Computational Design of Nanoporous Materials: New Structures, Applications, and Advances in Methodology
A special issue of Materials (ISSN 1996-1944).
Deadline for manuscript submissions: closed (30 November 2019) | Viewed by 214
Special Issue Editor
Interests: advancing mathematical modeling methodology and simulation techniques; physics-informed machine learning; porous structures and interfaces: characterization, thermodynamics, and transport; structure–property relationships in soft matter; statistical mechanics, especially in application to complex media and molecules
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Special Issue Information
Dear Colleagues,
Nanoporous materials are now widespread in the chemical industry and in biomedical devices. Over the recent years, they have greatly expanded in terms of the available variety and applications. Rapid progress in computational facility and modeling techniques has enabled the physics and data driven discovery of new material structures and the optimization of their functions. This Special Issue presents recent advances in the fundamentals, methodology and applications of the computational design of nanoporous materials.
First, we invite manuscripts on the simulation design of microporous crystals (zeolites doped with various cations, new nodes and ligands of MOFs to achieve a desired morphology and functions), as well as amorphous carbons with tailored pore size distributions.
Contributions to the design of meso- and macro-porous solids may include both the construction of new templates to achieve a particular morphology and design of surface chemistry for particular applications, such as storage/release, separations, and catalysis. Another area of interest are glassy materials where the porous structure is not permanent but emerges on the exposure to liquids (for example, segregated polyelectrolytes). The development of semi-permeable membranes with this porosity type is an excellent application for computational methods, and we expect contributions on their pore structure and transport.
Last, but not least, we certainly welcome manuscripts on data-based machine learning approaches to computational design, including the prediction of new structures with machine-learned interparticle potentials, data-driven modifications of existing materials for particular application, and finally, the exploration of chemical space in pursuit of new porous structures, such as new zeolites, MOFs and more.
A short abstract cannot describe such a broad field, and the editor might have much to learn from manuscripts on materials, methods and applications that he is not aware of. In conclusion, this Special Issue welcomes original research and reviews on the computational design of nanoporous materials!
Dr. Aleksey M. Vishnyakov
Guest Editor
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Keywords
- Nanoporous materials
- Computational design
- Molecular modeling
- Mesoscale simulations
- Ab initio modeling
- Machine learning
- Structure–property relationships
- Zeolites
- Nanoporous carbons
- Templates porous materials
- Segregated polyelectrolytes
- Metal–organic frameworks
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