Material Process Research Articles

Using acoustic emission to understand the early-age reaction and cracking evolution of alkali-activated slag-brick powder paste

Real-time monitoring and accurately understanding the continuous occurring psychical-chemical characterization during the hardening process of alkali-activated materials present a formidable challenge. In this study, the early-age reaction process of alkali-activated slag-waste brick powder paste (ASWP) was in-situ and continuous monitored by using acoustic emission (AE) system and temperature. A novel machine learning method was employed to categorize the evolution of AE signals into three distinct stages: reaction acceleration, reaction stabilization and volume shrinkage stage.During reaction acceleration stage (0-2h), the waste brick powder (WBP) increased AE counts rate (4000-7300 counts/h), with RT values exceeding 200μs, indicating the settlement of WBP. Additionally, WBP reduced the high r-value AE activity in volume shrinkage stage, effectively mitigated the drastic volume shrinkage, and delayed its occurrence time by approximately 4 hours. Semi-quantitative analyses of FTIR and TG-DTG indicate that WBP reduced gel phase formation in the early-age stage, decreasing the relative areas in Q2 site by 16% before 36 hours. However, WBP positively impacted ASWP hydration at long ages, increasing Q2 site d areas by 60%-100%. AE technique offers a new perspective for in-depth understanding of the reaction mechanism and microstructural development of alkali-activated materials in situ and continuously.

A Three-Dimensional Surface-Adaptive Stretchable Sensor for Online Monitoring of Composite Materials Curing.

Recently, rigid sensors have been commonly applied to online monitoring of the core curing processes of composite materials to prevent both overcuring and under-curing. However, conventional rigid sensors are prone to causing cracks and bubbles in composite materials during the curing process, thereby affecting both the mechanical performance and the overall reliability of the materials. Herein, stretchable interdigital dielectric sensors with flexible substrates and electrodes are designed to conform to complex 3D surfaces, thus enabling embedded nondestructive monitoring of composite curing processes. The sensors obtained can endure 1000 cycles of bending from 0° to 180° and 1000 cycles of stretching at 30% strain while still conforming perfectly to complex 3D surfaces, thus overcoming the inability of traditional curing monitoring sensors to bend. Additionally, sensor integration with an electronic circuit enables real-time data collection and transmission, which makes the device more portable, compact, and lightweight. Moreover, after atmospheric exposure for 5 months, the unit sensitivity of the sensor decreased by only 0.1%, thus demonstrating its excellent reliability and stability. Furthermore, during curing monitoring of the complex three-dimensional surfaces of the Fendouzhe deep-sea submersible, the unit's sensitivity is close to that of conventional planar monitoring equipment, decreasing by only 0.4%. The proposed online nondestructive monitoring technology demonstrates high sensitivity, high monitoring accuracy, and high reliability during surface monitoring, thus enabling long-term curing monitoring under complex nonplanar conditions.

Analyzing Process Types in Nigerian Newspapers Political Headlines Using Systemic Functional Linguistics (SFL) Transitivity Approach

Purpose: This study aims to examine the use of process types in Nigerian political headlines using the transitivity approach within the framework of Systemic Functional Linguistics (SFL). The purpose of the research is to understand how language is used to construct political narratives in Nigerian newspapers, focusing on the different process types—material, mental, relational, verbal, behavioral, and existential—that shape public perception of political events and actors. Methodology: The study adopts a qualitative method, analyzing 50 political headlines from five major Nigerian newspapers: Vanguard, Leadership News, Punch, Daily Trust, and The Guardian Nigeria. The headlines, selected from articles published between January 2024 and September 2024, are categorized and analyzed based on Halliday's transitivity framework. Findings: The findings reveal that material processes are the most frequently used, representing 48% of the headlines, followed by mental (32%), verbal (20%), and relational processes (10%). Existential and behavioral processes were minimally represented. These results suggest that political discourse in Nigeria is predominantly action- and belief-oriented, with a focus on tangible actions and the intentions of political figures. Unique Contribution to Theory, Practice and Policy: This study makes a unique contribution to theory by applying the SFL transitivity framework to Nigerian political headlines, expanding the understanding of how process types reflect political actions, intentions, and relationships. The findings have practical implications for media practitioners and politicians in crafting messages that effectively engage the public, emphasizing actions and beliefs to influence perception. From a policy perspective, the study suggests the need for greater media literacy to enable the public to critically assess political communication and its impact on public discourse.

Electrification or Hydrogen? The Challenge of Decarbonizing Industrial (High-Temperature) Process Heat

The decarbonization of industrial process heat is one of the bigger challenges of the global energy transition. Process heating accounts for about 20% of final energy demand in Germany, and the situation is similar in other industrialized nations around the globe. Process heating is indispensable in the manufacturing processes of products and materials encountered every day, ranging from food, beverages, paper and textiles, to metals, ceramics, glass and cement. At the same time, process heating is also responsible for significant greenhouse gas emissions, as it is heavily dependent on fossil fuels such as natural gas and coal. Thus, process heating needs to be decarbonized. This review article explores the challenges of decarbonizing industrial process heat and then discusses two of the most promising options, the use of electric heating technologies and the substitution of fossil fuels with low-carbon hydrogen, in more detail. Both energy carriers have their specific benefits and drawbacks that have to be considered in the context of industrial decarbonization, but also in terms of necessary energy infrastructures. The focus is on high-temperature process heat (>400 °C) in energy-intensive basic materials industries, with examples from the metal and glass industries. Given the heterogeneity of industrial process heating, both electricity and hydrogen will likely be the most prominent energy carriers for decarbonized high-temperature process heat, each with their respective advantages and disadvantages.

Current development, optimisation strategies and future perspectives for lead-free dielectric ceramics in high field and high energy density capacitors.

To meet the United Nations' sustainable development goal of affordable and clean energy, there has been a growing need for low-cost, green, and safe energy storage technologies. High-field and energy-density capacitors have gained substantial attention from academics and industry, particularly for power electronics, where they will play a key role in optimising the performance of management systems in electric vehicles. The key figure of merit, energy density (Wrec), for high-field applications has dramatically increased year-on-year from 2020 to 2024, as evidenced by over 250 papers, demonstrating ever larger Wrec values. This review briefly introduces the background and principles of high energy density ceramics, but its focus is to provide constructive and comprehensive insight into the evaluation of Wrec, Emax, ΔP, and η, and more importantly, the normalised metrics, Wrec/Emax and Wrec/ΔP in lead-free dielectric ceramics. We also present several optimisation strategies for materials modification and process innovation that have been recently proposed before providing perspectives for the further development of high-field and high-energy density capacitors.

Prediction of catchment efficiency in direct energy deposition using dimensional analysis and machine learning

Direct Energy Deposition (DED) is an additive manufacturing process used to fabricate thin/thick-walled structures and high-value component restorations. As blown powder-based DED gains prominence, catchment efficiency becomes imperative for enhancing material utilization and process effectiveness. This study focuses on predicting catchment efficiency within a DED process by investigating four significant process parameters: laser power, powder feed rate, carrier gas flow rate, and deposition speed. The primary objective is to devise a dimensionless number capable of predicting catchment efficiency based on a combination of these parameters, categorizing efficiency into low, medium, and high regions. This approach reduces the need for resource-intensive experimentation. The experimental validation of the proposed dimensionless number was conducted, showing an error rate of around 8%. Additionally, six machine learning classifier algorithms – Support Vector Machines, K-Nearest Neighbours, Decision Tree, Random Forest, Linear Regression, and Gaussian Naive Bayes – were employed to categorize catchment efficiency zones. Support Vector Machine demonstrated the best performance with a predictive accuracy of 0.98. This study provides a methodology for catchment efficiency prediction, enhancing decision-making and resource optimization, and can be used to optimize process parameters for thin-wall or relatively thin-wall fabrication.

Preparation of high strength and rigidity carbon layer on SiO material surface by dynamic CVD method using gas carbon source C2H2

The main issue in the application of silicon-based negative electrode materials is the inevitable volume expansion, leading to negative electrode material fracture, which severely impacts the performance of batteries. This study employed Chemical Vapor Deposition (CVD) (C2H2@SiO), solid-phase coating method (Pitch@SiO), and liquid-phase coating method (RGFQ@SiO) to coat the surface of SiO materials with a dense amorphous carbon structure. Material property analysis revealed that C2H2@SiO has a relatively small specific surface area (1.8 m2 g−1) and surface carbon increment (2.4 %). It exhibited high reversible specific capacity (1563.4 mAh g−1), high initial Coulombic efficiency (81.45 %), and low volume expansion rate (9.3 %). Mechanical performance testing indicated that the surface carbon layer Young's modulus of C2H2@SiO was the highest (35 GPa), suggesting that using the CVD method to obtain a dense carbon layer can enhance the structural strength of the material. Based on the electrochemical-mechanical coupling theory simulation analysis of the stress during the charge-discharge process of electrode materials, the evolution of concentration and stress field during lithium insertion process was obtained, showing that the coating can further improve the electrochemical and mechanical performance of the negative electrode materials effectively. Additionally, the negative electrode sheets fabricated using sample C2H2@SiO were assembled into 18650 cylindrical batteries, exhibiting excellent cycling performance in 1000 cycles at 25 °C with a capacity retention rate of 85.7 %, along with good rate capability and high/low-temperature performance. The conclusions of this study provide certain guidance for the design and optimization of negative electrode materials for battery electrodes.

Fatigue life prediction of composite materials using strain distribution images and a deep convolution neural network

The damage process of composite materials, such as short fiber-reinforced plastics (SFRP), is complex. Therefore, it is necessary to accurately represent the damage process in fatigue life prediction. Herein, fatigue life prediction was conducted by combining the digital image correlation method, which is a non-destructive testing technique, with a convolutional neural network (CNN), using Xception as the network architecture. High prediction accuracy was obtained when training and testing were performed on the same SFRP specimens. In contrast, using different specimens for training and testing resulted in lower accuracy. This issue may be improved by increasing the number of specimens. The regions of interest in the model were visualized by Gradient-weighted Class Activation Mapping. Notably, the model indicated the breaking point as the region of interest from the early stages of the test. The breaking point was identified at an earlier stage by the CNN than by visual inspection, demonstrating the potential for a new method of damage observation.

Meta-analysis of ecological and phylogenetic biomass maturity metrics

Although a wide variety of biomass sources have been subjected to 16S rRNA gene sequencing, ecological and phylogenetic signatures of maturity have not been identified quantitatively. In this meta-analysis we reanalyzed data from the only published study with publicly available 16S and temperature data (Zhou et al., 2018), and then applied the Zhou results to 705 samples from 13 additional studies. Using the Zhou data, we found that Faith’s alpha diversity index correlated inversely with compost temperature and positively with maturity. We also noted a dramatic shift in the ratios of Bacilliota to Acidobacteriota, Planctomycetota, and Pseudomonadota, as samples cooled below 44 °C (p < 0.001). A negative correlation between Bacillota and Pseudomonadota was also observed in all 705 samples that included compost, sugarcane mill mud, anerobic digestates, and vermicompost. Even in the absence of temperature data for the majority of samples, our meta-analysis shows that microbiomes of diverse residuals converged on similar communities that resemble those of soil, regardless of the starting material or residual management process. We propose that approximately < 0.4 log(Bacillota:Pseudomonadota) and > 43 Faith’s phylogenetic diversity indices are indicative of maturity of diverse biomass materials destined for land application.

Indian philosophy as a precursor of the string theory of consciousness. Part 2

Introduction. The article examines the formation of the Ancient Indian philosophy and its connection to consciousness. The Indian philosophy has come a long way from its onset, in parallel with the Chinese and Ancient Greek philosophy. At the same time, the ideas of some of its branches and schools differ in a number of features. Purpose setting. By the example of the Sankhya school of philosophy, we have explored the evolution of the views of Ancient Indian philosophers on the evolution of the Universe, nature and man. We have put particular emphasis on the concept of consciousness.Methodology and methods of the study. In Sankhya system, the fundamental Prakriti and Purusha principles are identified. Other elements are supplementary. Ancient philosophers laid special emphasis on the three vibrating gunas. These are sattva, rajas, and tamas. We have revealed the functional connections between the gunas. The way they interact, in balance or dominance, determines the entire variety of material and spiritual processes. The evolution of the Universe in the Sankhya interpretation is close to the scientific theory of the Big Bang. The development of nature can be traced through the complication of atoms starting from the influence of a stimulus on unconscious chaos. The result of human evolution is the emergence of consciousness derivatives: intellect, mind and I (Ego). This allows better understanding of the behavioral characteristics of an existing personality. Yoga complements Sankhya system and makes it possible to transform consciousness in a number of states.Results. The analysis was carried out using scientific articles and monographs relatively unknown in the Russian press. Cognitive development occurs in a spiral. The scientific theory of strings appeared two and a half millennia after the emergence of the gunas concept. We have made a number of analogies between Ancient Indian gunas and contemporary string theory. And have substantiated the theory of consciousness not with quantum theory, but with a deeper string theory. The concept of consciousness is supported in line with the scientific paradigm of T. Kuhn. The leading ideas are the ideas about information of D. Chalmers and the physicist J. Wheeler.Conclusion. Thus, the phenomenon of consciousness has a silicon and biological basis. We insist on using the semantic concept of artificial consciousness instead of artificial intelligence. Therefore, between human consciousness and artificial consciousness there may be dangerous risks of dominance of the latter.

THE HERITAGE OF VLADIGEROV – THE MUSEUM UP CLOSE

The preservation, scientific processing and presentation of the rich material and musical heritage of the classic Bulgarian composer Pancho Vladigerov are the main goals of the Pancho Vladigerov House Museum – Sofia. In fulfillment of Vladigerov's will and thanks to the donative gesture of his wife, Mrs. Elka Vladigerova, today the composer’s former home houses his archive, painstakingly collected by him throughout his life. The diversity and uniqueness of the collections in the museum's holdings are a prerequisite for the development of thematic documentary exhibitions, educational programs, and multi-genre concerts, as well as many accompanying events that attract young audiences and introduce them to the composer's personality and the recognition he received as a leading figure in Bulgarian musical culture, as well as on a European and global scale. The team’s work is focused on turning the house that has preserved the unique atmosphere of Vladigerov's home in the capital's Lozenets district at 10 Yakubitsa Street into an attractive cultural center.

Multiscale modeling of metal-hydride interphases—quantification of decoupled chemo-mechanical energies

The quantification of interphase properties between metals and their corresponding hydrides is crucial for modeling the thermodynamics and kinetics of the hydrogenation processes in solid-state hydrogen storage materials. In particular, interphase boundary energies assume a pivotal role in determining the kinetics of nucleation, growth, and coarsening of hydrides, alongside accompanying morphological evolution during hydrogenation. The total interphase energy arises from both chemical bonding and mechanical strains in these solid-state systems. Since these contributions are usually coupled, it is challenging to distinguish via conventional computational approaches. Here, a comprehensive atomistic modeling methodology is developed to decouple chemical and mechanical energy contributions using first-principles calculations, of which feasibility is demonstrated by quantifying chemical and elastic strain energies of key interfaces within the FeTi metal-hydride system. Derived materials parameters are then employed for mesoscopic micromechanical analysis, predicting crystallographic orientations in line with experimental observations. The multiscale approach outlined verifies the importance of the chemo-mechanical interplay in the morphological evolution of growing hydride phases, and can be generalized to investigate other systems. In addition, it can streamline the design of atomistic models for the quantitative evaluation of interphase properties between dissimilar phases and allow for efficient predictions of their preferred phase boundary orientations.

PENGEMBANGAN E-COMIC BERBASIS PROBLEM BASED LEARNING (PBL) MATERI SISTEM EKSKRESI MANUSIA UNTUK MENINGKATKAN HASIL BELAJAR SISWA

This research was conducted because E-comic learning media based on Problem Based Learning material on the human excretory system was not yet available at Lolowau 2 State Junior High School and student learning outcomes did not meet the Minimum Completeness Criteria. The research applied is development research (Development Research) with the four D model. The results of the research obtained an average validity test score of 89.52%, practicality test by teachers 3.50 while students 3.57 and an average effectiveness test score 90.14 so it can be concluded that E-comic learning media can be applied in the learning process of human excretory system material in class Vlll.

Understanding of Wetting Mechanism Toward the Sticky Powder and Machine Learning in Predicting Granule Size Distribution Under High Shear Wet Granulation.

The granulation of traditional Chinese medicine (TCM) has attracted widespread attention, there is limited research on the high shear wet granulation (HSWG) and wetting mechanisms of sticky TCM powders, which profoundly impact the granule size distribution (GSD). Here we investigate the wetting mechanism of binders and the influence of various parameters on the GSD of HSWG and establish a GSD prediction model. Permeability and contact angle experiments combined with molecular dynamics (MD) simulations were used to explore the wetting mechanism of hydroalcoholic solutions with TCM powder. Machine learning (ML) was employed to build a GSD prediction model, feature importance explained the influence of features on the predictive performance of the model, and correlation analysis was used to assess the influence of various parameters on GSD. The results show that water increases powder viscosity, forming high-viscosity aggregates, while ethanol primarily acted as a wetting agent. The contact angle of water on the powder bed was the largest and decreased with an increase in ethanol concentration. Extreme Gradient Boosting (XGBoost) outperformed other models in overall prediction accuracy in GSD prediction, the binder had the greatest impact on the predictions and GSD, adjusting the amount and concentration of adhesive can control the adhesion and growth of granules while the impeller speed had the least influence on granulation. The study elucidates the wetting mechanism and provides a GSD prediction model, along with the impact of material properties, formulation, and process parameters obtained, aiding the intelligent manufacturing and formulation development of TMC.

Effect of Resin Content on the Properties of Roofing Tile for Building Materials

The production process of roofing tile materials uses among other materials thermosetting adhesive resins normally urea formaldehyde (UF), phenol formaldehyde (PF), di-isocyanate (PMDI) at various content mixtures, 3wt%, 5wt%, 7wt%, 9w% and 11wt% with a usual thickness of 6 mm. The fibers, adhesives, and other materials are then placed into a steel mold with the standard dimensions of 400 mm x 400 mm, to be then hydraulically pressed at high pressure and the required temperature. Overall, PMDI synthetic adhesives have better physical and mechanical properties than PF synthetic adhesives, however the thermal properties of UF and PF synthetic adhesives are better than PMDI. The physical properties testing were density, humidity content, absorption of water, thickness inflated and water permeability. The mechanical properties such as modulus of rupture (MOR) and modulus of elasticity (MOE), impact strength and tensile strength are all measured according to JIS A 5908-2003, ASTM D 256-2006a,TIS 535-2556 and ASTM D1037-12.The testing for the thermal conductivity, thermal resistivity and solar reflectance were done according to ASTM C177-2010 and ASTM E 891-87. The type of resin content and adhesive used had a significant impact on the physical, mechanical and thermal properties of the roofing tile materials of showed in the results of the analysis of variance (p &gt;0.05). The produced roofing tile has an improved thermal conductivity and heat insulation which can be a substitute for hazardous asbestos based roofing materials.

Study of thermal stress deformation in hybrid 3D printing and milling process of PEEK material

Hybrid manufacturing can enable rapid production of personalized artificial bones that are made of Polyether-ether-ketone (PEEK) by integrating 3D printing and milling. A main challenge, however, is the thermal stress deformation that arises from the fused deposition process, leading to warping and shrinkage. As a result, the fabrication accuracy is significantly diminished. This work aims to address this challenge by investigating the thermal stress deformation behavior of PEEK in hybrid manufacturing. The main contributions of this work, therefore, include the development of a model for this thermal deformation behavior, and the identification of key parameters such as cross-section length ( Ls), printed layer thickness ( Lh), and current workpiece height ( He). Further, experiments are conducted based on response surface methodology (RSM) to explore the relationships between temperature variation rate (Δ T), end surface height difference (Δ S), and length shrinkage rate (Δ L) with critical hybrid processing parameters. Optimal parameter combinations are then identified. Our experiments demonstrate that the proposed methods effectively reduce the effects of warping and shrinkage.

Bridging length and time scales in predictive simulations of thermo-mechanical processes

Abstract This work introduces a theoretical formulation and develops numerical methods for finite element implementation of the formulation so as to extend the Concurrent Atomistic-Continuum (CAC) method for modeling and simulation of finite-temperature materials processes. With significantly reduced degrees of freedom, the CAC simulations are shown to reproduce the results of atomically resolved molecular dynamics simulations for phonon density of states, velocity distributions, equilibrium temperature field of the underlying atomistic model, and also the density, type, and structure of dislocations formed during the kinetic processes of heteroepitaxy. This work also demonstrates the need of a mesoscale tool for simulations of heteroepitaxy, as well as the unique advantage of the CAC method in simulation of the defect formation processes during heteroepitaxy.

Phytochemical Constituent and Cumulative or Antagonistic Effects of Crops Plant Organ Combination on Free Radical Scavenging Capacity and Antioxidant Compound Content

Aims: In Burkina Faso, the majority of plant-based recipes are a combination of plant organs from the same or different species. For these recipes’ producers, the aim is to improve efficiency. However, our ethnobotanical surveys have revealed that for some species, efficacy is better when the species is not combined, or when it is combined in small proportions with other species. The aim of this study is to assess the effect of plant organ combination on free radical scavenging activity, phenolic compound content and flavonoid content. Study Design: The work combined harvesting and processing of plant material from September to November 2023, and laboratories analysis from January to March 2024 at Natural Substances Departement of Institut de Recherche en Sciences Appliquées et Technologie, Ouagadougou. Methodology: We prepared two batches of recipes, first combining two species from the same genus, then two species from different genera. The powder of each plant without combination was also used to compare data. Phytochemical screening was first carried out with TLC and LC-MS analysis on each plant extract. We then assessed the phenolic compound content (PCC) using Folin-Ciocalteu method, flavonoid content (FCC) using aluminum chloride test, antioxidant content using TEAC method and free radical scavenging activity using DPPH method, for different batches. Results: Phytochemical constituent in the three species are phenolic compounds, terpenoids and nitrogen derivatives. The results of biological property evaluation suggest that for best efficacy and to obtain a high phenolic compound content, Lippia multiflora leaves should be used separately, or combined in 70% proportions with Lippia alba, then in 50% proportions if the combination is made with Ocimum basilicum. Conclusion: This research has provided relevant results to guide players in the field of traditional medicine and users of herbal remedies.

Efficient Preparation of Metal-Ion Intercalated Vanadium-Based Cathodes for High-Performance Aqueous Zinc-Ion Batteries: Na2V6O16·3H2O as an Example.

The inherent challenges associated with aqueous zinc ion batteries (AZIBs), such as low energy density and slow diffusion kinetics, pose significant obstacles to their widespread adoption as energy storage systems. These limitations mainly stem from the nongreen and complex preparation process of high-quality cathode materials. In this study, we propose an approach utilizing microwave-assisted ball milling to expedite the fabrication of vanadium-based intercalated nanomaterials, aiming at solving the problem of prolonged reaction at high temperatures, which is unavoidable in the preparation of anode materials. Na2V6O16 (NVO) nanorods were synthesized in just 40 min under aqueous solvent conditions. These nanorods exhibit remarkable electrochemical properties, including a high specific capacity of 564 mA h g-1 at 0.1 A g-1 and an excellent cycle life, maintaining 164.2 mA h g-1 after 5000 cycles at 5 A g-1. Additionally, the incorporation of Na+ into the electrolyte effectively mitigates the stripping of Na+ and the deposition of Zn dendrimers from NVO, further contributing to enhanced cycling stability. The findings of this study offer a promising approach to the rapid and efficient synthesis of high-quality ZIB cathode materials.

An Analysis of the Conceptual Function of Facing the Sea with Spring Blossoms

Since Facing the Sea with Spring Blossoms has attracted widespread attention, many scholars have formed four interpretations from various perspectives, namely: the poem conveys the love of life and the pursuit of happiness; the poem is a deathbed poem, expressing the poet's despair of earthly life; the poet is a sad and bitter soul in pursuit of happiness; the poem is the poet's choice between “existence or destruction.” Poetry is the poet's choice between "existence or destruction," and he finally chooses to give up earthly happiness. Systemic functional grammar was founded by Halliday, who believed that language has three meta-functions: conceptual function, communicative function, and textual function, which are linked to the transitivity system, mood system, and thematic system. Since its inception, Systemic Functional Grammar has been applied to many text analyses, demonstrating its powerful interpretative power. Guided by this theory, the author conducted a conceptual-functional analysis of Facing the Sea with Spring Blossoms and found that there are 25 processes in the poem, including nine material processes, five mental processes, six relational processes, three verbal processes, and two existential processes. The author analyzed the three types of processes that are more typical in this poem and drew the following conclusions: first, happiness is an important theme for the poet; second, the poem is opened by me (the poet) choosing between two kinds of happiness; third, the poet finally chooses non-earthly happiness, i.e., “I only wish to face the sea, with spring blossoms.”