Materials Science Research Articles

Legal Protection of Copyright in Digital Film Piracy Cases in Indonesia (Case Study: Piracy of Keluarga Cemara Film)

Technological advancements in the Globalization 4.0 era, along with the rise of the internet, are perceived as progress that brings both positive and negative consequences. One of the negative effects is the facilitation of crimes, particularly in providing unrestricted access to individuals to commit copyright violations on film works for personal gain. This issue is highlighted in the ruling of Case Number 762/Pid.B/2020/PN-Jmb. This study utilizes a normative juridical approach by examining literature or secondary data as the primary research material, reviewing laws and literature related to the topic under investigation. The research findings indicate that the case was resolved through the Jambi District Court (litigation), where Aditya Fernando Phasyah was found guilty of infringing the exclusive rights of PT Visinema Pictures, the copyright holder of the Keluarga Cemara film. He was sentenced to 1 year and 2 months of imprisonment and fined Rp. 500,000,000.00 (five hundred million rupiah).

Koncepto turinio aprašymas remiantis kategorijos analize: koncepto „miesčioniškumas“ atvejis

The article discusses how different types of material can be used for concept content analysis. The analysis was based on the content associated with the category of philistinism and examples of conceptual metaphors of philistinism. The research conducted shows that this type of research material allows us to see a greater variety of features associated with the spoken concept and to reveal more nuances of the concept of philistinism associated with the worldview of the Lithuanian language. The analysis of the examples of verbalisation of the category of philistinism leads to the conclusion that this phenomenon of non-linguistic reality can be described as a combination of several mutually supporting features. The results of this analysis are complemented by a description of the actualisation of conceptual metaphors of philistinism in language. Significant features of the concept of philistinism are fear of change, emphasis on comfort and convenience, bad taste, lack of progress, stagnation and dormancy.

Digital Teaching Materials of Logical Thinking - Oriented Exposition Text for X Graders of SMA/MA/SMK

This research aims to develop a logical thinking-oriented exposition digital teaching material product that is feasible and effective for Indonesian Language learning in grade X students of SMA/MA/SMK. This research uses a research and development method (Research and Development) with the ADDIE (Analysis Design Development Implementation Evaluation) model. Data collection in the study was carried out and analyzed descriptively, both quantitative and qualitative. The result of the design and development of this digital teaching material is a digital module in the form of pdf and a Flipbook consisting of a cover, concept map, learning objectives, until author biodata. It also contains materials in videos to practice listening, reading and writing that can be accessed in youtube by scanning the link. The results of product validation by language, material and media validators and practitioners stated that the digital teaching materials of logical thinking-oriented exposition texts for SMA/MA/SMK with a result of 80.79% mean "Feasible" to use. The results of the implementation of digital teaching materials for logical thinking-oriented exposition texts for 63 grade X students at SMAN 1 Gantar, SMAN 1 Gantar and MA Ma'had al-Zaytun, showed that there was a significant development between student learning outcomes before and after the use of digital teaching materials after being assessed using the T-Test (Paired sample Test), meaning "effective" for learning exposition text materials. Thus, digital teaching materials for logical thinking-oriented exposition texts for teachers and students of class X SMA/MA/SMK are feasible and effective in learning.

Chiral Polar Bifunctional Polyimide Enantiomers for Asymmetric Photo- and Piezo-catalysis.

Chiral catalysts for asymmetric catalysis represent a crucial research focus in chemistry and materials science. However, a few cases about chiral-dependent photocatalysts primarily focus on plasmonic noble metals. Particularly, developing chiral nano-catalysts that can be driven by mechanical energy remains in the blank stage. Herein, organic polymer-based enantiomers, chiral polar polyimide (PI) microspheric nano-assembly are synthesized as novel bifunctional catalysts for asymmetric photocatalysis and piezocatalysis. The PI catalyst enantiomers present enantioselectivity towards left- and right-circularly polarized light, demonstrating chiral-dependent H2O2 photoproduction. Interestingly, enantioselectivity of the catalyst reverses under irradiation of different bands, presenting tunability in the interaction between chiral catalysts and circularly polarized light. For the first time, enantioselective piezocatalytic behavior is demonstrated by the chiral polar PI catalysts. They show remarkable chiral preference for asymmetric Diels-Alder reaction and enantioselective conversion of tyrosine substrates under ultrasonic vibration. The findings provide a new perspective into exploring metal-free chiral catalysts and their asymmetric catalysis applications across multiple energy forms.

More quantum chemistry with fewer qubits

Quantum computation is one of the most promising new paradigms for the simulation of physical systems composed of electrons and atomic nuclei, with applications in chemistry, solid-state physics, materials science, and molecular biology. This requires a truncated representation of the electronic structure Hamiltonian using a finite number of orbitals. While it is, in principle, obvious how to improve on the representation by including more orbitals, this is usually unfeasible in practice (e.g., because of the limited number of qubits available) and severely compromises the accuracy of the obtained results. Here, we propose a quantum algorithm that improves on the representation of the physical problem by virtue of second-order perturbation theory. In particular, our quantum algorithm evaluates the second-order energy correction through a series of time-evolution steps under the unperturbed Hamiltonian. An important application is to go beyond the active-space approximation, allowing to include corrections of virtual orbitals, known as multireference perturbation theory. Here, we exploit the fact that the unperturbed Hamiltonian is diagonal for virtual orbitals and show that the number of qubits is independent of the number of virtual orbitals. This gives rise to more accurate energy estimates without increasing the number of qubits. Moreover, we demonstrate numerically for realistic chemical systems that the total runtime has highly favorable scaling in the number of virtual orbitals compared to previous studies. Numerical calculations confirm the necessity of the multireference perturbation theory energy corrections to reach accurate ground-state energy estimates. Our perturbation theory quantum algorithm can also be applied to symmetry-adapted perturbation theory. As such, we demonstrate that perturbation theory can help to reduce the quantum hardware requirements for quantum chemistry. Published by the American Physical Society 2024

Chiral Polar Bifunctional Polyimide Enantiomers for Asymmetric Photo‐ and Piezo‐catalysis

Chiral catalysts for asymmetric catalysis represent a crucial research focus in chemistry and materials science. However, a few cases about chiral‐dependent photocatalysts primarily focus on plasmonic noble metals. Particularly, developing chiral nano‐catalysts that can be driven by mechanical energy remains in the blank stage. Herein, organic polymer‐based enantiomers, chiral polar polyimide (PI) microspheric nano‐assembly are synthesized as novel bifunctional catalysts for asymmetric photocatalysis and piezocatalysis. The PI catalyst enantiomers present enantioselectivity towards left‐ and right‐circularly polarized light, demonstrating chiral‐dependent H2O2 photoproduction. Interestingly, enantioselectivity of the catalyst reverses under irradiation of different bands, presenting tunability in the interaction between chiral catalysts and circularly polarized light. For the first time, enantioselective piezocatalytic behavior is demonstrated by the chiral polar PI catalysts. They show remarkable chiral preference for asymmetric Diels‐Alder reaction and enantioselective conversion of tyrosine substrates under ultrasonic vibration. The findings provide a new perspective into exploring metal‐free chiral catalysts and their asymmetric catalysis applications across multiple energy forms.

Three-Dimensional Morphological Study of MnTe-like Structures by Assessment of Tortuosity Tensor Using Computational Fluid Dynamics

This paper focuses on a morphological study of the MnTe-like structures, carried out by the evaluation of the tortuosity tensor and other related parameters using a computational fluid dynamics approach recently developed by our research group. The present work focuses on all possible crystals—existing or not developed yet—having the same structure as that of the manganese telluride. This analysis provides new information not present yet in the open literature. The motivation behind this study lies in the importance of this type of structure in physics and material science. In particular, the structures investigated are anisotropic and bi-disperse, with two independent geometrical parameters controlling the structure shape: the ratio of the particle diameters (r1) and the normalised inter-particle distance (r2). Exploiting this fact, several different structures of the same family are created, changing these two parameters independently, also allowing inter-penetration of particles to enlarge the study’s applicability. The results are primarily obtained in terms of the tortuosity tensor, needed to catch and quantify the anisotropy of the structures. Then, other morphological parameters, such as connectivity, principal diffusion directions, and anisotropy factors, are evaluated, obtaining in this way a novel morphological characterisation of the structure. It is found that high values of tortuosity are observed at lower and higher values of {r1, r2}, which means that there exists a minimum value between them. Additionally, the anisotropy factor is found to be higher at lower values of {r1, r2} and lower at higher ones. This is in accordance with the fact that, as the inter-particle distance and the ratio between particle diameters increase, the structure enlarges, which implies a lower influence of the particle distribution and, thus, a gradually more isotropic structure.

Development of optimized ensemble machine learning-based prediction models for wire electrical discharge machining processes

This paper proposes development of optimized heterogeneous ensemble models for prediction of responses based on given sets of input parameters for wire electrical discharge machining (WEDM) processes, which have found immense applications in many of the present-day manufacturing industries because of their ability to generate complicated 2D and 3D profiles on hard-to-machine engineering materials. These ensembles are developed combining predictions of the three base models, i.e. random forest, support vector machine and ridge regression. These three base models are first framed utilizing the training datasets, providing predictions for all the responses under consideration. Based on these predictions, two optimization problems are formulated for each of the responses, while minimizing root mean squared error and mean absolute error, for subsequent development of two optimized ensembles whose predictions are the weighted sum of the predictions of the base models. The prediction performance of all the five models is ascertained through nine statistical metrics, after which a cumulative quality loss-based multi-response signal-to-noise (MRSN) ratio for each model is computed, for each of the responses, where a higher MRSN ratio indicates greater accuracy in prediction. This study is conducted using two experimental datasets of WEDM process. Overall, the optimized ensemble models having higher MRSN ratios than the base models are indicated to deliver better prediction accuracy.

Comparative In Vivo Biocompatibility of Cellulose-Derived and Synthetic Meshes in Subcutaneous Transplantation Models.

Despite the increasing interest in cellulose-derived materials in biomedical research, there remains a significant gap in comprehensive in vivo analyses of cellulosic materials obtained from various sources and processing methods. To explore durable alternatives to synthetic medical meshes, we evaluated the in vivo biocompatibility of bacterial nanocellulose, regenerated cellulose, and cellulose nanofibrils in a subcutaneous transplantation model, alongside incumbent polypropylene and polydioxanone. Notably, this study demonstrates the in vivo biocompatibility of regenerated cellulose obtained through alkali dissolution and subsequent regeneration. All cellulose-derived implants triggered the expected foreign body response in the host tissue, characterized predominantly by macrophages and foreign body giant cells. Porous materials promoted cell ingrowth and biointegration. Our results highlight the potential of bacterial nanocellulose and regenerated cellulose as safe alternatives to commercial polypropylene meshes. However, the in vivo fragmentation observed for cellulose nanofibril meshes suggests the need for measures to optimize their processing and preparation.

A tutorial review on solid oxide fuel cells: fundamentals, materials, and applications

AbstractSolid oxide fuel cells (SOFCs) are recognized as a clean energy source that, unlike internal combustion engines, produces no CO2 during operation when H2 is used as a fuel. They use a highly efficient chemical-to-electrical energy conversion process to convert oxygen and hydrogen into electricity and water. They can provide smaller-scale power for transportation (e.g., cars, buses, and ships) and be scaled up to provide long-term energy for an electrical grid, making SOFCs a promising, clean alternative to hydrocarbon combustion. Conventional SOFCs faced challenges of high operating temperatures, high cost, and poor durability. Research into advanced cathode, anode, electrolyte, and interconnect materials is providing more insight into the ideal structural and chemical properties that enable the commercialization of highly stable and efficient intermediate temperature (IT) SOFCs. In this paper, we discuss the functional properties of the cathode, anode, electrolyte, and interconnectors for IT-SOFCs. The performance of SOFCs depends not only on the materials used but also on the optimization of operating conditions to maximize efficiency. The voltaic, thermodynamic, and fuel efficiency of SOFCs is presented.

Improvement of Capacitive Accelerometers: Integrating Modeling, Electrode Design, Signal Processing, and Material Selection

Abstract This work offers a thorough method for integrating advanced modeling, electrode design, signal processing, and material selection techniques to maximize the performance of capacitive accelerometers. Key performance measures, including noise reduction, sensitivity, and range, can be systematically analyzed and simulated to forecast how design decisions would affect the overall behavior of the sensor. Advanced electrode designs greatly increase capacitance, which results in more precise and trustworthy sensor readings. These designs include optimizing the shape and using high-permittivity materials. Furthermore, to guarantee that the accelerometer's output precisely represents actual motion even in noisy surroundings, noise reduction strategies including filtering and digital signal processing methods are essential. Additionally, calibration is emphasized as a critical step in preserving measurement accuracy over time and accounting for environmental changes and sensor drift. The choice of material, with an emphasis on thermally stable and high-permittivity materials, is crucial in determining the capacitance, sensitivity, and durability of the sensor. The study offers a paradigm for the creation of capacitive accelerometers that perform better across a variety of applications by striking a balance between these variables.

A hybrid approach for Bengali sentence validation

Bengali is the official language of Bangladesh and is widely used in Bangladesh and West Bengal in India. Due to the growing accessibility of the internet and smart devices, the use of digital text material and documents in Bengali is growing with time. An automated Bengali Sentence Validation System is proposed in this study to effectively determine the correctness of sentences in such extensively available Bengali content. As far as we know, no substantial work has been done in the field of Bengali Sentence Validation utilizing deep learning approaches. Due to the lack of linguistic resources, sophisticated Natural Language Processing tools, and benchmark datasets, developing an automated Sentence Validation System for a limited-resource language like Bengali is challenging. Additionally, Bengali Sentences come in two morphological varieties (Sadhu-bhasha and Cholito-bhasha), making the validation process more challenging. The proposed automated Bengali Sentence Validation system contains the CNN-BiLSTM hybrid classifier model. As of now, there is no standard dataset for Bengali sentence validation. Due to the lack of a standard dataset, we collected Bengali sentences from different sources in Bangladesh and developed a Bengali Sentence Validation (BSV) Dataset with around 5000 labelled sentences arranged into two categories such as correct and incorrect. Experimental results demonstrate that the proposed system outperformed other classifier models and existing approaches for Bengali Sentence Validation and is able to categorize a wide range of Bengali sentences based on their correctness. The system’s F1 score for the Bengali Sentence Validation is 98%.

Identification of Peptide Binding Motifs for Calcium Sulfate Hemihydrate UsingPhage Display.

Selective control over crystallization in complex multicomponent systems such as hydrating cements is a key issue in modern material science. In this context, rational selection-based approaches appear highly promising in the quest for new additive chemistries. Here we have used phage display to identify peptide structures showing high affinity to adsorb on the surfaces of calcium sulfate hemihydrate (also referred to as bassanite), an important hydraulic binder employed in large scales by the construction industry. The results suggest a triplet of amino acids consisting of aspartic acid, serine and leucine, to maintain strong interactions with the surfaces of hemihydrate particles. This notion is confirmed by actual hydration experiments, in which the identified peptide motif provides strictly selective effects during the transformation of bassanite into more stable gypsum. Our work thus contributes to a better understanding of hydraulic binders and their required improvement for a sustainable future.

How Does a Generative Large Language Model Perform on Domain-Specific Information Extraction?─A Comparison between GPT-4 and a Rule-Based Method on Band Gap Extraction.

The advent of generative Large Language Models (LLMs) has greatly impacted the field of Natural Language Processing. However, it is inconclusive how generative LLMs perform on domain-specific information extraction tasks. This study compares the performance of GPT-4 and a rule-based information extraction method based on ChemDataExtractor on band gap information extraction, a task that has important implications for the materials science domain. No training data is required for either method, which is desirable because there is a lack of training data in the materials science domain compared with a variety of material information that is of interest. Manual evaluation on 415 randomly selected articles showed that the GPT-4 model achieved a higher level of accuracy in extracting materials' band gap information than the rule-based method (Correctness 87.95% vs 51.08%, Partial correctness 11.33% vs 36.87%, incorrectness 0.72% vs 12.05%). Further analysis of the errors reveals the strengths and weaknesses of the GPT-4 model compared to the rule-based method. The GPT-4 model shows stronger performance in interdependency resolution and complicated material name recognition, while it also has weaknesses in hallucination, identifying band gap values, and identifying band gap types. Revised prompt based on the error analysis leads to improved accuracy for GPT-4. To the best of our knowledge, this study is the first to compare the GPT-4 model and ChemDataExtractor for the band gap extraction task. This study provides evidence to support using generative LLMs for domain-specific information extraction tasks.

Scalable Synthesis of Organic Core/Shell Architectures toward Dual-Wavelength Optical Waveguides.

Organic core/shell heterostructures have undergone rapid progress in materials chemistry owing to the integration of a wide array of unique properties. Nonetheless, the intricate challenge of regulating homogeneous nucleation and phase separation processes in excessively analogous cocrystal structures presents a formidable barrier to expanding the synthesis strategy for organic core/shell heterostructures. Herein, we successfully achieved a phase separation growth process facilitated by the organic alloy interface layer through a dynamic visualization to capture the intricate morphological evolution. By finely regulating the nucleation process, homogeneous self-assembly induced by high chemical and structural compatibility is circumvented, enabling the formation of organic core/shell heterostructures. Notably, this core/shell architecture boasts dual-wavelength emission at 496 and 696 nm, accompanied by an optical loss coefficient of 0.092 dB per micrometer. This methodology shows potential for extending to the scalable design of other conformational cocrystal heterostructure systems, thereby offering valuable insights into the realm of organic photonics.

Computational Models of Dynamic Load Sources for Modeling of Construction Structures Operation Used in Monitoring of Technical Condition of Buildings and Structures

This research aims to develop principles for assessing the impact of mega-cyclic vibrodynamic loads on the reliability of construction structures. The relevance of the reasons for the development and improvement of algorithms for numerical modeling of multicycle dynamic loads on building structures is due to the steadily increasing intensity of such loads on buildings and structures in megacities, as well as the acute practical problem of significant differences in the dynamic characteristics of buildings and structures obtained as a result of mathematical modeling and determined by experimental methods. The article presents research materials on computational equivalent models of dynamic load sources for numerical modeling of the behavior of construction structures under their influence, using the method of vibroacoustic analogies. The article examines models of sources of dynamic impact on construction sites. Algorithms and final formulas for computational modeling of the simplest sources of dynamic load are developed using the method of vibroacoustic analogies. The dynamic properties of the simplest dynamic load sources were analyzed. A significant difference between the computational models of real and ideal dynamic load sources. The article presents research and development results intended for calculating the distribution of dynamic loads on elements of construction structures in industrial and civil engineering projects located in areas with high levels of transport vibrodynamic impacts. An important property of the proposed computational equivalent models of sources of dynamic impact on building structures is the possibility of computational verification of critical elements, points, or nodes of load-bearing structures of buildings and structures under dynamic overloads. The position of these critical elements, points, and nodes of load-bearing structures under dynamic loads can differ significantly from their position determined using static and quasistatic computational modeling methods.

Understanding the Effect of Corrosion Resistance in Welded AA2198‐T8 Alloy: Microstructural‐Electrochemical Insights

ABSTRACTIn this study, we explore the corrosion resistance of AA2198‐T8 alloy in friction stir‐welded zones, focusing on microstructure changes and resulting corrosion susceptibility. Macrogalvanic coupling effects are observed in weldment under corrosive conditions, particularly in the welding joint (WJ), heat‐affected zones, and base metal (BM). Severe localized corrosion is prevalent in anodic zones, revealing intricate trenching patterns around micrometric particles in cathodic domains. Investigating isolated zones exposes SLC across all welding‐affected regions and BM, underscoring the involvement of microgalvanic cells in corrosion. The novel utilization of a syringe cell as an electrochemical tool proves to be instrumental in delineating the electrochemical characteristics of welding testing zones. Notably, stir zone within WJ emerges as the region depicting the lowest corrosion resistance, a critical finding substantiated by localized electrochemical impedance spectroscopy. These insights into the interplay of electrochemical phenomena and microstructural attributes have implications for advancing corrosion mitigation strategies and alloy engineering in materials science.

Sub‐Nanometer‐Scale Cu9S5 Enables Efficiently Electrochemical Nitrate Reduction to Ammonia

AbstractThe sub‐nanometer is a key feature size in materials science. Unlike single‐atom and nanomaterials, size effects and inter‐component cooperative actions in sub‐nanomaterials will effective on its performance is more significant. Here, 0.95 nm ordered arrangement Cu9S5 sub‐nanowires (Cu9S5 SNWs) are synthesized through the co‐assembly effect of inorganic nuclei (Cu9S5) and clusters (phosphotungstic acid‐PTA), achieving a significant increase in the specific surface area of the sample and ≈100% atomic exposure rate, which is the key to its high catalytic activity. PTA clusters not only act as a “charge transfer station” to accelerate the inter‐component electron transfer process, but also facilitate the dissociation of water and provide more hydrogen protons, thus dramatically facilitating the electrocatalytic process. The experimental results show that the Cu9S5 SNWs exhibited excellent nitrate reduction reaction (NO3−RR) properties. The Faraday efficiency (FE) of NO3−RR is 90.4% at the optimum potential −0.3 VRHE (reversible hydrogen electrode) and the ammonia production is as high as 0.37 mmol h−1 cm−2, which is superior to most reported electrocatalysts. In addition, the Zn‐NO3− liquid‐flow battery devices assembled using Cu9S5 SNWs as electrode materials show excellent application results. This work provides a reference for the design of highly efficient sub‐nanoscale NO3−RR electrocatalysts.

Sequence Context in DNA i-Motifs Can Nurture Very Stable and Persistent Kinetic Traps.

I-motifs are non-canonical DNA structures with recognized biological significance and a proven utility in material engineering. Consequently, understanding and control of i-motif properties is essential to sustain progress across both disciplines. In this work, we systematically investigate how proximity to the most common form of DNA, a double-stranded duplex, influences the thermodynamic and kinetic properties of adjacent i-motifs. We demonstrate that double-stranded stems in i-motif loops promote kinetic trapping of very stable and persistent partially folded conformations. Further, we investigate pathways toward rational control over a folding topology makeup.

A Dynamic H-Bonding Network Enables Stimuli-Responsive Color-Tunable Chiral Afterglow Polymer for 4D Encryption.

The development of stimuli-responsive and color-tunable chiral organic afterglow materials has attracted great attention but remains a daunting challenge. Here, a simple yet effective strategy through the construction of a dynamic H-bonding network is proposed to explore the multi-color stimuli-responsive chiral afterglow by doping a self-designed chiral phosphorescent chromophore into a polyvinyl alcohol matrix. A stimuli-responsive deep blue chiral afterglow system with a lifetime of up to 3.35 s, quantum yield of 25.0%, and luminescent dissymmetry factor of up to 0.05 is achieved through reversible formation and breakdown of the H-bonding network upon thermal-heating and water-fumigating. Moreover, multi-color stimuli-responsive chiral afterglow can be obtained by chiral and afterglow energy transfer, allowing the establishment of afterglow information displays and high-level 4D encryption. This work not only offers a facile platform to develop advanced stimuli-responsive materials but also opens a new avenue for developing next-generation optical information technology with enhanced functionality and responsiveness.