We introduce porous carbon nitride fullerenes (PCNFs), a novel family of cage molecules. They can be considered as the zero-dimensional (0D) counterparts of two-dimensional (2D) porous graphitic carbon nitrides, in a similar analogy to how icosahedral fullerenes are the 0D counterparts of graphene. In this theoretical study, we show how such structures can be designed from Goldberg polyhedra.

We perform a detailed investigation of the properties of two representative members of this family, icosahedral C₆₀N₆₀ and C₁₂₀N₆₀. Applying state-of-the-art DFT approximations and Reax-FF molecular dynamics, we perform a detailed investigation of their structural, vibrational, and electronic properties, as well as their thermal stability. Our results demonstrate that these molecules are dynamically stable. Additionally, their electronic state is robust, as evidenced by the large HOMO-LUMO gaps. The large values of their electron affinities suggest that they might be used in several applications as electron acceptors. Moreover, upon performing molecular dynamics simulations under NVT conditions with ReaxFF force fields, we showed that C₆₀N₆₀ and C₁₂₀N₆₀ are thermally stable well above 1000 K and 2000 K, respectively.

By inheriting the advantageous properties of their 2D counterparts, coupled with their distinct 0D characteristics, PCNFs represent promising structures for a range of applications. These include permeation, molecular trapping, and catalysis, offering potential uses that could extend beyond the capabilities of existing 2D graphitic carbon nitrides. The introduction of PCNFs establishes a significant new class of fullerene-based cage molecules, opening up exciting new directions in nanomaterials research and technology.

The article discusses elevated ambient temperatures in the workplace, which can have a negative impact on humans. This is a hot microclimate, which is defined by Wet Bulb Globe Temperature norms and standards. Despite the Health and Safety regulations in force in Poland and recommendations regarding air conditioning, ventilation and access to drinks, in many industries—including metallurgy, construction and agriculture—the risk of overheating remains high and the problem remains unresolved. The aim of the study was to design and preliminarily evaluate an innovative textronic cooling module intended to reduce heat stress in work clothing. A heat exchange model was developed for three levels of physical exertion (light, moderate, intense), taking into account skin temperature, ambient temperature (WBGT), and the heat exchange mechanisms of the worker's body. The model was verified in laboratory tests conducted under conditions similar to real-life conditions on a human skin model. The results obtained confirmed that the use of the cooling module leads to a significant reduction in temperature in the undergarment area and a reduction in the heat load on the worker's body. A cooling power exceeding 220 W/m² proved sufficient to effectively reduce heat stress, even during intense physical exertion >300 W/m² energy expenditure. The high correlation between the model results and measurements, with a 9% coefficient of variation between measured and modelled values, confirmed the effectiveness of the proposed solution and the correctness of the computational assumptions. The developed module has great implementation potential in industries with elevated workplace temperatures, where employees are exposed to overheating. This contributes to the development of new textronic protective clothing that increases work safety. Further research is recommended, focusing on optimizing the module's design and evaluating its effectiveness in real-world conditions, taking into account ergonomics and user comfort.

The aim of this study is to define the conditions and assumptions used in developing physical–mathematical models that reproduce—or, to some extent, question—the results of experiments and numerical calculations at the appropriate scales. The goal of describing a physical phenomenon as accurately as possible at larger scales starts with fermionic interactions in the excited state, such as Campton waves, which already have experimental and practical applications. This work presents that even in the unexcited state, electrons act as electrostatic oscillators of the wave function. At the atomic scale, the assumption of a process at the speed of light is no longer possible. Here, we discuss Fermi quantities. This work also asks the question of the constancy of Planck's constant, which arises from the angular momentum and is influenced by the electron density of an individual material. The function that would link the relationship between distance and time changes begins with the creation of a physical model of the wave function that allows the speed of light to transition to Fermi quantities, which helps to connect free (valence) electrons in physical chemistry problems. The identity of the change in electron density as the electron states of the corresponding scale allows us to calculate the elastic constant as the Bulk modulus. The scaling procedure is based on the 2D screening of a certain experiment and acquires a more realistic application that can be verified experimentally. Its use is equivalent to the square of the wave function. The problem of quantum mechanics with a volumetric change in space is also associated with scaling, which can be described as one of the Lebesgue spaces. Scaling allows us to obtain a topological sequence of the necessary physical quantities and form a complex chain connected by a causal relationship of space–time variation.

The structures and electronic properties of Ag_nCu_(8-n) clusters were investigated in detail using density functional theory (DFT), employing the Perdew–Wang 1991 (PW91) exchange–correlation functional combined with the triple‐zeta valence correlation‐consistent basis set with pseudopotentials (cc‐pVDZ‐PP). All calculations were performed in the gas phase to obtain intrinsic structural and electronic characteristics without solvent effects. Two of the most stable geometries of the pure Ag₈ and Cu₈ clusters were considered: the tetracapped tetrahedron and the monocapped pentagonal bipyramid. A series of computational evaluations was carried out, including the determination of ionization potential, electron affinity, electronegativity, chemical hardness, electrophilicity index, average binding energy, second‐order energy difference, and the HOMO–LUMO energy gap. The results indicate that the tetracapped tetrahedron geometry is the most dominant and energetically favorable form, whereas only the Cu₈ cluster adopts the monocapped pentagonal bipyramid as its most stable configuration. When forming Ag_nCu_(8-n) bimetallic clusters, the most stable geometry consistently follows the rule that copper atoms preferentially occupy the inner positions of the cluster, while silver atoms are located on the outer shell. Natural bond orbital (NBO) analysis reveals that the frontier orbitals are strongly dominated by the d orbitals of copper atoms, influencing the clusters’ reactivity. Furthermore, electrostatic potential (ESP) mapping was performed to identify the most chemically active sites on the clusters. These findings provide valuable insights and suggest promising directions for applying silver–copper bimetallic clusters in chemical sensing, molecular adsorption, and catalytic processes for various chemical reactions.

Introduction: In dual-energy cone-beam computed tomography (CBCT), structures with different X-ray absorption properties at different energy spectra are better depicted. In the case of breast microcalcifications, such a technique can lead to an accurate characterization of Type I and Type II microcalcifications, which indicates malignancy. The emergence of photon counting detectors has made dual-energy applications possible at low patient doses. CBCT detector technology relies on cesium iodine (CsI) scintillator. Materials of higher effective atomic number (Z_eff), density, and scintillation efficiency than CsI crystals could help in dense breast imaging. This study investigates whether material properties could improve image quality in dual-energy breast CBCT imaging.

Methodology: A micro-CBCT system was simulated in GATE, accompanied with seven different detector material schemes: CsI, bismutium germanate (BGO), lutetium oxyorthosilicate (LSO), lutetium–yttrium oxyorthosilicate (LYSO), GAGG, lanthanum bromide (LaBr₃), and CZT, followed by the same electronic processing set up. Dual-energy methodology was applied to 25keV and 40keV.

Four breast phantoms, containing microcalcifications of Type I (CaCO₃ and CaC₂O₄) and Type II (HAp, hydroxyapatite), were imaged under monoenergetic and polyenergetic conditions. Planar images and tomographic data, reconstructed with filtered backprojection (FBP) and ordered subset expectation maximization (OSEM) algorithm, were used. CNR was calculated for each configuration for every microcalcification present.

Results: HAp-CNR values were the highest since they present the highest physical and electronic density. CZT and GAGG average relative CNR values were 1.17 and 1.15 for the monoenergetic application, and 1.08 and 1.03 for the polyenergetic model, respectively, in relation to HAp detection.

Conclusions: Detector material selection plays a crucial role in dual-energy CBCT. Both CZT and GAGG materials present a 3–17% increase in HAp-CNR values in comparison to CsI. These materials present superior stopping power, energy resolution, and light yield, and are an excellent alternative to a CsI scintillator.

This research investigates the influence of different masonry panel configurations on the seismic performance of reinforced concrete (RC) frame buildings, with particular attention to the effects of openings and variations in the spatial distribution of infills across multiple stories. The primary objective is to understand how these configurations modify structural stiffness, energy dissipation capacity, and damage patterns during earthquake loading. To achieve this, a comprehensive parametric study was performed, evaluating a range of infill arrangements and discontinuities that may occur in real construction scenarios. Numerical models of the RC frames were developed, where masonry infills were represented using equivalent single-strut models capable of capturing their contribution to lateral strength. Nonlinear time–history analyses were then carried out using incrementally intensified earthquake ground motions, in accordance with the incremental dynamic analysis (IDA) methodology. From these simulations, fragility functions were derived through intensity measure (IM)-based procedures, enabling systematic comparison among different structural cases. These fragility curves provide critical insight into the likelihood of exceeding various performance or damage states. The results demonstrate that both the distribution pattern of masonry infills and the presence of openings have a substantial impact on seismic response, with certain configurations exhibiting markedly higher vulnerability and reduced resilience under strong ground shaking.

Microplastic pollution is an emerging environmental concern, and polyethylene terephthalate (PET) particles are among the most widespread synthetic polymers. Recent studies suggest that microplastics can act as carriers for biomolecules, including allergens, potentially influencing their transport, persistence, and biological activity. In this work, we investigate the adsorption mechanism of Cry j 1, a major Japanese cedar pollen allergen, onto a PET microplastic surface using atomistic molecular dynamics (MDs) simulations. A PET slab was constructed from a 6-mer repeat unit with CHARMM36 force field parameters and solvated in a TIP3P water box containing physiological ion concentrations. The Cry j 1 structure, obtained from AlphaFold2, was preprocessed and positioned 2 nm above the PET surface using Packmol. Simulations were conducted in GROMACS at 310 K under NPT conditions to monitor protein conformational changes, adsorption energy, hydrogen bonding, and hydrophobic interactions. Preliminary 20 ns trajectories reveal a progressive reduction in protein–surface separation distance, accompanied by stable hydrophobic contacts between PET aromatic rings and Cry j 1 surface residues. Ongoing analyses aim to quantify residue-specific interactions, solvent-accessible surface area changes, and adsorption free energy to better understand the driving forces behind allergen binding. This study provides atomistic insight into allergen–microplastic interactions, offering a predictive framework for assessing environmental exposure risks and informing strategies to mitigate the impact of microplastic-associated allergens in polluted ecosystems.

This study focuses on the quaternary Heusler alloy CoFeZrGe, explored through first-principles calculations to evaluate its potential in spintronic and optoelectronic applications. Heusler alloys attract significant interest due to their diverse electronic and magnetic characteristics, particularly their capacity to exhibit half-metallic ferromagnetism, a property crucial for high-performance spintronic devices. Here, the structural, electronic, magnetic, mechanical, and optical properties of CoFeZrGe are systematically investigated.

Computations were carried out within the framework of density functional theory (DFT) using the full-potential linearized augmented plane wave (FP-LAPW) method implemented in WIEN2k. Three atomic configurations compatible with the F-43m space group (Y1, Y2, and Y3) were considered, with structural optimization identifying the Y1 arrangement as the lowest energy configuration. The electronic structure was analyzed using both the generalized gradient approximation (GGA-PBE) and the modified Becke–Johnson (TB-mBJ) potential.

The findings reveal that CoFeZrGe possesses half-metallic ferromagnetism, featuring an indirect minority-spin band gap of 0.48 eV (GGA) and 1.27 eV (TB-mBJ). The material exhibits a total magnetic moment of 1 μB per formula unit, consistent with the Slater–Pauling rule. Calculated elastic constants verify mechanical stability and indicate ductility, supported by favorable values of bulk modulus, shear modulus, Poisson’s ratio, and Pugh’s ratio. Optical results, including the dielectric function, absorption coefficient, and energy loss spectra, highlight pronounced interband transitions and strong absorption across the visible and ultraviolet regions.

Overall, CoFeZrGe demonstrates a combination of stable half-metallicity, mechanical robustness, and excellent optical response, making it a strong candidate for future spintronic and optoelectronic technologies.

Understanding the complexity of glass formation remains a significant challenge in materials science. Solving the mystery of the dynamic processes involved during glass transition involves answering the key questions of where and why the transition begins and ends during the cooling process.

This study focuses on silica glass, considered to be the most fundamental glass-forming material. The research community has gathered extensive experimental data on both the physical properties and analytical techniques related to silica crystals and silica glass. These data can be used to assess new theories. This study recognizes that both the crystal and glass forms of silica are made up of SiO₄ tetrahedra. A thorough understanding of the crystallization process requires knowledge of how SiO₄ tetrahedra behave under different temperatures during slow-cooling. Based on this understanding and fundamental physical laws, it becomes possible to predict how SiO₄ tetrahedra react during rapid cooling. The available experimental data can help to verify the accuracy of these predictions. Once the silica glass transition process is understood, the insights gained can also be applied to the transitions of more complex glasses.

This analysis indicates that, during rapid cooling, silica structures within the temperature range from the melting point to the polymorphic inversion temperature, 1470°C, are heterogeneous, featuring embryonic clusters, and begin to shift toward more stable structures at 1470°C. Experimental data confirm that this is a continuous structural transition occurring over several hundred degrees.

It is concluded that the silica glass transition can be identified as a second-order phase transition, resulting in a glass state with a unique structure and properties that differ from those of liquid and crystalline silica. The method for determining the glass transition temperatures where the transition begins is straightforward and can also be applied to complex silicate glasses.

Non-destructive evaluation techniques are increasingly recognised as effective alternatives to destructive testing for estimating the compressive strength of lightweight aggregate concrete (LWAC). Among these, ultrasonic pulse velocity (UPV) is a well-established and widely employed method, characterised by its rapidity, non-invasiveness, and relative simplicity of implementation. In this study, an experimental dataset comprising 640 core segments from 160 cylindrical specimens, provided for analysis, was investigated. Each segment was described by physical and processing variables, including lightweight aggregate and concrete densities, casting and vibration times, experimental dry density, and P-wave velocity obtained through UPV testing. A segregation index (SI), derived from UPV measurements and defined as the ratio of local to mean P-wave velocity within each specimen, was also considered, following approaches previously suggested in the literature. A range of machine learning techniques was applied to assess the predictive capacity of local P-wave velocity and SI. Most ensemble-based methods and support vector regression achieved the highest accuracy when SI was excluded, indicating that its contribution was redundant. By contrast, Gaussian process regression showed slight improvements when SI was included. The results confirmed that the P-wave velocity measured by UPV testing is a reliable non-destructive predictor of compressive strength in LWAC. At the same time, the added value of SI remains negligible under conditions of low segregation, as reflected by SI values above 0.8. These findings highlight the practical potential of integrating UPV-based measurements with data-driven modelling to enhance the reliability of concrete characterisation and quality control.