Tesis doctoralsDepartament de Química

More is Different: Modern Computational Modeling for Heterogeneous Catalysis

  • Identification data

    Identifier:  TDX:3909
    Authors:  García Carrillo, Sergio Pablo
    Abstract:
    The combination of Experimental observations and Density Functional Theory studies is one of the pillars of modern chemical research. As they enable the collection of additional physical information of a chemical system, hardly accessible via the experimental setting, Density Functional Theory studies are widely employed to model and predict the behavior of a diverse variety of chemical compounds under unique environments. Particularly, in heterogeneous catalysis, Density Functional Theory models are commonly employed to evaluate the interaction between molecular compounds and catalysts, lately linking these interpretations with experimental results. However, high complexity found in both, catalytic settings and reactivity, implies the need of sophisticated methodologies involving automation, storage and analysis to correctly study these systems. Here, I present the development and combination of multiple methodologies, aiming at correctly asses complexity. Also, this work shows how the provided techniques have been actively used to study novel catalytic settings of academic and industrial interest.
  • Others:

    Publisher: Universitat Rovira i Virgili
    Date: 2022-07-11, 2022-07-20T12:05:25Z, 2022-07-20T12:05:25Z
    Identifier: http://hdl.handle.net/10803/674854
    Departament/Institute: Departament de Química Analítica i Química Orgànica, Universitat Rovira i Virgili.
    Language: eng
    Author: García Carrillo, Sergio Pablo
    Director: López Alonso, Núria
    Source: TDX (Tesis Doctorals en Xarxa)
    Format: application/pdf, application/pdf, 277 p.
  • Keywords:

    Automation
    Machine Learning
    Heterogeneous Catalysis
    Automatización
    Aprendizaje automático
    Catálisis heterogénea
    Automatització
    Aprenentatge automàtic
    Catàlisi heterogènia
    519.1
    Ciències
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