Material Process Research Articles

Methods for Checking the Reliability of Mathematical Models for Describing Deformation Processes of Polymer Textile Materials

Methods for Checking the Reliability of Mathematical Models for Describing Deformation Processes of Polymer Textile Materials

A Comparative Analysis of American and Vietnamese Presidents' Speeches: A Systemic Functional Grammar Perspective

This study presents a comparative analysis of the inaugural speeches of U.S. President Joe Biden and Vietnamese President To Lam, utilizing Michael Halliday's Systemic Functional Grammar (SFG) framework. By examining the Ideational (Transitivity), Interpersonal (Modality), and Textual (Texture and Cohesion) metafunctions, the study reveals how each leader's linguistic choices mirror the distinct political and cultural contexts of their respective nations. Joe Biden’s speech underscores the urgency of immediate action and crisis management, employing Material Processes to stress the importance of unity and national recovery. Conversely, To Lam's speech is rooted in long-term nation-building and the leadership of the Communist Party, with a focus on Relational Processes to reinforce collective responsibility and national unity. The Modality analysis demonstrates Joe Biden’s use of High Modality to convey decisiveness and transparency, aligning with American expectations for solid and clear commitments. In contrast, To Lam emphasizes collective duty and the Party's enduring leadership, reflecting Vietnam's socio-political ethos. Additionally, both speeches use Theme-Rheme structures and lexical repetition to ensure textual cohesion, though their cultural and ideological differences lead to distinct rhetorical approaches. By deepening our understanding of how political leaders use language to shape identities, communicate visions, and influence public perception, this study contributes to the broader field of political communication, offering insights into the strategic use of language across different cultural contexts.

Boosting Electrochemical Degradation of Water Pollutants Using Sulfur‐Rich Porous Polyimide‐Derived Laser‐Induced Graphene Catalytic Membrane

Water pollution is an inevitable concern associated with technological advancement. To address this problem, it is necessary to significantly shorten the manufacturing process of porous materials while enabling effective pollutant removal. Herein, a facile, rapid, and scalable approach is reported to obtain sulfur‐doped hierarchically porous laser‐induced graphene (S‐LIG) as a catalytic membrane with three‐dimensional networks by localized laser irradiation, along with possible adsorption and electrochemical degradation mechanisms for pollutant removal. S‐LIG is derived from sulfur‐containing porous polyimide film which is prepared via thermally induced phase separation followed by stepwise thermal imidization. Methylene blue (MB) adsorption behavior on the S‐LIG membrane closely fits the pseudo‐second‐order and Freundlich isotherm models, suggesting a complex sorption mechanism, including both strong chemical interaction and physical adsorption. Furthermore, S‐doping enhances catalytic activity for generating reactive oxygen species (ROS), aiding MB degradation via indirect oxidation, and improves direct oxidation on the anode by accelerating electron transfer at the electrodes. This results in a stable 93% MB degradation at a low 1.5 V after 24 h. Additionally, the impact of solution pH reveals that electrostatic attraction forces under basic conditions and the high generation of ROS under acidic conditions favor adsorption and electrochemical oxidation.

Real-Time Modeling for Design and Control of Material Additive Manufacturing Processes

The use of digital twin and shadow concepts for industrial material processes has introduced new approaches to bridge the gap between physical and cyber manufacturing processes. Consequently, many multidisciplinary areas, such as advanced sensor technologies, material science, data analytics, and machine learning algorithms, are employed to create these hybrid systems. Meanwhile, new additive manufacturing (AM) processes for metals and polymers, based on emerging technologies, have shown promise for the manufacturing of sophisticated parts with complex geometries. These processes are undergoing a major transformation with the advent of digital technology, hybrid physical-data-driven modeling, and fast-reduced models. This study presents a fresh perspective on hybrid physical-data-driven and reduced order modeling (ROM) techniques for the digitalization of AM processes within a digital twin concept. The main contribution of this study is to demonstrate the benefits of ROM and machine learning (ML) technologies for process data handling, optimization/control, and their integration into the real-time assessment of AM processes. Therefore, a novel combination of efficient data-solver technology and an architecturally designed neural network (NN) module is developed for transient manufacturing processes with high heating/cooling rates. Furthermore, a real-world case study is presented, showcasing the use of hybrid modeling with ROM and ML schemes for an industrial wire arc AM (WAAM) process.

Investigation of etch rate distribution by micro-hemisphere for the anisotropic wet etching of Ga-face gallium nitride crystal

The Ga-face gallium nitride (GaN) crystal has recently attracted significant research interest in the micro/nano device due to its exceptional properties. Therefore, exploring low-cost and high-efficiency anisotropic wet etching processes for GaN material is essential. This research investigates the measurement of the overall anisotropic etching rates by introducing a novel micrometer-level hemispherical structure. For the first time, we report the full anisotropic etching rate distribution for Ga-face GaN crystal planes based on the etched results of the micro hemisphere and wagon-wheel structure specimen. The etching experiments were carried out in 85 %wt H₃PO₄ etchant at 130°C and 150°C. The etching result of Ga-face GaN crystal orientations displays a hexagonal symmetry pattern. In addition, the overall etch rates measurement enables the identification of the crystal planes with maximum and minimum etch rates at different temperatures, and the experiment also shows the etch rate of primary crystallographic orientations, such as +c-plane, m-plane, and a-plane. Finally, the atomic structures of GaN crystallographic planes are analyzed to explain the anisotropy in the etching process on different crystal zones by the step-flow mechanism. The resulting etch rate database allows the numerical simulation of the etch front and helps understand the etching mechanism of the GaN crystal.

Simple three-stage control scheme achieving interrupt-free integrated polarization stabilization

It is a long-outstanding challenge to achieve low-complexity interrupt-free integrated polarization stabilization of infinitely changing light. Integrated phase shifters have finite tuning range and experience abrupt switching or reset when reaching the limits of their tuning ranges during the polarization stabilization process. We propose a three-stage interrupt-free integrated polarization stabilization scheme with nested electronic-photonic loops (NEPL) and dimensionality reduction (DR) method. Based on the NEPL structure, only three Mach-Zehnder interferometer (MZI) stages are needed to achieve interrupt-free polarization stabilization scheme. The input state is first constrained into a predetermined range using a nested loops with the first MZI stage and then processed by regular two-stage scheme. Throughout the entire operation, all phase shifters are tuned continuously without any pause, abrupt switching or reset. Furthermore, a DR method is introduced to reduce the control complexity and enhance control speed and accuracy of the regular two-stage scheme. A detailed analysis of the proposed design is provided, and its effectiveness is verified using electronic-photonic co-simulation in the Cadence platform. This scheme consists of only phase shifters, couplers and photodiodes (PDs) with simple electronic controllers, and can be implemented in various material systems and process platforms. To the best of our knowledge, this is the first three-stage interrupt-free polarization stabilization scheme reported in the literature.

Visualizing Triplet Energy Transfer in Organic Near-Infrared Phosphorescent Host-Guest Materials.

Limited by the energy gap law, purely organic materials with efficient near-infrared room temperature phosphorescence are rare and difficult to achieve. Additionally, the exciton transition process among different emitting species in host-guest phosphorescent materials remains elusive, presenting a significant academic challenge. Herein, using a modular nonbonding orbital-π bridge-nonbonding orbital (n-π-n) molecular design strategy, we develop a series of heavy atom-free phosphors. Systematic modification of the π-conjugated cores enables the construction of a library with tunable near-infrared phosphorescence from 655 to 710 nm. These phosphors exhibit excellent performance under ambient conditions when dispersed into a 4-bromobenzophenone host matrix, achieving an extended lifetime of 11.25 ms and a maximum phosphorescence efficiency of 4.2 %. Notably, by eliminating the interference from host phosphorescence, the exciton transition process in hybrid materials can be visualized under various excitation conditions. Spectroscopic analysis reveals that the improved phosphorescent performance of the guest originates from the triplet-triplet energy transfer of abundant triplet excitons generated independently by the host, rather than from enhanced intersystem crossing efficiency between the guest singlet state and the host triplet state. The findings provide in-depth insights into constructing novel near-infrared phosphors and exploring emission mechanisms of host-guest materials.

Enhanced Efficiency of Latent Heat Energy Storage by Inclination

Latent heat storage (LHS) has emerged as a promising solution for addressing the challenges of large-scale and long-term energy storage, offering a clean and reusable system. Being in the developmental stage, and with only limited theoretical predictions being available, there is a need to enhance the efficiency of LHS systems. In this study, we use numerical simulations to study the melting process of a phase-change material (PCM) in a rectangular domain. A significant enhancement in the melt rate of the PCM is found by a simple inclination of the domain, with a 60% increase in melt rate compared to a standard square unit without inclination through enhanced heat transfer. We establish a theoretical relation for the optimal PCM melt rate, based on the inclination angle and the domain aspect ratio, outlining the optimal conditions for the PCM melt rate, which is solely dependent on the domain geometry. We further propose a heat-transfer model that predicts the optimal aspect ratio for achieving the maximum melt rate as a function of the Rayleigh and Prandtl numbers. Published by the American Physical Society 2024

Visualizing Triplet Energy Transfer in Organic Near‐Infrared Phosphorescent Host‐Guest Materials

AbstractLimited by the energy gap law, purely organic materials with efficient near‐infrared room temperature phosphorescence are rare and difficult to achieve. Additionally, the exciton transition process among different emitting species in host–guest phosphorescent materials remains elusive, presenting a significant academic challenge. Herein, using a modular nonbonding orbital‐π bridge‐nonbonding orbital (n‐π‐n) molecular design strategy, we develop a series of heavy atom‐free phosphors. Systematic modification of the π‐conjugated cores enables the construction of a library with tunable near‐infrared phosphorescence from 655 to 710 nm. These phosphors exhibit excellent performance under ambient conditions when dispersed into a 4‐bromobenzophenone host matrix, achieving an extended lifetime of 11.25 ms and a maximum phosphorescence efficiency of 4.2 %. Notably, by eliminating the interference from host phosphorescence, the exciton transition process in hybrid materials can be visualized under various excitation conditions. Spectroscopic analysis reveals that the improved phosphorescent performance of the guest originates from the triplet‐triplet energy transfer of abundant triplet excitons generated independently by the host, rather than from enhanced intersystem crossing efficiency between the guest singlet state and the host triplet state. The findings provide in‐depth insights into constructing novel near‐infrared phosphors and exploring emission mechanisms of host–guest materials.

Optimized Tungsten Disulfide via Pyrolytic Deposition for Improved Zn‐Ion Batteries

AbstractThe selection and optimization of cathode materials are crucial for enhancing the performance of aqueous zinc‐ion batteries. In this work, different active materials were created by combining Sulfur powder and polydopamine in four different mass ratios. The novel N‐doped carbon/WS2 is obtained. Thanks to the optimization of the dopamine‐carrying tungsten ion precursor and Sulfur powder (1 : 2, 1 : 4, 1 : 6 and 1 : 8), the four samples exhibited different morphology. The N−C/WS2‐6‐based zinc ion batteries with the highest specific capacity, 120.0 mAh/g in the first discharge at 2.0 A/g, and 78.0 mAh/g after 2500 cycles, with a capacity retention of 65 %, had a relatively good overall performance, according to the results. The reaction kinetics characteristics of the N−C/WS2‐6 cathode reveal that diffusion has a significant impact on the processes in the aqueous zinc ionic material N−C/WS2‐6.

Advances in Catalytic Hydrogenation of Liquid Organic Hydrogen Carriers (LOHCs) Using High‐Purity and Low‐Purity Hydrogen

AbstractLiquid organic hydrogen carriers (LOHCs) are emerging as a promising solution for global hydrogen logistics. The LOHC process involves two primary chemical reactions: hydrogenation for hydrogen storage and dehydrogenation for hydrogen reconversion. In the exothermic hydrogenation reaction, hydrogen‐lean compounds are converted to hydrogen‐rich compounds, storing hydrogen from various sources such as water electrolysis, fossil fuel reforming, biomass processing, and industrial by‐products. Conversely, hydrogen is extracted from hydrogen‐rich compounds through an endothermic dehydrogenation reaction and supplied to several hydrogenation utilization offtakers. This review article discusses the development trends in catalytic hydrogenation processes for various LOHC materials, including benzene, toluene, naphthalene, biphenyl‐diphenylmethane, benzyltoluene, dibenzyltoluene, and N‐ethylcarbazole. It introduces references for catalytic hydrogenation processes utilizing both high‐purity and low‐purity (alternatively, mixed) hydrogen feedstocks, with particular emphasis on low‐purity hydrogen applications. The direct storage of hydrogen with minimal purification, using by‐product hydrogen and mixed hydrogen from hydrocarbon and biomass reforming, is crucial for the economic viability of this hydrogen carrier system.

The Influence of Fibers from Domestic Laundry Wastewater on the Clogging Process of a Filter

This study presents the impact of the size and shape of particles in laundry wastewater on the clogging process of a porous material. Clogging can be defined as a mechanical limitation of flow through porous media. The process of mechanical clogging was investigated in this study. The research was conducted in laboratory conditions in a filter column filled with glass beads whose diameter corresponded to coarse sand. The results reveal the influence of graywater quality on filter hydraulic conductivity and bed clogging, showing the impact of fiber particles in wastewater (sewage from home laundry) on the clogging process in soil. The results confirm that fiber particles significantly reduce filter permeability, particularly due to the formation of a filter cake. As analyzed in this paper, the distribution of quantitative data on particles of different sizes found in laundry wastewater indicates that they mainly accumulate in the upper layer, where particles with fiber lengths ranging from 0 to 1600 µm can be found. The average length of the fibers decreased with increasing depth. At a depth of approximately 10 cm, fibers with dimensions in the range of 0 to 100 μm were predominantly observed.

Numerical simulation of strengthening/deterioration and damage development of cementitious materials under sulfate attack environment

Cementitious materials exposed to sulfate environments often suffer from the combined effects of external sulfate attack and dry wet cycling. In order to predict the long-term performance of cement-based materials in sulfur rich environments, this paper aims to establish a numerical model that can reasonably characterize the degradation process of cementitious materials in sulfate environments. Using this model, we can address durability problems common to cementitious materials in real sulphate environments, such as determining the degree of corrosion, predicting the durability life of materials, and calculating the time to failure. The model consists of three parts: transportation, chemical reactions, and material damage. We establish the degradation model for cement-based materials in sulfate environments by considering ion diffusion, water convection, chemical reactions, accumulation of corrosion products, and the development of material strengthening/degradation. Compared with existing sulfate corrosion models, this model not only considers ettringite, but also takes into account the volume changes of gypsum formation, calcium leaching, and salt crystallization precipitation, which can more reasonably simulate the sulfate corrosion process in real environments. The model can reasonably simulate the distribution pattern of ion concentration, hydration products and corrosion products in the cementitious material, and on this basis calculate the porosity of the cementitious material. In order to make the simulation results more applicable to experimental and non-destructive testing results, the model uses easily obtainable relative dynamic elastic modulus to evaluate the degree of material strengthening/degradation and predict the durability life of the material.

Analisis Transitivitas pada Penokohan dalam Cerpen Bas les masques dan Délivrance: Kajian Linguistik Sistemik Fungsional

This study aims to describe the characterizations in the “Bas les masques” and “Délivrance” short stories based on the transitivity process and describe the characterization techniques used in the “Bas les masques” and “Délivrance” short stories. This research uses a descriptive approach with a qualitative method. The data are the clauses explaining characterizations in the short stories “Bas les masques” by Benoît Broyart and “Délivrance” by Jean-Paul Nozière. The data collection of this research is carried out by scrutinizing and note-taking techniques. The data are analyzed using the transitivity theory in Halliday’s Systemic Functional Linguistics and Nurgiyantoro’s character depiction theory. The results of this study indicate that the characterization in these two stories are dominantly described by material process, i.e. 8 clauses (35%) in the “Bas les masques” short story and 9 clauses (39%) in the “Délivrance” short story. The processes that are not found are behavioral process because the characters’ behavior cannot be explained from their own perspective. Regarding the character depiction techniques, the two short stories both use conversation techniques and other character’s reaction techniques. Apart from that, there is also the stream of consciousness technique which is only used in “Bas les masques” short story and the character reaction technique which is only used in “Délivrance” short story. From the results of this research, it can be concluded that transitivity analysis can support the study of characterization in literary works because the character's personality can be represented through their experiences in the story.

Machine learning approaches for predicting impact sensitivity and detonation performances of energetic materials

Excellent detonation performances and low sensitivity are prerequisites for the deployment of energetic materials. Exploring the underlying factors that affect impact sensitivity and detonation performances as well as exploring how to obtain materials with desired properties remains a long-term challenge. Machine learning with its ability to solve complex tasks and perform robust data processing can reveal the relationship between performance and descriptive indicators, potentially accelerating the development process of energetic materials. In this background, impact sensitivity, detonation performances, and 28 physicochemical parameters for 222 energetic materials from density functional theory calculations and published literature were sorted out. Four machine learning algorithms were employed to predict various properties of energetic materials, including impact sensitivity, detonation velocity, detonation pressure, and Gurney energy. Analysis of Pearson coefficients and feature importance showed that the heat of explosion, oxygen balance, decomposition products, and HOMO energy levels have a strong correlation with the impact sensitivity of energetic materials. Oxygen balance, decomposition products, and density have a strong correlation with detonation performances. Utilizing impact sensitivity of 2,3,4-trinitrotoluene and the detonation performances of 2,4,6-trinitrobenzene-1,3,5-triamine as the benchmark, the analysis of feature importance rankings and statistical data revealed the optimal range of key features balancing impact sensitivity and detonation performances: oxygen balance values should be between −40% and −30%, density should range from 1.66 to 1.72 g/cm3, HOMO energy levels should be between −6.34 and −6.31 eV, and lipophilicity should be between −1.0 and 0.1, 4.49 and 5.59. These findings not only offer important insights into the impact sensitivity and detonation performances of energetic materials, but also provide a theoretical guidance paradigm for the design and development of new energetic materials with optimal detonation performances and reduced sensitivity.

Experimental and calculation investigations of the photocatalytic selective and performance for CO2 reduction by cobalt-doped Bi4O5Br2 nanosheets

This study delves into the photocatalytic process of an innovative Co-doped Bi4O5Br2 material synthesized through a straightforward process. Experimental and theoretical findings corroborate that cobalt doping remarkably enhances the CO2 reduction capability of Bi4O5Br2 catalysts under visible light. Findings indicate that Co-doped Bi4O5Br2 exhibits substantial advantages over its pristine counterpart in photocatalytic CO2 reduction. Notably, the catalyst with 4 at.% Co doping demonstrates the highest photocatalytic CO2 reduction efficiency, achieving CO and methane production activities of up to 9.46 and 0.20 μmol/g/h, respectively. Furthermore, the low activation energy for CO2 reduction in Co-doped Bi4O5Br2, as indicated by reaction pathways calculations, facilitates the process. Detailed experimental results reveal that Co incorporation does not alter the surface morphology or the crystalline phase of the photocatalyst. The superior efficiency of Co-doped Bi4O5Br2 is attributed to multiple factors: a narrow band gap, expanded visible light absorption spectrum, greater absorption intensity within the visible range, and enhanced separation efficiency of photogenerated electrons and holes compared to pristine Bi4O5Br2. This highlights the practical application of Co-doped Bi4O5Br2 for enhancing photocatalytic performance, supporting future advancements in solar energy utilization and the creation of high-value chemical products.

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.

Microstructure evolution process and multi-scale deterioration mechanism model of graphite tailings cement-based materials subjected to high temperature

This manuscript investigated the thermal stability, crystal reconstruction and microstructure evolution of graphite tailing cement mortar subjected to high temperature. Simultaneously, a computational model for heat transfer and degradation considering chemical transformations had been developed by combining multiscale mechanics with the laws of thermodynamics. The results show that 20% graphite tailings can increase the tobermorite crystal content under high temperature and inhibit its transformation into disordered form. Furthermore, the dormant active SiOx in graphite tailing is gradually activated under the action of high temperature, which catalyzes and induces the formation of more belite crystal in graphite tailing cement mortar. Additionally, 40% graphite tailing can promote the generation of anorthite by the induction of high temperature. Finally, a new multi-scale model considering the chemical transformation is established to calculate the high-temperature degradation process of graphite tailing cement mortar.

Translational and rotational drives of micro-droplets of nematic liquid crystal with chiral dopant

The translational and rotational control of liquid crystal micro-droplets by electric fields has been explored for the future use in MEMS and lab-on-a-chip devices. The liquid crystal droplets are generated by the phase transition process of a liquid crystalline material, 4-n-4’-pentylcyanobiphenyl (5CB), from the isotropic to the nematic phase, and are thus suspended in the isotropic phase of 5CB. The addition of a chiral dopant to 5CB induces the symmetry breaking of the molecular orientation configuration within the droplet, leading to the formation of helical molecular orientation configurations. The helical configuration of the molecular orientation field is the key to enabling the translational and rotational drives of the droplet. Under electric fields, the translational drive of the droplets occurs in a direction perpendicular to both the electric field and the helical axis, and the rotational drive of the droplets occurs to align the helical axis perpendicular to the electric field. Finally, we propose the method for 2D and 3D manipulation of the droplets by combining the translational and rotational drives.

Effect of Fin Configuration on the Early Stage of the Melting Process of a Phase Change Material

Thermal storage systems are essential for optimizing energy resource utilization, particularly in the current context where sustainability and efficiency are critical. Phase Change materials (PCMs) offer a promising solution for improving thermal management efficiency without additional power consumption. Considering that the low thermal conductivity of phase change materials (PCMs) is a limiting factor for heat transfer, this study employs the enthalpy-porosity method to analyze the melting characteristics of a high-Prandtl number PCM. Additionally, this study investigated the effect of varying the number of fins in the heat sink on the heat transfer rate. The material melting process was modeled by considering buoyancy effects and treating the flow as incompressible, Newtonian, transient, and laminar. Lauric acid was selected as the working material with temperature-dependent properties that were incorporated into the simulations for greater accuracy. Three different heat sink configurations were analyzed, varying the number of fins from 5 to 10 and their lengths from 0.02 meters to 0.04 meters. The objective was to optimize the cooling performance using aluminum, which was selected for its excellent balance of lightweight properties and high thermal conductivity. This analysis aimed to assess how these variations in the fin count and dimensions affect the overall heat dissipation efficiency and thermal management of the system. The inclusion of a finned heat sink within a heat exchanger has demonstrated significant efficiency, particularly in regions with substantial boundary layer development, resulting in enhanced heat transfer. These findings highlight the effectiveness of using finned heat sinks in these regions. However, an interesting observation emerged regarding the effect of increasing the number of fins over long periods. Although initially beneficial, a larger number of fins eventually led to a reduced performance over time, notably affecting the thermal storage capacity and molten liquid mass production. Additionally, this study elucidates the influence of natural convection on thermal boundary layer development, highlighting the complexity of the heat transfer processes.