Proyectos

Slope-based Variational Analysis and Optimization

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.

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.

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

Uso de la química de elementos altamente siderófilos y calcófilos para discriminar rocas asociadas a yacimientos minerales productivos

Climate projections anticipate an increase in frequent droughts, episodes of extreme fire behavior, in addition to heat waves and unstable atmospheric conditions, all phenomena related to climate change. Drought intensification has been projected to increase in frequency in several regions across the globe, including the southwestern part of South America, the European Mediterranean Basin, Northern Africa, the Middle East, Central Asia, Australia, and the USA. Particularly, the former three areas have been recognized as locations highly likely to face unprecedented droughts during the 21st century, and within Southwestern South America, Chile has been alarmingly pointed out as the country earlier in this era experiencing this phenomenon, regardless of the greenhouse gas emissions scenario. Catastrophic effects such as extreme droughts and changes in fire behavior are important drivers of ecosystem degradation in arid, semiarid, dry temperate and Mediterranean ecosystems. Mediterranean ecosystems of central Chile have been indicated as the earliest in its type experiencing effects of climate change; where an accelerated aridification is already registered; therefore, representing a scenario to anticipate the effects of climate anomalies at other ecosystems of its type. Persistent droughts and land burning can compromise belowground conditions that are essential to support aboveground life in terrestrial ecosystems. Nevertheless, despite their importance for ecosystem functioning and recovery after environmental disturbances, there still a considerable lack of comprehension on how belowground attributes respond to combined stressors such as droughts and fires. This is of particular concern in conditions where post-fire plant and soil recovery have been shown to be inhibited or retarded due to severe droughts. Therefore, this project aims to evaluate individual and combined effects of drought and fires over time in soil microbial communities and carbon and nitrogen functional dynamics along with the relationship of these attributes and the state of sclerophyll vegetation in Mediterranean forests of central Chile. To accomplish this goal a multiscale approach will be applied in this research by integrating scientific disciplines from landcape ecology to molecular biology. By using remote sensing study site will be selected within an area known to be affected by an extended drought period (since 2010), in addition to hyper-dry years (2019 and 2021), which in addition has experienced the occurrence of historical wildfires as the case of 2017. From this initial screening 18 study conditions resulting from three climate anomaly categories identified (high, medium, low) according to differences in precipitation with respect to historical average, three categories for forest response to drought (recovered, unaffected and unrecovered) based on analysis of Normalized Burn Index (NBR = [NIR - SWIR] / [NIR + SWIR]) and two burned conditions (with and without) will be obtained for soil and vegetation assessments. Classical soil physicochemical analyses and NG-sequencing techniques including high-throughput amplicon sequencing (metabarcoding), whole genome sequencing (metagenomics), and gene expression (metatransciptomics), in addition to soil physiological analyses will be performed. Moreover, vegetation recovery following drought and fire will be evaluated. Results from this study will allow to better understand the individual versus the combined effects of drought and fires in soil microbial community structure and carbon and nitrogen functionality, which are expected to be exacerbated with the combined occurrence of these phenomena, giving insights on the resilience capacity of soil microbiomes and carbon and nitrogen biogeochemical cycles. From this work, results will also allow to gain a more comprehensive understanding of the linkages between soil functionality and vegetation responses to drought and fires over time, which will allow to identify ecological drivers related to ecosystem stability.

Plants, with their two-layered immune system, are equipped to combat pathogen invasion. The first layer, Pattern Triggered Immunity (PTI), is a powerful defense mechanism. It relies on Pattern Recognition Receptors (PRRs) to detect Microbe-Associated Molecular Patterns (MAMPs) from microbes, triggering a robust defense response. This response, including signaling cascades, gene expression changes, and production of antimicrobials and defense hormones, contributes to restricting pathogen colonization. PTI activation can trigger a systemic response known as Induced Systemic Resistance (IRS), enhancing plant defenses throughout the organism and leading to Non-Host-Resistance. The potential of PTI activation to enhance a plant's overall defensive capacity is a promising strategy to improve crop health. PTI activation at infection sites triggers the production of mobile signals within the plant, which then spread IRS throughout the plant, enhancing its overall defensive capacity. Flg22 and xyn11, two well-known MAMPs, trigger PTI in tomato, activating various defense responses and, interestingly, including IRS in tomatoes and other plants. Plant roots, often overlooked in discussions of plant immune systems, possess their own immune system, though less potent than leaves. They respond to MAMPs like Flg22 and chitin, but with weaker production of defense chemicals. Despite this difference, roots activate various defenses like PR proteins and callose deposition. Uniquely, roots secrete antifungal secondary metabolites like flavonoids. These root exudates play a crucial role in shaping the surrounding microbiome, attracting beneficial microbes, and possess antimicrobial activity itself. Studies have shown that root exudate composition can be manipulated to influence the soil microbiome and potentially enhance plant growth. This underlines the importance of considering roots in our understanding of plant immune systems, particularly how defense responses are displayed in the root after immune activation in leaves in terms of a systemic immune response. This often overlooked aspect is crucial for a comprehensive understanding of plant immunity. Plants and microbes communicate two-way, establishing an interaction, by instance, plant root exudates influence the composition of the rhizosphere microbiome, which in turn regulates plant growth and immunity. Research suggests that specific bacteria within the rhizosphere microbiome can enhance plant immunity. In fact, transplanting the microbiome from a resistant tomato variety to a susceptible one improved disease resistance. Understanding this plant-microbiome-soil interaction is crucial for developing sustainable agriculture. Our ongoing research investigates how soil type influences tomato immunity and its connection to the soil microbiome. Preliminary results show that different soil types affect the strength of plant immunity responses, even though the overall bacterial types (phyla) are similar. Interestingly, specific bacterial isolates from a soil type with higher immunity were able to directly trigger plant defense mechanisms. Unraveling the intricate interplay between soil type, the rhizosphere microbiome, and tomato immunity holds the key to unlocking sustainable and resilient agricultural practices. This proposal aims to investigate the potential of targeted Pattern-Triggered Immunity (PTI) activation in tomato leaves to enhance plant defense against diverse pathogens. We hypothesize that leaf application of microbial elicitors (flg22 and Xyn11) will trigger PTI, leading to changes in root gene expression and root exudate composition. These alterations are expected to enrich beneficial bacteria in the rhizosphere microbiome, ultimately enhancing resistance against both the foliar pathogen Pseudomonas syringae pv. tomato and the soil-borne pathogen Fusarium oxysporum f.sp. lycopersici. To achieve this, we have defined three specific objectives: 1) Evaluate the impact of leaf-applied elicitors on pathogen susceptibility, root gene expression, root exudate composition, and soil microbiome composition. 2) Develop synthetic exudates mimicking PTI-activated plants and construct synthetic microbial communities potentially containing beneficial bacteria. 3) Assess the effectiveness of leaf-applied elicitors and synthetic microbial communities on the root microbiome and plant health under field conditions. With this, we aim to elucidate the mechanisms by which leaf-based PTI activation influences root-level processes and shapes the rhizosphere microbiome to enhance tomato plant defense against various pathogens. The findings hold promise for developing novel and sustainable strategies for disease management in tomato production.

Slope-based Variational Analysis and Optimization

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.

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