Material Quality Research Articles

Development and effectiveness of short video tutorials in basic turning learning to enhance students' cognitive ability

This study aims to develop and evaluate the effectiveness of short tutorial videos in teaching the essential operation of lathe machines in mechanical engineering. Utilizing the ADDIE model (Analysis, Design, Development, Implementation, Evaluation), the research was conducted at SMK N 1 Sumatera Barat, involving 65 vocational school students. The short tutorial videos were designed to enhance students' comprehension and cognitive ability in lathe machine operations, addressing the challenges posed by traditional teaching methods. Data were collected through questionnaires and practical tests to assess students' understanding and skills. The findings revealed that the short tutorial videos significantly improved students' comprehension and cognitive ability, although variations in understanding levels were observed. Normality tests confirmed a normal data distribution, allowing for the use of paired sample t-tests, which indicated no significant difference between the Mechanical Engineering and Industrial Mechanical Engineering groups after using the tutorials. Validation by media and content experts demonstrated the high quality and relevance of the instructional material. This study underscores the importance of developing more interactive and adaptive learning media and highlights the need to explore further other factors influencing cognitive ability.

Testing Mortars for 3D Printing: Correlation with Rheological Behavior

Three-dimensionally printed concrete is a transformative technology that addresses housing shortages due to population growth and enables innovative architectural designs. The objective of this study is to investigate the connection between a conventional test and the rheological properties of 3D-printed concrete. A more precise assessment of material quality based on traditional evaluation techniques is proposed. Standard tests are conducted to evaluate the consistency of 3D-printed concrete materials. Complementarily, a rheometer is employed to accurately measure key rheological properties, thereby establishing a link with empiric testing methodologies. The correlation between the flow table test and rheological coefficients, such as yield stress and viscosity, has been identified as the most effective in basic experiments for evaluating material behavior. This approach allows for a preliminary assessment of printability without the need for additional complex equipment. The study has successfully established a relationship between flow table tests and rheological parameters. However, further research involving a broader range of materials and print-test experiments is essential to enhance the correlation between other conventional testing methods and rheometer results.

FEM Investigation of the Roughness and Residual Stress of Diamond Burnished Surface

Characterization of surface integrity is possible with three critical metrics: microstructure, surface roughness, and residual stress. The latter two are discussed in this paper for low-alloyed aluminum material quality. Ball burnishing is a regularly used finishing procedure to improve surface roughness, shape accuracy, and fatigue life, taking advantage of the fact that it can favorably influence the variation in stress conditions in the material. The effect of burnishing is investigated using finite element simulation with DEFORM 2D software using the real surface roughness of the workpiece. The FEM model of the process is validated with experimental tests, the surface roughness is measured using an AltiSurf520 measuring device, and the residual stress is analyzed with a Stresstech Xstress 3000 G3R X-ray diffraction system (Stresstech, Vaajakoski, Finland). The results indicate that the burnishing process improves the surface roughness and stress conditions of AlCu6BiPb low-alloyed aluminum, and the study shows that there is good agreement between the FE and experimental results, further revealing the effect of the process parameters on the distribution of the compressive residual stress.

Numerical and experimental study on reinforced 3DCP walls filled with light-weight concrete

This paper explores the structural viability of 3DCP as a novel additive manufacturing method in the construction industry, focusing on its integration and standardization challenges due to its emerging nature. With the construction industry's increasing interest in innovative materials and robotic construction, 3DCP's unique characteristics necessitate thorough investigation to understand its potential fully. This study aimed to assess the structural capacity of 3DCP walls, employing flexural tests on samples filled with lightweight concrete containing EPS, and comparing the outcomes with those of traditionally cast concrete. Through a comprehensive approach that combines experimental work with numerical analysis, this study intended to calibrate the material's properties based on small-scale tests to inform the design of larger structures. Macro and micro-scale numerical modeling methods were investigated for the analysis of 3DCP. The findings revealed that the inherent strength of 3DCP significantly depends on the material's composition and quality. Moreover, it was observed that the structural integrity of 3DCP walls was somewhat inferior to that of fully cast counterparts. However, a strong correlation between the numerical simulations and experimental data underscores the value of this research. By calibrating 3DCP's properties from small-scale experiments, the study provides a foundational basis for designing larger structures with enhanced reliability. Both numerical methods demonstrate high accuracy for the analysis of 3DCP and can be adopted for the analysis of larger structures.

Polypropylene Crystallinity Reduction through the Synergistic Effects of Cellulose and Silica Formed via Sol-Gel Synthesis.

This study focuses on the development of environmentally sustainable polypropylene (PP)-based composites with the potential for biodegradability by incorporating cellulose and the oligomeric siloxane ES-40. Targeting industrial applications such as fused deposition modeling (FDM) 3D printing, ES-40 was employed as a precursor for the in situ formation of silica particles via hydrolytic polycondensation (HPC). Two HPC approaches were investigated: a preliminary reaction in a mixture of cellulose, ethanol, and water, and a direct reaction within the molten PP matrix. The composites were thoroughly characterized using rotational rheometry, optical microscopy, differential scanning calorimetry, and dynamic mechanical analysis. Both methods resulted in composites with markedly reduced crystallinity and shrinkage compared to neat PP, with the lowest shrinkage observed in blends prepared directly in the extruder. The inclusion of cellulose not only enhances the environmental profile of these composites but also paves the way for the development of PP materials with improved biodegradability, highlighting the potential of this technique for fabricating more amorphous composites from crystalline or semi-crystalline polymers for enhancing the quality and dimensional stability of FDM-printed materials.

Methodological approaches to assessing the invasion of process fluids into the core pore space

Background. The reliability of the lithological and petrophysical studies is largely determined by the quality of the core material. The invasion of drilling mud filtrate into the core will primarily affect the measurements of the fluid type, residual oil and water saturation, porosity, permeability, geochemical properties and wettability of the rock. Evaluating the suitability of the core material for laboratory studies is one of the main tasks in the study of low-invasion core. Objective. To determine the most informative methods of penetration of process fluids into the pore space of the rock to assess the suitability of the core for laboratory studies. Materials and methods. The paper uses the methods of lithological and petrophysical research of core and reservoir fluids. Results. The application of the used research methods is analyzed. The advantages and limitations of each of the presented methods are determined. Conclusions. The assessment of the degree of mud filtrate invasion into the core determines the suitability of the core material for further petrophysical research.

Порівняння ущільнюваності асфальтобетонної суміші із золою-винесення та вапняковим наповнювачем

Introduction. In Ukraine, about 30 % of all electricity is generated from the combustion of solid fuels — coal, shale, peat. In our country, there are about 15 operating thermal power plants that generate about 5 – 6 million tons of ash and slag waste per year as a secondary product. Thus, the fuel and energy complex waste generated in the furnaces of thermal power plants is a huge accumulation of ash in the form of dusty residues and lumpy sludge, as well as various ash and slag mixtures. These products of high-temperature processing (1 200 – 1 700 ºС) of the mineral part of the fuel are widely used in many countries of the world and, given the global trend towards an increase in the share of the secondary market for the use of waste, it is necessary to predict an increase in the rate of their processing in Ukraine. Problem Statement. The road construction industry is one of the strategic industries of Ukraine, and the issue of quality and availability of basic building materials for road construction is particularly acute now, which is directly related to its high material intensity. The known reserves of high-quality raw materials that could be used as asphalt concrete components are constantly decreasing, so it is necessary to look for alternative sources of raw materials for construction materials and explore the possibility of their use. In this regard, the most effective use of local raw materials is the use of industrial waste, which can be one of the solutions to the problem of lack of raw materials of inorganic origin.

Spectroscopic Analysis of Chrysotile Asbestos and its Environmental Resistance in Asbestos Cement Waste Products

Most asbestos-related studies have focused on asbestos exposure risks, their associated health implications, and waste management issues. Our research introduced a unique perspective that has rarely been explored: the impact of environmental factors on asbestos cement products. The novelty of the study is that, in contrast to previous research, in addition to determining the material quality of asbestos, it analyses the trace materials, additives and the emissive nature of chrysotile fibers. This study aims to identify the chrysotile-asbestos content in three common asbestos cement products found in Hungary, with regard to the release of their fibers upon exposure to the environment and to identify trace elements that could be used to identify the origin and function of each of these products. Our analyses revealed the presence of chrysotile in each tested sample, with spectral matches ranging from 59.6% to 86.7%. Asbestos cement products exposed to various environmental influences for long periods showed a greater chrysotile emission capacity than those unexposed or hermetically sealed ones. Additionally, we established that all asbestos cement products contained glass fibers, with an average spectral match of 62.1%. We further identified polysilicate in the materials with an average spectral match of 66.0%, as it was included in asbestos cement products to enhance their heat resistance. Our results pave the way for a new methodology for assessing asbestos cement products with regard to the implementation of their trace element level assessments.

Variation in the Phenolic Profile and Antioxidant, Antihyperglycemic, and Anti-Inflammatory Activity in Leaves of Cotoneaster zabelii during Growing Season

Cotoneaster zabelii is a medicinal plant that is beneficial due to its polyphenol-rich leaves. In the course of optimizing the harvest time for C. zabelii cultivated in Poland, the leaf samples were collected monthly during the annual plant vegetation season, and the hydromethanolic leaf extracts were evaluated for their phenolic composition and model biological activities, including antioxidant, antihyperglycemic, and anti-inflammatory effects in vitro. The phenolic profiles were analyzed using UHPLC-PDA-ESI-MS3, HPLC-PDA, and spectrophotometric methods (total phenolic content, TPC) to understand their seasonal variability and its correlation with bioactive properties. The identified phenolic compounds included caffeic acid derivatives, flavan-3-ols (especially (−)-epicatechin and procyanidins B-type), and flavonoids like quercetin mono- and diglycosides. Leaves harvested in July and October contained the highest polyphenolic levels and demonstrated significant antioxidant activity in most tests. The leaves harvested in July, September, and October showed optimal anti-inflammatory effects, whereas the highest antihyperglycemic activity was observed in the leaves collected from June to July. Regarding polyphenolic levels and bioactivity, the summer and autumn months appear to be the most advantageous for harvesting leaf material of optimal quality for phytotherapy.

Fabrication Strategies for 2D Halide Perovskite Towards Next-Generation Optoelectronic Applications

AbstractHalide perovskites have emerged as promising materials in high-performance optoelectronics due to their exceptional optoelectrical properties, such as long carrier lifetime and tunable bandgap. Despite the promising capabilities of three-dimensional (3D) halide perovskites in applications like solar cells and light-emitting diodes, their operational stability remains a critical challenge. This review focuses on quasi-two-dimensional (2D) halide perovskites, which offer enhanced stability through their reduced dimensionality. We discuss the unique properties of these materials, including the ability to modify optical and electronic characteristics by altering the organic cations and the layer number in the perovskite structure. Additionally, we review various fabrication techniques, highlighting the shift from traditional low-temperature solution processes to more advanced solid, liquid, and vapor-phase methods, which address the limitations of conventional fabrication and enhance material quality. This comprehensive review aims to provide insights into the development of stable and efficient 2D halide perovskite-based optoelectronic devices, paving the way for their integration into next-generation optoelectronic applications.

Charge Transport in Interband Cascade Lasers: An Ab‐Initio Self‐Consistent Model

AbstractInterband cascade lasers (ICLs) stand out due to their low threshold current and minimal power consumption, rendering them viable sources for compact and mobile devices in the mid‐infrared. Since their first demonstration, they experienced major performance improvements. Mostly they originate from either improved material quality or the outcomes of numerical analysis of secluded parts. Encouraged by the impact of secluded models, an ICL‐specific simulation tool can lead to performance breakthroughs and a better comprehension of governing mechanisms. Drawing from an evaluation of existing tools designed for quantum cascade structures, a self‐consistent density matrix rate equation model is implemented to simulate the transport in both conduction and valence band heterostructures. Albeit the extensive inclusion of the quantum effects, special care was taken to maintain a high numerical efficiency. The charge transport model additionally considers optical field calculations, allowing for predictive calculations of light–current–voltage curves. The model is benchmarked against well‐established ICL designs and demonstrate reliable performance predictability. Additionally, detailed insights into device characteristics extracted from the model are provided. This ultimately allows to deepen the understanding of ICL and not only refine existing ones but also generate novel optimized designs.

Assessing research needs for informing pet food industry decisions

Abstract The global pet food industry continues to grow being fueled by increased pet ownership, higher disposable income of pet owners, and a growing demand for premium products. While this growth has attracted increased interest of researchers in animal nutrition and product formulation, the overall body of management and economic literature to guide product innovation and marketing strategies in the pet food industry is still limited. This study aims to identify and highlight the most important, relevant, and current research needs for informing product and marketing decisions in pet food. The methods include a quantitative analysis of primary data from a survey of 76 pet food decision makers involved in the procurement of raw material, production, and marketing. The findings suggest the need for extensive research in various areas pertaining to the quality and availability of raw materials, processing methods, and forecasting consumer preferences. The findings also emphasize high value research areas such as identifying alternative protein sources, enhancing nutrient retention during the extrusion process, identifying opportunities for product innovation that align with customer preferences, and accurately predicting consumer demand.

Investigation on effects of nano-reinforcement on the mechanical properties, fatigue, and microstructural analysis of dissimilar AA6061- Mg AZ31B weld joints

Weld joints have been subject to substantial improvement in mechanical durability and wear resistance in recent years. This research work challenge can be answered by incorporating nano-materials into the weld zone. Mechanical and metallurgical aspects of friction stir welded (FSW) butt joints made of AA6061 aluminum and Mg AZ31B alloys have been examined in this work, both with and without the use of naturally derived biochar nanoparticles. The biochar particle was extracted from rice husk. Throughout the whole weld joint manufacturing process, a tool with a rotational speed of 1400 rpm, a welding speed of 40 mm min−1, and a tapered pin profiled tool were employed. During the joint fabrication process, the constant axial load of 7 kN, plunge depth of 0.2 mm, and constant dwell time of 0.3 s were also maintained. In order to improve the mechanical attributes of the weld joints, different wt% of biochar such as 1%, 2%, and 3%, were applied at the interface region of the weld joints. The experimental results revealed that the percentage of reinforced nano-materials plays a significant effect in improving the weld joint qualities. The testing results of reinforced friction stir-welded joint qualities were compared to those of simple friction stir welded joints made without and with adding the nanoparticles. The best results were obtained when 2 wt% of biochar particles was added to the weld interface region. The presence of biochar nano-particles, in addition to their contribution to increased grain refinement in the weld nugget region, was also seen in the region. It was discovered that the event distribution of particles at the nugget zone significantly enhanced the mechanical and wear resistance qualities of the weld joints that were manufactured. The optical microscope was used to analyze the microstructures in the weld nugget region, and a scanning electron microscope (SEM) was utilized to examine the fracture analysis of the tensile samples. The presence of 2 wt% biochar particles in the weld nugget region resulted in a considerable increase in the mechanical characteristics of the weld connections. The ultimate tensile strength, hardness, and yield strength of the weld nugget results 197 MPa, 173 HV, 163 MPa. Overall, when compared to the qualities of the base material and plain weld joints. The mechanical properties and wear resistance of the weld joints have improved significantly. When biochar particles were used as reinforcement particles during the fabrication phase of the joint, a mechanism for pinning was observed in the weld microstructure.

A new approach for optimal design of intensive care unit

Planning and budgeting for healthcare facilities necessitate precise estimation and a thoughtful analysis of the required area for each department, as well as extensive knowledge of the most important elements that can influence the design and provide an appropriate environment for staff and patients. A gross conversion factor is influential in calculating the entire area of a department. However, there is no precise standard indicating how this factor should be calculated. To address this problem, quality function deployment (QFD) has been implemented. The intensive care unit (ICU) is one of the highly equipped departments that should be properly planned; therefore, it was selected for application. The five steps of the QFD are used to identify and rank the most important and efficient design features. Only the top factors are considered in calculating the required area for the ICU department. This approach presents a unique method for estimating the gross square area based on calculating the gross conversion factor. To demonstrate the proposed approach’s efficacy, it was applied to two Egyptian public hospitals. The results reveal that 15–16% of the total space of both hospitals can be reduced from the total department space. Moreover, an outstanding reduction in ICU design and preparation expenses has been achieved. The design reduces the required budget for a project while maintaining the same construction material quality and accommodating extra beds. Additionally, the QFD proves its ability to redesign the ICU department while reducing costs.

Optimization of microbial consortia and materials composition enhances gluconic acid content in kombucha.

The objective of this study was to optimize the microbial and ingredient composition of kombucha for enhanced production of gluconic acid (GA). Fourteen strains of Komagataeibacter spp. and one yeast strain of Dekkera sp. were isolated from kombucha. Among them, Komagataeibacter swingsii SS1 (SS1) and Komagataeibacter saccharivorans SS11 (SS11) were selected for their high GA production. A rapid reduction of pH, high GA content relative to acetic acid, and high cellulose production were observed in the tea infusion fermented by the microbial consortium (SS1 + SS11 + Dekkera bruxellensis Y24). From the correlation between the materials composition and quality indicators of kombucha, the decrease in pH was the most critical quality indicator of kombucha and the most closely related to GA content. Maximal GA production (11.7mg/mL) was obtained under the conditions of 1% (w/v) tea extract, 8.5% (w/v) glucose, and 1.5% (v/v) ethanol through the optimization of materials composition by response surface methodology. The GA content of kombucha was enhanced threefold in comparison to general kombucha by fermentation with Komagataeibacter spp. and optimization of the composition of the ingredients. Overall, this study showed that a specific microbial consortium and materials composition could be established by correlation analysis among the ingredients, which results in increased GA levels in kombucha. These findings offer valuable foundational data for both commercial production and quality control of kombucha.

Probing the link between vision and language in material perception using psychophysics and unsupervised learning.

We can visually discriminate and recognize a wide range of materials. Meanwhile, we use language to describe what we see and communicate relevant information about the materials. Here, we investigate the relationship between visual judgment and language expression to understand how visual features relate to semantic representations in human cognition. We use deep generative models to generate images of realistic materials. Interpolating between the generative models enables us to systematically create material appearances in both well-defined and ambiguous categories. Using these stimuli, we compared the representations of materials from two behavioral tasks: visual material similarity judgments and free-form verbal descriptions. Our findings reveal a moderate but significant correlation between vision and language on a categorical level. However, analyzing the representations with an unsupervised alignment method, we discover structural differences that arise at the image-to-image level, especially among ambiguous materials morphed between known categories. Moreover, visual judgments exhibit more individual differences compared to verbal descriptions. Our results show that while verbal descriptions capture material qualities on the coarse level, they may not fully convey the visual nuances of material appearances. Analyzing the image representation of materials obtained from various pre-trained deep neural networks, we find that similarity structures in human visual judgments align more closely with those of the vision-language models than purely vision-based models. Our work illustrates the need to consider the vision-language relationship in building a comprehensive model for material perception. Moreover, we propose a novel framework for evaluating the alignment and misalignment between representations from different modalities, leveraging information from human behaviors and computational models.

Simultaneous carbon fiber layer thickness and direction measurement and identification using a novel eddy current sensor and simplified multi-scale 1D-ResNet network

A novel eddy current sensor, featuring a triangular excitation coil and three rectangular receiving coils, is proposed for simultaneously detecting carbon fiber layer thickness and directions in the manufacturing process of carbon fiber reinforced polymer (CFRP) materials. It can disclose various carbon fiber layers and directions based on the signals obtained from the three receiving coils. However, classification of carbon fiber layers and directions proves challenging due to the complexity of signal features resulting from different combinations of carbon fiber layers and directions. To address this issue, we propose the use of a simplified multi-scale 1D-ResNet network. Comparative analysis reveals that our proposed network achieves higher train and validation accuracy compared to single-scale 1D-ResNet networks and different layers 1D-ResNet networks. Furthermore, the proposed simplified network not only achieves high classification accuracy with 100% and 99.7% for carbon fiber layers and directions, respectively, but also requires less training time compared to multi-scale 1D-ResNet networks. The novel eddy current sensor proposed in this study enables accurate recognition of carbon fiber layers and their directional orientation through the implementation of a simplified multi-scale 1D-ResNet network in the manufacturing process of CFRP materials. This innovation significantly enhances the quality of CFRP materials during manufacturing, ensuring their strength aligns with predetermined orientations.

Innovative strategies for time-release PCE design and cement paste flowability control

Extending the retention time of cement paste flowability with the addition of admixtures containing slow-release components is standard practice for ensuring the continued building quality of cement-based materials. This study aims to control the release rate of PCE and enhance its time-varying dispersion effect in fresh cement paste by utilizing Time-dependent Release PCEs (TRPCEs) with varying side-chain structures. The structural characterization of the synthesized TRPCEs was investigated using GPC (Gel Permeation Chromatography), FTIR (Fourier Transform Infrared Spectroscopy), and 1H NMR (Proton Nuclear Magnetic Resonance) techniques. Furthermore, experiments were carried out on time-varying flowability with different dosages of TRPCEs to investigate the flowability changes under the time-varying release effect. The influence of TRPCEs on cement hydration was examined using isothermal calorimetry by measuring the early hydration heat of cement paste. The time-dependent adsorption behaviors of TRPCEs were also examined using a TOC (Total Organic Carbon) analyzer. The findings show that TRPCEs have a minor effect on the cement hydration process's rapid reaction period but little effect on its induction and acceleration periods because of variations in the initial dispersion effect. Additionally, the adsorption behaviors of TRPCEs on cement particles vary significantly due to the hydrolysis of slow-release groups. The varying adsorption and consumption of TRPCEs on cement particles and hydration products in different hydration phases are key controlling factors for the time-varying flowability changes in cement paste. Finally, this innovative approach offers a novel perspective for designing and preparing new types of PCEs with a strong capability for time-varying flowability retention.

Factors Influencing The Selection And Acquisition Of Clothing Items Among Undegraduates In Federal Polytechnic Ado-Ekiti

This study examined the factors influencing the selection and acquisition of clothing items among undergraduates in Federal Polytechnic Ado-Ekiti, Ekiti State. Many undergraduates often find themselves in situations where they borrow clothes for social events like parties, buy clothes on credit, or allocate a significant portion of their pocket money to clothing purchases. These behaviors stem from a desire to maintain a certain social image, adhere to fashion trends, or fit in with peers, often leading to financial strain and dependence on borrowing. Three research questions and one hypothesis guided the study. The study examined the physical features of the clothing, psychological and socio-economic factors that influenced the selection and acquisition of clothing items among these undergraduates. A descriptive survey research approach was adopted for this study. Simple random sampling techniques were used to select Two Hundred and Five (205) respondents. The questionnaire used for data collection was designed and titled “Factors Influencing the Selection and Acquisition of Clothing Items (FISACI)”. Findings from the respondents showed that, Physical features like style, quality of material, and fit (x=3.24), significantly influence undergraduates’ clothing choices, psychological factors, including the desire to express personal identity and peer pressure (x=3.29), drive many clothing purchases among undergraduates, Socioeconomic factors, such as income level and financial literacy (x=3.11), strongly impact students’ ability to make informed clothing purchases. Data were analyzed using mean, standard deviation and t-test. Based on the findings, undergraduates should learn to live within their means by budgeting for all clothing expenses before buying. Also, undergraduates desired of good taste in clothing selection can make up for the extra expenses by engaging in part time jobs; among other recommendations were made.

Acceleration of ferromagnetic resonance measurements by Bayesian experimental design.

Ferromagnetic resonance (FMR) is a broadly used dynamical measurement used to characterize a wide range of magnetic materials. Applied research and development on magnetic thin film materials is growing rapidly alongside a growing commercial appetite for magnetic memory and computing technologies. The ability to execute high-quality, fast FMR surveys of magnetic thin films is needed to meet the demanding throughput associated with rapid materials exploration and quality control. Here, we implement optimal Bayesian experimental design software developed by [McMichael etal. J. Res. Natl. Inst. Stand. Technol. 126, 126002 (2021)] in a vector network analyzer-FMR setup to demonstrate an unexplored opportunity to accelerate FMR measurements. A systematic comparison is made between the optimal Bayesian measurement and the conventional measurement. Reduced uncertainties in the linewidth and resonance frequency ranging from 40% to 60% are achieved with the Bayesian implementation for the same measurement duration. In practical terms, this approach reaches a target uncertainty of ±5MHz for the linewidth and ±1MHz for the resonance frequency in 2.5× less time than the conventional approach. As the optimal Bayesian approach only decreases random errors, we evaluate how large systematic errors may limit the full advantage of the optimal Bayesian approach. This approach can be used to deliver gains in measurement speed by a factor of 3 or more and as a software add-on has the flexibility to be added on to any FMR measurement system to accelerate materials discovery and quality control measurements, alike.