Types Of Materials Research Articles

Gaussian processes modeling for the prediction of polymeric nanoparticle formulation design to enhance encapsulation efficiency and therapeutic efficacy.

Conventional drugs have been facing various drug delivery obstacles, including first-pass metabolism for oral medications, drug degradation by cellular enzymes, off-target effects, and cytotoxicity of healthy cells. Nanoparticles (NP) application in drug delivery can compensate for these drawbacks to a great extent. NPs can be fabricated using different materials and structures to achieve desired therapeutic effects. For each type of NP material, its physicochemical properties determine compatibility with specific drugs and other supplemental compositions. The optimized material selection becomes prominent in NP development to improve NP performances. Due to the nature of NP fabrication, the process is long and expensive. To accelerate NP composition optimization, machine learning (ML) techniques are among the most promising methods for efficient data predictions and optimizations.As a proof-of concept, we created Gaussian Process (GP) models to make predictions for drug encapsulation efficiency (EE%) and therapeutic efficacy of 32 poly (lactic-co-glycolic acid) (PLGA) NPs that are formed with materials with different physicochemical properties. Two model drugs, doxorubicin (DOX) and docetaxel (DTX) were loaded separately. The IC50 values for the various NPs formulations were evaluated using the OVCAR3 epithelial ovarian cancer cell line. EE% GP model has the highest prediction accuracy with the lowest normalized root-mean-squared-error (RMSE) of 0.187. The DOX and DTX IC50 GP models have normalized RMSEs of 0.296 and 0.206, respectively, which are higher than that of the EE% GP model.

Towards a Sustainable Laser Powder Bed Fusion Process via the Characterisation of Additively Manufactured Nitinol Parts

Is additive manufacturing (AM) a sustainable process? Can the process be optimised to produce sustainable AM parts and production techniques? Additive manufacturing offers the production of parts made of different types of materials in addition to the complex geometry that is difficult or impossible to produce by using the traditional subtractive methods. This study is focused on the optimisation of laser powder bed fusion (L-PBF), one of the most common technologies used in additive manufacturing and 3D printing. This research was carried out by modulating the build layer thickness of the deposited metal powder and the input volumetric energy density. The aim of the proposed strategy is to save the build time by maximizing the applied layer thickness of nitinol powder while retrieving the different AM part properties. The saving in the process time has a direct effect on the total cost of the produced part as a result of several components like electric energy, inert gas consumption, and labour. Nickel-rich nitinol (52.39 Ni at.%) was selected for investigation in this study due to its extremely high superplastic and shape memory properties in addition to the wide application in various industries like aerospace, biomedical, and automotive. The results obtained show that significant energy and material consumption can be found by producing near full dens AM parts with limited or no alteration in chemical and mechanical properties.

Exploring the usage of learning resources by medical students in the basic science stage and their effect on academic performance

BackgroundThe United States Medical Licensing Examination (USMLE) step 1 is one of the two examinations written after completion of the first two years (basic science stage) of medical school to be eligible to apply for residency training in the USA. A huge number and types of study materials are available to prepare for the exam which might confuse students choosing a resource.We investigated learning resources being used by the third and fifth-semester medical students and their association with academic performance. We also compared learning resources and exam scores of high-performing and low-performing students.MethodsData collection was done using structured (quantitative study) and semi-structured (qualitative study) questionnaires during a face-to-face interview. This article is about the quantitative part which was designed as a correlational study. Single factor one-way analysis of variance (ANOVA), Pearson correlation coefficient test, T-test, and Fisher’s exact test were used to analyze the data.ResultsAbout half of all students used three or more commercial resources dealing with the same content. A weak negative correlation was observed between the number of commercial resources and the exam scores, especially when the number of these resources was three or more (r = -0.26). The mean exam score of textbook users was statistically significantly higher than the mean score of textbook non-users (p = 0.01). The usage of textbooks was statistically significantly higher in the cohort of top performers in comparison to the rest of the students (p = 0.006). In addition to less usage of textbooks, the mean number of review books was higher in the group of weakest students (2.84 versus 3.7; p = 0.75).ConclusionsMost students did not use professional textbooks and about half used too many commercial review resources. While the former fact was significantly associated with poor academic performance, the later fact had weak negative correlation with exam score.Pedagogical interventions are urgently needed to make the right type of learning resources available by making professional textbooks more USMLE-oriented and helping the students choose the best and right number of resources for optimum academic performance. By fulfilling the observed needs of the students in this way, they might feel empowered because of self-determination which will motivate studies.

Pressure-Dependent Superconductivity in Topological Dirac Semimetal SrCuBi.

The discovery of superconducting states in diverse topological materials generated a burgeoning interest to explore a topological superconductor and to realize a fault-tolerant topological quantum computation. A variety of routes to realize topological superconductors have been proposed and many types of topological materials have been developed. However, a pristine topological material with a natural superconducting state is relatively rare as compared to topological materials with artificially induced superconductivity. Here, we report that the planar honeycomb structured three-dimensional (3D) topological Dirac semimetal (TDS) SrCuBi, which is the Zintl phase, shows a natural surface superconductivity at 2.1 K under ambient pressure. It is clearly identified from theoretical calculations that a topologically non-trivial state exists on the (100) surface. Further, its superconducting transition temperature (Tc) increases by applying pressure, exhibiting a maximal Tc of 4.8 K under 6.2GPa. We believe that this discovery opens up a new possibility of exploring exotic Majorana fermions at the surface of 3D TDS superconductors. This article is protected by copyright. All rights reserved.

Paper Battery: The Future and Solution for Traditional Battery

Today is the biggest problems are faced by the electronics industry size of batteries gadgets ultra-thin and small day by day.Paper batteries will the replace the li-ion battery and paper battery. Paper-based batteries have emerged as a promising solution for sustainable energy storage owing to their eco-friendly nature, lightweight, flexibility, and cost-effectiveness. This paper presents a comprehensive overview of recent advancements in the field of paper-based batteries, focusing on their fabrication techniques, materials selection, and performance optimization strategies. Various types of paper substrates, conductive materials, and electrolytes employed in paper-based batteries are discussed, along with their impact on the overall performance and environmental sustainability. Additionally, this paper highlights the potential applications of paper-based batteries in portable electronics, medical devices, and wearable technologies, emphasizing their role in promoting the development of green energy storage solutions. Finally, challenges and future directions for the research and development of paper-based batteries are outlined, aiming to inspire further innovation and integration of these eco-friendly energy storage devices into real-world applications. This biodegrable and CNT. Electronics device are classified into two types primary and secondary. The paper are shown in SWCNT and MWCNT are the contain in this type. Title: Advancements in Paper-Based Batteries: A Sustainable Approach towards Energy Storage Keywords: CNT (carbon Nano tube), SWCNT (singled walled carbon Nano tube), MWCNT (multi walled carbon Nano tube, Paper Batteries), Flexibility.

Devonian Harpetidae from the central and eastern Anti–Atlas, Morocco

Devonian Harpetidae from the central and eastern Anti–Atlas, Morocco

Combined Machine Learning and High-Throughput Calculations Predict Heyd-Scuseria-Ernzerhof Band Gap of 2D Materials and Potential MoSi2N4 Heterostructures.

We present a novel target-driven methodology devised to predict the Heyd-Scuseria-Ernzerhof (HSE) band gap of two-dimensional (2D) materials leveraging the comprehensive C2DB database. This innovative approach integrates machine learning and density functional theory (DFT) calculations to predict the HSE band gap, conduction band minimum (CBM), and valence band maximum (VBM) of 2176 types of 2D materials. Subsequently, we collected a comprehensive data set comprising 3539 types of 2D materials, each characterized by its HSE band gaps, CBM, and VBM. Considering the lattice disparities between MoSi2N4 (MSN) and 2D materials, our analysis predicted 766 potential MSN/2D heterostructures. These heterostructures are further categorized into four distinct types based on the relative positions of their CBM and VBM: Type I encompasses 230 variants, Type II comprises 244 configurations, Type III consists of 284 permutations, and 0 band gap comprises 8 types.

Mathematical Model of Vibration-Centrifugal Processing of Parts Using Loose Abrasive

The article presents some new theoretical and experimental solution of a scientific and applied problem of technological support for vibratory centrifugal processing of complex-profiled parts in a bulk abrasive environment. This solution aims to increase productivity while ensuring the desired quality of the processed surfaces. The authors have developed a mathematical model that describes the action of abrasive particles on the surface of the parts, taking into account the parameters of the granular abrasive medium based on Voigt’s law. This allows the description of dynamic processes in the processing environment for a wide range of material types. The natural frequencies of oscillations of the processed medium layer have been determined, which depend on the amplitude of its vibrations for different densities of soft and hard materials of the processed medium and the medium with linear-elastic properties. The methodology includes the use of test equipment to conduct experimental research on the process, which involves determining changes in specific metal removal rates and surface roughness using the frequency converter Altivar 71 with the PowerSuite v.2.5.0 software.

Study of the Relation between Aging and Pesticides: A Review

Aims: The main aim of this study was to use specific data from the literature on ageing, correlating this with the pesticide contamination, in order to understand the relationship with an increasingly ageing population. Study Design: A systematic review was performed. Place and Duration of Study: Laboratory of Biomathematics of the Federal University of Alfenas, Minas Gerais State, Brazil, between April 2023 and August 2023. Methodology: A systematic search of articles was performed using the CAPES Periodic platform, a searcher from the Education Ministry of Brazil that contains Web of Science, Scopus, MedLine, from August 2020 to May 2023. For this review, the subject’s “aging theory”; “neuroscience and pathologies to aging”; “aging and aging-associated changes”; “pesticides and pesticide toxicity”; “pesticide toxicity and neurotoxicity”; “longevity and healthy aging”; “aging human and pesticides” were searched together using the type of material “articles” in English language. Some articles about “population growth”; “world population”; “population-aging” were used for epistemological composition of this work content subjects. Results: From the 19.720 articles after the exclusion and the inclusion criteria made with the subjects most pertinent to the objectives of this work; 19.570 articles were excluded, remaining 150 ones, of which 116 were qualitative in scope and 34 quantitative. Conclusion: The complex relationship between the pesticide contamination and the condition of the exposed individual may be associated with premature ageing and a greater susceptibility to debilitating age-related diseases. Although technology is increasingly improved in its innovations, health and environmental regulations have not been able to rid the production processes of their potential to pollute the environment and cause health problems for those exposed to them.

Photocatalytic Degradation of Quinolones by Magnetic MOFs Materials and Mechanism Study

With the rising incidence of various diseases in China and the constant development of the pharmaceutical industry, there is a growing demand for floxacin-type antibiotics. Due to the large-scale production and high cost of waste treatment, the parent drug and its metabolites constantly enter the water environment through domestic sewage, production wastewater, and other pathways. In recent years, the pollution of the aquatic environment by floxacin has become increasingly serious, making the technology to degrade floxacin in the aquatic environment a research hotspot in the field of environmental science. Metal–organic frameworks (MOFs), as a new type of porous material, have attracted much attention in recent years. In this paper, four photocatalytic materials, MIL-53(Fe), NH2-MIL-53(Fe), MIL-100(Fe), and g-C3N4, were synthesised and applied to the study of the removal of ofloxacin and enrofloxacin. Among them, the MIL-100(Fe) material exhibited the best photocatalytic effect. The degradation efficiency of ofloxacin reached 95.1% after 3 h under visible light, while enrofloxacin was basically completely degraded. The effects of different materials on the visible photocatalytic degradation of the floxacin were investigated. Furthermore, the photocatalytic mechanism of enrofloxacin and ofloxacin was revealed by the use of three trappers (®O2−, h+, and ®OH), demonstrating that the role of ®O2− promoted the degradation effect of the materials under photocatalysis.

Development of Diffraction Research Methodologies for Mediloy S-CO Alloy Speciments Made Using LPBF Additive Manufacturing

Abstract This study focuses on the application and improvement of diffraction measurement methodologies for the optimization of manufacturing parameters of CoCr alloy components made by additive manufacturing (AM) – particularly for Mediloy S-Co alloy specimens made using Laser Powder Bed Fusion (LPBF) additive manufacturing. We measured the phase composition of specimens obtained in AM processes, the measurement of residual stresses resulting from the manufacture of these printed parts, as well as the effectiveness of stress relaxation through the use of heat treatments dedicated to this type of material. Findings reveal several insights into how printing strategies affect the porosity and residual stresses in additive manufacturing. Specimens with higher porosity, particularly those created using specific strategies that resulted in lower energy densities, exhibited lower residual stresses. Notably, printing direction and energy density were found to significantly affect the mechanical stresses within the specimens, with directional choices playing a critical role in the final properties of the parts. Additionally, our findings underscore the complex relationship between various printing parameters and the development of mechanical stresses, highlighting the impact of adjustments in printing strategy on the properties of printed components.

LDH-Based Voltammetric Sensors

Layered double hydroxides (LDHs), also named hydrotalcite-like compounds, are anionic clays with a lamellar structure which have been extensively used in the last two decades as electrode modifiers for the design of electrochemical sensors. These materials can be classified into LDHs containing or not containing redox-active centers. In the former case, a transition metal cation undergoing a reversible redox reaction within a proper potential window is present in the layers, and, therefore, it can act as electron transfer mediator, and electrocatalyze the oxidation of an analyte for which the required overpotential is too high. In the latter case, a negatively charged species acting as a redox mediator can be introduced into the interlayer spaces after exchanging the anion coming from the synthesis, and, again, the material can display electrocatalytic properties. Alternatively, due to the large specific surface area of LDHs, molecules with electroactivity can be adsorbed on their surface. In this review, the most significant electroanalytical applications of LDHs as electrode modifiers for the development of voltammetric sensors are presented, grouping them based on the two types of materials.

Experimental investigation of bond behavior with lap splice for CFRP-steel composite bars in coral sea-sand aggregate seawater concrete

The pull-out tests on a total of 81 lap-spliced specimens in 27 groups were conducted to investigate the lap-spliced behavior and the appropriate splice length for CFRP-steel composite bars (C-FSCB) in coral sea-sand aggregate seawater concrete (CSSC). The test variables included the C-FSCB diameter (dc), splice length, concrete cover thickness, concrete strength, lap spacing, stirrup ratio, and materials type. Then, the influence of various test variables on the lap-spliced behavior of C-FSCB in CSSC was analyzed. The results showed that when the splice length was less than 17dc, the specimens exhibited pull-out and concrete splitting failure, while C-FSCB fracture failure occurred when the splice length exceeded 17dc. Severe shear damage was observed on the C-FSCB surface in the case of pull-out and concrete splitting failure. When the splice length was less than 14dc, the bond strength of the specimens was approximately 7.2 MPa. As the splice length increased beyond 14dc, the bond strength gradually decreased. After the cover thickness was greater than 4dc or the compressive strength of CSSC was greater than 30 MPa, the variation in bond strength of the specimens can be negligible. Increasing the stirrup ratio led to an increase in bond strength and a significant reduction in crack width. Compared to specimens with steel bars, the bond strength reduction for specimens with C-FSCB exceeded 25%. Based on the test results, calculation formulas for the bond strength and splice length of C-FSCB in CSSC were established. Furthermore, referring to the approach in the Chinese code GB 50010–2010, a simplified calculation formula for splice length was proposed.

Feed-In-Tariff Is Key to Japan’s Current Biomass Power’s Viability, Even with Environmental Externalities

Abstract Bioenergy is increasingly recognized as an effective tool for removing carbon dioxide from the atmosphere. However, its economic feasibility remains underexplored, particularly when accounting for environmental impacts. This study proposes a quantitative assessment framework to calculate the cost-benefit ratio of biomass power generation and to assess the sustainability of its supporting policy tools, such as feed-in-tariffs (FIT). The framework accounts for benefits through electricity generation and environmental externalities, namely emissions from feedstock production and procurement, such as the transportation of biomass materials. This allows for quantification and a detailed discussion of multiple environmental burdens of biomass energy and economic costs. As a case study, this framework was applied to a hypothetical biomass plant in Japan, which has the fifth-largest biomass market globally. We prepare several scenarios to consider diverse conditions within the Japanese biomass industry, including the types of biomass materials used (pellets vs. chips), their sources (domestic vs. international), and the biomass technologies employed. The results show that using pellets, predominantly imported, significantly increases biomass energy costs. The increase in cost is directly proportional to the quantity of utilized pellets and their transportation distances. However, pellet production location —whether in Vietnam or Canada—doesn't significantly change the overall cost calculations in our study. Our result is consistent across various biomass technologies, showing that the high selling price under the feed-in-tariff system, rather than material type, supply origin, or transportation mode, plays the most critical role in economic feasibility, even when accounting for environmental externalities. Thus, decision-makers must reevaluate the efficacy of FIT policies for wood biomass powers, where fuel costs share a substantial portion. We also discuss its synergies with local industries and trade-offs with other land-use objectives.

A study on the optimal design of UAM seats

The objective of this study is to enhance the efficiency of urban air mobility (UAM) air transportation by determining the optimal design, materials, and processes of seven different manufactured fiber-reinforced plastics (FRP), and to confirm their applicability for next-generation UAM aircraft seats. Structural designs for the aircraft seat models were carried out using carbon fiber-reinforced plastic (CFRP), glass fiber-reinforced plastic (GFRP), and GFRP chop materials, employing Autoclave, Hot-press, and vacuum-assisted resin transfer molding (VaRTM) processes, resulting in a total of seven FRP configurations. It was confirmed that CFRP seats were 50% lower weight than aluminum models, while GFRP seats showed a 30% reduction. Although Autoclave processing resulted in the highest tensile strength at 985[Formula: see text]MPa, VaRTM processing also produced strength levels comparable to Autoclave processing. Structural integrity assessments of the seat models, utilizing the Korean aviation standards (KAS), confirmed that the designed seat models exhibited no failure or deformation under the conditions required by the technical standards. This study provides insights into the potential application of the seven types of FRP materials in the design of aircraft seats, offering weight reduction benefits and meeting the structural integrity requirements outlined by KAS.

Phosphate-Solubilizing Microorganisms Stimulate Physiological Responses of Perennial Ryegrass to Phosphorus Deficiency with Assistance of Straw Compost

Biofertilizers with phosphate-solubilizing microorganism (PSM) inoculations have been suggested to diminish the limitation of phosphorus (P) deficiency in plants. However, their applications in agriculture are restricted due to the inconstant effects of various PSMs. Proper carriers for the inoculations may overcome this shortcoming and improve PSMs’ effectiveness. The objective of this study was to investigate whether straw compost, a type of organic material, can act as a carrier for improving the efficiencies of phosphate-solubilizing bacteria and fungi named Acinetobacter sp. and Aspergillus niger, respectively, in soils. We monitored the growth and cellular physiological responses of one type of model plants, named perennial ryegrass (Lolium perenne L.), under four soil treatments, including non-fertilization, PSM inoculation alone, straw compost addition alone, and the combined applications of both PSMs and straw compost. We found the combined treatments significantly improved the growth by 14.7% for shoot height and 79.7% for shoot weight, respectively, on average. P and potassium (K) uptakes of ryegrass were also increased by 102.5% and 65.3%, respectively, after the application of both PSMs and straw compost. Furthermore, physiological properties, such as photosynthetic efficiency and P-transportation capacity, of ryegrass were also significantly improved under combined treatments when compared to other treatments, regardless of the types of PSM included. The piecewise structural equation model further indicated that PSM inoculation and straw compost input are synergistically contributing to the nutrient uptake of ryegrass through many direct and indirect ways. We propose that straw compost is a good carrier material for PSMs’ survival and would improve their plant growth promotion ability in soil. Our results provide valuable insights into the exploitation and utilization of P-biofertilizers in agriculture.

Performance analysis and application fields of reactive powder concrete

Reactive Powder Concrete (RPC) is a novel concrete material prepared from highly active composite admixtures, cement, fine sand, and micro steel fibers through appropriate curing and processing techniques. RPC not only exhibits ultra-high strength and durability but also demonstrates outstanding toughness, good volume stability, and excellent environmental performance. Its use can reduce the demand for natural resources, extend the service life of structures, and reduce waste generation, aligning with the direction of sustainable development and green building. This makes it an ideal choice for constructing large-span lightweight structures and structures operating in harsh environmental conditions, attracting extensive research attention in the international engineering materials field. In summary, RPC, as a new type of concrete material, has broad application prospects in the construction field. With continuous research and technological development, RPC will undoubtedly bring more innovations and new solutions to the construction industry, promoting its continuous progress and development.

Application and Perspectives: Magnesium Materials in Bone Regeneration.

The field of bone regeneration has always been a hot and difficult research area, and there is no perfect strategy at present. As a new type of biodegradable material, magnesium alloys have excellent mechanical properties and bone promoting ability. Compared with other inert metals, magnesium alloys have significant advantages and broad application prospects in the field of bone regeneration. By searching the official Web sites and databases of various funds, this paper summarizes the research status of magnesium composites in the field of bone regeneration and introduces the latest scientific research achievements and clinical transformations of scholars in various countries and regions, such as improving the corrosion resistance of magnesium alloys by adding coatings. Finally, this paper points out the current problems and challenges, aiming to provide ideas and help for the development of new strategies for the treatment of bone defects and fractures.

From topological nodal-line semimetals to quantum spin Hall insulators in tetragonal SnX monolayers (X=F, Cl, Br, I)

Abstract Two-dimensional (2D) topological materials have recently garnered significant interest due to their profound physical properties and promising applications for future quantum nanoelectronics. Achieving various topological states within one type of materials is, however, seldom reported. Based on first-principles calculations and tight-binding models, we investigate topological electronic states in a novel family of 2D halogenated tetragonal stanene (T-SnX, X = F, Cl, Br, I). All the four monolayers are found being unusual topological nodal-line semimetals (NLSs), protected by a glide mirror symmetry. When spin-orbit coupling (SOC) is turned on, T-SnF and TSnCl are still ascertained as topological NLSs due to the remaining band inversion, primarily composed of Sn pxy orbitals, while T-SnBr and T-SnI become quantum spin Hall insulators. The phase transition is ascribed to moving up in energy of Sn s orbitals and increasing of SOC strengths. The topology origin in the materials is uniformly rationalized through elementary band representations. The robust and diverse topological states found in the 2D T-SnX monolayers position them as an excellent material platform for the development of innovative topological electronics.

In-situ particle analysis with heterogeneous background: a machine learning approach

We propose a novel framework that combines state-of-the-art deep learning approaches with pre- and post-processing algorithms for particle detection in complex/heterogeneous backgrounds common in the manufacturing domain. Traditional methods, like size analyzers and those based on dilution, image processing, or deep learning, typically excel with homogeneous backgrounds. Yet, they often fall short in accurately detecting particles against the intricate and varied backgrounds characteristic of heterogeneous particle–substrate (HPS) interfaces in manufacturing. To address this, we've developed a flexible framework designed to detect particles in diverse environments and input types. Our modular framework hinges on model selection and AI-guided particle detection as its core, with preprocessing and postprocessing as integral components, creating a four-step process. This system is versatile, allowing for various preprocessing, AI model selections, and post-processing strategies. We demonstrate this with an entrainment-based particle delivery method, transferring various particles onto substrates that mimic the HPS interface. By altering particle and substrate properties (e.g., material type, size, roughness, shape) and process parameters (e.g., capillary number) during particle entrainment, we capture images under different ambient lighting conditions, introducing a range of HPS background complexities. In the preprocessing phase, we apply image enhancement and sharpening techniques to improve detection accuracy. Specifically, image enhancement adjusts the dynamic range and histogram, while sharpening increases contrast by combining the high pass filter output with the base image. We introduce an image classifier model (based on the type of heterogeneity), employing Transfer Learning with MobileNet as a Model Selector, to identify the most appropriate AI model (i.e., YOLO model) for analyzing each specific image, thereby enhancing detection accuracy across particle–substrate variations. Following image classification based on heterogeneity, the relevant YOLO model is employed for particle identification, with a distinct YOLO model generated for each heterogeneity type, improving overall classification performance. In the post-processing phase, domain knowledge is used to minimize false positives. Our analysis indicates that the AI-guided framework maintains consistent precision and recall across various HPS conditions, with the harmonic mean of these metrics comparable to those of individual AI model outcomes. This tool shows potential for advancing in-situ process monitoring across multiple manufacturing operations, including high-density powder-based 3D printing, powder metallurgy, extreme environment coatings, particle categorization, and semiconductor manufacturing.