University of Antofagasta

Silvered-glass mirrors represent the state of the art in concentrated solar thermal systems. Compared with polymer- or aluminum-based reflector materials, these mirrors offer clear technological advantages, including high solar reflectance of approximately 94.5% combined with low angular scattering (<3 mrad). In addition, they have become increasingly cost-effective, with prices as low as approximately €12 m−2, depending primarily on production volume and energy costs. Silvered-glass mirrors have also demonstrated excellent long-term durability under field conditions. For instance, mirrors installed in the Solar Energy Generating Systems (SEGS) power plants constructed in the United States during the 1980s have operated for more than 30 years with only minimal reflectance losses.The high corrosion resistance of silvered-glass mirrors is largely attributed to passivating, lead-containing pigments used in their protective coatings. However, the paint and printing ink industries have been pursuing the elimination of lead from their formulations at national, European, and international levels to reduce exposure to toxic and carcinogenic lead compounds. The mirror industry is therefore likely to be affected by forthcoming restrictions or bans on lead-based pigments, following regulatory measures already implemented in the PVC sector. These developments have resulted in a significant contraction of the lead pigment market and a substantial increase in material costs. Consequently, the development of lead-free protective coating systems for solar mirrors is required, both to address environmental and health concerns and to mitigate the risk associated with potential regulatory bans.In this study, lead-free protective coatings for solar mirrors were developed and applied to silvered and coppered glass substrates under both laboratory-scale and industrial manufacturing conditions. The resulting samples were evaluated under outdoor exposure at eight distinct sites for periods of up to eight years, as well as under accelerated aging in climatic chambers. Their corrosion resistance was benchmarked against that of lead-containing reference coatings, and the corresponding service lifetimes were estimated.

The development of efficient and durable electrocatalysts requires precise control over noble-metal utilization and catalyst morphology to enhance hydrogen evolution reaction kinetics and mechanical stability. In this study, palladium was electrodeposited onto titanium substrates by potentiostatic pulse electrocrystallization to tailor nanoparticle size and catalytic performance. Deposition parameters, including precursor concentration, applied potential, and pulse duration (ton/toff), were systematically varied, including charge-controlled experiments. Morphological analysis revealed nanogranular coatings with different degrees of surface continuity, compatible with a three-dimensional Volmer–Weber growth mode. Electrochemical characterization in alkaline medium showed apparent Tafel slopes in the range of 167–277 mV·dec⁻¹ and significant variations in exchange current density, with overpotentials as low as 178 mV at 10 mA cm⁻². An apparent electrochemically accessible area was estimated from palladium oxide reduction charge, allowing comparison between geometric and area-normalized exchange current densities. The results indicate that enhanced hydrogen evolution reaction performance may arise either from increased accessible surface area or from more efficient utilization of active sites. These findings demonstrate that pulse-controlled electrodeposition enables tuning of both morphology and electrocatalytic behavior, providing practical guidelines for the design of Pd-based electrodes for alkaline electrolysis.

Natural hypobaric hypoxia is a defining feature of high-altitude environments and may alter human motor strategies during repetitive work tasks. This study investigated whether acute exposure and 48 h of continuous natural hypobaric hypoxia modify movement variability during a standardized, submaximal upper-limb reaching task in healthy lowlanders. Ten adults performed a 180 s paced reaching–retrieving task (1 Hz) under three conditions: normobaric normoxia at sea level, acute natural hypobaric hypoxia within 3 h of arrival at 3,600 m, and after 48 h of continuous exposure at 3,600 m. Wrist triaxial acceleration was recorded and processed offline to quantify linear variability metrics (mean acceleration, acceleration standard deviation, root mean square) and nonlinear metrics (sample entropy, maximum Lyapunov exponent) across movement axes, directions, and phases. Multivariate analyses showed significant effects of condition (p < 0.001), axis (p < 0.001), and phase (p = 0.007), as well as significant condition-by-axis (p = 0.016) and condition-by-phase (p = 0.003) interactions. Compared with sea level, hypobaric hypoxia increased acceleration magnitude in task-relevant axes and reduced variability in non-primary axes and early movement phases, whereas nonlinear metrics remained unchanged. These findings suggest that natural hypobaric hypoxia selectively redistributes linear movement variability during repetitive upper-limb performance.

The VIP collaboration operates a Broad-Energy Germanium (BEGe) detector at the Gran Sasso National Laboratory to measure radiation in the few-keV to 100 keV range, aiming to search for spontaneous collapse-induced radiation and atomic transitions violating the Pauli Exclusion Principle. Here, we present a machine-learning-based upgrade for the BEGe detector of an event-selection strategy aimed at improving the efficiency in detecting low-energy events down to 10 keV. The method employs a denoising autoencoder to suppress electronic and microphonic noises and reconstruct pulse shapes, followed by a convolutional neural network that classifies waveforms as normal single-site events or anomalous events. The workflow was validated on a dataset comprising more than 20,000 waveforms recorded in 2021. The classifier achieves a receiver operating characteristic (ROC) curve with an area under the curve (AUC) of 0.99 and an accuracy of 95%. Applying this procedure lowers the minimum detectable energy of the final spectrum to approximately 10 keV. It also yields a measurable enhancement in spectral quality, including an improvement of about 14% in the signal-to-background ratio and improvement of the energy resolution for the characteristic Pb and Bi gamma lines. These developments enhance the sensitivity of the BEGe detector to rare low-energy signals and provide a scalable framework for future precision tests of quantum foundations in low-background environments.

Flotation circuits typically incorporate grinding stages, yet mathematical models for these processes often operate on different principles, leading to misalignment in circuit design. Building on a previously established grinding model for flotation performance, this research introduces significant advances to develop a more comprehensive and industrially relevant framework. The primary innovation is the integration of mechanical entrainment and gangue recovery into the kinetic model, distinguishing between species captured by true flotation and those carried to the surface despite being non-hydrophobic. We developed a robust set of grinding-mill equations based on first-order kinetics to describe the mass-fraction transformation of both true-flotation and entrainment species. To ensure practical applicability, a systematic experimental and modeling methodology for parameter adjustment is introduced, providing a clear sequence for identifying breakage rate constants and flotation kinetic parameters. The proposed strategy was validated using two distinct case studies: an expanded analysis of a copper sulfide ore (ore A) and a new case involving significant gangue entrainment (ore B). The results demonstrate that the model accurately predicts species kinetics, providing a high-fidelity, cost-effective tool to optimize mineral recovery and prevent economic losses from overgrinding in industrial processing plants.