Search Results (8)

Precipitation hardening is the primary mechanism for strengthening 6xxx series aluminium alloys. The characteristics of the precipitates play a crucial role in determining the mechanical properties. In particular, predicting yield strength (YS) based on microstructure is experimentally complex and costly because its key variables, such as precipitate radius, spacing, and volume fraction (VF), are difficult to measure. Physics-based models have emerged to tackle these complications utilising advancements in simulation environments. Nevertheless, pure physics-based models require numerous free parameters and ongoing debates over governing equations. Conversely, purely data-driven models struggle with insufficient datasets and physical interpretability. Moreover, the complex dynamics between internal model variables has led both approaches to adopt heuristic optimisation methods, such as the Powell or Nelder–Mead methods, which fail to exploit valuable gradient information. To overcome these issues, we propose a gradient-based optimisation for the Kampmann–Wagner Numerical (KWN) model, incorporating CALPHAD (CALculation of PHAse Diagrams) and a strength model. Our modifications include facilitating differentiability via smoothed approximations of conditional logic, optimising non-linear combinations of free parameters, and reducing computational complexity through a single size-class assumption. Model calibration is guided by a mean squared error (MSE) loss function that aligns the YS predictions with interpolated experimental data using L2 regularisation for penalising deviations from a purely physics-based modelling structure. A comparison shows that the gradient-based adaptive moment estimation (ADAM) outperforms the gradient-free Powell and Nelder–Mead methods by converging faster, requiring fewer evaluations, and yielding more physically plausible parameters, highlighting the importance of calibration techniques in the modelling of 6xxx series precipitation hardening. Full article

To understand the fluid evolution of Permian pegmatites, three pegmatite fields of the Austroalpine basement units located in the Rappold Complex at St. Radegund, the Millstatt Complex, and the Polinik Complex were investigated. To achieve this goal, fluid inclusions trapped in the magmatic accessories of garnet, tourmaline, spodumene, and beryl were studied using host mineral chemistry combined with fluid inclusion microthermometry and Raman spectrometry. Taking into account the previous work by the authors on pegmatite fields in the Koralpe and Texel Mountains, Permian fluid was determined to have evolved from two stages: Stage 1 is characterized by the homogeneous entrapment of two cogenetic immiscible fluid assemblages, a CO₂-N₂ ± CH₄-rich and a low-saline H₂O-rich fluid. Both fluids are restricted to inclusions in the early-magmatic-garnet-core domains of the Koralpe Mountains. Stage 2 is linked with the CO₂-N₂-CH₄-H₂O-NaCl-CaCl₂ ± MgCl₂ fluid preserved as an inclusion in all the pegmatite accessories of the KWNS. It represents the mechanical mixture of the stage 1 fluid caused by compositional changes along the solvus, which is typical for a hydrothermal vein environment process. Increasing X_CH4±N2 proportions from the eastern toward the western pegmatite fields of the KWNS results in a tectonic model that includes magmatic redox-controlled fluid flow along deep crustal normal faults during the anatexis of metasediments in Permian asymmetric graben structures. Because of a high number of solids within the inclusions as well as their irregular shapes, post-entrapment modifications have caused density changes that have to be considered with caution. However, the conditions in the range of 6–8 kbar at >670 °C for stage 1 and ca. 4 kbar at <670 °C for stage 2 represent the best approximations to explain the uprise of a two-stage Permian fluid associated with accessory mineral crystallization in close relation to fractionating melt. Full article

This research delves into a case study of a photovoltaic (PV) energy community, leveraging empirical data to explore the integration of renewable energy sources and storage solutions. By evaluating energy generation and consumption patterns within real-world energy communities (a nominal generation capacity of 33 kWn) in Gipuzkoa, Spain, from May 2022 to May 2023, this study comprehensively examines operational dynamics and performance metrics. This study highlights the critical role of energy consumption patterns in facilitating the integration of renewable energy sources and underscores the importance of proactive strategies to manage demand fluctuations effectively. Against the backdrop of rising energy costs and environmental concerns, renewable energies and storage solutions emerge as compelling alternatives, offering financial feasibility and environmental benefits within energy communities. This study emphasizes the necessity of research and development efforts to develop efficient energy storage technologies and the importance of economic incentives and collaborative initiatives to drive investments in renewable energy infrastructure. The analyzed results provide valuable insights into operational dynamics and performance metrics, further advancing our understanding of their transformative potential in achieving a sustainable energy future. Specifically, our study suggests that storage capacity should ideally support an average annual capacity of 23%, with fluctuations observed where this capacity may double or reduce to a minimum in certain months. Given the current market conditions, our findings indicate the necessity of significant public subsidies, amounting to no less than 67%, to facilitate the installation of storage infrastructure, especially in cases where initial investments are not covered by the energy community. Full article

The Kampmann and Wagner numerical model was adapted in MATLAB to predict the precipitation and growth of Al₃Sc precipitates as a function of starting concentration and heat-treatment steps. This model was then expanded to predict the strengthening in alloys using calculated average precipitate number density, radius, etc. The calibration of this model was achieved with Bayesian optimization, and the model was verified against experimentally gathered hardness data. An analysis of the outputs from this code allowed the development of optimal heat treatments, which were validated experimentally and proven to result in higher final strengths than were previously observed. Bayesian optimization was also used to predict the optimal heat-treatment temperatures in the case of limited heat-treatment times. Full article

An integrated precipitation and strengthening model, incorporating the effect of precipitate morphology on precipitation kinetics and yield strength, is developed based on a modified Kampmann–Wagner numerical (KWN) framework with a precipitate shape factor. The optimized model was used to predict the yield strength of Al-Si-Mg-Mn casting alloys produced by vacuum high pressure die casting at various aged (T6) conditions. The solid solution strengthening contribution of Mn, which is a common alloying element to avoid die soldering, was included in the model to increase the prediction accuracy. The experimental results and simulations show good agreement and the model is capable of reliably predicting yield strength of aluminum die castings after T6 heat treatment, providing a useful tool to tailor heat treatment for a variety of applications. Full article

The rapid increase in the emergence of antifungal-resistant Candida albicans strains is becoming a serious health concern. Because antimicrobial peptides (AMPs) may provide a potential alternative to conventional antifungal agents, we have synthesized a series of peptides with a varying number of lysine and tryptophan repeats (KW_n-NH₂). The antifungal activity of these peptides increased with peptide length, but only the longest KW₅ peptide displayed cytotoxicity towards a human keratinocyte cell line. The KW₄ and KW₅ peptides exhibited strong antifungal activity against C. albicans, even under conditions of high-salt and acidic pH, or the addition of fungal cell wall components. Moreover, KW₄ inhibited biofilm formation by a fluconazole-resistant C. albicans strain. Circular dichroism and fluorescence spectroscopy indicated that fungal liposomes could interact with the longer peptides but that they did not release the fluorescent dye calcein. Subsequently, fluorescence assays with different dyes revealed that KW₄ did not disrupt the membrane integrity of intact fungal cells. Scanning electron microscopy showed no changes in fungal morphology, while laser-scanning confocal microscopy indicated that KW₄ can localize into the cytosol of C. albicans. Gel retardation assays revealed that KW₄ can bind to fungal RNA as a potential intracellular target. Taken together, our data indicate that KW₄ can inhibit cellular functions by binding to RNA and DNA after it has been translocated into the cell, resulting in the eradication of C. albicans. Full article

Control of the homogenization process is important in obtaining high extrudability and desirable properties in 6xxx aluminum alloys. Three consecutive steps of the process chain were modeled. Microsegregation arising from solidification was described with the Scheil–Gulliver model. Dissolution of Mg₂Si, Si (diamond) and β-AlFeSi (β-Al₅FeSi) to α-AlFeSi (α-Al₁₂(FeMn)₃Si) transformation during homogenization have been described with a CALPHAD-based multicomponent diffusion Dual-Grain Model (DGM), accounting for grain size inhomogeneity. Mg₂Si precipitation and associated strengthening during homogenization cooling were modeled with the Kampmann–Wagner Numerical (KWN) precipitation framework. The DGM model indicated that the fractions of β-AlFeSi and α-AlFeSi exhibit an exact spatial and temporal correspondence during transformation. The predictions are in good agreement with experimental data. The KWN model indicated the development of a bimodal particle size distribution during homogenization cooling, arising from corresponding nucleation events. The associated strengthening, arising from solid solution and precipitation strengthening, was in good agreement with experimental results. The proposed modeling approach is a valuable tool for the prediction of microstructure evolution during the homogenization of 6xxx aluminum alloys, including the often-neglected part of homogenization cooling. Full article

The presence of lysine (Lys) or arginine (Arg) and tryptophan (Trp) are important for the antimicrobial effects of cationic peptides. Therefore, we designed and synthesized a series of antimicrobial peptides with various numbers of Lys (or Arg) and Trp repeats [(KW and RW)_n-NH₂, where n equals 2, 3, 4, or 5]. Antifungal activities of these peptides increased with chain length. Light microscopy demonstrated that longer peptides (n = 4, 5) strongly inhibited in vitro growth of Fusarium solani, and Fusarium oxysporum, at 4–32 μM. Furthermore, longer peptides displayed potent fungicidal activities against a variety of agronomical important filamentous fungi, including F. solani and F. oxysporum, at their minimal inhibitory concentrations (MICs). However, RW series peptides showed slightly higher fungicidal activities than KW peptides against the two strains. Taken together, the results of this study indicate that these short peptides would be good candidates for use as synthetic or transgenic antifungal agents. Full article