ABSTRACT

Technical Abstract

This DMR project creates a computational-based design, applied to amorphous microporous materials that complement and dramatically enhance traditional experimental methods. A fundamental understanding of amorphous microporous materials is being generated that will allow new materials to be discovered for the benefit of the general scientific community. This project involves training a new generation of materials scientists who think differently about data. Open-data paradigms in which students/researchers think of their data as a public good to be eventually shared and used by others would transform the materials research enterprise, and catalyzed through this work.
The proposed research focuses on investigate three new classes of nanoporous materials through the use of molecular simulations, which will direct chemical synthesis and facilitate the understanding and preparation of novel amorphous materials. Tailoring and optimization of these materials include: 1) Polymer and organic molecules of intrinsic microporosity (PIMs and OMIMs), which will greatly enhance their suitability as heterogeneous catalysts, adsorbents and gas storage materials. 2) Crosslinked polyolefin terpolymers as promising candidates for natural gas (NG) storage, and 3) Stilbene containing alternating copolymers, semi-rigid amorphous copolymers, as new polyelectrolytes and other functionalizations for optical applications. Concurrent to the above goals, is the generation of large-data sets and the extraction of critical information from that data (e.g., structure factors to understand the intrinsic correlations between structure and properties/behavior) to catalyze materials breakthroughs. This work, will generate the knowledge to develop appropriate structure-property relations for novel microporous molecular and polymeric materials, which will result in the design, synthesis and characterization of optimized materials that will possess technological relevance.
Additionally, students will receive significant training through close interactions with the PI and program colleagues. Students will benefit from the interaction and immersion in a global collaborative research environment with national and international experts that will complement the intensive training in simulation that they receive at Penn State. The PI plans to empower the next generation of junior researchers by the application of open-data paradigms that include data sharing as a public good, and thus transform the materials research enterprise.

This award is funded by the Division of Materials Research in the Mathematical and Physical Sciences Directorate (Computational and Data-Driven Materials Research).

Non-Technical Abstract

One of the principal aims of modern science is to use computational methods to help understand and even predict the results from experimentation. Today, exciting opportunities exist for a transformation in the way materials research is conducted, including a data-driven revolution in materials discovery and design.

The overarching goal of this research is to create a computational-based design, applied to amorphous microporous materials that complement and dramatically enhance traditional experimental methods. Here, the research includes the improvement of knowledge transfer and facilitation of the development and application of a vast variety of amorphous materials to industrial applications. A fundamental understanding of amorphous microporous materials will be generated that will allow new materials to be discovered for the benefit of the general community. This involves training a new generation of materials scientists who think differently about data. Open-data paradigms in which students think of their data as a public good to be eventually shared and used by others would transform the materials research enterprise, and catalyzed through this work. Additionally, undergraduates and graduate students will benefit from the interaction and immersion in a global collaborative research environment with national and international experts that will complement the intensive training in simulation that they receive at Penn State.
In summary, the next generation of junior researchers will be empowered by the application of open-data paradigms that include data sharing as a public good, and thus transform the materials research enterprise.

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