| Grant number: | 22/12919-8 |
| Support Opportunities: | Research Grants - Innovative Research in Small Business - PIPE |
| Start date: | December 01, 2023 |
| End date: | August 31, 2024 |
| Field of knowledge: | Engineering - Materials and Metallurgical Engineering |
| Principal Investigator: | Alexsandro Kirch |
| Grantee: | Alexsandro Kirch |
| Company: | Multiscale Solutions Tecnologia e Consultoria Ltda |
| CNAE: |
Desenvolvimento de programas de computador sob encomenda
Pesquisa e desenvolvimento experimental em ciências físicas e naturais Atividades profissionais, científicas e técnicas não especificadas anteriormente |
| Associated scholarship(s): | 23/14520-8 - Be multiscale: multiscale methods applied to materials optimization,
BP.PIPE 23/14523-7 - Development of computational protocol for materials optimization applied to industry, BP.TT |
Abstract
Following the advancement of processing power observed in recent decades, computer simulations have been increasingly used in several areas to optimize the development of new products and industrial processes. In the oil industry, for example, computer models are already used effectively to predict the flow of fluids through porous media. In addition, the use of computational tools such as machine learning (AM) combined with density functional theory (DFT) has been growing in the design of new materials. In our research group (SAMPA-IFUSP), these and other computational methods have been successfully applied in the Oil & Gas industry. We believe that a B2B business model can provide this service in a more adequate way than what is being done by the University, which is normally limited to research projects restricted to the interest of the department, and also has limitations in terms of resource management, deadlines and contracting. Of qualified labor. In this project we seek to investigate the technical-economic feasibility of computational modeling applied to materials in problems in the O&G context but also in other segments of the Brazilian industry, such as the automotive, steel, metal-mechanics, additive manufacturing, semiconductors, pharmacy/chemistry, biomedicine, aeronautics and aerospace, among others. In fact, multiscale methods (DFT, molecular dynamics, Boltzmann networks, etc.) can be used to determine and predict the electronic, structural, dynamic and thermodynamic properties of complex materials, surfaces and interfaces with energy applications (fossil fuels and renewable energy), environment (contaminants and CO2 capture and sequestration), infrastructure (cement, metal alloys and asphalt) and nanofluidics. As an advantage, the use of computational modeling will allow a substantial reduction in time and costs associated with the development of new materials and processes. (AU)
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