Abstract: A carbon element exhibits complex behavior. It can be due to its various allotropes. From various carbon precursors, a carbon material can result. The published studies on carbon-based materials are not groundbreaking enough. The discussed results also lack the original science and engineering of carbon materials. The study of each carbon allotrope is a first need. It should follow the binding of the same-state atoms. Depending on the processing conditions of a carbon precursor, a carbon atom can change its state behavior. In the state conversion of a carbon atom, the energy bits shaped-like dashes transfer electrons to nearby unfilled states. The involved dash-shaped energy bit maintains partially conserved behavior. Atoms in the graphite state also study a one-dimensional structure under the execution of electron dynamics. A structure in the nanotube atoms is two-dimensional. A fullerene structure is four-dimensional. In the structural formation of diamond, lonsdaleite, or graphene, the energy bits shaped like a golf stick bind their atoms. The binding of the diamond atoms is from the surface to the south, whereas the formation of a diamond structure is from the south to the surface. In the structural formation of a glassy carbon, the layers of gaseous, graphitic, and lonsdaleite atoms bind simultaneously. The motivation behind this study is to explore the atomic structure in carbon, state conversion, binding in carbon atoms, the glassy carbon structure, and the hardness of carbon materials. It provides a new insight into the basic and applied science of carbon-based materials.

Abstract: A comprehensive thermodynamic and molecular-level investigation of adsorption on MgY and NH₄Y zeolites is presented using inverse gas chromatography at infinite dilution combined with a Hamaker-based formalism and an extended five-parameter Lewis acid–base model. The study establishes a unified framework that integrates dispersive, polar, and donor–acceptor interactions while explicitly accounting for temperature-dependent intermolecular geometry. The results demonstrate that adsorption is governed by a dynamic interplay between London dispersion forces, specific acid–base interactions, and thermal effects, rather than by static or purely additive contributions. The London dispersive surface energy decreases linearly with temperature, reflecting the progressive weakening of electronic correlation forces, while the inter-molecular separation distance exhibits a well-defined linear expansion, enabling the determination of intrinsic contact distances at 0 K. A major finding of this work is that the molecular surface area of adsorbed probes is not a constant geometric property but a thermodynamic quantity that follows a quadratic temperature dependence, revealing the adaptive nature of adsorption geometry. The comparison between MgY and NH₄Y highlights two distinct adsorption regimes: MgY is characterized by a structured and strongly dispersive interaction field associated with Mg²⁺ cations, whereas NH₄Y exhibits enhanced polarity, stronger specific interactions, and increased molecular flexibility driven by hydrogen bonding and protonic effects. The thermodynamic analysis of Lewis acid–base interactions shows that classical linear models are insufficient to describe adsorption on zeolite surfaces. A rigorous statistical evaluation demonstrates that the Hamieh five-parameter model provides the most accurate and physically meaningful description, capturing nonlinear donor–acceptor interactions and amphoteric coupling effects. Overall, this work introduces a novel thermodynamic methodology that links macroscopic surface energetics to microscopic interaction parameters, providing new insights into adsorption mechanisms and offering a powerful tool for the rational design of porous materials in catalysis, separation, and energy-related applications.

Abstract: The preparation of high-performance radiation detector materials such as cadmium zinc telluride (CZT) relies on rigorous and efficient quality control to ensure the consistency of device performance. Traditional manual evaluation based on wafer-by-wafer inspection is time-consuming and makes it difficult to assess the downstream product yield at the ingot level in advance. This paper proposes a machine-learning-based prediction framework for CZT ingots, in which the product-level yield of test wafers from the same ingot is predicted using the double-sided electrical performance and spectral characterization data of a limited number of evaluation wafers. To address the limited number of ingot samples and the significant internal variability among wafers, statistical aggregate features, A/B-side difference features, threshold-ratio features, and intra-ingot Bootstrap resampling were combined, and multiple regression methods, including linear models, Random Forest, XGBoost, and neural networks, were systematically evaluated. The results show that the XGBoost model achieved the best overall performance, with the lowest mean squared error of 0.0352, a mean absolute error of 0.1448, and a Pearson correlation coefficient of 0.3187 on the test set. Furthermore, after combining model prediction with empirical rules, the true yield of test wafers for the top 22% candidate ingots increased from 61.50% to 63.59%. These results indicate that the proposed method can effectively support early ingot screening and processing-priority decisions. This study demonstrates the application potential of data-driven methods in early-stage quality evaluation of CZT crystals and provides a reference framework for yield prediction in similar multi-wafer crystalline materials.

Abstract: The photoreduction of CO2 is a growingly interesting research topic due to the intriguing possibility of producing solar fuels through a concerning pollutant. TiO2 photocatalysts were the first materials used for this application, but since then, various strategies have been developed to optimise the catalytic performance and operating conditions to obtain competitive yield. This review presents the findings of the last decade of research on dif-ferent semiconductors, TiO2 and g-C3N4 and their composites. The main features of the re-action and its key issues are first overviewed, focusing on the effect of different reaction conditions on the performance and recalling the mechanism of the reaction. The strategies developed to overcome the challenges of this demanding reaction are described in the fol-lowing paragraphs, including the use of dopants or co-catalysts, of heterojunctions be-tween different semiconductors and the use of electron transfer mediators. Finally, some unifying concepts are summarised, suggesting the calculation of the stored energy amount and the relative efficiency to allow a safer comparison between literature data collected under widely variable conditions and leading to different products.

Abstract: As global energy demand continues to rise and the need for environmental conservation grows more urgent, solar energy has attracted substantial attention owing to its inherent cleanliness and sustainability.Perovskite solar cells (PSCs), an innovative photovoltaic technology, have shown significant improvements in photoelectric conversion efficiency (PCE) since their introduction.Nevertheless, significant challenges remain in enhancing efficiency and ensuring long-term stability.Naturally abundant and environmentally benign carbon materials represent a promising alternative.Incorporating carbon materials into PSCs can yield beneficial effects, such as controlling the crystallization rate of the perovskite layer, improving carrier transport properties, and realizing interface modification between various functional layers.This article systematically reviews the application of carbon materials in PSCs, including carbon nanotubes, carbon dots, carbon nanofibers, fullerenes, and their derivatives.

Abstract: Previous work has attempted, often within the framework of strip yield-type models, to predict crack growth rates based on the accumulation of fatigue damage ahead of the crack tip as it moves through a structure. This study performs similar calculations using results from plastic 2D plane stress analyses run on a finite element (FE) model containing a sharp semi-circular notch representing an edge crack. Stress-distance profiles ahead of the crack tip (notch root) were extracted at the maximum and minimum points of a range of fatigue cycles with different loading amplitudes. These were used with data from smooth specimen Low Cycle Fatigue (LCF) tests to predict the build-up of fatigue damage at regularly spaced locations ahead of the crack tip and hence crack growth rates. The FE analyses were performed for a wide range of K_max values at loading R-ratios of 0, -1 and 0.5, and the growth rate predictions were compared with test data. The method was then extended to predict overload behaviour. The material studied was the nickel-based superalloy fine grain (FG) RR1000 at 20°C.

Abstract: This study investigates the effect of dust and environmental debris (soiling) on reflective components in Concentrated Solar Thermal (CST) systems, a phenomenon that significantly reduces specular reflectivity and overall optical efficiency. Recent research efforts in the field have focused on advanced coatings capable of modifying surface wettability to improve self-cleaning performance and reduce water consumption for maintenance. Traditional methods for evaluating wettability rely on static contact angle measurements to characterize hydrophobic or hydrophilic surfaces; however, this parameter alone does not adequately reflect actual water usage in cleaning operations, which is influenced by environmental conditions, particulate composition, and operational constraints.Experimental assessment in operational solar fields remains impractical, as no facilities are currently fully equipped with self-cleaning mirrors, leaving the real impact on water consumption largely unknown. To address this gap, a laboratory-based gravimetric methodology has been proposed to quantify water retained on mirror surfaces during cleaning. By systematically correlating surface wettability with water retention and cleaning efficiency under controlled conditions, this approach provides a predictive framework for estimating water use based on coating properties.The methodology offers a standardized way to compare self-cleaning surface technologies and supports the design of coatings that minimize water consumption while maintaining high reflectivity, ultimately contributing to more sustainable and efficient solar thermal systems.

Abstract: This study systematically investigated the preparation conditions of palygorskite/Fe₃O₄ composites. The grain size of Fe₃O₄ was analyzed by fitting the Williamson–Hall equation. Combined with the catalytic degradation experiments of methylene blue via the Fenton reaction, the influence of Fe₃O₄ grain size on the catalytic performance of the composite was elucidated. Under different preparation conditions, the Fe₃O₄ grain size in the composites exhibited distinct variation characteristics. With an increase in the Fe₃O₄ loading ratio, the Fe₃O₄ grain size gradually increased, accompanied by an enhancement in the catalytic degradation performance. When the preparation temperature was varied, the Fe₃O₄ grain size increased with rising temperature, whereas the catalytic degradation performance of the composite gradually declined. Increasing the mechanical stirring speed led to a decrease in the Fe₃O₄ grain size, and the catalytic degradation performance of the composite increased accordingly. The results indicate that the Fe3O4 loading amount, preparation temperature, and mechanical stirring intensity can all regulate the Fe3O4 grain size in the palygorskite/Fe₃O₄ composite. Moreover, loading an appropriate amount of Fe₃O₄ particles onto the palygorskite surface and reducing the Fe3O4 grain size can both effectively improve the catalytic degradation performance of the PAL/Fe₃O₄ composite.

Abstract: Agrivoltaics (Agri-PV) represents a promising solution to improve land-use efficiency by simultaneously allowing crop growth and photovoltaic (PV) energy generation, with additional benefits for crop production if properly engineered. However, when crystalline silicon (c-Si) PV modules are used for Agri-PV, even in semi-transparent configurations, shading occurs over crops, potentially reducing agricultural yields. Enhancing light diffusion is a key strategy to partially compensate for this effect, as diffuse light is more efficiently utilized by most plants. This study aims at engineering the transparent section of a semi-transparent c-Si PV module, assessing its optical, light-scattering, and efficiency-related properties for Agri-PV applications. The experimental work involved fabricating and testing various transparent stack configurations and mini-module prototypes to evaluate their suitability for Agri-PV integration. Optical characterization using a spectrophotometer revealed that certain stack configurations significantly enhance light diffusion, while maintaining good transmittance values for crops growth. To further analyze angular light scattering, a custom-built setup to measure the Bidirectional Transmittance Distribution Function (BTDF) was developed. The results showed that primarily anti-glare films (AG) and secondarily specific encapsulants (TPO) and flexible layers can effectively improve light distribution, helping to mitigate shading effects. Following AG application, Haze values exceeded 89%, indicating enhanced light diffusion capabilities. The impact of different stacks on module efficiency was also assessed through mini-modules testing. Findings indicate that enhanced light diffusion can be achieved with minimal efficiency losses. Specifically, the application of the AG resulted in a reduction of the Cell-To-Module efficiency ratio (CTM_η) of less than 1%. These results confirm that semi-transparent PV modules can be optimized for Agri-PV applications without significantly compromising energy output.

Abstract: This study examines the microspherical high-calcium fly ash (HCFA) and the high-strength binder material based on it by method of scanning electron microscopy and energy-dispersive X-ray spectroscopy (SEM-EDS). The composition of 568 individual microspheres of the initial HCFA was determined and presented as ternary diagrams CaO–Al2O3–SiO2 and CaO–FeO–SiO2. The binder specimens have a compressive strength of 24–90 MPa at a curing time of 3–300 days. Their strength is close to that of CEM I 42.5N cement specimens with a curing time of up to 28 days, but exceeds it with a curing time of up to 300 days. The SEM-EDS method showed that the predominant composition of hydration products is concentrated in the high-calcium region of the CaO–Al2O3–SiO2 diagram with a CaO content of 60–80%. The SiO2 content in them is 15-30%, and their composition includes 1–15% Al2O3 and 5–14% FeO. The SEM-EDS method allowed us to understand the transformation of calcium silicate glass microspheres into C-S-H gel, which is the main component of the strengthening matrix. The results contribute to the data for development of models for predicting the effect of HCFA on the properties of composite binders.

Abstract: A Fe3O4/HNTs composite was synthesized, characterized by XRD, FTIR, SEM, and N2 adsorption-desorption, and was used for an ibuprofen adsorption and oxidation study. The response surface methodology (RSM) and Box-Behnken experimental designs were used. The effect of pH, contact time, IBU concentration, and Fe3O4/HNTs dosage on ibuprofen adsorption were evaluated. Additionally, adsorption isotherms and a kinetic study were performed. The effect of pH, H2O2 concentration, and Fe3O4/HNTs dosage for IBU oxidation were also studied. The results of ibuprofen adsorption on Fe3O4/HNTs indicate that adsorption was favored at acidic pH. The adsorption followed pseudo-second-order kinetics and a Freundlich isotherm. A 99.99% IBU oxidation and 99% mineralization were achieved at pH 7, Fe3O4/HNTs dosage of 1.5 g L-1, and 0.5 M H2O2. The Fe3O4/HNTs catalyst prepared in this study was efficient in removing aqueous ibuprofen through heterogeneous Fenton-like reaction.

Abstract: This study introduces a rational, template-free synthetic strategy for the scalable preparation of high-performance monodisperse spherical mesoporous silica particles (MSPs), engineered specifically as advanced heterogeneous catalytic supports. Leveraging Ostwald ripening as the core morphogenetic driver—rather than conventional organic structure-directing agents—the approach achieves both environmental compatibility and process robustness. Precise pH modulation to 8.0 using biocompatible organic acids (e.g., acetic or citric acid) enables controlled silica dissolution–reprecipitation kinetics, yielding MSPs with exceptional sphericity (PDI < 0.08), narrow size distribution, a specific surface area of up to 484 m²/g, uniform pore diameters centered at ~2 nm, and radially aligned, thermodynamically stabilized mesochannels—structural attributes that collectively satisfy stringent design criteria for high-efficiency catalytic carriers, including maximized active-site accessibility, minimized diffusion limitations, and mechanical resilience under reaction conditions. A systematic pH-screening study reveals a distinct structural transition: at pH < 7.5, incomplete condensation and suppressed ripening yield polydisperse aggregates with disordered worm-like porosity; at pH > 8.5, accelerated silicate dissolution induces particle coalescence and partial mesostructural degradation. Critically, pore ordering, channel dimensionality, surface area, and particle morphology are all quantitatively modulated by pH—establishing it as a master variable for hierarchical textural programming. This study compares the methoxychlor (MXC) degradation efficiency of polyhedral Bi2WO6 and MSP/Bi2WO6 under identical irradiation conditions to assess MSP’s catalytic impact. Mechanistic analysis of charge dynamics, interfacial electron transfer, and active species reveals how MSP enhances photocatalytic activity.

Abstract: UV−curable L(-)−borneol−functionalized antibacterial hydrogels for packaging of fresh−cut banana and cherry tomato (UV−LBs) were designed from L(-)−Borneol−Functionalized polyurethane acrylate prepolymers (LB−PUAs) and thiol–functionalized PVA (PVA–SH) by UV initiated thiol−ene click reaction. UV−LBs exhibit good thermal stability with Td5 in the range of 225−240 oC, high mechanical performance with the tensile strength and the elongation at break in the range of 1.38−2.05 MPa and 44.4−68.6%, respectively. The antibacterial efficiency of UV−LBs against S. aureus, E. coli, and M. albican can reach 67.4%, 75.6% and 83.7%, respectively. The storage time of fresh−cut banana and cherry tomato packaged can be extended from 12 h to 30 h, 4 d to 5 d, respectively.

Abstract: Background: A lean crystal engineering study was performed on early pre-clinical POLθ inhibitor MSC178 to enable sufficient exposure for high-dose PK studies. Methods: COSMOquick derived excess enthalpies in combination with toxicological assessment of co-formers were used for selection of four co-formers. Experimental crystallization trials were performed in a staged approach from 15 mg-scale over 50 mg upscale to final g-scale upscale of most promising co-crystal form with 2,4-DHBA. Results: 2,4-DHBA co-crystal form revealed a more enhanced and sustained supersaturation profile in biorelevant non-sink dissolution test compared to amorphous free base form as well as compared to 3,4-DHBA co-crystal form and 1,2-EDSA salt form. Moreover, 2,4-DHBA co-crystal form was shown to be physically stable in suspension vehicle for PK study. The high physical stability towards physical form conversion in the suspension vehicle as well as the more sustained supersaturation behavior in non-sink dissolution profile could be attributed to intrinsic features of the crystal structure as well as surface hydrophilicity assessment of the co-crystal particles, both suggesting that rather hydrophobic surfaces are present that aid to preferably attract stabilizing surfactants from the dissolution medium (taurocholate) and from the suspension vehicle (polysorbate, methocel), respectively. Successful upscale of the 2,4-DHBA co-crystal form was achieved in small g-scale, revealing mainly isotropic crystal growth in primary particles as well as pronounced tendency for isotropi-cally shaped dendrite-like secondary particles, both being favored by multi-dimensional hydrogen bonding network being present. Resulting favorable powder properties are also deemed highly promising for application in more sophisticated formulation vehicles such as Powder-In-Capsules for higher species animal PK studies. Excellent agreement was shown for extent of in-vitro supersaturation behavior and in-vivo exposure gain in high-dose PK study for the 2,4-DHBA co-crystal form vs amorphous free form. Conclu-sion: Co-crystal strategy can be successfully developed in early pre-clinical industrial re-search with lean methodologies to optimize sub-optimal phys.-chem. properties of a free base compound to achieve improved and less variable in-vivo exposure between animals in high-dose PK studies.

Abstract: The development of high-performance and sustainable carbon electrodes is increasingly important for next-generation supercapacitors, yet controlling heteroatom doping and hierarchical pore evolution in biomass-derived carbons remains a key challenge. Lignin, as an abundant aromatic biopolymer, offers a structurally rich platform for designing functional carbons, but its rigid cross-linked architecture limits precise pore regulation and efficient nitrogen incorporation. In this work, nitrogen-doped hierarchical porous carbons were engineered from enzymatically treated lignin through a synergistic urea-assisted nitrogen doping and KOH activation strategy. The urea–KOH co-activation drives the coordinated evolution of micropores and mesopores. This approach yields an optimized carbon material possessing a high BET surface area of 2569 m².g⁻¹, an interconnected micro–mesoporous architecture, and a favorable distribution of pyridinic, pyrrolic, and graphitic nitrogen species. The engineered pore hierarchy enhances ion transport kinetics, whereas nitrogen functionalities introduce redox-active sites and improve interfacial wettability. As a result, selected material delivers a high specific capacitance of 221 F g⁻¹ at 0.5 A g⁻¹, strong rate capability with 84.4% retention at 20 A g⁻¹, and excellent cycling durability with 90.7% capacitance retention after 50,000 cycles. This study demonstrates a mechanistically informed, scalable pathway for coupling enzymatic structural regulation with chemical activation, offering a sustainable route for transforming lignin into high-value carbon electrodes suitable for advanced supercapacitor applications.

Abstract: Ice adhesion on exposed structures remains a major operational challenge, motivating the search for passive, material-based anti-icing strategies. Molecular Dynamics offers a controlled way to investigate ice-surface interactions beyond the limits of experimental setups. In this work, we develop a simulation framework to model the impact of solid hexagonal ice droplets on metallic substrates. Ice impacts are simulated across a range of velocities (10–120 m/s), temperatures (120–250 K), and face-centered cubic surface materials (gold, copper, silver, aluminum, and nickel). Using LAMMPS, mW water force field, EAM/Alloy metal potentials, and Lennard-Jones water-surface interactions, we quantify phase evolution through angular order parameter and quasi-liquid layer measurements, complemented by the CHILL+ algorithm in OVITO. By isolating all external factors, we show that melting increases with velocity and temperature and correlates with substrate properties: metals with high thermal diffusivity and low Young’s modulus tend to de-crease post-collision ice melting. The ratio of the former to the latter, a derived index of merit Υ, significantly correlates with melting percentage and identifies silver as the most effective anti-ice material examined. Statistical analyses strongly suggest that these surface properties influence interfacial melting, supporting the use of this modelling framework for screening and designing anti-icing materials.

Abstract: This study investigates the development of mechanically reprocessed poly(lactic acid) (rPLA) films reinforced with rice husk (RH) and rice husk biochar (RHB) to evaluate their processing behavior, key functional properties, and disintegration under composting conditions. rPLA was produced from PLA through an additional processing cycle to simulate the valorization of industrial PLA waste, while composites containing 1 and 3 wt.% RH or RHB were manufactured by melt extrusion followed by compression molding process. Reprocessing increased the melt flow index and decreased intrinsic viscosity and viscosimetric molecular weight, evidencing the occurrence of chain scission during mechanical reprocessing. The addition of RH slightly restricted melt flow and promoted higher surface hydrophilicity, whereas RHB showed a filler-loading-dependent effect on melt flow and increased surface hydrophobicity at low content, consistent with its carbonized and less polar nature. Both RH and RHB promote nucleating effect, with increased crystallinity in RHB-containing films, and tensile tests showed that filler incorporation mainly reduced ductility compared with unfilled rPLA, while stiffness and strength was maintained or exhibited more moderate variations. Despite these contrasting trends in surface properties and thermo-mechanical performance, all formulations achieved complete disintegration within 21 days under composting conditions at laboratory scale level. Overall, RH and RHB provide a viable route to valorize agro-industrial residues in rPLA films and to tune structure–property relationships within circular-economy framework.

Abstract: This work presents a comprehensive investigation of the thermal decomposition of nickel oxalate dihydrate as a precursor for the synthesis of porous NiO, with particular emphasis on microstructural formation and evolution. The transformations occurring at successive stages of the reaction were examined using SEM, TEM, N₂ adsorption, TG–DSC–MS, and in situ powder XRD, enabling the mechanisms of pore formation to be elucidated. The decomposition results in the formation of a porous pseudomorph composed of NiO nanoparticles with an average size of approximately 4 nm. The resulting microstructure exhibits hierarchical porous architecture. During dehydration, macropores are generated as a result of crystal fragmentation into blocks several hundred nanometers in size. Subsequent oxalate decomposition leads to the formation of mesoporous aggregates composed of nanometer-sized particles. The factors governing the parameters of the porous microstructure are analyzed. Owing to its hierarchical pore system, the obtained NiO demonstrates significant potential for applications in heterogeneous catalysis, gas sensing, electrodes for super-capacitors and Li-ion batteries, and photoelectrochemical devices. In such systems, macropores facilitate mass transport by reducing diffusion resistance, while mesopores provide a high accessible surface area for adsorption and catalytic reactions.

Abstract: This study investigates the corrosion behavior of a WC-6Co cemented carbide (94 wt% WC, 6 wt% Co) in acidic (pH 2) and alkaline (pH 13) aqueous environments, with em-phasis on implications for reconditioning processes. Both electrolytes, characterized by their high electrical conductivity, are used in industrial electrochemical stripping of PVD coatings. While acidic electrolytes are already established for stripping coatings from hard metal substrates, the influence of the alkaline electrolytes on substrate integrity remains insufficiently explored, especially considering the implication of reconditioning. Elec-trochemical characterization was performed using potentiodynamic polarization method, followed by surface analysis via SEM, EDX, and laser confocal microscopy. Two distinct corrosion mechanisms were identified, corresponding to the respective pH conditions and consistent with predictions from Pourbaix diagrams. In acidic media, cobalt dissolution occurred alongside strong passivation of tungsten through the formation of WO₃. In contrast, under alkaline conditions, tungsten formed soluble tungstate ions (WO₄²⁻), leading to progressive leaching of WC grains, while cobalt exhibited passivation via a Co(OH)₂ layer, mitigating binder degradation. Within the scope of this work, electrolytes used for electrochemical stripping were examined. The investigation focused on their corrosive impact on uncoated hard-metal substrates under electrochemical stripping conditions, as these become exposed to both the electrolyte and applied potential once the coating is removed. Coating removal itself was not addressed. A key finding is that oxide or hydroxide passivation on cemented carbides does not inherently guarantee protection. Its effectiveness depends strongly on the nature of the formed layer. In the acidic elec-trolyte, pseudo-passivation by formation of WO₃ layer initially inhibits corrosion but leads to significant material loss upon its breakdown. These findings provide valuable guidance for the application of cemented carbides in electrochemical stripping processes used for PVD coating removal.

Abstract: This study presents a distribution-optimized mesostructure estimation method for modeling near-surface aggregate size distributions in concrete by optimizing the spatial arrangement of polydisperse spherical aggregates with respect to formwork boundaries. The approach is based on minimizing the deviation between a generated cumulative aggregate volume function and an idealized linear target function corresponding to a constant area fraction along the specimen depth. To enable efficient computation for systems containing a large number of aggregates, grain size classes derived from the grading curve are represented using symmetric Beta distributions, allowing each group to be described by a single shape parameter. The resulting optimization problem is solved using a derivative-free Powell algorithm. The method inherently captures wall effects, leading to a migration of smaller aggregates toward the specimen boundaries to compensate for geometric constraints of bigger aggregates. Experimental validation was performed by determining the depth-dependent mean bulk density of a concrete cube using incremental surface grinding combined with high-resolution 3D laser scanning. The optimized mesostructure shows strong agreement with measured density profiles, significantly improving over a non-optimized distribution. Furthermore, increasing aggregate volume fractions intensify near-surface accumulation of fine particles. The proposed method provides a computationally efficient framework for incorporating wall effects into mesoscale concrete models.