Public Abstract

DE-SC0010419: Quantification of Dynamic Disorder in Electronic and Excitonic Organic Materials

Award Status: Inactive

Institution: Regents of the University of California, Davis, Davis, CA
UEI: TX2DAGQPENZ5
DUNS: 047120084

Most Recent Award Date: 06/29/2021
Number of Support Periods: 9
PM: Kerch, Helen

Current Budget Period: 08/01/2021 - 07/31/2022
Current Project Period: 08/01/2019 - 07/31/2022
PI: Moule, Adam

Supplement Budget Period: N/A

Public Abstract

It is currently not possible to predict electronic or excitonic materials properties from structural data in organic materials in general and organic electronic materials specifically. This means that new materials are found through lucky guesses and/or new synthetic routes. To generate designer organic electronic materials for specific applications, it would be necessary to accurately predict relevant materials properties, such as hole and electron charge mobility or exciton coherence length based on the chemical structure. This is currently not possible due to limitations in the ability of both electronic and classical models to simultaneously predict structure, structural disorder, dynamics, and dynamical disorder over relevant length scales. In our previous DOE-BES award, we developed a method to match density functional theory (DFT) simulations to both X-ray diffraction and inelastic neutron scattering (INS) dynamics data for crystalline samples with plane-wave DFT and then applied an electronic transport model to predict hole mobility. Here we propose to expand our scope by developing scalable simulation methods such as density functional tight binding (DFTB) and molecular dynamics (MD) that will enable us to predict electronic materials properties for disordered, mixed, and polymeric materials. In addition, we propose to build the next generation of measurement tools to enable new science on excitonic materials by designing and building an optical excitation measurement environment for the INS instrument at Oak Ridge National Lab called “VISION”. This contribution will be significant because our proposed tool to link INS validated force potentials to MD and DFTB models will enable electronic and excitonic materials properties predictions in amorphous, mixed, and polymeric materials that make up the majority of commercial organic electronic materials. For neutron sciences, the proposed research develops interpretation tools and new sample environments that will enhance capabilities for the user community and the VISION beamline at Oak Ridge National Lab specifically. The significance in organics electronics is felt in the areas of materials characterization, electronic property prediction, and materials design. The dynamic data generated coupled with multiscale models will become a database for machine learning for advanced computational tools to predict properties of new materials. The wider significance of the multi-scale tool to interpret INS data is that researchers in other materials fields, such as metal organic frameworks, structural polymers and gels, biomaterials etc. will now be able to utilize INS as a method to measure dynamics.

It is currently not possible to predict electronic or excitonic materials properties from structural data in organic materials in general and organic electronic materials specifically. This means that new materials are found through lucky guesses and/or new synthetic routes. To generate designer organic electronic materials for specific applications, it would be necessary to accurately predict relevant materials properties, such as hole and electron charge mobility or exciton coherence length based on the chemical structure. This is currently not possible due to limitations in the ability of both electronic and classical models to simultaneously predict structure, structural disorder, dynamics, and dynamical disorder over relevant length scales. In our previous DOE-BES award, we developed a method to match density functional theory (DFT) simulations to both X-ray diffraction and inelastic neutron scattering (INS) dynamics data for crystalline samples with plane-wave DFT and then applied an electronic transport model to predict hole mobility. Here we propose to expand our scope by developing scalable simulation methods such as density functional tight binding (DFTB) and molecular dynamics (MD) that will enable us to predict electronic materials properties for disordered, mixed, and polymeric materials. In addition, we propose to build the next generation of measurement tools to enable new science on excitonic materials by designing and building an optical excitation measurement environment for the INS instrument at Oak Ridge National Lab called “VISION”. This contribution will be significant because our proposed tool to link INS validated force potentials to MD and DFTB models will enable electronic and excitonic materials properties predictions in amorphous, mixed, and polymeric materials that make up the majority of commercial organic electronic materials. For neutron sciences, the proposed research develops interpretation tools and new sample environments that will enhance capabilities for the user community and the VISION beamline at Oak Ridge National Lab specifically. The significance in organics electronics is felt in the areas of materials characterization, electronic property prediction, and materials design. The dynamic data generated coupled with multiscale models will become a database for machine learning for advanced computational tools to predict properties of new materials. The wider significance of the multi-scale tool to interpret INS data is that researchers in other materials fields, such as metal organic frameworks, structural polymers and gels, biomaterials etc. will now be able to utilize INS as a method to measure dynamics.