Repurposing Crystalline Materials for Strong Terahertz Generation

The discovery of new materials is driving technology development in many fields, such as renewable energy and communications. Researchers often record useful characteristics of materials in searchable databases. These databases are valuable because materials designed with one purpose in mind could find completely different applications.

How to discover these unrealized applications is a both a great challenge and an opportunity. This project will combine data mining with computer-based modeling to predict how efficiently any given material will generate terahertz (THz) light. High quality crystals of promising candidates will be grown and tested.

This approach will lead to new state-of-the-art high-intensity terahertz generating materials, in turn enabling advances in biological research, chemical monitoring, and wireless communications. This project will help to train a new generation of students in the interdisciplinary areas of data science and materials development. The PI directs the Talmage Research Internship program to provide research experiences to undergraduate students from colleges without strong research programs.

The co-PI coordinates a freshman mentoring program to ensure a diverse group of undergraduate students can begin and continue to participate in research that leads to productive careers as researchers in chemistry and material science.

The design and discovery of advanced solid materials with useful properties and functionalities is essential to the advancement of many fields, including spectroscopy, catalysis, electron transport, energy storage and release, and air and water purification. For these applications, the microscopic properties of molecular building blocks, along with specific surface geometries, molecular packing, and molecular orientation in the solid state govern the function of the material.

Traditionally, it can take years to identify, crystalize, and develop THz generators. The research team uses data mining tools to search structural databases and identify materials with unique solid-state properties, which can be optimized for applications that differ from their original reported use. Combining data mining with first-principles calculations enables the identification of extremely promising materials to maximize success rates in materials development.

This powerful combination enables the identification of ideal candidate molecules with high molecular hyperpolarizabilities that pack with high densities and favorable interactions giving non-centrosymmetric head-to-tail configurations for efficient THz generation. The most promising candidates will be synthesized, crystallized, and tested for THz generation efficiency.

The research team’s strategy greatly accelerates the materials development process by allowing the team to use crystallographic data and first-principles computations to calculate linear and nonlinear optical properties at near IR and THz frequencies, enabling the team to predict the strength of THz generation, as well as the generated THz spectrum for essentially any material in the Cambridge Crystallographic Data Centre (CCDC) database. The research team demonstrates that data mining combined with first-principles calculations can maximize success rates in materials development, which will be applicable to many research areas.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.