This paper reports the successful fabrication of a new nanofibrous membrane, F-PI/PAN, through electrospinning of polyacrylonitrile (PAN) and fluorinated polyimide (F-PI). The nanofibrous membrane exhibits comprehensive properties for high-temperature filtration and robust PM_2.5 (particulate matter with an aerodynamic equivalent diameter of 2.5 microns or less) removal. The introduction of F enhances the hydrophobicity of the PI. The relationship between the hydrophobic performance and the filtration performance of particles is investigated. The chemical group of the composite membrane was demonstrated using FITR, while the surface morphology was investigated using field emission scanning electron microscopy. The TGA results indicated good thermal stability at 300 °C. Various ratios of F-PI membranes were prepared to characterize the change in properties, with the optimal mass ratio of F-PI being 20 wt%. As the proportion of F-PI increases, its mechanical and filtration efficiency properties and hydrophobicity become stronger. The contact angle reaches its maximum of 128 ± 5.2° when PAN:F-PI = 6:4. Meanwhile, when PAN:F-PI = 8:2, the filtration efficiency reaches 99.4 ± 0.3%, and the elongation at break can reach 76%. The fracture strength can also reach 7.1 MPa, 1.63 times that of the pure PAN membrane. Full article

Recovering cobalt from waste batteries is crucial for resource recycling and environmental protection. Here, MOF-OH, a Zr-based MOF, was synthesized and merged into a polyacrylonitrile (PAN) matrix to create MOF-OH-PAN nanofibers (NFs). These NFs showed a high cobalt ion adsorption capacity of 33.1 mg/g, retaining over 90% of the capacity after six cycles. The adsorption mechanism involves Co(II) surface diffusion followed by strong bonding with functional groups. This technology enables efficient cobalt recovery from waste batteries, supporting reuse and reducing resource depletion and environmental pollution. The study provides insights into waste battery resource management, highlighting environmental and economic benefits and contributing to green resource recovery and circular economy initiatives. Full article

Within the dynamic realm of social media, the proliferation of harmful content can significantly influence user engagement and emotional health. This study presents an in-depth analysis that bridges diverse domains, from examining the aftereffects of personal online attacks to the intricacies of online trolling. By leveraging an AI-driven framework, we systematically implemented high-precision attack detection, psycholinguistic feature extraction, and sentiment analysis algorithms, each tailored to the unique linguistic contexts found within user-generated content on platforms like Reddit. Our dataset, which spans a comprehensive spectrum of social media interactions, underwent rigorous analysis employing classical statistical methods, Bayesian estimation, and model-theoretic analysis. This multi-pronged methodological approach allowed us to chart the complex emotional responses of users subjected to online negativity, covering a spectrum from harassment and cyberbullying to subtle forms of trolling. Empirical results from our study reveal a clear dose–response effect; personal attacks are quantifiably linked to declines in user activity, with our data indicating a 5% reduction after 1–2 attacks, 15% after 3–5 attacks, and 25% after 6–10 attacks, demonstrating the significant deterring effect of such negative encounters. Moreover, sentiment analysis unveiled the intricate emotional reactions users have to these interactions, further emphasizing the potential for AI-driven methodologies to promote more inclusive and supportive digital communities. This research underscores the critical need for interdisciplinary approaches in understanding social media’s complex dynamics and sheds light on significant insights relevant to the development of regulation policies, the formation of community guidelines, and the creation of AI tools tailored to detect and counteract harmful content. The goal is to mitigate the impact of such content on user emotions and ensure the healthy engagement of users in online spaces. Full article

Background: Immune checkpoint inhibition has revolutionized melanoma therapy, but many patients show primary or secondary resistance. Biomarkers are, therefore, urgently required to predict response prior to the initiation of therapy and to monitor disease progression. Methods: In this prospective study, we analyzed the serum C-C motif chemokine ligand 20 (CCL20) concentration using an enzyme-linked immunosorbent assay. Blood was obtained at baseline before the initiation of immunotherapy with anti-PD-1 monotherapy or Nivolumab and Ipilimumab in advanced melanoma patients (stages III and IV) enrolled at the University Medical Center Hamburg-Eppendorf. The CCL20 levels were correlated with clinico-pathological parameters and disease-related outcomes. Results: An increased C-C motif chemokine ligand 20 (CCL20) concentration (≥0.34 pg/mL) at baseline was associated with a significantly impaired progression-free survival (PFS) in the high-CCL20 group (3 months (95% CI: 2–6 months) vs. 11 months (95% CI: 6–26 months)) (p = 0.0033) and could be identified as an independent negative prognostic factor for PFS in univariate (Hazard Ratio (HR): 1.98, 95% CI 1.25–3.12, p = 0.004) and multivariate (HR: 1.99, 95% CI 1.21–3.29, p = 0.007) Cox regression analysis, which was associated with a higher risk than S100 (HR: 1.74). Moreover, high CCL20 levels were associated with impaired overall survival (median OS not reached for low-CCL20 group, p = 0.042) with an HR of 1.85 (95% CI 1.02–3.37, p = 0.043) in univariate analysis similar to the established prognostic marker S100 (HR: 1.99, 95% CI: 1.02–3.88, p = 0.043). Conclusions: CCL20 may represent a novel blood-based biomarker for the prediction of resistance to immunotherapy that can be used in combination with established strong clinical predictors (e.g., ECOG performance score) and laboratory markers (e.g., S100) in advanced melanoma patients. Future prospective randomized trials are needed to establish CCL20 as a liquid biopsy-based biomarker in advanced melanoma. Full article

To avoid delay in oncological treatment, a 6-weeks norm for time to treatment has been agreed on in the Netherlands. However, the impact of the COVID-19 pandemic on health systems resulted in reduced capacity for regular surgical care. In this study, we investigated the impact of the COVID-19 pandemic on time to treatment in surgical oncology in the Netherlands. Methods: A population-based analysis of data derived from five surgical audits, including patients who underwent surgery for lung cancer, colorectal cancer, upper gastro-intestinal, and hepato-pancreato-biliary (HPB) malignancies, was performed. The COVID-19 cohort of 2020 was compared to the historic cohorts of 2018 and 2019. Primary endpoints were time to treatment initiation and the proportion of patients whose treatment started within 6 weeks. The secondary objective was to evaluate the differences in characteristics and tumour stage distribution between patients treated before and during the COVID-19 pandemic. Results: A total of 14,567 surgical cancer patients were included in this study, of these 3292 treatments were started during the COVID-19 pandemic. The median time to treatment decreased during the pandemic (26 vs. 27 days, p < 0.001) and the proportion of patients whose treatment started within 6 weeks increased (76% vs. 73%, p < 0.001). In a multivariate logistic regression analysis, adjusting for patient characteristics, no significant difference in post-operative outcomes between patients who started treatment before or after 6 weeks was found. Overall, the number of procedures performed per week decreased by 8.1% during the pandemic. This reduction was most profound for patients with stage I lung carcinoma and colorectal carcinoma. There were fewer patients with pulmonary comorbidities in the pandemic cohort (11% vs. 13%, p = 0.003). Conclusions: Despite pressure on the capacity of the healthcare system during the COVID-19 pandemic, a larger proportion of surgical oncological patients started treatment within six weeks, possibly due to prioritisation of cancer care and reductions in elective procedures. However, during the pandemic, a decrease in the number of surgical oncological procedures performed in the Netherlands was observed, especially for patients with stage I disease. Full article

Neuroblastoma presents with two patterns of disease: locoregional or systemic. The poor prognostic risk factors of locoregional neuroblastoma (LR-NB) include age, MYCN or MDM2-CDK4 amplification, 11q, histology, diploidy with ALK or TERT mutations, and ATRX aberrations. Anti-GD2 immunotherapy has significantly improved the outcome of high-risk (HR) NB and is mostly effective against osteomedullary minimal residual disease (MRD), but less so against soft tissue disease. The question is whether adding anti-GD2 monoclonal antibodies (mAbs) benefits patients with HR-NB compounded by only soft tissue. We reviewed 31 patients treated at SJD for HR-NB with no osteomedullary involvement at diagnosis. All tumors had molecular genetic features of HR-NB. The outcome after first-line treatment showed 25 (80.6%) patients achieving CR. Thirteen patients remain in continued CR, median follow-up 3.9 years. We analyzed whether adding anti-GD2 immunotherapy to first-line treatment had any prognostic significance. The EFS analysis using Cox models showed a HR of 0.20, p = 0.0054, and an 80% decrease in the risk of relapse in patients treated with anti-GD2 immunotherapy in the first line. Neither EFS nor OS were significantly different by CR status after first-line treatment. In conclusion, adding treatment with anti-GD2 mAbs at the stage of MRD helps prevent relapse that unequivocally portends poor survival. Full article

Cryptofaunal nematodes, those living on the hard substrate of the coral reefs, are largely unknown in terms of diversity and assemblage structure. We described nematode assemblages at seven sites spanning about 200 km along Jardines de La Reina, a well-preserved reef system in the Greater Antilles. We identified about 3000 nematodes, mostly of the families Desmodoridae and Chromadoridae; the most abundant species were Croconema cinctum, Desmodora communis, and Euchromadora vulgaris. The regional richness was moderate with 70 observed species (0.95 confidence interval: 65–75 species) and 75 extrapolated species (0.95 CI: 68–83 species). This richness was lower than in other reef biotopes, maybe reflecting evolutionary constraints due to interactions with stony corals. The local expected richness at 100 individuals was similar among sites, with a median of 26 species (0.95 CI: 20–34 species), and likely caused by diversification rate and evolutionary time acting at the same pace on populations. The taxonomic β-diversity was high and without differences among sites (median: 0.85; 0.95 CI: 0.33–1), probably due to significant substrate heterogeneity at 10-cm scale. The prevalence of replacement over richness difference suggests that local processes (e.g., environmental filtering and competition) contribute more to β-diversity than niche availability, which would be largely similar across the reef terraces. Contrary to our expectations, no gradient of assemblage structure occurred, nor significant effect of benthic cover on nematodes. However, nematode functional structure showed a conservative set of biological traits reflecting adaptations to hydrodynamic regime: armed oral cavity/intermediate colonizing capability/ornamented cuticles/conical tail. Our results provide insights about the taxonomic and functional diversity of nematodes and highlight the vast knowledge gaps about the processes ruling the meiofauna community structure in coral reefs. Full article

The time-varying gravity field models derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission suffer from pronounced longitudinal stripe errors in the spatial domain. A potential way to mitigate such errors is to combine GRACE data with observations from other sources. In this study, we investigate the impacts on GRACE monthly gravity field solutions of incorporating the GPS data collected by the Gravity Field and Steady-State Ocean Circulation Explorer (GOCE) mission. To that end, we produce GRACE/GOCE combined monthly gravity field solutions through combination on the normal equation level and compare them with the GRACE-only solutions, for which we have considered the state-of-the-art ITSG-Grace2018 solutions. Analysis in the spectral domain reveals that the combined solutions have a notably lower noise level beyond degree 30, with cumulative errors up to degree 96 being reduced by 31%. A comparison of the formal errors reveals that the addition of GOCE GPS data mainly improves (near-) sectorial coefficients and resonant orders, which cannot be well determined by GRACE alone. In the spatial domain, we also observe a significant reduction by at least 30% in the noise of recovered mass changes after incorporating the GOCE GPS data. Furthermore, the signal-to-noise ratios of mass changes over 180 large river basins were improved by 8–20% (dependent on the applied Gaussian filter radius). These results demonstrate that the GOCE GPS data can augment the GRACE monthly gravity field solutions and support a future GOCE-type mission for tracking more accurate time-varying gravity fields. Full article

The potential of artificial intelligence (AI) and machine learning (ML) in agriculture for improving crop yields and reducing the use of water, fertilizers, and pesticides remains a challenge. The goal of this work was to introduce Hyperfidelis, a geospatial software package that provides a comprehensive workflow that includes imagery visualization, feature extraction, zonal statistics, and modeling of key agricultural traits including chlorophyll content, yield, and leaf area index in a ML framework that can be used to improve food security. The platform combines a user-friendly graphical user interface with cutting-edge machine learning techniques, bridging the gap between plant science, agronomy, remote sensing, and data science without requiring users to possess any coding knowledge. Hyperfidelis offers several data engineering and machine learning algorithms that can be employed without scripting, which will prove essential in the plant science community. Full article

Multiple datasets related to pond and marine aquaculture have been published using diverse remote sensing technologies, yet a comprehensive dataset detailing spatial distribution on both land and sea sides is lacking. Firstly, a meticulous comparison of datasets which we selected related to aquaculture ponds and marine, ensuring consistency in trends. Subsequently, the datasets published by our team were edited and integrated to illustrate aquaculture activities on both sides of China’s coastal zone. Finally, a spatial differentiation of coastal aquaculture in major provinces was analyzed. This analysis also utilizes the types of coastline and statistical data, guiding coordinated resource management efforts. The results unveil a distinctive spatial distribution pattern, concentrating aquaculture in the northern regions—Bohai Sea, Jiangsu, Fujian, and Pearl River coasts in Guangdong. The provinces rich in aquaculture resources, such as Shandong, Guangdong, and Liaoning, exhibit extensive coastlines. However, remote sensing monitoring suggests an underestimation of Liaoning’s marine aquaculture compared to statistical yearbook data. Furthermore, southern provinces like Guangdong and Fujian exhibit significantly higher aquaculture output than Liaoning. Zhejiang leads in fishing output. The paper outlines the future development direction of coastal aquaculture, emphasizing a strategic, integrated land–sea approach for sustainable development. Full article

Short-range elastic backscatter lidar (SR-EBL) systems are remote sensing instruments for studying low atmospheric boundary layer processes. This work presents a field campaign oriented to filling the gap between the near-surface aerosol processes regarding aerosol radiative properties and connecting them with the atmospheric boundary layer (ABL), centering attention on the residual layer and the ABL transition periods. A Colibri Aerosol Lidar (CAL) instrument, based on the short-range lidar with high spatio-temporal resolution, was used for the first time in the ACTRIS AGORA facility (Andalusian Global Observatory of the Atmosphere) in Granada (Spain). This study showed the possibility of combining lidar and in situ measurements in the lowermost 150 m. The results address, on the one hand, the characterization of the short-range lidar for developing a method to find the calibration constant of the system and to correct the incomplete overlap to further data exploitation. On the other hand, relevant radiative properties such as the temporal series of the aerosol lidar ratio and extinction coefficient were quantified. The campaign was divided in three different periods based on the vehicular emission peak in the early mornings, namely, before, during, and after the emission peak. For before and after the emission peak data classification, aerosol properties presented closer values; however, large variability was obtained after the emission peak reaching the maximum values of extinction and a lidar ratio up to 51.5 ± 11.9 ${\left(\mathrm{Mm}\right)}^{-1}$ and 36.0 ± 10.5 sr, respectively. During the emission peaks, the values reached for extinction and lidar ratio were up to 136.8 ± 26.5 ${\left(\mathrm{Mm}\right)}^{-1}$ and 119.0 ± 22.7 sr, respectively. Full article

The proliferation of invasive plant species poses a significant ecological threat, necessitating effective mapping strategies for control and conservation efforts. Existing studies employing unmanned aerial vehicles (UAVs) and multispectral (MS) sensors in complex natural environments have predominantly relied on classical machine learning (ML) models for mapping plant species in natural environments. However, a critical gap exists in the literature regarding the use of deep learning (DL) techniques that integrate MS data and vegetation indices (VIs) with different feature extraction techniques to map invasive species in complex natural environments. This research addresses this gap by focusing on mapping the distribution of the Broad-leaved pepper (BLP) along the coastal strip in the Sunshine Coast region of Southern Queensland in Australia. The methodology employs a dual approach, utilising classical ML models including Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM) in conjunction with the U-Net DL model. This comparative analysis allows for an in-depth evaluation of the performance and effectiveness of both classical ML and advanced DL techniques in mapping the distribution of BLP along the coastal strip. Results indicate that the DL U-Net model outperforms classical ML models, achieving a precision of 83%, recall of 81%, and F1–score of 82% for BLP classification during training and validation. The DL U-Net model attains a precision of 86%, recall of 76%, and F1–score of 81% for BLP classification, along with an Intersection over Union (IoU) of 68% on the separate test dataset not used for training. These findings contribute valuable insights to environmental conservation efforts, emphasising the significance of integrating MS data with DL techniques for the accurate mapping of invasive plant species. Full article

This study investigates the mechanical properties of titanium carbide/aluminum metal matrix composites (AMMCs) using both experimental and computational methods. Through accumulative roll bonding (ARB) and cryorolling (CR) processes, AA1050 alloy surfaces were reinforced with TiCp particles to create the Al–TiCp composite. The experimental analysis shows significant improvements in tensile strength, yield strength, elastic modulus, and hardness. The finite element analysis (FEA) simulations, particularly the microstructural modeling of RVE−1 (the experimental case model), align closely with the experimental results observed through scanning electron microscopy (SEM). This validation underscores the accuracy of the computational models in predicting the mechanical behavior under identical experimental conditions. The simulated elastic modulus deviates by 5.49% from the experimental value, while the tensile strength shows a 6.81% difference. Additionally, the simulated yield strength indicates a 2.85% deviation. The simulation data provide insights into the microstructural behavior, stress distribution, and particle–matrix interactions, facilitating the design optimization for enhanced performance. The study also explores the influence of particle shapes and sizes through Representative Volume Element (RVE) models, highlighting nuanced effects on stress–strain behavior. The microstructural evolution is examined via transmission electron microscopy (TEM), revealing insights regarding grain refinement. These findings demonstrate the potential of Al–TiCp composites for lightweight applications. Full article

Modified asphalt binders are still considered important in asphalt pavement. However, the comprehensive use of various modifiers is limited due to storage stability issues. Moreover, there is a scarcity of detailed analyses regarding the degree of separation for asphalt binders among each method despite the utilization of various methods to assess the storage stability of binders. Therefore, a comprehensive analysis was conducted to assess the storage stability of asphalt binder modified with a crumb rubber modifier (CRM) and styrene–isoprene–styrene (SIS), utilizing five evaluation factors following the ASTM D7173 guidelines based on four mixing methods (A: high-shear mixing method, B: low-speed agitating method, C: high-shear mixing method + low mixing method, D: low-speed agitating method + low mixing method). To produce the modified asphalt binder, the proportions of the CRM were 5% and 10% for each binder, and 10% SIS was added to all binders. The results in this study convey that (1) the addition of the modifier led to an increase in G*/sin δ with different mixing methods, but using mixing methods (C and D) for a relatively long time resulted in a lower G*/sin δ, indicating suboptimal performance; (2) through the multiple stress creep recovery (MSCR), rheological properties of J_nr and % rec exhibited trends similar to G*/sin δ evaluation, highlighting an improved elastic recovery with a higher modifier content; (3) storage stability assessment revealed consistent trends in high-shear mixing groups (A and C), while low-speed mixing groups (B and D) exhibited an elevated separation index (SI), suggesting a sensitivity to modification conditions; (4) evaluation using the MSCR method indicated that % rec with a 3.2 kPa load is effective for the sensitive assessment of binder storage stability and J_nr showed a limited sensitivity across varying loads, advocating for % rec for precise evaluation; and (5) despite permitting various tests, achieving consistent results remains challenging. Future research should explore diverse modifiers and optimal evaluation methods to enhance knowledge of binder behavior and separation dynamics. Full article

This research study focused on the effect of adding boric acid to epoxy resin in order to obtain a composite material with improved properties and performance. To this end, a fine powder of boric acid (H₃BO₃) was introduced into epoxy resin in different amounts, i.e., 0.5 g, 1.0 g, and 1.5 g. As the matrix of the epoxy composites, styrene-modified epoxy resin based on bisphenol A (BPA) (Epidian 53) was used. It was cross-linked with two types of curing agents, i.e., an amine (ET) and a polyamide (PAC). The mechanical properties of the obtained epoxy composites (in terms of compressive strength, compressive modulus, and compressive strain) were determined at room temperature in order to assess the effect of the addition of boron acid and of the type of curing agent employed to cure the epoxy on these characteristics. Calorimetric measurements were made to highlight any changes in the glass transition temperature (Tg) as a result of the addition of boric acid to epoxy resin. Finally, flammability tests were performed on both Epidian 53/PAC and Epidian 53/ET epoxy composites to analyze their fire behavior and consequently establish the effectiveness of the selected additive as a flame retardant. Full article

The objective of this research is to enhance the high-temperature antirutting and antiaging characteristics of bioasphalt. In this study, silica fume (SF) was selected to modify bioasphalt. The dosage of bio-oil in bioasphalt was 5%, and the dosage of SF was 2%, 4%, 6%, 8%, and 10% of bioasphalt. The high- and low-temperature characteristics, aging resistance, and temperature sensitivity of Bio + SF were evaluated by temperature sweep (TS), the multiple stress creep recovery (MSCR) test, the bending beam rheology (BBR) test, and the viscosity test. Meanwhile, the road behavior of the Bio + SF mixture was evaluated using the rutting test, low-temperature bending beam test, freeze–thaw splitting test, and fatigue test. The experimental results showed that the dosage of SF could enhance the high-temperature rutting resistance, aging resistance, and temperature stability of bioasphalt. The higher the dosage of SF, the more significant the enhancement effect. However, incorporating SF weakened bioasphalt’s low-temperature cracking resistance properties. When the SF dosage was less than 8%, the low-temperature cracking resistance of Bio + SF was still superior to that of matrix asphalt. Compared with matrix asphalt mixtures, the dynamic stability, destructive strain, freeze–thaw splitting strength ratio, and fatigue life of 5%Bio + 8%SF mixtures increased by 38.4%, 49.1%, 5.9%, and 68.9%, respectively. This study demonstrates that the development of SF-modified bioasphalt could meet the technical requirements of highway engineering. Using SF and bio-oil could decrease the consumption of natural resources and positively reduce environmental pollution. Full article

Lead-free K_0.5Bi_0.5TiO₃ (KBT) ceramics with high density (~5.36 g/cm³, 90% of X-ray density) and compositional purity (up to 90%) were synthesized using a solid-state reaction method. Strongly condensed KBT ceramics revealed homogenous local microstructures. TG/DSC (Thermogravimetry-differential scanning calorimetry) techniques characterized the thermal and structural stability of KBT. High mass stability (>0.4%) has proven no KBT thermal decomposition or other phase precipitation up to 1000 °C except for the co-existing K₂Ti₆O₁₃ impurity. A strong influence of crystallites size and sintering conditions on improved dielectric and non-linear optical properties was reported. A significant increase (more than twice) in dielectric permittivity (ε_R), substantial for potential applications, was found in the KBT-24h specimen with extensive milling time. Moreover, it was observed that the second harmonic generation (λ_SHG = 532 nm) was activated at remarkably low fundamental beam intensity. Finally, spectroscopic experiments (Fourier transform Raman and far-infrared spectroscopy (FT-IR)) were supported by DFT (Density functional theory) calculations with a 2 × 2 × 2 supercell (P4₂mc symmetry and C4v point group). Moreover, the energy band gap was calculated (E_g = 2.46 eV), and a strong hybridization of the O-2p and Ti-3d orbitals at E_g explained the nature of band-gap transition (Γ → Γ). Full article

In the realm of high-tech materials and energy applications, accurately measuring the transient heat flow at media boundaries and the internal thermal conductivity of materials in harsh heat exchange environments poses a significant challenge when using conventional direct measurement methods. Consequently, the study of photothermal parameter reconstruction in translucent media, which relies on indirect measurement techniques, has crucial practical value. Current research on reconstructing photothermal properties within participating media typically focuses on single-objective or time-invariant properties. There is a pressing need to develop effective methods for the simultaneous reconstruction of time-varying thermal flow fields and internal thermal conductivity at the boundaries of participating media. This paper introduces a computational model based on the numerical simulation theory of internal heat transfer systems in participating media, stochastic particle swarm optimization algorithms, and Kalman filter technology. The model aims to enable the simultaneous reconstruction of various thermal parameters within the target medium. Our results demonstrate that under varying levels of measurement noise, the inversion results for different target parameters exhibit slight oscillations around the true values, leading to a reduction in reconstruction accuracy. However, overall, the model demonstrates robustness and accuracy in ideal conditions, validating its effectiveness. Full article

Metakaolin-based geopolymers have substantial potential as replacements for cement, but their relatively inferior mechanical properties restrict their application. This paper aims to enhance the mechanical properties of metakaolin-based geopolymers by incorporating appropriate amounts of calcium sources. CaCO₃, Ca(OH)₂, and CaSO₄ are three types of calcium sources commonly found in nature and are widely present in various industrial wastes. Thus, the effects of these three calcium sources on the performance of metakaolin-based geopolymers were studied. Through the analysis of the mechanical properties, heat-release behavior during hydration, hydration products, and microstructure of geopolymers, the effectiveness of the aforementioned calcium sources in improving the performance of metakaolin-based geopolymer was evaluated, and the mechanisms of action were elucidated. The results indicate that the pozzolanic reaction between CH and MK could promote MK hydration and increase the proportion of CASH gel in the hydration products, thereby facilitating the setting of the geopolymer and enhancing its strength. CS could react with the active aluminates in MK to form ettringite, thus forming a higher early strength. CC had a lower reactivity with MK and does not improve the performance of MK-based geopolymers. Full article

To investigate the impact of Al and Nb elements on the formation of a protective oxide layer on the surface of Fe-35Ni-20Cr-xAl-yNb (x = 0, 2, 4, 6 wt.%; y = 0, 1, 2 wt.%) alloys, their oxidation behavior was examined at 1000 °C, 10⁻¹⁷ atm. and 10⁻²⁵ atm. oxygen pressure, and the oxidation mechanism was analyzed by Factsage and Pandat calculations. Enhancing the Al content at 10⁻¹⁷ atm. inhibited the generation of FeCr₂O₄ on the alloy surface and increased the Al content in the M₂O₃ layer. When the Al content exceeded 6 wt.%, the oxide film partially peeled off. It was found that the addition of Nb increased the activity of Cr and Al and decreased the activity of Ni and Fe and promoted the formation of Al₂O₃, and the appearance of Nb₂O₅ in the subsurface layer increased the density of the oxide film. In addition, under an oxygen pressure of 10⁻²⁵ atm., the only protective layer on the surface of the alloy comprised of Al₂O₃. The experimental results demonstrated that the Fe-35Ni-20Cr-4Al-2Nb alloy generated a continuous and dense Al₂O₃ protective film, and the reduction in oxygen pressure and the addition of Nb elements were favorable for selective external oxidation of Al₂O₃. Full article

(1-x)(Ba_0.75Sr_0.1Bi_0.1)(Ti_0.9Zr_0.1)O₃-x(Sb_0.5Li_0.5)TiO₃ (abbreviated as BSBiTZ-xSLT, x = 0.025, 0.05, 0.075, 0.1) ceramics were prepared via a conventional solid-state sintering method under different sintering temperatures. All BSBiTZ-xSLT ceramics have predominantly perovskite phase structures with the coexistence of tetragonal, rhombohedral and orthogonal phases, and present mainly spherical-like shaped grains relating to a liquid-phase sintering mechanism due to adding SLT and Bi₂O₃. By adjusting the sintering temperature, all compositions obtain the highest relative density and present densified micro-morphology, and doping SLT tends to promote the growth of grain size and the grain size distribution becomes nonuniform gradually. Due to the addition of heterovalent ions and SLT, typical relaxor ferroelectric characteristic is realized, dielectric performance stability is broadened to ~120 °C with variation less than 10%, and very long and slim hysteresis loops are obtained, which is especially beneficial for energy storage application. All samples show extremely fast discharge performance where the discharge time t_0.9 (time for 90% discharge energy density) is less than 160 ns and the largest discharge current occurs at around 30 ns. The 1155 °C sintered BSBiTZ-0.025SLT ceramics exhibit rather large energy storage density, very high energy storage efficiency and excellent pulse charge–discharge performance, providing the possibility to develop novel BT-based dielectric ceramics for pulse energy storage applications. Full article

The simultaneous increase in strength and plasticity of aluminum and its alloys at cryogenic temperatures has been shown in previous research, but the deformation mechanism was still unclear. Therefore, the purpose of this investigation was to reveal the relationship between slip behavior and mechanical response at low temperatures. A quasi-in situ scanning electron microscope was used to observe the evolution of slip bands in the selected aluminum single crystals with two typical orientations at 25 °C, −100 °C, and −180 °C. The results showed that irrespective of orientation, the density of the slip plane was increased with the decline in temperature, which inhibited slip localization and significantly improved plasticity and work hardening. In detail, at RT, the slip bands were widening until the micro-cracks were generated, causing early failure during deformation. When the temperature was decreased to −180 °C, the slip plane density was increased, and the deformation was more homogenous. Moreover, the slip mode was influenced by orientation and temperature. In particular, a single slip system was activated in the sample with the [112] orientation at all the temperatures investigated. Multiple slip systems were found to activate at 25 °C and −100 °C, and only the primary slip system was activated in the sample with [114] orientation at −180 °C. These findings deepen the understanding of slip behavior at cryogenic temperatures, providing new insights into the deformation mechanism of aluminum and its alloys. Full article