Facultad de Ingeniería

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https://repositorio.uft.cl/handle/20.500.12254/2325

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A comprehensive review of smart energy management systems for photovoltaic power generation utilizing the internet of things
(KeAi chinese roots global impact, 2025-04-25) Rao, Challa Krishna; Sahoo, Sarat Kumar; Yanine, Fernando
Renewable energy represents the most reliable and widely recognized solution for meeting the escalating global energy demands. The optimization of solar energy generation necessitates a strong focus on predictive maintenance and advanced deployment methodologies. To enhance solar power utilization, Internet of Things enabled solar monitoring systems have been proposed for real-time data acquisition and analytics, facilitating performance forecasting and ensuring consistent power output. A critical challenge in demand-side energy management lies in optimizing the integration of renewable resources while maintaining cost efficiency and minimizing energy losses. Therefore, strategic planning for the integration of renewable energy sources is imperative. Intelligent energy management systems play a pivotal role in optimizing energy distribution, particularly in scenarios with high grid dependency. Cloud computing infrastructures address the complexities and scalability challenges posed by expanding smart grids, enabling real-time data processing and adaptive energy control mechanisms. This study explores the practical implementation of energy management system in industrial settings and research domains, both of which serve as key stakeholders in advancing smart energy solutions. A comprehensive review of internet of things applications in photovoltaic power generation highlights key research objectives and technological developments in the field. The evolving landscape of internet of things driven innovations presents numerous research opportunities, including the formulation of performance evaluation metrics and the development of novel optimization techniques. Additionally, the growing emphasis on energy management within intelligent architectural frameworks underscores the necessity for deeper investigations into adaptive control strategies and system interoperability. This ongoing research is essential for driving advancements in internet of things enabled energy solutions and enhancing the efficiency of smart grid ecosystems.
A new dynamic, secondary-memory metric index
(Red de Universidades Nacionales con carreras en Informática (RedUNCI); Universidad Nacional de la Plata, 2024-10-07) Paredes, Rodrigo; Reyes, Nora Susana; Figueroa, Karina; Hoffhein, Manuel
Metric space searching addresses the problem of efficient similarity searching in many applications. Although promising, the metric space approach is still immature in several aspects that are well established in traditional databases. Particularly, most indexing schemes are not dynamic, that is, few of them tolerate insertion of elements at reasonable cost over an existing index with none or mild performance degrading; and even less of them work efficiently in secondary memory. The List of Clusters (LC) is a competitive index in main memory. We introduce a new dynamic, secondary-memory variant of the LC. Our new index handles well the secondary memory scenario and is competitive with the state of the art, becoming a useful alternative in a wide range of database applications. Also, our ideas are applicable to other secondary-memory indexes, where it is possible to control the disk page occupation.
A review of IoT enabled intelligent smart energy management for photovoltaic power forecasting and generation
(Elsevier, 2026-01-05) Rao, Challa Krishna; Sahoo, Sarat Kumar; Yanine, Fernando
Renewable energy has emerged as one of the most reliable and widely accepted approaches to address the rising global energy requirements. Among these, solar power development requires focused attention on both maintenance strategies and application methods. To enhance solar energy utilization, Internet of Things (IoT)-enabled monitoring frameworks have been designed, allowing real-time collection and analysis of solar parameters for predicting efficiency and ensuring stable electricity generation. A major concern in demand-side energy regulation lies in utilizing renewable sources effectively while keeping costs manageable and minimizing unnecessary consumption. Hence, careful planning of renewable resource integration is essential. Advanced energy management platforms play a crucial role in supervising energy distribution, especially in scenarios where heavy dependence on the grid exists. The complexities and opportunities introduced by expanding grid networks can be efficiently managed through cloud-based technologies. This work emphasizes the practical application of energy management systems in both industrial operations and academic research, treating them as key stakeholders in the energy sector. The investigation offers a detailed evaluation of IoT applications in photovoltaic power systems and highlights the promising future avenues available to researchers. These include developing new benchmarks to measure IoT performance and refining existing systems through innovative approaches. Furthermore, there is an increasing demand for comprehensive studies on intelligent energy frameworks in smart infrastructures. Such research is critical to advancing IoT-driven applications and sustaining continuous progress in this domain.
A review of IoT-based smart energy solutions for photovoltaic systems
(Springer Nature, 2025-08-11) Rao, Challa Krishna; Sahoo, Sarat Kumar; Yanine, Fernando
Harnessing renewable energy stands out as the most reliable and widely accepted method to address the surging global energy needs. In particular, advancing solar energy systems requires focused efforts in operational upkeep and practical deployment. To optimize solar output, Internet of Things enabled monitoring frameworks have been introduced, enabling data collection and analysis for performance evaluation and consistent energy delivery. A core obstacle in managing energy from the consumer side lies in leveraging green power sources efficiently while keeping expenses in check and avoiding excessive energy usage. As a result, thoughtful planning is essential when integrating alternative energy technologies. Smart energy systems critically optimize consumption amid growing grid reliance. Cloud computing resolves challenges and unlocks opportunities in modern power networks. This work examines energy coordination tools' dual role in industrial operations and academic research, demonstrating their synergistic value in advancing energy efficiency and grid resilience through technological and theoretical innovation. The investigation covers comprehensive evaluations of IoT’s role in solar power generation. Emerging IoT developments open new pathways for scholarly exploration, including the formulation of evaluation standards and the pursuit of novel improvement strategies. Furthermore, deeper investigations into intelligent energy systems within smart infrastructures are increasingly necessary. Such efforts are critical for enriching the knowledge base of IoT-driven solutions and promoting steady technological progress. Articulo WoS y SCOPUS Q2 El aprovechamiento de las energías renovables destaca como el método más fiable y ampliamente aceptado para hacer frente al creciente demanda energética mundial. En particular, el avance de los sistemas de energía solar requiere esfuerzos específicos en el mantenimiento operativo y la implementación práctica. Para optimizar la producción solar, se han introducido marcos de supervisión habilitados para el Internet de las cosas, que permiten la recopilación y el análisis de datos para la evaluación del rendimiento y el suministro constante de energía. Uno de los principales obstáculos en la gestión de la energía desde el lado del consumidor radica en aprovechar las fuentes de energía verde de manera eficiente, al tiempo que se controlan los gastos y se evita el uso excesivo de energía. Por lo tanto, es esencial una planificación cuidadosa a la hora de integrar tecnologías de energía alternativa. Los sistemas energéticos inteligentes optimizan de manera crítica el consumo en medio de una creciente dependencia de la red eléctrica. La computación en la nube resuelve los retos y abre nuevas oportunidades en las redes eléctricas modernas. Este trabajo examina la doble función de las herramientas de coordinación energética en las operaciones industriales y la investigación académica, demostrando su valor sinérgico en la promoción de la eficiencia energética y la resiliencia de la red eléctrica a través de la innovación tecnológica y teórica. La investigación abarca evaluaciones exhaustivas del papel del IoT en la generación de energía solar. Los nuevos avances en el IoT abren nuevas vías para la exploración académica, incluida la formulación de normas de evaluación y la búsqueda de nuevas estrategias de mejora. Además, cada vez es más necesario profundizar en la investigación de los sistemas energéticos inteligentes dentro de las infraestructuras inteligentes. Estos esfuerzos son fundamentales para enriquecer la base de conocimientos de las soluciones impulsadas por el IoT y promover un progreso tecnológico constante.
A review of IoT-based smart energy solutions for photovoltaic systems.
(Springer Nature, 2025-12-10) Rao, Challa Krishna; Sahoo, Sarat Kumar; Yanine, Fernando
Harnessing renewable energy stands out as the most reliable and widely accepted method to address the surging global energy needs. In particular, advancing solar energy systems requires focused efforts in operational upkeep and practical deployment. To optimize solar output, Internet of Things enabled monitoring frameworks have been introduced, enabling data collection and analysis for performance evaluation and consistent energy delivery. A core obstacle in managing energy from the consumer side lies in leveraging green power sources efficiently while keeping expenses in check and avoiding excessive energy usage. As a result, thoughtful planning is essential when integrating alternative energy technologies. Smart energy systems critically optimize consumption amid growing grid reliance. Cloud computing resolves challenges and unlocks opportunities in modern power networks. This work examines energy coordination tools’ dual role in industrial operations and academic research, demonstrating their synergistic value in advancing energy efficiency and grid resilience through technological and theoretical innovation. The investigation covers comprehensive evaluations of IoT’s role in solar power generation. Emerging IoT developments open new pathways for scholarly exploration, including the formulation of evaluation standards and the pursuit of novel improvement strategies. Furthermore, deeper investigations into intelligent energy systems within smart infrastructures are increasingly necessary. Such efforts are critical for enriching the knowledge base of IoT-driven solutions and promoting steady technological progress.
A review of IoT-Enabled Intelligent Smart Energy Management for Photovoltaic Power Forecasting and Generation
(KeAi chinese roots global impact, 2025-11-09) Rao, Challa Krishna; Sahoo, Sarat Kumar; Yanine, Fernando
Renewable energy has emerged as one of the most reliable and widely accepted approaches to address the rising global energy requirements. Among these, solar power development requires focused attention on both maintenance strategies and application methods. To enhance solar energy utilization, Internet of Things (IoT)-enabled monitoring frameworks have been designed, allowing real-time collection and analysis of solar parameters for predicting efficiency and ensuring stable electricity generation. A major concern in demand-side energy regulation lies in utilizing renewable sources effectively while keeping costs manageable and minimizing unnecessary consumption. Hence, careful planning of renewable resource integration is essential. Advanced energy management platforms play a crucial role in supervising energy distribution, especially in scenarios where heavy dependence on the grid exists. The complexities and opportunities introduced by expanding grid networks can be efficiently managed through cloud-based technologies. This work emphasizes the practical application of energy management systems in both industrial operations and academic research, treating them as key stakeholders in the energy sector. The investigation offers a detailed evaluation of IoT applications in photovoltaic power systems and highlights the promising future avenues available to researchers. These include developing new benchmarks to measure IoT performance and refining existing systems through innovative approaches. Furthermore, there is an increasing demand for comprehensive studies on intelligent energy frameworks in smart infrastructures. Such research is critical to advancing IoT-driven applications and sustaining continuous progress in this domain. Aspectos destacados • En el sector energético, es necesario un mecanismo operativo cooperativo integrado que tenga en cuenta la entidad de la oferta y la demanda de energía para reducir el desajuste. • La tarea operativa de gestión de la energía busca el desarrollo de un sistema de gestión energética inteligente (SEMS) económico y eficiente. Además, el despliegue de algoritmos de negociación de energía con capacidad de comunicación fiable es esencial para reducir el consumo total de energía y, por lo tanto, minimizar el coste de la electricidad. • Es esencial una iniciativa integral en materia de redes inteligentes, que incluya un marco de gestión energética asociado a un entorno de Internet de las cosas que supervise y visualice el consumo de energía en las instalaciones de los consumidores. • Se deben evaluar las técnicas de optimización para encontrar el enfoque más rentable y eficiente desde el punto de vista computacional para las limitaciones de los consumidores del lado de la demanda. • Se requiere una predicción precisa de la generación de energía o de la disponibilidad de energía para un mecanismo de programación adecuado.
A study of software architects’ cognitive approaches: kolb’s learning styles inventory in action
(Springer, 2024-10-19) Hidalgo Barrientos, Mauricio Fernando; Astudillo, Hernán; Castro, Laura M.
The multidisciplinary nature of software architects demands a diverse set of skills, ranging from technical expertise to interpersonal abilities. Within this domain, software architects are responsible for designing systems that adhere to quality standards, meet functional requirements, and align with organizational goals. However, educating or training software architects presents a challenge due to the complexity of their roles and responsibilities. To address this challenge, this paper proposes an approach to understanding the learning styles of software architects using Kolb’s Learning Style Inventory (KLSI). It aims to provide a characterization of their teaching and learning preferences, thus facilitating the design and execution of educational strategies tailored to their specific needs. In conducting our research, we utilized LinkedIn as a platform to distribute the KLSI Test, ultimately gathering a sample comprising 18 Senior and Mid-Senior Software Architects. Through trend analysis of their responses, we consistently observed a discernible pattern. This led us to identify the Deciding Learning Style as the primary approach among the sample of software architects regarding their learning preferences. This finding offers initial insights into the predominant learning style within this profession, providing valuable guidance for educational practitioners and institutions aiming to optimize their training programs for software architects.
A Sub-Hourly Precipitation Dataset from a Pluviographic Network in Central Chile
(MDPI, 2025-06-22) Sangüesa, Claudia; Ibañez, Alfredo; Pizarro, Roberto; Vidal-Silva, Cristian; Garcia-Chevesich, Pablo; Mendoza, Romina; Toledo, Cristóbal; Pino, Juan; Paredes, Rodrigo; Ingram, Ben
This data descriptor presents a unique high-resolution rainfall dataset derived from 14 pluviograph stations across central Chile’s Mediterranean region, covering variable peri- ods starting from between 1969 and 1992, up to 2009. The dataset provides continuous precipitation records at a 5 min temporal resolution, obtained through the digitization and processing of pluviograph strip charts using specialized software. This high temporal resolution is unprecedented for the region and enables detailed analysis of rainfall inten- sity, duration, and frequency patterns critical for hydrological research, climate studies, and water resource management in general. Each station’s data was subjected to quality control procedures, including manual validation and correction of digitization errors to ensure data integrity. The dataset reveals the significant temporal variability of rainfall in central Chile, capturing both short-duration high-intensity events and longer precipi- tation patterns. By making this dataset publicly available, we provide researchers with a valuable resource for studying rainfall behavior in a Mediterranean climate zone subject to significant climate variability and change. The dataset supports various applications, including the development of intensity–duration–frequency curves, analysis of rainfall erosivity, calibration of hydrological models, and investigation of precipitation trends in the context of climate change.
A systematic review of recent developments in IoT-based demand side management for PV power generation
(De Gruyter, 2024-06-21) Rao, Challa Krishna; Sahoo, Sarat Kumar; Yanine, Fernando
Demand-side management (DSM) with Internet of Things (IoT) integration has become a vital path for optimizing photovoltaic (PV) power generating systems. This systematic review synthesizes and evaluates the latest advancements in IoT-based DSM strategies applied to PV power generation. The review encompasses a comprehensive analysis of recent literature, focusing on the key elements of IoT implementation, data analytics, communication protocols, and control strategies in relation to solar energy DSM. The combined results show how IoT-driven solutions are changing and how they might improve PV power systems’ sustainability, dependability, and efficiency. The review also identifies gaps in current research and proposes potential avenues for future investigations, thereby contributing to the ongoing discourse on leveraging smart DSM in the solar energy domain using IoT technology.
Adipocyte extracellular vesicles (AdEVs) promote a proinflammatory and profibrotic profile in human renal and endothelial cells in vitro
(Springer Nature, 2026-02-23) Carrión, Pablo; Hernández, María Paz; Pérez, Jorge A.; Tapia-Castillo, Alejandra; Vecchiola, Andrea; Sandoval-Bórquez, Alejandra; Baudrand, René F.; Fardella, Carlos E.; Carvajal, Cristian A.
OBJECTIVES: In obesity, white adipose tissue (WAT) undergoes hypertrophic and hyperplastic changes that are driven by phenotypical changes in preadipocytes and adipocytes. WAT also causes a chronic inflammatory state that modifies gene expression and the secretome, including the shedding of adipose-derived extracellular vesicles (AdEVs) into the circulation, which may influence distant cell types and modulate their phenotypes. AIM: To evaluate the effects of AdEVs on renal and endothelial cells and determine their impact on gene expression related to inflammation, fibrosis, and endothelial function. METHODS: Human SW872 preadipocytes were differentiated into adipocytes and subsequently characterized. AdEVs were isolated by ultracentrifugation and analyzed according to ISEV guidelines. Recipient human renal (HCD) and endothelial (EA.hy926) cells were exposed to AdEVs for 24 hours. Gene expression of adipokines, cytokines (IL-6, IL-1B), fibrosis markers, neutrophil gelatinaseassociated lipocalin (NGAL), and eNOS was assessed by RT-qPCR and western blotting. RESULTS: Differentiated SW872 cells displayed typical adipocyte morphology and accumulated abundant lipid droplets. Isolated AdEVs showed a donut-like morphology, characteristic size distribution, and expression of CD9 and TSG101, consistent with canonical EV markers. Both renal and endothelial cells internalized PKH67-labeled AdEVs and exhibited increased IL-6 and IL-1B expression (p < 0.05). Renal cells demonstrated increased NGAL mRNA levels, whereas endothelial cells showed reduced eNOS mRNA expression following AdEV exposure (p < 0.05). CONCLUSION: AdEVs from SW872 upregulated cytokine (e.g., IL-6) and NGAL expression in renal cells, while reducing eNOS expression in endothelial cells. These findings suggest that AdEVs may influence early inflammatory and vascular responses inobesity.
An IoT-based intelligent smart energy monitoring system for solar PV power generation
(De Gruyter Mouton, 2023-09-15) Rao, Challa Krishna; Sahoo, Sarat Kumar; Yanine, Fernando
As the world’s attention turns to cleaner, more dependable, and sustainable resources, the renewable energy sector is rising quickly. The decline in world energy use and climate change are the two most significant factors nowadays. PV forecasting was essential to enhancing the efficiency of the real-time control system and preventing any undesirable effects. The smart energy management systems of distributed energy resources, the forecasting model of irradiation received from the sun, and therefore PV energy production might mitigate the impact of uncertainty on PV energy generation, improve system dependability, and increase the incursion level of solar power generation. Smart sensors and Internet of Things technologies are essential for monitoring and controlling applications in a broad range of fields. As a result, solar power generation forecasting was essential for microgrid stability and security, as well as solar photovoltaic integration in a strategic approach. This paper examines how to use IoT, a solar photovoltaic system being monitored, and shows the proposed monitoring system is a potentially viable option for smart remote and in-person monitoring of a solar PV system.
Análisis de canasta de mercado en supermercados mediante mapas auto-organizados
(Universidade Federal do Paraná, 2021-11-08) Cordero, Joaquín; Bolt, Alfredo José; Valle, Mauricio A.
Introducción: Una cadena importante de supermercados de la zona poniente de la capital de Chile, necesita obtener información clave para tomar decisiones. Esta información se encuentra disponible en las bases de datos, pero necesita ser procesada debido a la complejidad y cantidad de información, lo que genera una dificultad a la hora de visualizar. Método: Para este propósito, se ha desarrollado un algoritmo que utiliza redes neuronales artificiales, aplicando el método SOM de Kohonen. Para llevarlo a cabo, se han debido seguir ciertos procedimientos claves, como preparar la información, para luego utilizar solo los datos relevantes a las canastas de compra de la investigación. Luego de efectuado el filtrado, se tiene que preparar el ambiente de programación en Python para adaptarlo a los datos de la muestra, y luego proceder a entrenar el SOM con sus parámetros fijados luego de resultados de pruebas. Resultado: El resultado del SOM obtiene la relación entre los productos que más se compraron, posicionándolos topológicamente cerca, para conformar promociones y bundles, para que el retail mánager tome en consideración. Conclusión: En base a esto, se han hecho recomendaciones sobre canastas de compra frecuentes a la cadena de supermercados que ha proporcionado los datos utilizados en la investigación.
Análisis de viabilidad para implementar las plataformas X1 Wind para brindar suministro energético a la comuna de Chonchi, Región de Los Lagos, Chile
(Universidad Finis Terrae (Chile) Facultad de Ingeniería, 2025) Oliviera Parra, María Ignacia; Herrera Garrido, Francisco prof. guía
La presente investigación evalúa la viabilidad técnica, económica y ambiental de implementar las plataformas eólicas flotantes de la empresa X1 WIND en la comuna de Chonchi, Región de Los Lagos, Chile. Esta zona presenta un alto índice de viviendas sin acceso a energía eléctrica, lo que se agrava por su geografía insular y dispersión territorial. Ante ello, se propone el uso de tecnología offshore flotante como solución viable para suministrar energía limpia y sustentable. Se realiza un análisis del recurso eólico basado en datos históricos de la estación meteorológica de Mocopulli, abarcando cinco años de registro entre 2019 y 2023. A partir de estos datos se determina un factor de planta promedio de 77,26%, calculado en base a la información de velocidad del viento registrada en dicho periodo (Dirección Meteorológica de Chile, 2024). Este valor permite estimar la Producción Anual de Energía (AEP) y dimensionar la cantidad de plataformas necesaria. Se consideran además aspectos técnicos como el diseño de anclaje tipo TLP y la orientación pasiva del sistema PivotBuoy, propios del prototipo X30 de X1 WIND. Desde el punto de vista económico, se estiman los costos CAPEX y OPEX a partir de valores referenciales, obteniendo un Costo Nivelado de Energía (LCOE) de 50,41 CLP/kWh, lo que lo posiciona como una opción competitiva frente a otras fuentes renovables. Finalmente, se proponen posibles ubicaciones para la subestación eléctrica y se evalúan los impactos ambientales y sociales de la intervención. Los resultados sugieren que el proyecto es técnicamente factible y económicamente atractivo, con oportunidades reales de mejorar la cobertura energética en sectores vulnerables.
Análisis de viabilidad técnica-económica en la implementación de vehículos eléctricos en la última milla de Santiago de Chile
(Universidad Finis Terrae (Chile) Facultad de Ingeniería, 2025) Pino Maturana, Fernando Andrés; Candia, Alfredo prof. guía
El servicio de delivery de última milla en Santiago de Chile enfrenta desafíos económicos y operativos debido al uso predominante de vehículos de combustión interna (VCI), los cuales generan altos costos en combustible y mantenimiento. En respuesta, esta investigación evaluó la viabilidad técnico-económica de la implementación de vehículos eléctricos (VE) en este sector, considerando los costos operativos, el análisis de flujo de caja y la infraestructura de carga disponible. Para ello, se realizó un análisis comparativo entre VCI y VE, considerando costos de adquisición, operacionales y tiempos de recuperación de la inversión. Se utilizaron herramientas de modelado financiero para proyectar el flujo de caja de una flota de 50 vehículos de cada tipo, permitiendo determinar la rentabilidad y los factores clave que afectan la adopción de VE en la última milla. Los resultados indicaron que, aunque los VE presentan costos operativos un 70-80% menores que los VCI, su inversión inicial es un 25-35% más alta. Se determinó que los VCI recuperan su inversión hacia el final del segundo año, mientras que los VE alcanzan el punto de equilibrio casi al finalizar el tercer año. Además, la infraestructura de carga en Santiago aún presenta limitaciones en cobertura y velocidad de carga, dificultando la adopción masiva de VE en el sector logístico. Se concluyó que, si bien la transición a vehículos eléctricos es viable a mediano y largo plazo, su adopción será aún más conveniente en los próximos años cuando los costos de adquisición disminuyan y se equiparen con los de combustión interna. Para facilitar este proceso, se recomendaron estrategias como la expansión de la infraestructura de carga, incentivos fiscales y la optimización tecnológica para mejorar la eficiencia operativa de las flotas eléctricas.
Application of dual descriptor to understand the activity of Cu/ZrO2 catalysts in the water gas shift reaction
(Springer Nature, 2017) Cerón, María Luisa; Calatayud, Mónica
A comparative theoretical study applying Dual Descriptor has been performed using Water Gas Shift reaction, catalyzed by copper supported on monoclinic and tetragonal zirconia. The Dual Descriptor and thermodynamic considerations were used to understand the structural effects that occur in the reaction when it is catalyzed by Cuon both zirconia phases. It was found that the formation of carbonates in the Cu supported on tetragonal zirconia dehydrogenates consistently with experimental results.
Applying multi-criteria analysis in a port system
(2017) Córdova, Felisa M.; Durán, Claudia
This work presents a study developed in a medium port system composed of 50 public and private actors interacting with their macro-environment, which can generate strategic synergistic relationships. In order to determine these synergistic links between their components, the strategic phrases contained in their missions are analysed and classified according to the multicriteria that are part of the macro-environment of each port actor: political, economic, social, technological, environmental, risk and learning. Likewise, new characterizations and classifications are proposed for groups and sub-groups of port actors. From absolute frequencies, Contingency Tables and the Chi-square test, quantitative results are obtained, which show the potential cases of strategic synergistic relations in the port system and the behavior of each group and sub-group of actors, as well as dependence / independence between every pair of criteria. Finally, it is verified that it is possible to use quantitative methods to analyze the strategic synergistic relationships between the actors of the port system.
Au Adatom-Linked [Au(XCH3)2] (X= S,Se,Te) Complexes on Gold (111) Surface Clusters
(Springer Nature, 2026-02-09) Herrera, Pablo; Ceron, María Luisa; Miranda-Rojas, Sebastián; Mendizabal, Fernando
We present a study on the nature of the forces dominating the interaction between [Au(XCH3)2] - (X = S, Se, Te) complexes and gold(111) surface. For this purpose, we modeled a series of gold complexes and gold clusters (Au26 and Au58). The models were calculated at the DFT-D3(BJ) (PBE and TPSS) levels of theory. The results show that noncovalent interactions are associated with the Au-adatom-Au and chalcogen-Au (surface) distances. Also, the NBO, NCI, and QTAIM analysis exposed a low-density character between the gold-adatom-Au(surface) and chalcogen-Au(surface) atoms, revealing that this contribution explains the stability of the complexes. Moreover, the Energy Decomposition Analysis shows that the polarization-charge-transfer and dispersion contributions are more relevant in the description of the van der Waals interaction.
Automatons immersed in ocean currents for transformation of biomass into fuel
(Springer, 2021) Cañete, Lucio; Córdova, Felisa; Perez de Arce, Andrés
When observing the Chilean sea from both biotic and mechanical perspective, oceanographers note that the Humboldt Current carries abundant biomass and that the movement of the water itself has the capacity to do work. Taking advantage of these two qualities of the ocean current, this article exposes the sketch of an automated device, the computational simulation when it was conceived and its mathematical model to make efficient the capture of biomass that will be processed, stored and dispatched as biodiesel. Said submerged automaton has a structural configuration that was outlined by cybernetic design resulting in a body that carries out the transformation process by itself, which starts on the side that faces the current with its content of biomass. This raw material is trapped thanks to an intelligent system that informs the reactor about the relative importance of the state variables that its body can control, stimulating those swimming organisms to move in the desired direction. The captured biomass begins its process until it becomes biodiesel by virtue of the mechanical energy provided by the same flow of seawater that affects the reactor. The rear part of the reactor releases both incident water and by-products into the sea without harmful environmental consequences. Some users of this new type of device are armies in time of conflict and merchant marines during algae bloom.
Beyond bloch: A teotherical blueprint of conjugated polymer optoelectronics
(IOP Publishing, 2026-03-31) Lagos, Miguel; Kiwi, Miguel; Paredes, Rodrigo
Conjugated polymers have recently regained strong interest because of their potential in organic electronic devices such as organic light-emitting diodes (OLEDs), field-effect transistors (FETs), and organic photovoltaics (OPVs). Unlike inorganic semiconductors where electrons are commonly treated as delocalized or quasi-free Bloch states,electrons in conjugated polymers occupy strongly coupled, localized σ and π orbitals and interact intensely with the ionic lattice. These materials therefore deviate markedly from the assumptions underlying Bloch-based approaches, motivating the development of alternative theoretical descriptions of charge transport. Here we present a many-body model that explicitly includes electron-electron interactions, both on-site and between π states on alternating chain sites. The model naturally explains semiconducting behavior in the undoped polymer and predicts two novel flat bands of excited bonding states. These excited states exhibit bosonic character and enable an unconventional charge-transport channel. The model also quantitatively reproduces experimental observations, yielding excellent fits to measured UV-Vis absorption and electro-luminescence spectra.
BOLDSC: A New Dynamic, Secondary-Memory Metric Index
(Springer Nature, 2025-10-01) Paredes, Rodrigo; Reyes, Nora; Figueroa, Karina; Hoffhein, Manuel
Metric space searching addresses the problem of efficient similarity searching across diverse applications, in particular for non-structured objects, for instance, natural language or images. Although promising, this approach is still immature in several aspects that are well-established in traditional databases. Particularly, most indexing schemes are not dynamic, as they cannot efficiently handle insertions over an ongoing index without significant performance degradation. Moreover, very few of them work efficiently in secondary memory. The List of Clusters (LC) has proven to be a competitive index in main memory due to its simplicity and good search performance in high dimensional metric spaces. We introduce a new dynamic, secondary-memory LC variant. Our new index efficiently handles the secondary memory scenario and achieves competitive search and insertion times compared to the state-of-the-art, making it a practical alternative for large-scale database applications. Also, our ideas are applicable to other secondary-memory indexes, where it is possible to control the disk page occupation.

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