Proyectos

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]Slope-based Variational Analysis and Optimization[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]Estudio de propiedades métricas y estructurales de los espacios de Wasserstein (provenientes de la teoría de transporte óptimo), y búsqueda de aplicaciones en optimización bajo incertidumbre.[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]Combinatorial objects frequently appear in various areas of computer science and discrete mathematics. These objects are central to questions in algorithmic design, where we aim to program a computer to efficiently perform tasks involving them. These tasks may include counting objects based on certain parameters, sampling an object uniformly at random, optimizing with respect to an objective function, searching for objects that satisfy specific properties, or generating all objects exactly once. This project focuses on two of these problems: combinatorial generation and the search for highly distinct combinatorial objects. While many of the aforementioned tasks have general-purpose techniques that allow them to tackle multiple problems simultaneously, the situation becomes less clear when dealing with combinatorial generation or the search for distant objects. Much of the effort in these areas has been devoted to developing ad hoc methods. Despite this, these last two problems can be naturally phrased in the language of flip graphs, which encode the similarity between combinatorial objects. In this context, the problem transforms into the traditional graph problems of Hamiltonicity (finding a path that traverses all the vertices exactly once) and diameter (finding two vertices that are farthest apart). Recent research has highlighted the significant value of exploiting polytopal properties and symmetry of flip graphs, leading to unified frameworks that can address many problems simultaneously. The main objective of this project is to contribute to this perspective. Specifically, it aims to enhance our understanding of the polytopal and symmetric properties of flip graphs and use this knowledge to develop efficient algorithms for tackling Hamiltonicity and diameter problems[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]The primary objective of this research is to evaluate the feasibility of using ultrasonic acoustic imaging as a non-intrusive, in situ technique to assess the plastic behavior of commercial metals and alloys. Specifically, it aims to explore the potential of ultrasonic acoustic imaging to identify and monitor various plastic deformation mechanisms in stainless steel and aluminum. The selection of materials is based on their distinct plastic deformation behaviors: aluminum releases internal energy through dislocation mechanisms, while stainless steel releases energy through deformation, first by dislocation and then by twinning. To achieve this goal, the study will continuously measure changes in sound velocity and the nonlinear acoustic parameter β while subjecting the materials to uniaxial tensile tests at different levels of applied stress. Previous studies conducted by our research group have demonstrated that changes in sound velocity, in relation to strain, offer a reliable means of quantifying dislocation density in local measurements on aluminum, copper, and stainless steel specimens. Furthermore, these studies have observed that alterations in the nonlinear acoustic parameter, specifically second harmonic generation, exhibit more pronounced changes compared to variations in linear acoustics (speed of sound). Building upon these findings, the proposed research involves the generation of both linear and nonlinear acoustic images over wider spatial regions to advance our understanding of the plastic behavior of materials undergoing different microstructural changes. The challenge of applying the results of this research to in situ measurements in the industry is not trivial, as the highly controlled laboratory conditions are not maintained in service components. In this regard, the incorporation of machine learning tools in the proposal aims to identify the parameters most sensitive to the various deformation mechanisms through clustering techniques. It is expected that the correlation of different acoustic parameters with the various plastic deformation mechanisms of both materials under study will generate an optimal database that reflects the variety of scenarios present in service components, thus paving the way for the industrial use of the proposed characterization system. The adoption of diagnostic techniques and the utilization of metallic material state analysis in service significantly enhance our ability to comprehend and control plastic deformation mechanisms, contributing to improved material reliability and robustness, and facilitating informed decision-making and maintenance strategies. Additionally, ex-situ standard microstructural tests, including XRD (X-ray diffraction), EBSD (electron backscatter diffraction), and TEM (transmission electron microscopy), will be performed to characterize the material’s state after deformation. These complementary tests will provide valuable microstructural information, enabling the correlation of deformation states with the acquired acoustic images. All the acoustic and microstructural information described above, in conjunction with previous research group data, will be stored in a robust and comprehensive database. This database will serve as the input for a Machine Learning algorithm, which will facilitate the identification of patterns of correspondence between acoustic and microstructural parameters. This approach aims to enable the future prediction, with a high level of probability, of the specific type of plastic deformation mechanism that a material is undergoing based on the acoustic parameter measurements. The successful development of this research proposal would yield several significant outcomes. Firstly, it would enable the early detection of microstructural changes in materials long before fractures occur. Moreover, it would establish a non-intrusive tool for characterizing materials by identifying the underlying mechanisms driving plastic deformation and monitoring the evolution of materials in service over time. Ultimately, this research has the potential to advance our understanding of the plastic behavior of stainless steel and aluminum, opening avenues for improved analysis, design, and performance evaluation of materials in various industrial applications.[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]Medium manganese steels (MMnS) are currently a subject of active scientific research due to a number of reasons. First, their unique combination of strength and ductility makes them promising candidates for lightweight structural applications in automotive and aerospace industries, where reducing weight without sacrificing mechanical properties is critical. Second, their ability to retain austenite at room temperatures offers advantages in terms of formability and resistance to hydrogen embrittlement, which are significant challenges in steel manufacturing. Third, medium Mn steels have shown potential in enhancing wear and impact resistance, making them suitable for applications in mining, construction, and machinery sectors. Additionally, their corrosion resistance and potential for cost-effective alloying with other elements further expand their utility across various engineering fields. Scientific research on medium Mn steels aims to optimize their microstructure, processing parameters, and alloy compositions to unlock their full potential, thereby contributing to the development of advanced materials that meet the performance requirements of modern industries while promoting sustainability and efficiency in manufacturing processes. The proposed research aims to investigate the stability of austenite in medium manganese steels within ternary Fe-C-Mn and Fe-C-Mn-X systems (X: Al, Si, Cr), focusing on its correlation with processing parameters. The primary objective is to assess the stability of austenite via (i) experimentally determining the martensite start temperature (thermal stability) using dilatometry and thermal analysis techniques, and (ii) to evaluate the fraction of austenite as a function of strain (mechanical stability) under tensile test. These measurements will provide crucial data to understand how variations in processing conditions influence austenite stability. Else, the study will correlate austenite stability with mechanical properties through mechanical tests and in-depth microstructural characterization, aiming to establish predictive models. Additionally, thermodynamic and kinetic calculations will aid in assessing the phase transformation behavior under different thermal histories. The research will extend its scope to evaluate impact and wear properties in relation to austenite stability, crucial for applications in industries requiring high strength and toughness, such as mining and construction. By systematically exploring these relationships, the project seeks to advance the fundamental understanding of medium Mn steels, potentially leading to the development of lightweight, durable materials with enhanced performance characteristics. Ultimately, the findings aim to contribute to the optimization of steel manufacturing processes and the realization of more efficient and reliable engineering solutions in demanding operational environments[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]Uso de la química de elementos altamente siderófilos y calcófilos para discriminar rocas asociadas a yacimientos minerales productivos[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]Monogenetic volcanoes are the most common expression of magmatism on the Earth’s surface, and they are found in every tectonic setting, yet key aspects of the behavior and evolution of monogenetic volcanic systems remain poorly understood. Understanding the processes that govern the evolution of monogenetic volcanoes, and the timescales over which these processes operate, is critical for hazard assessment in active distributed volcanic fields. The Southern Volcanic Zone (SVZ), one of the three volcanic regions of The Andes, displays a diverse landscape characterized by historically and potentially active volcanic structures, including ~60 large stratovolcanoes, three giant silicic caldera systems, and hundreds of small eruptive centers. Even these monogenetic volcanoes are considerably smaller in size and volume, they tend to be grouped in space and time, forming distributed volcanic fields, and provide information from source to surface processes that are usually obscured by the commonly dominant more evolved compositions in the Andean arc. Among the Holocene clustered small eruptive centers within the SVZ, this project focuses on the youngest distributed volcanic field in Chile, Carrán-Los Venados, which includes not only the most recent monogenetic eruption in Chile, which occurred in 1979, but it also hosts two other historical eruptions in 1907 and 1955. The Carrán-Los Venados distributed volcanic field (CLV) has received limited attention, despite its placement at position No. 9 in the specific risk ranking of active volcanoes in Chile compiled by SERNAGEOMIN in 2020. Past research on the CLV has mostly focused on chronicling and observing the impacts of the historic eruptions. While some studies have touched upon the geochemical and tectonic aspects of the region, there remains a distinct absence of a comprehensive and cohesive examination of the entire volcanic field. Therefore, building upon previous research conducted in CLV, this project aims to tackle this knowledge gap, and we propose to carry out a detailed multi-disciplinary study (physical volcanology, petrology/geochemistry, and volcanic hazards). Primary research questions include: When did the volcanism start in CLV? What processes contribute to the formation of this volcanism, and what are the magmatic factors that influence its evolution? Where does the volcanic activity take place, and how does it manifest on the surface? What should we expect in the next eruption? To answer these questions, we propose a methodology based on deposit characterization and mapping, geochronology, morphometry, rheology, petrography, mineral chemistry, geothermobarometry and hygrometry, and geochemical characterization and modelling. The integration of these diverse datasets will provide key constraints on the sources, processes, and timescales of magma ascent and storage leading to eruption of the CLV clustered small eruptive centers and small stratovolcanoes, providing an important framework for better understanding the behavior of distributed volcanic fields globally. Furthermore, this project aims to provide valuable support to undergraduate and graduate students, who will have the unique opportunity to engage in all aspects of this research project, making it a significant component of their dissertation studies. Additionally, the study will foster ongoing international collaboration, creating avenues for future student and faculty exchanges. Moreover, it will facilitate outreach educational initiatives for the local community, including specialized seminars, thereby promoting knowledge dissemination and interactive learning experiences.[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]El proyecto tiene como objetivo desarrollar e implementar modelos de aprendizaje automático (Machine Learning, ML) para analizar datos ómicos generados a partir de plantas agronómicas, con el fin de identificar patrones moleculares clave asociados a su productividad, resistencia a estreses abióticos (como sequía y salinidad) y bióticos (como plagas y enfermedades), y su adaptación a condiciones climáticas cambiantes.[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]The main objective of this proposal is to study the miRNA:mRNA post-transcriptional regulatory networks in non-model plant species associated with the process of climate change stress resilience.The proposal integrates the development of computational algorithms, the use of massive data of public non-coding RNA sequences, and the use of a biological model to study post-transcriptional regulatory networks (at the genome-scale) in biological processes associated with climate resilience and adaptation of endemic plant species.[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]

[vc_section el_class="container mx-auto align-items-center circle--pattern" css=".vc_custom_1648956589196{padding-top: 3rem !important;}"][vc_row el_class="pb-5"][vc_column][vc_wp_custommenu nav_menu="6"][uoh_breadcrumb_component automatic_breadcrumb="true"][uoh_title_component title_dropdown="big" title_decorator="true"]{{title}}[/uoh_title_component][vc_column_text css=""]Producción Escalable de Inmunoestimulantes Nanoestructurados para el Control de Piscirickettsiosis en Salmón del Atlántico[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649209804184{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5"][vc_row el_class="container mx-auto align-items-center p-md-0 pt-5"][vc_column el_class="p-0"][/vc_column][/vc_row][/vc_section][vc_section css=".vc_custom_1649210787516{background-color: #f6faff !important;}" el_class="p-md-0 pt-md-5 pb-md-5"][vc_row el_class="container mx-auto align-items-center"][vc_column][/vc_column][/vc_row][/vc_section]