Bilal Tasdemir, Svitlana Krüger, Pinank Sohagiya
et al.
The growing demand for higher-energy lithium-ion batteries, encompassing consumer electronics, stationary grid storage, and electric mobility to specialized sectors like aerospace, medical devices, and industrial robotics, requires cathode materials that offer higher capacity while remaining cost-effective. This trend has intensified the development of nickel-rich LiNi<sub>1−x−y</sub>Mn<sub>x</sub>Co<sub>y</sub>O<sub>2</sub> (NMC) systems. However, high-Ni NMCs such as LiNi<sub>0.9</sub>Mn<sub>0.05</sub>Co<sub>0.05</sub>O<sub>2</sub> (NMC90) suffer from limited thermal and cycling stability. Core–shell architectures using LiNi<sub>0.6</sub>Mn<sub>0.2</sub>Co<sub>0.2</sub>O<sub>2</sub> (NMC622) as a shell can partially alleviate these drawbacks, but structural degradation caused by interdiffusion between the core and shell persists as a major challenge. This study investigates whether a tungsten oxide interlayer can act as a protective barrier that suppresses interdiffusion, stabilizes the crystal structure, and improves long-term electrochemical performance. In this work, NMC cathode powders were synthesized via a one-pot oxalate co-precipitation route, followed by structural characterization using X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and ion scattering spectroscopy (ISS). Electrochemical performance, including capacity retention, cycling stability, and internal resistance, was evaluated through galvanostatic charge–discharge (GCD) testing and electrochemical impedance spectroscopy (EIS). The core–shell configuration delivered higher specific discharge capacity compared to the individually synthesized core-only and shell-only reference materials, and the incorporation of a tungsten oxide interlayer resulted in a twofold increase in cycle life. These results demonstrate that tungsten oxide effectively enhances cycling stability by inhibiting core–shell interdiffusion, offering a promising pathway toward more durable high-Ni NMC cathodes.
Production of electric energy or power. Powerplants. Central stations, Industrial electrochemistry
We present a perspective on molecular machine learning (ML) in the field of chemical process engineering. Recently, molecular ML has demonstrated great potential in (i) providing highly accurate predictions for properties of pure components and their mixtures, and (ii) exploring the chemical space for new molecular structures. We review current state-of-the-art molecular ML models and discuss research directions that promise further advancements. This includes ML methods, such as graph neural networks and transformers, which can be further advanced through the incorporation of physicochemical knowledge in a hybrid or physics-informed fashion. Then, we consider leveraging molecular ML at the chemical process scale, which is highly desirable yet rather unexplored. We discuss how molecular ML can be integrated into process design and optimization formulations, promising to accelerate the identification of novel molecules and processes. To this end, it will be essential to create molecule and process design benchmarks and practically validate proposed candidates, possibly in collaboration with the chemical industry.
Estimating reaction rates and chemical stability is fundamental, yet efficient methods for large-scale simulations remain out of reach despite advances in modeling and exascale computing. Direct simulation is limited by short timescales; machine-learned potentials require large data sets and struggle with transition state regions essential for reaction rates. Reaction network exploration with sufficient accuracy is hampered by the computational cost of electronic structure calculations, and even simplifications like harmonic transition state theory rely on prohibitively expensive saddle point searches. Surrogate model-based acceleration has been promising but hampered by overhead and numerical instability. This dissertation presents a holistic solution, co-designing physical representations, statistical models, and systems architecture in the Optimal Transport Gaussian Process (OT-GP) framework. Using physics-aware optimal transport metrics, OT-GP creates compact, chemically relevant surrogates of the potential energy surface, underpinned by statistically robust sampling. Alongside EON software rewrites for long timescale simulations, we introduce reinforcement learning approaches for both minimum-mode following (when the final state is unknown) and nudged elastic band methods (when endpoints are specified). Collectively, these advances establish a representation-first, modular approach to chemical kinetics simulation. Large-scale benchmarks and Bayesian hierarchical validation demonstrate state-of-the-art performance and practical exploration of chemical kinetics, transforming a longstanding theoretical promise into a working engine for discovery.
杨世明1,刘克瑾2,姚辉江2,黄硕硕2,杜春来1,章敬波1 YANG Shiming1, LIU Kejin2, YAO Huijiang2, HUANG Shuoshuo2, DU Chunlai1, ZHANG Jingbo1
旨在为筒仓的设计和优化提供参考，基于自主设计的半圆柱形有机玻璃平底筒仓模型，进行了平均粒径分别为15、3.5 mm和5.5 mm陶球颗粒的室内筒仓中心卸料试验和离散元数值模拟。采用流态观察、速度分析、颗粒位移追踪3种方法探究了3组粒径颗粒的流态演变过程，分析了仓壁压力分布及变化规律，通过PFC 2D得到孔隙率、力链等细观变量分布并联合宏观层次的物理试验探讨了粒径大小对流态及仓壁压力的影响。结果表明：粒径对颗粒流态的整体演化过程无显著影响，不同粒径颗粒的流态均由整体流经漏斗流过渡为管状流；大粒径颗粒完成卸料过程耗时更久，卸料速率更慢；粒径对颗粒的流动轨迹无显著影响；边界区并不是一成不变的，在卸料过程中随着粒径的增大而逐渐上移；不同粒径颗粒组的峰值卸料压力最大值均位于距离仓底约1/3的位置；粒径越大，仓壁的压力波动越剧烈，峰值卸料压力也越大。综上，粒径对平底筒仓中心卸料的流态无显著影响，不同粒径的颗粒流态演化过程和颗粒流动轨迹具有相似性，粒径越大产生的仓壁卸料压力也越大。在实际工程中，需考虑粒径对筒仓结构安全性的影响。
To provide a reference for the design and optimization of silos, based on a self-designed semi-cylindrical plexiglass flat-bottom silo model, indoor silo center discharge tests and discrete element numerical simulations were conducted using ceramic ball particles with average particle size of 15, 3.5 mm and 5.5 mm. Three methods of flow pattern observation, velocity analysis, and particle displacement tracking were used to explore the flow pattern evolution of the three groups of particles with different particle sizes. The pressure distribution and variation of the silo wall were analyzed, and the distribution of microscopic variables such as porosity and force chain obtained from PFC 2D, along with macroscopic physical tests, were used to investigate the effect of particle size on flow pattern and silo wall pressure. The results showed that particle size had no significant effect on the overall evolution of particle flow pattern, and the flow pattern of particles with different particle size shifted from mass flow through funnel flow to tubular flow. Larger particle sizes of particles resulted in a longer discharge process with slower discharge rates. Particle size had no significant effect on the particle flow trajectories. The boundary zone was not fixed and gradually moved upwards with the increase of particle size during the discharge process. The peak of discharge pressure for different particle size groups was located approximately one-third of the way from the silo bottom. The larger the particle size, the more severe the pressure fluctuations on the silo wall, and the higher the peak of discharge pressure. In summary, particle size has no significant effect on the flow pattern of the silo center discharge. The flow pattern evolution and particle flow trajectories of particles with different particle sizes are similar. Larger particles generate higher discharge pressure on the silo wall. In practical engineering, the impact of particle size on silo structure safety should be considered.
Charlotte H. Müller, Miguel Steiner, Jan P. Unsleber
et al.
Automated and high-throughput quantum chemical investigations into chemical processes have become feasible in great detail and broad scope. This results in an increase in complexity of the tasks and in the amount of generated data. An efficient and intuitive way for an operator to interact with these data and to steer virtual experiments is required. Here, we introduce Heron, a graphical user interface that allows for advanced human-machine interactions with quantum chemical exploration campaigns into molecular structure and reactivity. Heron offers access to interactive and automated explorations of chemical reactions with standard electronic structure modules, haptic force feedback, microkinetic modeling, and refinement of data by automated correlated calculations including black-box complete active space calculations. It is tailored to the exploration and analysis of vast chemical reaction networks. We show how interoperable modules enable advanced workflows and pave the way for routine low-entrance-barrier access to advanced modeling techniques.
We present an innovative of artificial intelligence with column chromatography, aiming to resolve inefficiencies and standardize data collection in chemical separation and purification domain. By developing an automated platform for precise data acquisition and employing advanced machine learning algorithms, we constructed predictive models to forecast key separation parameters, thereby enhancing the efficiency and quality of chromatographic processes. The application of transfer learning allows the model to adapt across various column specifications, broadening its utility. A novel metric, separation probability ($S_p$), quantifies the likelihood of effective compound separation, validated through experimental verification. This study signifies a significant step forward int the application of AI in chemical research, offering a scalable solution to traditional chromatography challenges and providing a foundation for future technological advancements in chemical analysis and purification.
This is a brief review of liquid scintillators, an important technology for detection of ionizing radiation. We will first review the basic mechanisms of light production in most organic liquid scintillators. For most practical detector applications, the scintillators need to be optimized for choices of photosensors and compatibility with optical windows. A summary of important past experimental projects with liquid scintillators is provided. We will complete the review with a list of modern practices, particularly of metal doping, and development of water based hybrid materials that allow simultaneous detection of Cherenkov and scintillation light.
XI Qinqin, TIAN Xiaoju, ZHOU Ting, LIU Siyuan, LI Qiang, WANG Zixin
In order to investigate the composition and changing pattern of metabolites during the brewing process of goji wine, this study analyzed the changes of metabolites at three stages (pretreatment, primary fermentation and aging) during the brewing process using the widely targeted metabolomics based on ultra-high performance liquid chromatography-electrospray-triple quadrupole linear ion trap-tandem mass spectrometry (UPLC-ESI-QTRAP-MS/MS). The results showed that a total of 1 092 metabolites, including 195 flavonoids, 193 phenolic acids, 174 alkaloids, 121 lipids, 85 organic acids, 80 amino acids and their derivatives, 48 nucleotides and their derivatives, 45 lignans and coumarins, 35 terpenoids, 10 steroids, and 106 other substances were identified during the brewing process of goji wine. Volcano plots identified 260, 619 and 130 differential metabolites for the pretreatment, primary fermentation and aging stages, respectively. These differential metabolites were dominated by lipids, phenolic acids, flavonoids and alkaloids. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that the lysine degradation pathway, the valine, leucine and isoleucine biosynthesis pathways, the phytohormone signal transduction pathway, and the flavonoid biosynthesis pathway were significantly enriched during the brewing process of goji wine. This study provides data support for understanding the changes of metabolites during the brewing process of goji wine, and provides a theoretical basis for optimizing the brewing process of goji wine and developing goji-based functional products.
Tlehema Gwandu Umbayda, Anthony Daniel Funga, Alinanuswe Joel Mwakalesi
Innovative approaches for extending the shelf life of tomatoes are required due to increased postharvest losses of climacteric-fruits. The use of edible coatings is recently considered as a promising approach due to their non-toxicity and affordability properties. The coatings form physical barriers that alter the internal atmosphere of the fruit and slow down a ripening process. The influence of an edible coating comprising of chitosan and macadamia nut oil on the antioxidant and physical properties of tomato fruits is reported. The antioxidant and physical qualities of tomato fruits were investigated using different coating solutions. Various concentrations of macadamia nut oil, ranging from 1 % to 2.5 %, were used as independent coating solutions. Additionally, another set of coating solutions was prepared by mixing macadamia nut oil in the same concentration range (1 % to 2.5 %) with 1 % w/v chitosan. The tomatoes were dipped into the coating solutions and stored under a postharvest shed (23.8–30 °C, 65.8–97.5 % RH) for 20 days to monitor total phenolic content, total flavonoid content, ascorbic acid content, color, percentage weight loss, decay percentage, and shelf life after every 5-days interval. The results showed a significant difference (P < 0.05) between coated and uncoated tomato samples. The coated tomatoes showed the significant retention of total flavonoid content, total phenolic content, hue angle and red-green (a*) compared to uncoated tomatoes. On contrast, the decrease of decay, weight loss, the lightness (L), blue-yellow (b*), chroma, and ascorbic acid content was lower for coated compared to control tomatoes. The findings indicated that 1 % macadamia nut oil exhibited the highest retention of antioxidant and physical properties, and lowest decrease in ascorbic acid content from 0.014 mg/100 g on the 5th day to 0.0096 mg/100 g on the 20th day was observed. Thus, the findings from this study suggest that the macadamia nuts can serve as a cheap and low-cost source of edible oil suitable for prolonging the shelf life of tomatoes and related fruits.
Microcystins with leucine arginine (MC-LR) is a virulent hepatotoxin, which is commonly present in polluted water with its demethylated derivatives [Dha7] MC-LR. This study reported a low-cost molecularly imprinted polymer network-based electrochemical sensor for detecting MC-LR. The sensor was based on a three-dimensional conductive network composed of multi-walled carbon nanotubes (MWCNTs), graphene quantum dots (GQDs), and gold nanoparticles (AuNPs). The molecularly imprinted polymer was engineered by quantum chemical computation utilizing p-aminothiophenol (p-ATP) and methacrylic acid (MAA) as dual functional monomers and L-arginine as a segment template. The electrochemical reaction mechanism of MC-LR on the sensor was studied for the first time, which is an irreversible electrochemical oxidation reaction involving an electron and two protons, and is controlled by a mixed adsorption–diffusion mechanism. The sensor exhibited a great detection response to MC-LR in the linear range of 0.08–2 μg/L, and the limit of detection (LOD) is 0.0027 μg/L (S/N = 3). In addition, the recoveries of the total amount of MC-LR and [Dha7] MC-LR in the actual sample by the obtained sensor were in the range from 91.4 to 116.7%, which indicated its great potential for environmental detection.
HIGHLIGHTS
A molecularly imprinted electrochemical sensor was proposed for detecting MC-LR.;
The sensor was based on a 3D conductive network composed of MWCNTs, GQDs and AuNPs.;
The molecularly imprinted polymer was engineered by quantum chemical computation.;
The reaction mechanism of MC-LR on the sensor was studied.;
The total amount of MC-LR in actual samples was detected successfully.;
Anju Pokharel, Randhir Kumar Jaidka, N. U. Sruthi
et al.
White salted (udon) noodles are one of the major staple foods in Asian countries, particularly in Japan. Noodle manufacturers prefer the Australian noodle wheat (ANW) varieties to produce high-quality udon noodles. However, the production of this variety has reduced significantly in recent years, thus affecting the Japanese noodle market. Noodle manufacturers often add tapioca starch to compensate for the flour scarcity; however, the noodle-eating quality and texture are significantly reduced. This study, therefore, investigated the effect of the addition of porous tapioca starch on the cooking quality and texture of udon noodles. For this, tapioca starch was initially subjected to enzyme treatment, ultrasonication, and a combination of both to produce a porous starch where a combined enzyme (0.4% alpha amylase)–ultrasound treatment (20 kHz) yielded a porous starch with increased specific surface area and better absorbent properties which are ideal for udon noodle manufacturing, Later, udon noodles were prepared using three varieties of ANW, a hard Mace variety, and commercial wheat flour by incorporating the prepared porous tapioca starch at a concentration of 5% and 10% of dry ingredients. Adding this porous starch resulted in a lower cooking time with higher water absorption and desirable lower cooking loss compared to the control sample with 5% of the porous starch chosen as the optimum formulation. Increasing the level of the porous starch reduced the hardness of the noodles whilst maintaining the desired instrumental texture. Additionally, a multivariate analysis indicated a good correlation between responses’ optimum cooking time and water absorption capacity as well as turbidity and cooking loss, and a cluster analysis grouped noodle samples prepared from different varieties into the same clusters based on the porous starch added, indicating the possibility of different market strategies to improve the quality of the udon noodles produced from different wheat varieties.
Objective. We previously described that different concentration Nucleobindin-2 (NUCB2)/Nesfatin-1 gradients differently regulated visceral hypersensitivity in irritable bowel syndrome. Therefore, this study is aimed at evaluating the effect of NUCB2/Nesfatin-1 on model rats with chronic visceral hyperalgesia. Methods. Neonatal and mature Sprague-Dawley rats were randomly divided into the healthy control and chronic visceral hyperalgesia model groups. The model was built by combining maternal separation with the acetic acid enema. The models were identified by the distension volume threshold to reach abdominal withdraw reflex AWR score=3, histological staining, and myeloperoxidase (MPO) detection. The visceral sensitivity to chronic visceral hyperalgesia was then evaluated. Result. Rats in the model group responded more strongly to pulling stimulation than healthy controls; the distension volume threshold causing AWR3 response in model rats was lower than the control group before NUCB2/Nesfatin-1 intervention. After intervention, the distension volume threshold was significantly lower in the NUCB2/Nesfatin-1 central intervention group than in the NUCB2/Nesfatin-1 peripheral intervention group, and the peak value of external oblique muscle electrical activity was significantly higher. Additionally, compared with the male intervention group, in the female intervention group, the volume threshold was significantly lower and the peak value was higher. Conclusion. NUCB2/Nesfatin-1 could regulate visceral sensitivity in chronic visceral hyperalgesia model rats; its regulatory effect correlated with the type of NUCB2/Nesfatin-1 intervention approaches (central or peripheral) and sex (male or female).
A’am Rifaldi Khunaifi, Arif Supriyadi, Dedy Setyawan
Guru SMAN 1 Pandih Batu belum menggunakan Learning Management System (LMS) secara maksimal sehingga membutuhkan pelatihan dalam menggunakan aplikasi ini. Tujuan kegiatan ini adalah untuk meningkatkan pemahaman guru mengenai LSM khususnya menggunakan Sevima Edlink. Metode yang digunakan dalam pelatihan ini adalah demonstrasi, praktek, dan diskusi. Peserta pada kegiatan ini adalah 30 orang guru di SMAN 1 Pandih Batu. Target pelatihan ini yaitu guru mampu menggunakan Sevima Edlink, pembuatan topik materi, invite siswa, pengunggahan materi pelajaran, dan kuis daring. Hasil dari kegiatan ini menunjukan terjadi peningkatan kemampuan berdasarkan hasil pretest dengan nilai 62,3 meningkat pada hasil postest dengan nilai 80,5. Hasil skor N-Gain menunjukan terjadi peningkatan kemampuan guru sebesar 0,48 dengan kategori sedang. Peserta menilai bahwa pelatihan ini dapat memberikan manfaat berupa peningkatan pengetahuan dan keterampilan diri bagi peserta dengan metode ceramah maupun kegiatan demonstrasi dan peserta juga menilai bahwa pemateri baik ceramah maupun praktek sangat baik dalam penguasaan metode dan materi.
Food processing and manufacture, Academies and learned societies
Enkelejda Velo, Fabrizio Balestrino, Fabrizio Balestrino
et al.
The pathogen transmitting Aedes albopictus mosquito is spreading rapidly in Europe, putting millions of humans and animals at risk. This species is well-established in Albania since its first detection in 1979. The sterile insect technique (SIT) is increasingly gaining momentum worldwide as a component of area-wide-integrated pest management. However, estimating how the sterile males will perform in the field and the size of target populations is crucial for better decision-making, designing and elaborating appropriate SIT pilot trials, and subsequent large-scale release strategies. A mark-release-recapture (MRR) experiment was carried out in Albania within a highly urbanized area in the city of Tirana. The radio-sterilized adults of Ae. albopictus Albania strain males were transported by plane from Centro Agricoltura Ambiente (CAA) mass-production facility (Bologna, Italy), where they were reared. In Albania, sterile males were sugar-fed, marked with fluorescent powder, and released. The aim of this study was to estimate, under field conditions, their dispersal capacity, probability of daily survival and competitiveness, and the size of the target population. In addition, two adult mosquito collection methods were also evaluated: BG-Sentinel traps baited with BG-Lure and CO2, (BGS) versus human landing catch (HLC). The overall recapture rates did not differ significantly between the two methods (2.36% and 1.57% of the total male released were recaptured respectively by BGS and HLC), suggesting a similar trapping efficiency under these conditions. Sterile males traveled a mean distance of 93.85 ± 42.58 m and dispersed up to 258 m. Moreover, they were observed living in the field up to 15 days after release with an average life expectancy of 4.26 ± 0.80 days. Whether mosquitoes were marked with green, blue, yellow, or pink, released at 3.00 p.m. or 6.00 p.m., there was no significant difference in the recapture, dispersal, and survival rates in the field. The Fried competitiveness index was estimated at 0.28. This mark-release-recapture study provided important data for better decision-making and planning before moving to pilot SIT trials in Albania. Moreover, it also showed that both BG-traps and HLC were successful in monitoring adult mosquitoes and provided similar estimations of the main entomological parameters needed.
Nowadays, huge amounts of data are generated every second, and a quantity of that data can be defined as sensitive. Blockchain technology has private, secure, transparent and decentralized exchange of data as native. It is adaptable and can be used in a wide range of Internet-based interactive systems in academic and industrial settings. The essential part of programmable distributed ledgers such as Ethereum, Polkadot, Cardano and other Web 3.0 technologies are smart contracts. Smart contracts are programs executed on the global blockchain, the code is public as well as all of the data managed within the transactions, thus creating a system that is reliable and cannot be cheated if designed properly. In this paper, in order to make the educational system more transparent and versatile we will describe an educational learning platform designed as a distributed system.
Anne Metje van Genderen, Katja Jansen, Marleen Kristen
et al.
Introduction: To date, tubular tissue engineering relies on large, non-porous tubular scaffolds (Ø > 2 mm) for mechanical self-support, or smaller (Ø 150–500 μm) tubes within bulk hydrogels for studying renal transport phenomena. To advance the engineering of kidney tubules for future implantation, constructs should be both self-supportive and yet small-sized and highly porous. Here, we hypothesize that the fabrication of small-sized porous tubular scaffolds with a highly organized fibrous microstructure by means of melt-electrowriting (MEW) allows the development of self-supported kidney proximal tubules with enhanced properties.Materials and Methods: A custom-built melt-electrowriting (MEW) device was used to fabricate tubular fibrous scaffolds with small diameter sizes (Ø = 0.5, 1, 3 mm) and well-defined, porous microarchitectures (rhombus, square, and random). Human umbilical vein endothelial cells (HUVEC) and human conditionally immortalized proximal tubular epithelial cells (ciPTEC) were seeded into the tubular scaffolds and tested for monolayer formation, integrity, and organization, as well as for extracellular matrix (ECM) production and renal transport functionality.Results: Tubular fibrous scaffolds were successfully manufactured by fine control of MEW instrument parameters. A minimum inner diameter of 1 mm and pore sizes of 0.2 mm were achieved and used for subsequent cell experiments. While HUVEC were unable to bridge the pores, ciPTEC formed tight monolayers in all scaffold microarchitectures tested. Well-defined rhombus-shaped pores outperformed and facilitated unidirectional cell orientation, increased collagen type IV deposition, and expression of the renal transporters and differentiation markers organic cation transporter 2 (OCT2) and P-glycoprotein (P-gp).Discussion and Conclusion: Here, we present smaller diameter engineered kidney tubules with microgeometry-directed cell functionality. Due to the well-organized tubular fiber scaffold microstructure, the tubes are mechanically self-supported, and the self-produced ECM constitutes the only barrier between the inner and outer compartment, facilitating rapid and active solute transport.
Avocado (<i>Persea Americana</i> Mill.) generates byproducts, especially the avocado seeds. Hence, the aim of this study was to investigate the potential utilization of avocado seed as a very important, high phenolic content, climacteric fruit with unique characteristics and high nutritional properties. As such, theantioxidative test is conducted, then spray drying is used to produce avocado seed powder. The objective of this study was to develop an avocado seed powder using the spray drying technique by investigating the solution stability with different avocado seed extract concentrations, and to determine the physical properties of spray dried avocado powder that consists of powder yield, moisture, water activity, solubility, and color. The avocado seed extract was mixed with maltodextrin and water and homogenized for 10 min at 8000 rpm. The avocado seed solution was then spray dried with different inlet temperatures and feed flow rates. The spray dried avocado seed powder was analyzed for its yield, moisture content, water activity, solubility, and color. It was reported that the solution with the least avocado extract concentration (10 g) had the best stability in terms of presence of solute particles and color. The avocado seed powder obtained from this experiment had yield ranges from 24.46−35.47%, moisture content ranges from 7.18−7.96%, water activity ranges from 0.27−0.34, solubility ranges from 55.50−79.67 seconds, L* value ranges from 38.38−41.05, a* value ranges from 6.20−7.25, and b* value ranges from 13.33−15.17. In addition, increasing inlet temperature resulted in an increase in powder yield, solubility, a* value, and b*value, as well as a decrease in moisture, water activity, and L* value. Meanwhile, increasing the feed flow rate resulted in an increase in powder yield, moisture, water activity, and all L*, a*, b* values, as well as a decrease in solubility. In conclusion, spray drying technology is able to develop avocado seed powder.
In this study, a novel composite polymer electrolyte consist of 8-arm block liquid crystalline copolymer (8-PEG-MALC), 8-arm poly(ethylene glycol) (8-PEG), polyethylene (glycol) diacrylate (PEGDA) and bistrifluoromethanesulfonimide lithium salt (LiTFSI) was prepared successfully. The branching 8-PEG ensure high ionic conductivity of the all solid state polymer, crosslinking agent PEGDA endow good mechanical property, and 8-arm block liquid crystalline copolymer with a birefringent mesogens to tune the morphology of the composite polymer electrolytes. The polymer electrolytes can form a transparent and flexible film with nanoscale microphase separation structure, which creating well-defined ion conducting channels. The electrochemical properties of composite polymer electrolytes are analyzed and the highest ionic conductivity reaches 6.2 × 10-5 S cm-1 at room temperature after annealed from fixed temperature. It also displays high temperature stability up to 150°C, which is higher than traditional electrolytes. More intriguingly, the assembled LiFePO4/Li cells using the composite polymer electrolytes exhibit good charge/discharge cycles at 95°C. The good electrochemical properties, temperature stability and bendability of the composite polymer electrolytes indicate it potentially as a very promising material for all-solid-state flexible lithium ion batteries.
Industrial electrochemistry, Physical and theoretical chemistry