Browsing by Author "González, Marcelo"

Now showing 1 - 4 of 4
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    Developing a very high-strength low-CO2 cementitious matrix based on a multi-binder approach for structural lightweight aggregate concrete
    (2020) Mena, J.; González, Marcelo; Remesar Lera, José Carlos; López Casanova, Mauricio Alejandro; CEDEUS (Chile)
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    Pro-angiogenic Role of Insulin: From Physiology to Pathology
    (2017) Escudero, Carlos A.; Herlitz, Kurt; Troncoso, Felipe; Guevara, Katherine; Acurio, Jesenia; Godoy Sánchez, Alejandro Samuel; Aguayo, Claudio; González, Marcelo
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    Reduction of Blood Amyloid-beta Oligomers in Alzheimer's Disease Transgenic Mice by c-Abl Kinase Inhibition
    (2016) Estrada, Lisbell D.; Chamorro Veloso, David Daniel; Yáñez, María José; González, Marcelo; Leal, Nancy; Bernhardi Montgomery, Rommy von; Dulcey, Andrés E.; Marugan, Juan; Ferrer, Marc; Soto, Claudio; Zanlungo Matsuhiro, Silvana; Inestrosa Cantín, Nibaldo; Álvarez Rojas, Alejandra
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    Sustainable Cement Paste Development Using Wheat Straw Ash and Silica Fume Replacement Model
    (Multidisciplinary Digital Publishing Institute (MDPI), 2024) Bastías, Bryan; González, Marcelo; Rey-Rey, Juan; Valerio, Guillermo; Guindos, Pablo
    © 2024 by the authors.Conventional cement production is a major source of carbon dioxide emissions, which creates a significant environmental challenge. This research addresses the problem of how to reduce the carbon footprint of cement paste production using agricultural and industrial waste by-products, namely wheat straw ash (WSA) and silica fume (SF). Currently, accurate models that can predict the mechanical properties of cement pastes incorporating these waste materials are lacking. To fill this gap, our study proposes a model based on response surface methodology and Box-Behnken design, designed to predict the strength of cement pastes with partial substitutions of WSA and SF. Through mechanical and characterization tests, the model demonstrated high accuracy in predicting the strength of the pastes, validated with three mixes, which showed maximum errors of less than 6% at different ages (7, 28, and 56 days). Response surface analysis revealed that replacing cement with 0–20% WSA and more than 5% SF can effectively reduce the carbon footprint by maximizing waste incorporation. This model allows for the calculation of optimal cement substitution levels based on the required strength, thus promoting sustainability in the construction industry through the use of local waste/resources.