Real Materials Research Articles

“Pick-Me” Black women: tactical patriarchal femininity in the Black manosphere

ABSTRACT This essay analyzes anti-feminist (“Pick-Me”) Black women content creators on YouTube who exist within the Black manosphere—online spaces populated by Black men who support Black patriarchal dominance. These “Pick-Me” content creators use what I term “tactical patriarchal femininity” to attract the financial provision of an economically stable Black man and to derive income from sympathetic viewers. Tactical patriarchal femininity is an elaborate, all-consuming embodied performance that is as much about emotion work as it is about exuding conventional attractiveness and behavior that is aligned with traditional femininity. Tactical patriarchal femininity exists to combat the matrices of oppression created by capitalism, white supremacy, and institutional patriarchy. Anti-feminist Black women work in reaction to the misogynoirist material realities that victimize Black women. Ultimately, the Black manosphere’s explicit disavowal of Black women’s worth, apart from what they may provide for men in their role as a patriarchalized wife, is dangerous to all Black women—including and especially those Black women who claim anti-feminism. Anti-feminism does not combat dehumanizing views that posit Black women as masculine, unmarriageable, and underserving of care and support. Rather, anti-feminist Black women work to make themselves exceptions to the rule in a bid for conditional respect and protection that rarely materializes long-term.

Exploring the micro-to-macro response of granular soils with real particle shapes by way of μCT-aided DEM analyses

This contribution provides high-fidelity images of real granular materials with the aid of X-ray micro-computed tomography (μCT), and employs a multi-sphere representation to reconstruct non-spherical particles. Through discrete-element method (DEM) simulations of granular samples composed of these non-spherical clumps, the effect of particle shape on the macroscopic mechanical response and microscopic soil fabric evolution is examined for soil assemblies under triaxial compression. Simulation results indicate that materials with more irregular particles tend to show higher shear resistance in both peak and critical states, while exhibiting higher void ratio under isotropic loading conditions and in the critical state. The proposed critical state parameters for describing the sensitivity of the mean coordination number to confining pressures are larger as particles become more irregular. At a microscopic level of observation, directional and scalar parameters of particle contacts are sensitive to predefined particle shapes. More irregular materials appear to exhibit higher fabric anisotropy with respect to particle orientation in the critical state, while the branch vector is affected by both contact modes and particle shape. The critical stress ratio from the simulation results is validated by comparing with experimental results, and further found to be linearly linked to the shape-weighted fabric anisotropy indices.

From creep to flow: Granular materials under cyclic shear

When unperturbed, granular materials form stable structures that resemble the ones of other amorphous solids like metallic or colloidal glasses. Whether or not granular materials under shear have an elastic response is not known, and also the influence of particle surface roughness on the yielding transition has so far remained elusive. Here we use X-ray tomography to determine the three-dimensional microscopic dynamics of two granular systems that have different roughness and that are driven by cyclic shear. Both systems, and for all shear amplitudes Γ considered, show a cross-over from creep to diffusive dynamics, indicating that rough granular materials have no elastic response and always yield, in stark contrast to simple glasses. For the system with small roughness, we observe a clear dynamic change at Γ ≈ 0.1, accompanied by a pronounced slowing down and dynamical heterogeneity. For the large roughness system, the dynamics evolves instead continuously as a function of Γ. We rationalize this roughness dependence using the potential energy landscape of the systems: The roughness induces to this landscape a micro-corrugation with a new length scale, whose ratio over the particle size is the relevant parameter. Our results reveal the unexpected richness in relaxation mechanisms for real granular materials.

The Origin of Geomagnetism

The paper clarifies that a magnetic field is not a real material existence and concludes that a magnetic field is essentially a contracting electric field in motion. Based on this new principle, all electromagnetic laws can be derived and proven. Experiments confirm that there is indeed an electrostatic field around a static magnetic field, which is a powerful scientific proof of the new principle that a magnetic field is a contracting electric field in motion. The paper believes that the westward movement of negative ion-containing air in the Earth's upper layers is the fundamental reason for the generation of geomagnetism. Due to the fact that a magnetic field is a contracting electric field in motion, the author determines that people in different motion situations will see different moving electric fields on the Earth, namely, they will see different geomagnetic fields. He further determines that an observer outside the Earth who is stationary relative to the Sun will see a strong geomagnetic field with the North Pole being the South pole.

The unfinished promise of infrastructure in post‐apartheid South Africa

AbstractThis article explores aspects of the “unfinished” using notions of human‐centered design in African public infrastructure and the importance of involving the “users” and “beneficiaries” in infrastructure development and delivery. Infrastructure, both conceptually as an idea and in its constructed material reality, has a huge impact on society, socially and economically, and has been promised as one of the most effective drivers of economic growth in South Africa. Increasingly in South Africa, facilities are falling into disrepair. Infrastructure is being adapted and used in unintended ways that often do not provide the socio‐economic benefits intended. In considering medical infrastructure across three sites in post‐apartheid South Africa, my argument asks how factors such as statecraft, governance and funding models, design considerations, project implementation methodologies, operational and maintenance policies affect the promise of infrastructural change in contemporary South Africa?

The Realist Discursive Study of Religion

Abstract Filip Rasmussen (2024) argues that the discursive study of religion is misunderstood when one assumes that it focuses only on discourse, ignoring material entities and forces. A discursive approach, he proposes, need not deny the existence or the effects of the material world, and so it is not in conflict with, for example, a critical realist approach to social theory that seeks to explain social behavior in terms of material mechanisms. Rasmussen’s synthesizing position gives us an opportunity to consider the relationship between the apparently rival theories of the discursive approach and critical realism – and, in particular, the relationship between discourse and the material realities in the world that do not depend on discourse for their existence or powers. My view is that Rasmussen is right and that a discursive approach combined with critical realism gives us the best account of forms of life, like religions, that combine discursive and nondiscursive elements. This paper therefore argues for the coherence of a realist discursive study of religion.

The anti-dogbone: Evaluating and designing optimal tensile specimens for deep learning of constitutive relations

Traditional tensile testing with “dogbone”-shaped specimen (ASTM E8, first standardized in 1924) strives for strain uniformity. Multiple tests with such samples help fit simple constitutive relation parameters on real materials. With the development of deep learning, the concept of employing entirely data-driven constitutive relations to capture more intricate material behavior has arisen. Nevertheless, these methods demand experimental data that are distributed throughout the complete stress–strain configuration space to effectively train the machine learning models. This is particularly crucial for mechanisms like hardening, which are time-dependent and sensitive to loading history. In this work, we investigate the potential to efficiently gather a wider range of experimental data points in the stress–strain configuration space using non-uniform samples and displacement-field mapping, leveraging advancements in computer vision techniques. We developed a metric to quantify stress state diversity in 2D tensile experiments and used it to optimize the shape of the sheet sample. The goal was to increase stress–strain diversity obtained within a single test, particularly in the linear elastic regime. Additional geometric constraints can be introduced on the design features, considering factors such as size and curvature to adapt to the microstructural characteristics of the sample material.

A linear second-order convex splitting scheme for the modified phase-field crystal equation with a strong nonlinear vacancy potential

The modified phase-field crystal (MPFC) equation was extended to the MPFC equation with a strong nonlinear vacancy potential (VMPFC) to include vacancies. In this paper, we develop a linear, second-order, and unconditionally energy stable scheme for solving the VMPFC equation by proposing a new linear convex splitting, using the Crank–Nicolson formula to the contractive part and the second-order Adams–Bashforth formula to the expansive part, and adding a second-order Douglas–Dupont regularization. The unconditional energy stability of the developed scheme is proved. By solving the VMPFC equation, vacancies which exist in real materials can be observed in numerical simulations.

Reflections on Hermit Crab Creative Non-Fiction Methodology: Examples from a Narrative Study of Running Fathers

In this article, we draw on research employing creative nonfiction (CNF) in psychology and the sport sciences, to outline the value of one untapped CNF methodology: the hermit crab essay. We expand the methodological repertoire for CNF in arts based research by advocating for hermit crab CNFs that borrow from ready-made structures, to present ‘real research material’ in newly creative and accessible ways. We use the r/AmItheAsshole online advice community as our borrowed structure, to create examples ‘in action’ from a narrative study of running and fatherhood. We outline reflections researchers might consider if using this form of CNF.

Metacognitive Self-management in Developing Students' Rigorous Mathematical Thinking Skills

This study aims to describe the metacognitive self-management of students in developing rigorous mathematical thinking. This study uses a qualitative method with a case study approach. The participants were three students from the thirdlevel mathematics education department, who were selected and made a contract with for real analysis lectures. The first student experienced a significant change from the beginning of the meeting, resulting in the metacognitive self-management process being well-conditioned. He completed the task more confidently than the initial presentation, used several references and sources of information to complete the job, and represented each answer in the form of mathematical symbols. This studentscognitive function appears to be of level-1, with qualitative thinking. For the 2nd student, a change was observed in the learning process and the teacher’s motivation and guidance. The results of the interviews showed that the student applied strategies in completing assignments. He answered them systematically, based on experience, and mastered the prerequisite material. This student showed improved thinking skills related to mastery of concepts from new material, analyzing the problems given, being critical and focused when answering, and looking hard to get maximum evaluation results. This 2nd student entered the level of quantitative thinking with precision. Lastly, in the 3rd student, self-management seems stable, but was still lacking in adjusting the understanding of prerequisites with understanding concepts from new material. The development during the learning process shows that he can activate his mathematical knowledge, compose logical proofs of Real Analysis material problems, and build relationships between prerequisite concepts and new material. This type of student enters the level of abstract relational. The results of the study can be a reference for teachers to determine the learning model and the related instruments, so that they can grow the level of mathematical thinking before, during, and after the learning process. Keywords: Metacognitive, self-management, Mathematical thinking skill

Virtually measuring layered material appearance

This paper describes the design and the implementation of a virtual gonioradiometer dedicated to the analysis of layered materials BSDF. For a given material sample, interfaces between layers are represented by geometric meshes, associated with elementary reflectances. Light scattering is performed using path tracing. Our system is composed of five hemispherical sensors, whose cells have uniform solid angles, and a close-to-uniform geometry. The upper hemisphere captures the reflected radiance distribution, while the other four collect the light energy lost by the sample sides. Sensor resolutions can be set to gather very fine details of the BSDF. With the proposed system, any type of virtual surface reflection and transmission can be simulated, with several controllable surface layers, and with any type of reflection configuration, including direct reflections, two bounces of reflection, or all contributions. A series of results is provided with several types of layered materials, as well as discussion and analysis concerning the assumptions made with analytical layered BSDF models. We also propose an in-depth study of the side effects that inevitably appear when measuring such (real) material configurations. Finally, our system will be freely available to the community (open source dissemination).

Determining the dynamic properties of spruce wood using the Taylor anvil test

Spruce wood is one of the most widely used materials in the production of lightweight wood-based composites in central Europe. The quality, weight, and geometric parameters of wood chips have a significant impact on the resulting quality of the manufactured composite product. Numerical simulations are necessary for advanced optimization of the quality of composite components and the manufacturing process itself. These simulations require adequate input material data and a model to produce results applicable to the output of industrial practice. In this study, a material model for spruce wood was established using the Taylor anvil test (TAT). This, in contrast to the commonly used Hopkinson compression test, corresponds better to the actual loading process. A new measurement method for shock pulses was developed to implement TAT obtained data for a realistic material model. The method was compared with numerical simulations in Ansys LS DYNA. Based on the results, parameters for the Johnson-Cook equation were determined, which can be applied in the production of disintegrations and, consequently, in the dynamic loading of spruce composite materials.

Effective Prediction of Concrete Constitutive Models for Reinforced Concrete Shear Walls under Cyclic Loading.

One of the most challenging elements of modeling the behaviour of reinforced concrete (RC) walls is combining realistic material models that can capture the observable behaviour of the physical system. Experiments with realistic loading rates and pressures reveal that steel and concrete display complicated nonlinear behaviour that is challenging to represent in a single constitutive model. To investigate the response of a reinforced concrete structure subjected to dynamic loads, this paper's study is based on many different material models to assess the advantages and disadvantages of the models on 2D and 3D RC walls using the LS-DYNA program. The models consisted of the KCC model and the CDP model, which represented plasticity and distinct tensile/compressive damage models, and the Winfrith model, which represented plasticity and the smeared crack model. Subsequently, the models' performances were assessed by comparing them to experimental data from reinforced concrete structures, in order to validate the accuracy of the overall behaviour prediction. The Winfrith model demonstrated satisfactory results in predicting the behaviour of 2D and 3D walls, including maximum strength, stiffness deterioration, and energy dissipation. The method accurately predicted the maximum strength of the Winfrith concrete model for the 2D wall with an error of 9.24% and for the 3D wall with errors of 3.28% in the X direction and 5.02% in the Y direction. The Winfrith model demonstrated higher precision in predicting dissipation energy for the 3D wall in both the X and Y directions, with errors of 6.84% and 6.62%, correspondingly. Additional parametric analyses were carried out to investigate structural behaviour, taking into account variables such as concrete strength, strain rate, mesh size, and the influence of the element type.

On the thermoelastic model of real materials with relaxation dynamics of defects

On the thermoelastic model of real materials with relaxation dynamics of defects

Precise Regulation on the Bond Dissociation Energy of Exocyclic C-N Bonds in Various N-Heterocycle Electron Donors via Machine Learning.

Heterocycles with saturated N atoms (HetSNs) are widely used electron donors in organic light-emitting diode (OLED) materials. Their relatively low bond dissociation energy (BDE) of exocyclic C-N bonds has been closely related to material intrinsic stability and even device lifetime. Thus, it is imperative to realize fast prediction and precise regulation of those C-N BDEs, which demands a deep understanding of the relationship between the molecular structure and BDE. Herein, via machine learning (ML), we rapidly and accurately predicted C-N BDEs in various HetSNs and found that five-membered HetSNs (5-HetSNs) have much higher BDEs than almost all 6-HetSNs, except emerging boron-N blocks. Thorough analysis disclosed that high aromaticity is the foremost factor accounting for the high BDE of 5-HetSNs, and introducing intramolecular hydrogen-bond or electron-withdrawing moieties could also increase BDE. Importantly, the ML models performed well in various realistic OLED materials, showing great potential in characterizing material intrinsic stability for high-throughput virtual-screening and material design efforts.

Advancing respirable coal mine dust source apportionment: a preliminary laboratory exploration of optical microscopy as a novel monitoring tool

Exposure to respirable coal mine dust (RCMD) can cause chronic and debilitating lung diseases. Real-time monitoring capabilities are sought which can enable a better understanding of dust components and sources. In many underground mines, RCMD includes three primary components which can be loosely associated with three major dust sources: coal dust from the coal seam itself, silicates from the surrounding rock strata, and carbonates from the inert ‘rock dust’ products that are applied to mitigate explosion hazards. A monitor which can reliably partition RCMD between these three components could thus allow source apportionment. And tracking silicates, specifically, could be valuable since the most serious health risks are typically associated with this component-particularly if abundant in crystalline silica. Envisioning a monitoring concept based on field microscopy, and following up on prior research using polarized light, the aim of the current study was to build and test a model to classify respirable-sized particles as either coal, silicates, or carbonates. For model development, composite dust samples were generated in the laboratory by successively depositing dust from high-purity materials onto a sticky transparent substrate, and imaging after each deposition event such that the identity of each particle was known a priori. Model testing followed a similar approach, except that real geologic materials were used as the source for each dust component. Results showed that the model had an overall accuracy of 86.5%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$86.5\\%$$\\end{document}, indicating that a field-microscopy based monitor could support RCMD source apportionment and silicates tracking in some coal mines.

Material Property Prediction Using Graphs Based on Generically Complete Isometry Invariants

AbstractThe structure–property hypothesis says that the properties of all materials are determined by an underlying crystal structure. The main obstacle was the ambiguity of conventional crystal representations based on incomplete or discontinuous descriptors that allow false negatives or false positives. This ambiguity was resolved by the ultra-fast pointwise distance distribution, which distinguished all periodic structures in the world’s largest collection of real materials (Cambridge structural database). State-of-the-art results in property prediction were previously achieved by graph neural networks based on various graph representations of periodic crystals, including the Crystal Graph with vertices at all atoms in a crystal unit cell. This work adapts the pointwise distance distribution for a simpler graph whose vertex set is not larger than the asymmetric unit of a crystal structure. The new Distribution Graph reduces mean absolute error by 0.6–12% while having 44–88% of the number of vertices when compared to the Crystal Graph when applied on the Materials Project and Jarvis-DFT datasets using CGCNN and ALIGNN. Methods for hyper-parameters selection for the graph are backed by the theoretical results of the pointwise distance distribution and are then experimentally justified.

Structural Characterization of La0.6Sr0.4CoO3-δ Thin Films Grown on (100)-, (110)-, and (111)-Oriented La0.95Sr0.05Ga0.95Mg0.05O3-δ.

In this study, a detailed structural characterization of epitaxial La0.6Sr0.4CoO3-δ (LSC) films grown in (100), (110), and (111) orientations was conducted. LSC is a model air electrode material in solid oxide fuel and electrolysis cells and understanding the correlation of bulk structure and catalytic activity is essential for the design of future electrode materials. Thin films were grown on single crystals of the perovskite material La0.95Sr0.05Ga0.95Mg0.05O3-δ cut in three different directions. This enabled an examination of structural details at the atomic scale for a realistic material combination in solid oxide cells. The investigation involved the application of atomic force microscopy, X-ray diffraction, and high-resolution transmission electron microscopy to explore the distinct properties of these thin films. Interestingly, ordering phenomena in both cationic as well as anionic sublattices were found, despite the fact that the thin films were never at higher temperatures than 600 °C. Cationic ordering was found in spherical precipitates, whereas the ordering of oxygen vacancies led to the partial transition to brownmillerite in all three orientations. Our results indicate a very high oxygen vacancy concentration in all three thin films. Lattice strains in-plane and out-of-plane was measured, and its implications for the structural modifications are discussed.

Which horticultural activities are more effective for children's recovery from stress and mental fatigue? A quasi-experimental study.

Studies have established the benefits of horticultural therapy and activities for human health and well-being. Nonetheless, limited research has been conducted on the potential restorative advantages and distinctions between different types of horticultural activities in terms of stress reduction. This study employed a quantitative research method to investigate the stress recovery benefits of five horticultural activities (flower arrangement, sowing and transplanting seeds, kokedama crafting, pressed flower card making, and decorative bottle painting with dried flowers) and one reference activity (short composition writing) for children. The experiment was conducted in a children's activity center's multi-purpose classroom with 48 elementary students aged 9-12 years. The subjects first took a stress test to induce stress and then engaged in horticultural activities for 20 min. Physiological stress was assessed using electrocardiograms and electroencephalograms as feedback indicators. Psychological and emotional changes were determined using the Positive and Negative Affect Schedule for Children and Self-Assessment Manikin scales. The results demonstrated that horticultural activities greatly reduced physiological fatigue, and their recovery benefits were significantly greater than those of the reference activity. The recovery effects from different horticultural activities were similar across physiological indicators, although flower arrangement and sowing and transplanting seeds exhibited relatively robust recovery benefits. The heart rate and α-EEG-based generalized estimating equation revealed that horticultural activities offered significantly better relative recovery at each time phase of operation than the reference activity, with girls showing a 3.68% higher relative recovery value than boys. Flower arrangement and kokedama crafting offered better physiological recovery for students with prior horticultural experience, and these two activities received the highest scores in terms of positive effects and the "pleasure" dimension. Students believed that participating in horticultural activities resulted in a noteworthy increase in personal confidence and a greater sense of achievement. The study suggests that horticultural activities that involve real and vibrant plants or natural materials and are more attractive have more stress-relieving benefits. We conclude that horticultural activities are beneficial leisure activities that aid in stress relief for children and that it is important to consider the attributes of activities when developing horticultural programs for elementary students.

Fathering Identities and Men’s Engagement With Flexible Working Arrangements

This research examines how fathering identities and normative gendered expectations shape the way men engage with a broad range of flexible working arrangements (FWAs). Forty-three heterosexual white-collar Australian fathers participated in this qualitative research, involving one-to-one semi structured interviews which were discursively analysed using Foucauldian Discourse Analysis. Three fathering identities emerged from the data: “The Present and Visible Father”, “The Involved and Competent Father”, and “The Father as Helper.” The findings demonstrate that fathering identities have a profound impact on men’s flexible working practices, that fathering identity is fluid and complex, and that a tension still exists between the expectations surrounding involved fathering, persistent traditional fathering norms, and the material reality of men’s work practices.