted to serve as potential protein markers for freezing, thawing loss, hardness, and springiness of Perca fluviatilis fillets post-thawing. These findings provide a basis for further research into the quality change induced by protein degradation of frozen Perca fluviatilis.

An Eye into the Aorta: The Role of Extracellular Matrix Regulatory Genes ZNF469 and PRDM5, from Their Previous Association with Brittle Cornea Syndrome to Their Novel Association with Aortic and Arterial Aneurysmal Diseases

The extracellular matrix is a complex network of proteins and other molecules that are essential for the support, integrity, and structure of cells and tissues within the human body. The genes ZNF469 and PRDM5 each produce extracellular-matrix-related proteins that, when mutated, have been shown to result in the development of brittle cornea syndrome. This dysfunction results from aberrant protein function resulting in extracellular matrix disruption. Our group recently identified and published the first known associations between variants in these genes and aortic/arterial aneurysms and dissection diseases. This paper delineates the proposed effects of mutated ZNF469 and PRDM5 on various essential extracellular matrix components, including various collagens, TGF-B, clusterin, thrombospondin, and HAPLN-1, and reviews our recent reports associating single-nucleotide variants to these genes’ development of aneurysmal and dissection diseases.

A review of deep learning and Generative Adversarial Networks applications in medical image analysis

Nowadays, computer-aided decision support systems (CADs) for the analysis of images have been a perennial technique in the medical imaging field. In CADs, deep learning algorithms are widely used to perform tasks like classification, identification of patterns, detection, etc. Deep learning models learn feature representations from images rather than handcrafted features. Hence, deep learning models are quickly becoming the state-of-the-art method to achieve good performances in different computer-aided decision-support systems in medical applications. Similarly, deep learning-based generative models called Generative Adversarial Networks (GANs) have recently been developed as a novel method to produce realistic-looking synthetic data. GANs are used in different domains, including medical imaging generation. The common problems, like class imbalance and a small dataset, in healthcare are well addressed by GANs, and it is a leading area of research. Segmentation, reconstruction, detection, denoising, registration, etc. are the important applications of GANs. So in this work, the successes of deep learning methods in segmentation, classification, cell structure and fracture detection, computer-aided identification, and GANs in synthetic medical image generation, segmentation, reconstruction, detection, denoising, and registration in recent times are reviewed. Lately, the review article concludes by raising research directions for DL models and GANs in medical applications.

Insights into the potential dual-antibacterial mechanism of Kelisha capsule on Escherichia coli

Traditional Chinese medicine (TCM), AYURVEDA and Indian medicine are essential in disease prevention and treatment. Kelisha capsule (KLSC), a TCM formula listed in the Chinese Pharmacopoeia, has been clinically proven to possess potent antibacterial properties. However, the precise antimicrobial mechanism of KLSC remained unknown. This study aimed to elucidate the dual antibacterial mechanism of KLSC using network pharmacology, molecular docking, and experimental validation. By analyzing the growth curve of Escherichia coli (E. coli), it was observed that KLSC significantly inhibited its growth, showcasing a remarkable antibacterial effect. Furthermore, SEM and TEM analysis revealed that KLSC damaged the cell wall and membrane of E. coli, resulting in cytoplasmic leakage, bacterial death, and the exertion of antibacterial effects. The network pharmacology analysis revealed that KLSC exhibited an effect on E. coli ATP synthase, thereby influencing the energy metabolism process. The molecular docking outcomes provided evidence that the active compounds of KLSC could effectively bind to the ATP synthase subunit. Subsequently, experimental findings substantiated that KLSC effectively suppressed the activity of ATP synthase in E. coli and consequently decreased the ATP content. This study highlighted the dual antibacterial mechanism of KLSC, emphasizing its effects on cell structure and energy metabolism, suggesting its potential as a natural antibacterial agent for E. coli-related infections. These findings offered new insights into exploring the antibacterial mechanisms of TCM by focusing on the energy metabolism process.

Comprehensive Design and Analysis of Thin Film Sb2S3/CIGS Tandem Solar Cell: TCAD Simulation Approach

Abstract This research presents a design and analysis of a tandem solar cell, combining thin film wide bandgap Sb2S3 (1.72 eV) and narrow bandgap CIGS (1.15 eV) for the top and bottom sub-cells, respectively. The integration of all thin film layers enhances flexibility, rendering the tandem solar cell suitable for applications such as wearable electronics. To optimize the power conversion efficiency (PCE) of the tandem solar device, advanced technology computer-aided design (TCAD) simulation tools are employed to estimate loss mechanisms and fine-tune parameters for each layer. An experimentally validated optoelectronic model is introduced, calibrated and validated against fabricated reference solar cells for the individual top and bottom cells. The calibrated model is then utilized to propose optimization routines for the Sb2S3/CIGS tandem solar cell. The initial tandem cell exhibits a JSC of 15.72 mA/cm2 and a PCE of 15.36%. The efficiency drop in the tandem configuration is identified primarily in the top cell. A systematic optimization process for the top cell is initiated, exploring various configurations, including HTL-free and ETL-free setups. Moreover, an np homojunction structure for the top cell is proposed. Optimization routines are applied that involve determining optimal thickness and doping concentration of the n-layer, investigating the effect of p-layer doping concentration, and exploring the influence of the work function of the front contact. As a result, the tandem cell efficiency is significantly improved to 23.33% at the current matching point (CMP), with a JSC of 17.15 mA/cm2. The findings contribute to the advancement of thin-film tandem solar cell technology, showcasing its potential for efficient and flexible photovoltaic applications.&amp;#xD;

Difficulties of Preoperative Diagnosis of Cribriform Morular Thyroid Carcinoma

Background. Cribriform morular thyroid carcinoma has been recently renamed in the 2022 WHO classification as a thyroid tumor of uncertain histogenesis. The epidemiologic, pathological, and pathophysiological characteristics distinguish it from papillary thyroid carcinoma (PTC). Preoperative genetic testing plays a role in facilitating the differential diagnosis. Methods. This report presents a confirmed case of cribriform morular thyroid carcinoma. Initially, fine-needle aspiration cytology suggested a diagnosis of PTC. However, a genetic analysis did not reveal the typical mutations associated with follicular-cell-derived neoplasms. Results. A 31-year-old woman was found to have a thyroid nodule at the left lobe measuring 11.8 × 10.2 × 12.4 mm. Ultrasonography indicated a hypoechoic, solid nodule with regular margins. Cytology revealed a papillary structure of tall cells, leading to a PTC diagnosis. Nevertheless, the genetic analysis failed to detect mutations such as BRAF V600E, NRAS Q61R, NRAS Q61K, HRAS Q61R, or HRAS Q61K mutation or the fusion of CCDC6-RET, NCOA4-RET, PAX8-PPARG, ETV6-NTRK3, TPM3-NTRK1, IRF2BP2-NTRK1, or SQSTM1-NTRK1 in the aspirated follicular cells. The patient subsequently underwent total thyroidectomy with central lymph node dissection. Pathological examination revealed a cribriform pattern of spindle-shaped cells with morular areas. Immunohistochemical staining showed positive results for β-catenin and TTF-1, except in the morular regions, and negative results for PAX8, thyroglobulin, and BRAF (clone VE1). The diagnosis was confirmed to be cribriform morular thyroid carcinoma. Conclusion. Significant cytological similarity exists between PTC and cribriform morular thyroid carcinoma. Preoperative genetic analysis is important to differentiate these two diseases. Cribriform morular thyroid carcinoma can be differentiated from common follicular-cell-derived tumors by the absence of typical mutations; the presence of nuclear and cytoplasmic expressions of β-catenin; the presence of TTF-1, except in morular areas; and the absence of thyroglobulin.

Floral structure, histochemistry, and volatile compounds in Bulbophyllum species of the ‘Cirrhopetalum alliance’ (Orchidaceae)

Abstract Bulbophyllum is the most species-rich orchid genus. Recent molecular data groups certain of its species into a monophyletic ‘Cirrhopetalum alliance’. Within this alliance are a monophyletic section Cirrhopetaloides and a non-monophyletic section Cirrhopetalum. Floral morphology and scent are partially conserved phylogenetically compared to the molecular data. Here, floral morphology, histochemistry, anatomy, and floral volatile organic compounds (VOCs) of selected Bulbophyllum species are analysed to assess whether there are structural or chemical differences that support separation into the two sections, to update available VOC data from this genus, and to consider evolutionary adaptations in the ‘Cirrhopetalum alliance’. We found that ‘Cirrhopetalum alliance’ flowers differ from some sections of Bulbophyllum in the structure of cells lining the longitudinal groove on the labellum or lip and report, for the first time in Bulbophyllum, a type of atypical oleiferous trichome probably involved in VOC production. We show a clear difference in floral VOC profiles between B. bicolor (sect. Cirrhopetaloides) and four other Bulbophyllum species, three previously assigned to sect. Cirrhopetalum, but VOC profiles do not support separation into the two sections. The lack of congruence between already established molecular phylogeny, floral anatomy, and VOC data suggests that VOC differences are due to recently and independently evolved pollinator specificity. We therefore show that there is no clear separation of these sections based on floral anatomy, histochemistry, or VOC profiles.

Study on the Cross-Scale Effects of Microscopic Interactions and Mechanical Properties of Rigid Polyurethane Foam Driven by Negative-Temperature Environments

In order to investigate the cross-scale effects of the interaction between the hard and soft segments of stiff polyurethane foam on the material’s mesoscopic pore structure and macroscopic compression characteristics in various negative-temperature environments, this paper used molecular dynamics to calculate the interaction differences between hard and soft segments in different negative-temperature environments. The effects of various negative-temperature settings on the cell structure of stiff polyurethane foam were investigated using scanning electron microscopy and Image J software. Finally, macro experiments were used to determine the influence of a negative-temperature environment on the characteristics of stiff polyurethane foam (such as compressibility). The molecular simulation calculation results show that in a negative-temperature environment, decreasing temperature gradually increases the interaction between hard segment molecules and soft segment molecules, resulting in an increase in the molecules’ modulus and cohesive energy density. The scanning electron microscope results reveal that a negative-temperature environment gradually increases the pore diameter of stiff polyurethane foam. The compression experiment findings demonstrate that, for the same service duration, the compressive strength in the −20 °C environment is 27.53% higher than that in the 0 °C environment. The study’s findings reveal a microscopic mechanism for the following receiving alterations and toughness enhancement of rigid polyurethane foam throughout service in negative-temperature conditions.

Cell structure in steels induced by additive manufacturing

This review discusses the cell structure induced by additive manufacturing (AM) with a focus on stainless steel 316L and maraging steel 18Ni-300 produced by laser powder bed fusion. The microstructural characteristics of AM cell structure are described. The central role of AM cell structure in the process–microstructure–property–performance relationship of AM steels is demonstrated, in which the methodology of modifying AM cells and the strengthening mechanism by AM cells are critically reviewed. The limitations of the current research mainly lie in the reproducibility of microstructures and the solution to the strength-ductility trade-off of AM steels. Finally, suggestions for further studies are presented: to establish a fine-scale process–microstructure–property–performance relationship of AM steels and to print novel composite materials through microstructure design.

Synergetic Triple Absorber Based High‐Efficiency Solar Cell Design

AbstractComputational analysis of triple absorber‐based solar cell structure is undertaken. This solar cell device configuration allows better utilization of the incident solar spectrum. Three different absorbers with a band gap in the range 1–1.5 eV are sandwiched between high‐doped p+ and n+ regions in descending order of electron affinity to form an energy‐matched multiple absorber device. A comprehensive analysis of key device parameters influencing performance, including band gap, conduction band alignment, interfacial defects, and thickness, is presented. The optimized triple absorber device shows beyond Shockley–Queisser limit (SQ limit) performance under the constraint of passivated interfaces with defect density below 1013 cm−2. Wide spectrum coverage leads to high short circuit current and an efficiency of 40.3%, which is higher than the SQ limit for single band gap solar cell.

Stearate‐Modified Montmorillonite and Polylactic Acid Synergistically Enhanced the Microcellular of Thermoplastic Polyurethane Elastomer Foam and Improved Its Dimensional Stability

Thermoplastic polyurethane (TPU) elastomer is a commonly used material for foam preparation. However, its application is hindered by significant shrinkage behavior. To reduce the foam shrinkage, polylactic acid (PLA) and calcium stearate‐modified montmorillonite (MMT‐St) are incorporated into the polyurethane matrix. The TPU/PLA/MMT‐St composite foams are formed using an intermittent supercritical carbon‐dioxide‐foaming process. The addition of PLA inhibits the relaxation of TPU chain segments, while the introduction of calcium stearate (GaSt2) improves the dispersion of MMT within the matrix, increases the nucleation sites of cell growth, and improves cell structure. The cell diameter decreases from 10 to 4 μm, while the cell density increased from 4.1 × 1012 to 15.8 × 1012 cell cm−3. In addition, the cell distribution range narrows from 4–19 to 2–6 μm. Incorporating MMT‐St increases the crystallinity and thermal stability of TPU/PLA, mitigates chain relaxation at room temperature, and enhances foam dimensional stability. As a result, this leads to a decrease in shrinkage rate from 27.5% to 5%. As both matrices of the material are thermoplastic, this composite foam possesses recyclability with enhanced material utilization.

Internal temperature estimation for lithium-ion batteries through distributed equivalent circuit network model

Lithium-ion cells experience significant internal thermal gradients during operation, with a direct impact on their safety, performance, cost and lifetime. The estimation of the internal temperature of cells is therefore particularly important. In this work, a 3D distributed electro-thermal model for internal temperature estimation is developed for a cylindrical cell (LG M50T, NMC811). The model is parameterized and comprehensively validated against experimental data for 21700 cells, including direct core temperature measurements. Multiple types of electrical load are considered, including constant current discharge, pulse discharge, drive cycle and instant discharge/charge switching. The developed model is used to estimate core temperature based on surface temperature measurement. The predictions are shown to have good accuracy at relatively low computational cost. We show that the widely adopted two-node lumped thermal estimation model is increasingly inaccurate for more aggressive discharges, when thermal gradients become higher. Compared to the standard two-node model, the distributed equivalent circuit network model predicts the effects of detailed internal cell structure (electrode, current collector, metal can and tab) and distributed internal heat generation. The results are of immediate interest to cell manufacturers and battery pack designers, while the modelling and parameterization framework is a useful tool for energy storage systems design.