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Advanced Simulation Methods for Nanoporous Gas@Host Systems

Advanced Simulation Methods for Nanoporous Gas@Host Systems

Thomas Hofer (ORCID: 0000-0002-6559-1513)
  • Grant DOI 10.55776/P35427
  • Funding program Principal Investigator Projects
  • Status ongoing
  • Start July 4, 2022
  • End July 3, 2026
  • Funding amount € 257,418

Matching Funds - Tirol

Disciplines

Chemistry (65%); Computer Sciences (10%); Nanotechnology (25%)

Keywords

    Density Functional Tight Binding, Metal-Organic Frameworks, Covalent Organic Frameworks, Neural Network Potentials, Machine Learning, Gas@Host Systems

Abstract

The term nanoporous compound refers to the general class of solids possessing an unusually large fraction of microscopic cavities, either in form of tubular channels or spherical pores. The diameter of these cavities ranges from a few micrometers to a nanometer (i.e. on billionth of a meter). The channels and pores of these materials are typically not empty, but can be occupied by smaller chemical compounds, the so-called guest molecules. A well-known subtype of nanoporous substances synthesized in the lab are metal-organic and covalent organic frameworks (MOFs, COFs), which represent one of the most rapidly evolving class of functional materials. In contrast to naturally occurring nanoporous compounds such as the aluminium- and silicon-based zeolites and activated carbon, MOFs and COFs are widely known for their exceptional storage capacities of guest molecules. This property is of particular interest for the storage of green house gases such as carbon dioxide (CO 2) as well as technically relevant sources of energy such as molecular hydrogen (H2) and methane (CH4). However, the large number of possible combinations to create novel variants of these framework compounds makes the search for ideal storage media tedious, time-consuming and oftentimes costly. An alternative approach to estimate the storage capacity of these compounds are methods in the regime of computer-aided material sciences. By utilizing suitable computational methods the properties of the materials can be determined prior to the actual synthesis in the lab. This way suitable candidates for experimental investigations can be determined, while at the same time less-promising materials are discarded. The target of this project is the development of a stand-alone simulation program, enabling researchers to determine the properties of technically relevant compounds such as the gas storage capacity via computational methods. The events of the recent past have dramatically highlighted the demand for efficient storage strategies for the greenhouse gas carbon dioxide as well as sustainable energy carriers such as molecular hydrogen and methane. The software developed in the context of this project is expected to substantially contribute to the development of modern gas storage materials, supporting the global efforts aiming at the reduction of climate change and the utilization of renewable energy sources in a constructive manner.

Research institution(s)
  • Universität Innsbruck - 100%
International project participants
  • El-Eulmi Bendeif, Université de Lorraine - France

Research Output

  • 56 Citations
  • 7 Publications
Publications
  • 2025
    Title Comparative Study of UMCM-9 Polymorphs: Structural, Dynamic, and Hydrogen Storage Properties via Atomistic Simulations
    DOI 10.1021/acs.jpcc.4c07872
    Type Journal Article
    Author Gallmetzer J
    Journal The Journal of Physical Chemistry C
    Pages 5645-5655
    Link Publication
  • 2025
    Title Parametrization of Zirconium for DFTB3/3OB: A Pathway to Study Complex Zr-Compounds for Biomedical and Material Science Applications
    DOI 10.1002/jcc.70140
    Type Journal Article
    Author Penz A
    Journal Journal of Computational Chemistry
    Link Publication
  • 2024
    Title Equipartitioning of Molecular Degrees of Freedom in MD Simulations of Gaseous Systems via an Advanced Thermostatization Strategy
    DOI 10.1021/acs.jctc.4c01580
    Type Journal Article
    Author Gamper J
    Journal Journal of Chemical Theory and Computation
    Pages 102-113
    Link Publication
  • 2023
    Title Beyond the Status Quo: Density Functional Tight Binding and Neural Network Potentials as a Versatile Simulation Strategy to Characterize Host–Guest Interactions in Metal- and Covalent Organic Frameworks
    DOI 10.1021/acs.jpclett.3c00941
    Type Journal Article
    Author Hofer T
    Journal The Journal of Physical Chemistry Letters
    Pages 6018-6027
    Link Publication
  • 2023
    Title Storage and Diffusion of Carbon Dioxide in the Metal Organic Framework MOF-5?A Semi-empirical Molecular Dynamics Study
    DOI 10.1021/acs.jpcb.3c04155
    Type Journal Article
    Author Listyarini R
    Journal The Journal of Physical Chemistry B
    Pages 9378-9389
    Link Publication
  • 2023
    Title Storage and diffusion of CO2 in covalent organic frameworks—A neural network-based molecular dynamics simulation approach
    DOI 10.3389/fchem.2023.1100210
    Type Journal Article
    Author Kriesche B
    Journal Frontiers in Chemistry
    Pages 1100210
    Link Publication
  • 2023
    Title Structural Properties of Metal–Organic Frameworks at Elevated Thermal Conditions via a Combined Density Functional Tight Binding Molecular Dynamics (DFTB MD) Approach
    DOI 10.1021/acs.jpcc.2c05103
    Type Journal Article
    Author Purtscher F
    Journal The Journal of Physical Chemistry C
    Pages 1560-1575
    Link Publication

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