Application Fields Research Articles

Innovative magnetic flux leakage applications in non destructive testing of metallic ropes

The Magnetic Flux Leakage (MFL) principle applied to metallic ropes, also called Magneto-inductive (MI), is not a new non destructive testing (NDT) technique and has been applied from several tens of years in ropeway plants according standards as or CEI EN 12927. The recent evolution of international standards, regarding the discard criteria of metallic ropes in other sectors, as in ISO4309, start to introduce the MFL beside visual inspection in lifting applications. Even if the component under control is always one or more ropes, the discard criteria, the rope conformation and the fault typologies can be influenced by the application sector. Different magnetic detectors have been developed by the Authors in order to satisfy the several technical constraints and practical requirements of the different field of applications. Several new application in industrial and civil sector as hoisting and elevators are starting to use this kind of non destructive methodology and new sensor with peculiar characteristics have been developed and implemented. In this paper recent development on magnetic flux leakage applied on metallic ropes is then presented. Different theoretical and practical experiences in the magnetic design, material characterization of metallic ropes and in the signal filtering system is presented and discussed.

Effect of extrusion temperature on microstructure and mechanical properties of ZTM631 magnesium alloy

Magnesium alloys are widely used in the fields of aviation, electronics, and automotive manufacturing due to their advantages of lightweight and high specific strength. Studying high-performance and low-cost deformed magnesium alloys to adapt to more application scenarios has important value. In the present work, the effect of extrusion temperature on the microstructure and mechanical properties of Mg-6Zn-3Sn-0.9Mn (ZTM631) alloy was investigated. Besides, the ultra-high cycle fatigue (VHCF) performance and fatigue failure mechanism of ZTM631 alloy was explored. Results show that extrusion temperature significantly affect the microstructure of ZTM631 alloys. Firstly, alloys extruded at 300℃ possess a relatively fine grain size, because the lower extrusion temperature prevent the grain growth. Secondly, phases precipitate at 300°C and 350°C with a large size (more than 1µm) are mainly α-Mn phase. while for the alloys extruded at 400°C, both α-Mn and Mg2Sn phases with the size larger than 1µm can be found in the matrix. Thirdly, alloys extruded at 400℃ exhibit the best mechanical properties, due to the combination of the grain refinement and precipitation strengthening. Fourthly, during the VHCF failure process, the crack preferentially generates at the densely distributed α-Mn phases for the alloy extruded at 300°C and 350°C, while the crack initiate near the Mg2Sn particles for the alloy extruded at 400°C. Also, undynamic recrystallized (un-DRXed) grains with severe deformation exist in the alloys extruded at 300℃ and 350℃, thus accelerating the crack initiation. This fundamental investigation provides theoretical information for developing high-performance Mg-Zn-Sn alloys with high strength and expanded their application fields.

Measurement and Applications: Artificial Intelligence in the Field of Measurement Applications

Measurement and Applications: Artificial Intelligence in the Field of Measurement Applications

Advancements in printed components for proton exchange membrane fuel cells: A comprehensive review

Proton Exchange Membranes (PEM) are a promising technology for fuel cells and electrolyzer cells, in line with societal goals for clean and sustainable fuel conversion and generation, respectively, in a vast field of applications. PEM fuel cell (PEMFC) technology has an important advantage for energy conversion applications, because it requires a lower operating temperature and is lighter and more compact than other technologies, which makes it ideal for portable and transportation applications. However, open issues remain to be addressed for PEMFC that hinder their widespread adoption, both on the technical side, such as too high operational temperature range, cell efficiency, and long-term stability, as well as on the industrial side with implementation issues, material and device component availability, and cost. PEM technology research usually focuses on the synthesis of novel materials such as non-noble metal catalysts and non-halogenated membranes. In parallel, developing high-throughput and cost-effective manufacturing methods for components, in particular Membrane Electrode Assembly (MEA), can also lift an important barrier to their mass production, thus contributing to the same goals and securing industrial provision. From this perspective, printing technologies such as spray coating, inkjet printing, and screen printing have emerged as promising approaches with the required precision and scalability. This review covers recent advancements and developments in advanced PEMFC technology manufacturing, with a focus on 2D printing methodologies to fabricate some or all of the MEA components. Leveraging these techniques as simplified large-area manufacturing methods for PEM technology can become a more viable and industrially attractive solution. This work presents a comparison study addressing the key progress indicators both in process and in characterization to build a working framework in which both scientists, engineers and manufacturers can collaborate toward the industrial implementation of this emergent field.

A versatile surface micro structure design strategy for porous-based pressure sensors to enhance electromechanical performance

Pressure sensors based on porous structures offer comfortable user experiences and can adapt to the flexible movement of human limbs, which makes them attractive options for human–computer interaction and health monitoring. However, ascribed to the limitation of porous surfaces, foam-based pressure sensors are difficult to achieve accurate electric responses and stable signal output, limiting their great potential in wide application fields. Herein, a surface structure design strategy is proposed for improving the performance of porous foam-based pressure sensors. The coupling of microstructures and the collaboration of dual sensing mechanisms endow the sensor with high performance, achieving a ∼ 12 times signal fluctuation stability when compared to the sensor without any surface design. Even when working under complex vibration conditions, the developed sensor can also maintain a ∼ 7 times more stable output. An intelligent insole based on the algorithm model of a sensor array and multi-layer perceptron was developed for the diagnosis of human foot arch health. The sensors with surface structure could capture and differentiate signals more accurately, which results in a diagnostic accuracy of 99.75 % for the smart insole. The strategy for enhancement of sensor performance proposed in this work can be applied to foam sensors with multiple material systems, which is expected to broaden the potential application of porous flexible devices in fields like the Internet of Things, medical monitoring and brain-computer interface.

Constructing Two-Dimensional Heterostructure Channels with Engineered Biomembrane and Graphene for Precise Scandium Sieving.

The special properties of rare earth elements have effectively broadened their application fields. How to accurately recognize and efficiently separate target rare earth ions with similar radii and chemical properties remains a formidable challenge. Here, we constructed precise two-dimensional (2D) heterogeneous channels using engineered E. coli membranes between graphene oxidse (GO) layers. The difference in binding ability and corresponding conformational change between Lanmodulin (LanM) and rare earth ions in the heterogeneous channel allow for precisely recognizing and sieving of scandium ions (Sc3+). The engineered E. coli membranes not only can protect the integrity of structure and functionality of LanM, the rich lipids and sugars but also help the E. coli membranes closely tile on the GO nanosheets through interaction, preventing swelling and controlling interlayer spacing accurately down to the sub-nanometer. Apparently, the 2D heterogeneous channels showcase excellent selectivity for trivalent ions (SFFe 3+ /Sc 3+≈3), especially for Sc3+ ions in rare earth elements with a high selectivity (SFCe/Sc≈167, SFLa/Sc≈103). The long-term stability and tensile strain tests verify the membrane's outstanding stability. Thus, this simple, efficient, and cost-effective work provides a suggestion for constructing two-dimensional interlayer heterogeneous channels for precise sieving, and the valuable strategy is proposed for the efficient extraction of Sc. This article is protected by copyright. All rights reserved.

Visualizing biodiversity on maps

Abstract Maps play a central role in the transfer of knowledge for biodiversity conservation. However, their production and reception contexts have not been sufficiently investigated so far. While critical cartography has demonstrated that maps are not objective representations of nature but are influenced by social conventions, these insights have not been fully reflected in ecological mapping practice. This paper draws on critical map theory and expands it with a critical evaluation of map visualization. By analyzing the design of biodiversity maps, our study demonstrates that the way biodiversity is visualized in maps does not adequately reflect the dynamics and interdependencies of natural systems, nor does it adequately reflect the species-specific needs. It is argued that design-led research provides relevant knowledge about evaluating maps in terms of their functionality as communication tools. This is of central importance if we wish to further develop ecological cartography and make it practicable and effective in its field of application.

Unveiling the Influence of Copy Number Variations on Genetic Diversity and Adaptive Evolution in China’s Native Pig Breeds via Whole-Genome Resequencing

Copy number variations (CNVs) critically influence individual genetic diversity and phenotypic traits. In this study, we employed whole-genome resequencing technology to conduct an in-depth analysis of 50 pigs from five local swine populations [Rongchang pig (RC), Wuzhishan pig (WZS), Tibetan pig (T), Yorkshire (YL) and Landrace (LR)], aiming to assess their genetic potential and explore their prospects in the field of animal model applications. We identified a total of 96,466 CNVs, which were subsequently integrated into 7112 non-redundant CNVRs, encompassing 1.3% of the swine genome. Functional enrichment analysis of the genes within these CNVRs revealed significant associations with sensory perception, energy metabolism, and neural-related pathways. Further selective scan analyses of the local pig breeds RC, T, WZS, along with YL and LR, uncovered that for the RC variety, the genes PLA2G10 and ABCA8 were found to be closely related to fat metabolism and cardiovascular health. In the T breed, the genes NCF2 and CSGALNACT1 were associated with immune response and connective tissue characteristics. As for the WZS breed, the genes PLIN4 and CPB2 were primarily linked to fat storage and anti-inflammatory responses. In summary, this research underscores the pivotal role of CNVs in fostering the diversity and adaptive evolution of pig breeds while also offering valuable insights for further exploration of the advantageous genetic traits inherent to China’s local pig breeds. This facilitates the creation of experimental animal models tailored to the specific characteristics of these breeds, contributing to the advancement of livestock and biomedical research.

Cell membrane-coated nanoparticles in disease therapy

Nanotechnology has attracted increasing attention in the field of medical applications due to its significant potential for development. However, one major challenge that has emerged with nanoparticles is their tendency to activate the host immune clearance system, which hampers the achievement of desired therapeutic outcomes and may lead to harmful side effects. In recent years, membrane-coated nanoparticles have emerged as a promising solution, demonstrating their effectiveness in evading immune system clearance. These innovative nanoparticles inherit essential biological attributes from natural cell membranes, such as anchoring proteins and antigens. Consequently, membrane-coated nanoparticles exhibit unique capabilities such as immune evasion, prolonged circulation, targeted drug release, and immune modulation, substantially enhancing their versatility and prospects within the realm of biomedical applications. This review provides a comprehensive overview of the current applications of cell membrane-coated nanoparticles in disease therapy, highlighting their immense potential in this rapidly evolving platform. Additionally, the review outlines the promising prospects of this technology in disease therapy.

Wear protection assessment of ultralow viscosity lubricants in high-power-density engines: A novel wear prediction algorithm

AbstractDurability and reliability have been studied for decades through intensive trial-error experimentation. However, there are numerous fields of application where the costs associated with this approach are not acceptable. In lubricated machines with severe dynamic loads, such as high-power-density engines, simulation tools offer clear advantages over intensive testing. Prototypes and multiple scenarios can be cost-effectively simulated to assess different lubricants and engine configurations. The work presented here details the study of wear based on a validated elastohydrodynamic (EHD) simulation model of the connecting rod journal bearing. This model accounts for elastic deformation through a connecting rod finite element model (FEM). In addition, multiple lubricant rheological and tribological dependences, determined by specific experimental tests, are applied in the model through their interaction with the simulation software. Correspondingly, a novel wear algorithm is proposed to predict wear depth over time evolution along a proposed wear cycle based on the typical working ranges of high-performance engines. A final assessment is presented to compare 4 different ultralow-viscosity lubricants in their protective performance under severe conditions. The results show the evolution of the wear load and wear depth over the wear cycle. This evaluation is key to describing a lubricant selection procedure for high-power-density engines.

Recognition of Brugada type 1 pattern on ECG by Echo State Networks

Abstract Background/Introduction The development of artificial intelligence (AI) and machine learning (ML) techniques, which can identify data patterns in electrocardiography, has led to the development of automated analysis tools for standard 12-lead ECGs. These tools are able to identify specific features associated with different cardiac diseases, which may be helpful in clinical practice [1]. One field of application is represented by Brugada Syndrome (BrS) diagnosis, which, despite characteristic ECG features, can be challenging to diagnose and correctly distinguish from other diseases. Purpose Within the Brugada Syndrome and Artificial Intelligence Applications to Diagnosis system study, we are developing an innovative model for diagnosing Type 1 BrS based on electrocardiographic pattern recognition through the Echo State Networks (ESN), a Recurrent Neural Network (RNN) type of architecture. Methods From patients enrolled in 5 Centers, 306 12-lead ECGs were obtained. The datasets were composed of spontaneous Type 1 pattern (coved) (group A, 98 patients); patients undergoing ajmaline test, classified as positive (group B, 47 patients) or negative (group C, 35 patients) according to test results; 220 controls with no clinical and familial history of arrhythmias (group D). ESN analyzed, as input, data collected from 1 beat of the ECG V2 lead. The datasets were used for the ESN model training and were assessed through a double cross-validation approach. The ESN performance was compared with the evaluation of 4 independent cardiologists, and sensitivity, specificity and accuracy were determined. Results The ESN model correctly classified 280/306 ECGs (91.5%), with a performance of 3.6 points superior to clinicians (269/306, 88.0%). ESN sensitivity (87.0% vs. 86.9%) and specificity (94.5% vs. 89.1%) are described in Table 1; accuracy in each group of the dataset (groups A, B, C, and D), represented in Table 2, were comparable to or greater than those of clinicians. Conclusion(s) In this work, an ESN-based system for diagnosing Type 1 BrS pattern on ECG was developed. Our results show that this ML model can detect ECG patterns associated with Type 1 BrS with accuracy, sensitivity and specificity comparable or superior to clinicians. In the future, we will use a larger dataset to increase the model performance further, with the real possibility of becoming a tool for everyday clinical practice.ESN and clinicians' diagnostic accuracyECG accuracy in each dataset group

Aragonite and its composites: preparations, properties and applications.

Aragonite, a metastable crystal form of calcium carbonate, exhibits the highest density and hardness among all species. Diversified forms of aragonite composites can be produced through different preparation processes, forming a relatively complete system in various application fields. Their properties and applications are determined by their multiple levels of structures and shapes. However, research information for aragonite‐related fields is currently lacking integration and clarification. This review provides a comprehensive overview on the preparation methods, properties, and potential applications of three main aragonite‐based materials: aragonite particles, nacre‐inspired mineralized aragonite composites (NMACs), and shell‐derived aragonite nanoparticles (SANPs). The formation mechanisms and versatile applications of these materials are thoroughly surveyed based on their initial precursor, reaction conditions, product forms including filler of aragonite whiskers synthesized by carbonation reaction; functional materials of NMACs fabricated by amorphous calcium carbonate‐organic matter (ACC‐OM) mediated process; biomedical materials of SANPs derived from aragonite cockle shells. Overall, this review aims to provide assistance for customized production of aragonite‐based materials as well as new research directions for both pure aragonites and its composites.

First experience of focal pulsed field ablation for premature ventricular contractions

Abstract Introduction Pulsed field ablation (PFA) has emerged as a novel strategy to achieve ablation of cardiac tissue. Clinical evidence suggests a remarkable lesion durability and safety profile for AF ablation. Nonetheless, a growing interest exists in broadening its field of application for catheter ablation of ventricular arrhythmias (VA). The CENTAURI system arises as a promising PFA system for targeting VA as it allows pulsed electric field (PEF) delivery via standard, commercially available focal ablation catheters and concomitant coupling with their mapping systems. Purpose To assess, for the first time, the feasibility of focal PFA via the CENTAURI system for premature ventricular complex (PVC) ablation. Methods We conducted a prospective analysis of patients with either high burden (>10%) or symptomatic idiopathic PVC undergoing focal PFA using CENTAURI system at our institution. Procedures were performed between December 2022 and August 2023. Acute and long-term success were defined as no PVC recurrence during a 24h in-hospital monitoring period, and ≥80% burden reduction with absence of symptoms after at least 30 days post-ablation, respectively. PVC monitoring was performed by implantable loop recorder (ILR) or surface ECG Holter monitoring. Results Fourteen patients (age range: 16-87 years; 10 females) were included. Procedures were performed via the CENTAURI system in combination with CARTO 3 system and EnSite X EP system in 4 (28.6%) and 10 cases (71.4%) respectively. Targeted ablation sites were the right ventricular outflow tract (6 cases), right moderator band (2 cases), left postero-medial papillary muscle -PM- (2 cases), and right posterior PM, tricuspid annulus, left posterior fascicle and aortomitral continuity (AMC) in one case. On average, 6.5 applications were delivered to the site of origin with a mean contact force of 11g. Procedural duration and fluoroscopy time were 102 and 8.9 minutes. Two minor complications were observed: one transitory ST depression (solved after i.v. nitrate administration) after repeated applications to AMC, and a femoral pseudoaneurysm. The remaining 12 procedures were uneventful. Although most of the procedures were performed under general anesthesia due to concerns about potential significant muscular contraction, 3 cases (21.4%) were successfully managed with light sedation, without significant muscular contraction nor map shift. Incomplete abolishment of PVC during first 24 h was observed in 2 patients (14.3%). After a median follow-up of 113 days (IQR: 83-188), recurrences were detected in one patient (7.14%). Conclusion Herein we report the feasibility and efficacy of PVC ablation using a focal PEF delivery system (CENTAURI). Furthermore, we describe the possibility of performing PVC ablation with this technology under light sedation, which might be important for minimizing anesthesia impact on PVC burden.Table of characteristicsPVC morphologies

Multimedia Human-Computer Interaction Method in Video Animation Based on Artificial Intelligence Technology

With the development of computer technology innovation, be able to deal with the media comprehensive information and real-time information interaction with the computer multimedia technology arises at the historic moment, it promotes the application fields of computer widen to industrial all aspects of life. As the product of digital technology, animation technology plays an irreplaceable role in the production of multimedia courseware. However, the existing human-computer interaction methods have shortcomings such as incomplete extraction of video features and poor human-computer interaction effect. In this context, this paper designs a multimedia human-computer interaction method for animation works based on CNN model. First of all, the original video data is collected and preprocessed. Then it is input into the HCI framework based on CNN model for feature extraction. Finally, the effectiveness and practicability of the proposed method are proved by simulation experiments, which provides a reference and basis for the research of modern human-computer interaction.

Biosurfactant production by Bacillus amyloliquefaciens, characterization and its potential applications

Aim: To identify indigenous bacteria responsible for producing biosurfactants in soil contaminated by oil and to investigate their potential uses in the fields of pharmaceuticals and environmental applications. Methodology: The microorganisms of oil-contaminated soil were isolated, screened, and identified using 16S rRNA gene sequencing. Bacillus amyloliquefaciens was utilized to produce biosurfactants, and were characterized by UV, TLC, FTIR, HPTLC, and GCMS analysis. Antibacterial activity, plant growth promotion, biocompatibility, and wound healing activity of surfactant were performed. Results: Six bacterial cultures (B1 to B6) were isolated from the soil samples collected from various locations in Kerala and Tamil Nadu. Among the isolates screened for biosurfactant production, Bacillus amyloliquefaciens exhibited the highest capacity for biosurfactant production, confirmed through 16S rRNA gene sequencing. The biosurfactant produced was identified as surfactin of lipopeptide nature, characterized by various analytical techniques: UV absorption at 400 nm, TLC and HPTLC (Rf value of 0.58), FTIR (prominent peak at 3819 cm-1 corresponding to -OH groups), GCMS with a maximum retention time of 12.03. Surfactin effectively inhibited pathogenic bacteria, enhanced plant growth, was biocompatible, and enhanced the rate of cell migration towards wound scratch. Interpretation: The current study revealed that Bacillus amyloliquefaciens, isolated from oil-contaminated soil, is capable of producing biosurfactant surfactin. Additionally, it unveiled a broad spectrum of applications for surfactin, encompassing wound healing, biocompatibility, antimicrobial activity, and promotion of plant growth. Key words: Antibacterial activity, Biocompatibility, Bacillus amyloliquefaciens, Biosurfactant, Wound healing

Exploring the potential applications of lead-free organic–inorganic perovskite type [NH3(CH2)nNH3]MCl4 (n = 2, 3, 4, 5, and 6; M = Mn, Co, Cu, Zn, and Cd) crystals

The organic–inorganic hybrid perovskite compounds have been extensively studied since the dawn of a new era in the field of photovoltaic applications. Up to now, perovskites have proven to be the most promising in terms of power conversion efficiency; however, their main disadvantages for use in solar cells are toxicity and chemical instability. Therefore, it is essential to develop a hybrid perovskite that can be replaced with lead-free materials. This review focuses on the possibility of applying lead-free organic–inorganic perovskite types [NH3(CH2)nNH3]MCl4 (n = 2, 3, 4, 5, and 6; M = Mn, Co, Cu, Zn, and Cd) crystals. We are seeking organic–inorganic hybrid perovskite materials with very high temperature stability or without phase transition temperature, and thermal stability. Thus, by considering the characteristics according to the methylene lengths and the various transition metals, we aim to identify improved materials meeting the criteria mentioned above. Consequently, the physicochemical properties of organic–inorganic hybrid perovskite [NH3(CH2)nNH3]MCl4 regarding the effects of various transition metal ions of the anion and the methylene lengths of the cation are expected to promote the development and application of lead-free hybrid perovskite solar cells.

Methodological issues of the fuzzy set theory (generalizing article)

The theory of fuzziness is an important area of modern theoretical and applied mathematics. The methodology of the theory of fuzziness is a doctrine of organizing activities in the field of development and application of the scientific results of this theory. We discuss some methodological issues of the theory of fuzziness, i.e., individual components of the methodology in the area under consideration. The theory of fuzziness is a science of pragmatic (fuzzy) numbers and sets. The ancient Greek philosopher Eubulides showed that the concepts «Heap» and «Bald» cannot be described using natural numbers. E. Borel proposed to define a fuzzy set using a membership function. A fundamentally important step was taken by L. A. Zadeh in 1965. He gave the basic definitions of the algebra of fuzzy sets and introduced the operations of intersection, product, union, sum, negation of fuzzy sets. The main thing he did was demonstration of the possibilities of expanding («doubling») mathematics: by replacing the numbers and sets used in mathematics with their fuzzy counterparts, we obtain new mathematical formulations. In the statistics of non-numerical data, methods of statistical analysis of fuzzy sets have been developed. Interval and triangular fuzzy numbers are often used specific types of membership functions. The theory of fuzzy sets in a certain sense is reduced to the theory of random sets. We think fuzzy and that is the only reason we understand each other. The paradox of the fuzzy theory is that it is impossible to consistently implement the thesis «Everything in the world is fuzzy». For ordinary fuzzy sets, the argument and values of the membership function are crisp. If they are replaced by fuzzy analogues, then their description will require their own clear arguments and membership functions, and so on ad infinitum. System fuzzy interval mathematics proceeds from the need to take into account the fuzziness of the initial data and the prerequisites of the mathematical model. One of the options for its practical implementation is an automated system-cognitive analysis and the intellectual system «Eidos».

Comprehensive Study on the Properties of AZ91/x-Si3N4 Composites for Their Prospective Application

Metal alloy matrix composites are generally lightweight structural materials with a high strength-to-weight ratio. They can be extensively used in various fields of modern engineering applications, such as aerospace and automotive components and biomedical engineering. This study focuses on the development and characterization of lightweight metal alloy matrix composites for industrial applications, with a particular emphasis on magnesium (Mg) alloys as a replacement for aluminum-based alloys. Mg alloys offer significant weight advantages, being 33% lighter than aluminum and 75% lighter than steel, making them highly desirable for use in various engineering fields. In the present study, Mg (AZ91) alloy reinforced with x-Si3N4 composites (x = 0, 1, 3, 5, 7, 9 wt.%) were fabricated using a liquid state process. The AZ91/x-Si3N4 composites were evaluated through physical, mechanical, wear, and microstructural characterization. The experimental results, supported by statistical analysis, demonstrated that the incorporation of Si3N4 particles amplified the mechanical properties, wear resistance, and porosity of the composites. However, the presence of the reinforced particles resulted in reduced forgeability and elongation, limiting certain deformation characteristics. The existence of the reinforced particles within the composites was confirmed through SEM analysis, providing visual evidence of their distribution and interaction within the Mg alloy matrix. Finally, it was concluded that the implication of the study could be sought for the light structural parts of aerospace, automotive, biomedical, and prosthetic applications.

First-principles study of high-entropy sulfides and their alkali metal-doped modification as cathode material for sodium-ion batteries.

High-entropy materials (HEMs) have been explored as high-capacity cathode materials for sodium-ion batteries (SIBs) due to their excellent structural stability and abundant metal redox sites. Among them, high-entropy sulfides (HESs) have greater potential and more extensive research than high-entropy oxides, as they exhibit higher charging voltage and theoretical capacity as cathodes. Furthermore, alkali metal doping of HESs can further enhance their performance and broaden their application fields. Inspired by the cocktail effect of HEMs, we performed the first theoretical calculation of the properties of Na(MnFeCoNi)1/2S and its Li-doped derivative, Na7/8Li1/8(MnFeCoNi)1/2S, to understand their potential as SIB cathode materials. Using density functional theory based on first principles, we investigated the structure and electronic characteristics of Na(MnFeCoNi)1/2S and Na7/8Li1/8(MnFeCoNi)1/2S, and calculated their theoretical voltage and capacity, respectively. Compared with Na(MnFeCoNi)1/2S, Na7/8Li1/8(MnFeCoNi)1/2S showed better electronic performance in reducing the band gap and increasing the density of states, ultimately providing a specific capacity of 160.3 mAh·g-1 and a charging voltage of 4.85 V in sodium-ion storage. Moreover, Na7/8Li1/8(MnFeCoNi)1/2S exhibited remarkable structural stability throughout the sodium-ion deintercalation process, thus it can be reasonably concluded that Na7/8Li1/8(MnFeCoNi)1/2S can serve as an excellent cathode material for future SIB applications.

On the behavior of auxetic inserts: a numerical analysis to derive design guidelines

Abstract Auxetics are a class of materials and metamaterials with a negative Poisson’s ratio (ν) and have gained tremendous popularity over the last three decades. Many studies have focused on characterizing designs that allow obtaining a negative ν. However, some open issues remain concerning understanding the auxetic behavior in operational conditions. Studies have been centered on analyzing the response of specific auxetic topologies instead of treating auxeticity as a property to be analyzed in a well-defined structural context. This study aims to contribute to the investigation of auxetic materials with a structural application, focusing on maximizing performance. The field of application of auxetics for designing inserts was selected and a model of a nail-cavity system was created to determine the effects of different design choices on the system behavior by exploring relationships between selected parameters and the auxetic insert behavior. The exploration combines finite element modeling analyses with their surrogate models generated by supervised learning algorithms. This approach allows for exploring the system’s behavior in detail, thus demonstrating the potential effectiveness of auxetics when used for such applications. A list of design guidelines is elaborated to support the exploitation of auxetics in nail-cavity systems.