Barium hexaferrite (BaFe12O19 or BaF) is a hard ferrite with high coercivity and strong magnetization. In this work, flexible magnetic rubber composites were developed by incorporating waste-derived BaFe12O19 (W-BaF) filler, synthesized from steel industry waste, into natural rubber (NR) at loadings of 0–60 phr. The vulcanization characteristics, mechanical behaviors, and magnetic properties of the NR composites were evaluated and compared with those of NR composites containing commercial BaFe12O19 (C-BaF) filler. It was found that both W-BaF and C-BaF powders showed a plate-like hexagonal morphology. However, differences in particle size and morphology between W-BaF and C-BaF powders resulted in distinct dispersion behaviors of the fillers within the NR matrix. Consequently, the NR/BaF composites containing W-BaF filler exhibited differences in vulcanization characteristics, mechanical behavior, and magnetic properties compared with those containing C-BaF filler. Although the addition of W-BaF filler enhanced the magnetic properties of NR, its effect was less pronounced than that of the C-BaF filler. This finding suggests that a higher loading of W-BaF filler may be necessary to achieve the desired magnetic performance in flexible magnetic rubber composites for practical applications. Notably, this work found that the NR composites containing W-BaF exhibited better retention of tensile properties during thermal aging than those containing C-BaF. These findings demonstrate the feasibility of upcycling locally available steel industry waste into BaFe12O19 filler through local synthesis and processing, providing a waste valorization strategy for developing magnetic NR composites with potential applications as bonded permanent magnets in refrigerator gaskets and small motors.
The Mae-Kok River in northern Thailand is a transboundary river system influenced by multiple upstream and downstream anthropogenic pressures. This study presents a multi-matrix assessment of metal contamination by integrating river water, soils, and sediments with enrichment factor (EF) analysis, multivariate statistical approaches, and arsenic speciation. Concentrations of arsenic, lead, and nickel in river water frequently exceeded international guideline values, while EF results indicate substantial anthropogenic enrichment, particularly in the upstream reach of the river. Hierarchical cluster analysis, principal component analysis, and positive matrix factorization identify coherent groupings of elements (As, U, Co, Ni, and Cu) characterized by polymetallic geochemical associations. These patterns are compatible with upstream anthropogenic inputs involving sulfide-rich materials but do not uniquely identify specific point sources. In contrast, zinc and cadmium exhibit enrichment patterns and statistical character distinct from the polymetallic element group, consistent with diffuse anthropogenic influences such as agricultural activities, although these associations are indirect. Differences in clustering between river water and soil-sediment matrices highlight contrasting metal behavior between short-term aqueous transport and longer-term depositional accumulation. Synchrotron-based X-ray absorption spectroscopy shows that arsenic occurs predominantly as arsenate [As(V)], with localized enrichment of arsenite [As(III)] indicating spatial variability in redox conditions. Chromium is present mainly as Cr(III), suggesting limited mobility under prevailing environmental conditions. Overall, the results indicate a multi-source contamination regime shaped by overlapping upstream and local anthropogenic influences. This integrated approach improves understanding of metal behavior in transboundary river systems and provides a scientific basis for future monitoring and management efforts.
KherveFitting is a software written in Python and designed for fitting X-ray photoelectron spectroscopy (XPS) data. It provides a user-friendly graphical interface for researchers in materials science and surface analysis, offering features that include multiple background subtraction methods, various peak fitting models, and automated multipeak fitting with customisable constraints. This software aims to fill a gap in the market for XPS analysis tools, providing a freely available solution for users. This paper describes the software architecture and its theoretical background, including fitting algorithms and peak models. Its performance is validated by directly comparing quantification accuracy and peak fitting capabilities against established commercial software packages, demonstrating robust and reliable results across diverse test cases including ionic liquids, conducting oxides, and rare earth materials.
Vanadium-based oxides are among the most promising cathodes for aqueous zinc-ion batteries (AZIBs), yet their practical deployment is hindered by severe vanadium dissolution and inefficient interfacial charge/ion transport. Herein, L-tartaric acid (L-TA) is made to self-assemble on a preconstructed V2O5/V3O7 & sdot;H2O (V2V3) heterointerface, forming a hydrogen bond interfacial layer (HB-V2V3). The hydrogen-bond network reinforces interfacial cohesion and induces oriented dipoles, which cooperate with the heterojunction's built-in electric field to enhance electronic coupling and accelerate Zn2+ transport. Meanwhile, the strengthened V-O interactions and regulated interfacial hydration environment effectively suppress vanadium dissolution and preserve lattice integrity. Functioning as a noninvasive and compliant molecular "sheath", it regulates the local chemical environment while preserving the host lattice. As a result, HB-V2V3 delivers a reversible capacity of 464.53 mAh g-1 at 0.1 A g-1 within 0.2-1.6 V and exhibits outstanding durability, retaining 95.5% after 500 cycles at 2.0 A g-1 and 93.1% after 2200 cycles at 5.0 A g-1. It also maintains approximately 81% of its capacity after 300 cycles at 1 A g-1 in a pouch-cell configuration. These results establish hydrogen-bond-driven interfacial modulation as an effective and broadly applicable route to stabilize vanadium cathodes and enhance the performance of AZIBs.
Capturing and utilizing CO2 is a practical approach to achieving carbon cycling and reducing carbon emissions. Despite advancements in CO2 hydrogenation catalysts and the enhancement of catalyst efficiency through metal doping, the structure-activity relationship (SAR) of metal-doped catalysts in CO2 hydrogenation remains unclear. This is crucial for developing highly active catalysts. In this study, we report a La3+ -doped NiAlLa1-RMO catalyst with a CO2 conversion of 65.6 % and CH4 selectivity of 99.9 % at 200 degrees C and a GHSV of 48000 mL/(gcat & sdot;h). Notably, a series of characterizations (including in-situ DRIFTS), and DFT calculations demonstrate that La addition enhances H2 splitting and CO2 adsorption, improving the electron transfer efficiency at Ni-La-Al2O3 interfaces. This adjustment promotes the m-HCOO* intermediate, facilitating low-temperature CO2 methanation via formote formation. Instructively, the enhanced performance is attributed to a tri-synergistic catalysis of the regulated hydrotalcite material effect involving strong metal-support interaction, enriched H2 splitting and CO2 adsorption sites, and regulated intermediates due to La3+ doping.
