University of Atacama

Designing cost-effective, highly competent, and resilient transition metal-based electrodes has gained significant research interest towards energy storage and conversion. Herein, we present a rational design of a ZnO/CoNi2S4 heterojunction nanoarray electrode by incorporating ZnO nanoflakes with transition metal sulfides to construct a multifunctional hybrid array. Extensive investigations along with theoretical analysis revealed the nano- engineered interfaces promote interfacial charge redistribution, thereby accelerating rapid charge-transfer kinetics. Furthermore, the hetero-hybrid architecture affords ample of electroactive sites and strengthens the synergy created due to interfacial electronic interaction. The redistribution of interfacial electrons between ZnO and CoNi2S4 promotes robust synergistic effects from multimetallic centers, optimizing the overall electronic structure for superior catalytic activity. As a result, the ZnO/CoNi2S4 electrocatalyst delivered small overpotentials of 102.2 mV for HER and 198.7 mV for OER at 10 mA cm- 2, along with excellent long-term stability. The assembled hybrid electrolyzer requires only 1.56 V to achieve 10 mA cm- 2. In addition, this electrode also exhibits an ultrahigh specific capacity of 1319.0C g- 1 at 1 A g-1 and retained over 94% of its value after 15,000 cycles at 10 A g-1. This hybrid supercapattery combination (ZnO/CoNi2S4//activated carbon) achieved a high energy density of 62.7 W h kg-1 at 2100 W kg-1, preserving 84.8% specific capacity retention after prolonged cycling, highlighting its great potential for multifunctional energy storage applications. This study constructs an effective pathway for fabricating progressive electrodes with superior performance.

Arsenic (As) and mercury (Hg) are trace elements of major environmental and public health concern. Their relevance is due to their well-documented toxicological effects. In rapidly urbanizing port-industrial cities, soil contamination by these elements represents a critical challenge. This situation compromises sustainable urban development and environmental governance. This study had three main objectives: First, to evaluate the contamination status of As and Hg in urban soils using multiple geochemical indices; Second, to assess the potential human health risks associated with exposure in the urban environment of Talcahuano; Third, to identify the relative contributions of geogenic and anthropogenic sources based on spatial distribution patterns. A total of 420 soil samples were collected. These included 140 topsoil samples (TS; 0-10 cm), 140 subsoil samples (SS; 10-20 cm), and 140 deep-soil samples (DS; 150 cm). Arsenic concentrations were determined using hydride-generation atomic absorption spectrometry (HG-AAS). Mercury concentrations were measured by cold-vapour atomic absorption spectrometry (CV-AAS). Median As concentrations were 2.7 mg kg-1 in TS, 3.1 mg kg-1 in SS, and 2.5 mg kg-1 in DS. The corresponding median Hg concentrations were 0.2 mg kg-1 in TS and 1.4 mg kg-1 in both SS and DS. Spatial distribution maps were generated through ordinary kriging interpolation. Geochemical baseline values were calculated using the median + 2 & times; MAD approach. The resulting baseline values were 7.8 mg kg-1 for As and 3.6 mg kg-1 for Hg. Contamination assessment was conducted using the geoaccumulation index (Igeo), enrichment factor (EF), and contamination factor (Cf). Results indicate that most soils are classified as uncontaminated. Enrichment levels were minimal and contamination factors were low. Nevertheless, isolated outliers were identified. These included one significantly enriched As sample and several moderately enriched or slightly contaminated Hg samples. Human health risk assessment incorporated the Hazard Index (HI) and Total Carcinogenic Risk (TCR). Results indicate that neither non-carcinogenic nor carcinogenic risks exceed acceptable thresholds at any investigated soil depth. Spatial analysis suggests that anthropogenic activities are the dominant sources of As and Hg in the study area. Traffic emissions and industrial activities appear to be the primary contributors.

Defect engineering provides an effective means of tuning the charge transport in ferrimagnetic oxides. Here, we present a comparative study of M-type (BaFe12O19, SrFe12O19) and W-type (BaCo2Fe16O27, BaZn2Fe16O27) hexaferrites synthesized via sol-gel auto-combustion. Using XRD, SEM, TEM, dielectric measurements, and current-voltage measurements, lattice defects are linked to charge-carrier conduction pathways. XRD confirmed phase-pure hexagonal structures with nanocrystallite sizes of 33-36 nm. High-resolution TEM revealed edge dislocations and planar strain fields in BaFe12O19, along with stacking-fault arrays in BaCo2Fe16O27, which create localized strain-induced potential fluctuations. The presence of dislocations and oxygen-vacancy defects promotes field-assisted thermionic emission with trap densities of similar to 1016 cm-3 and earlier onset of space-charge-limited conduction. Dielectric spectroscopy revealed Maxwell-Wagner relaxation, while the J-E analysis indicated that Schottky emission dominates, with secondary space-charge-limited conduction occurring at high electric fields. The results demonstrate that oxygen-vacancy and strain-related defects serve as active transport mediators, providing a pathway to tune the electrical properties of ferrites for multifunctional electronic and energy applications.

Context. Symbiotic stars are interacting binary systems composed of a red giant transferring material to a hot compact star, typically a white dwarf. These systems are crucial for studying stellar evolution, accretion processes, mass transfer, and a variety of complex astrophysical phenomena. However, there is a significant discrepancy between the number of confirmed symbiotic stars (similar to 300) and the estimated population in the Milky Way (1.2 & times; 10(3) - 1.5 & times; 10(4)), suggesting that a large fraction remains undetected. Aims. To address this issue, we propose the identification of new symbiotic stars through the application of machine-learning techniques. Our approach combines multiband photometric data from Gaia DR3, 2MASS, and WISE, together with parallax measurements and the pseudo-equivalent width of H alpha, to effectively distinguish symbiotic candidates from other stellar populations. Methods. We trained a random forest model using a sample of 166 confirmed S-type symbiotic stars and a control sample of 1600 nonsymbiotic stars. To mitigate class imbalance and improve the classification performance, we applied the synthetic minority oversampling technique (SMOTE). The model achieved an F-1 score of 89% for the symbiotic class. Results. We applied our model to a catalog of approximately 2.5 million stars selected based on photometric colors consistent with those of S-type symbiotic stars. We identified 990 candidates in this sample with a classification probability of at least 70%. To refine the selection, we applied statistically and physically motivated cuts based on effective temperature, surface gravity, and metallicity and complemented the cuts by SkyMapper photometry. This process yielded 12 high-confidence candidates, characterized by cool temperatures, low surface gravities, solar-like metallicity, H alpha emission, luminosities ranging from moderate to high, and ultraviolet excesses consistent with the properties of S-type symbiotic systems. Conclusions. To evaluate the model performance, we applied it to a validation set of symbiotic stars recently confirmed in the literature. We recovered 92.3% of them. This result supports the effectiveness and generalizability of our classification approach.

Determining nickel extraction during the roasting-reduction stage of the Caron process is an essential tool for controlling the metallurgical efficiency of the technology. This study evaluated the performance of a new semi-empirical kinetic model for predicting nickel extraction during the reduction of lateritic ores predominantly composed of iron oxides and oxyhydroxides in multiple-hearth furnaces. To achieve this, the lateritic ore was characterised by scanning electron microscopy (SEM) before and after the reduction process. The temperature in hearth six was varied between 495 and 780 degrees C by adjusting the post-combustion air supply. The proposed model demonstrated high predictive accuracy for nickel extraction, with absolute and residual errors below 1.70% and 1.15%, respectively. The findings emphasise the importance of controlling metallurgical efficiency through mathematical models that incorporate key technological variables and the kinetic behaviour of the process.