Publications by authors named "Parker Sornberger"

We investigate the anisotropic thermal expansion behavior of a co-crystalline system composed of 4,4'-azopyridine and trimesic acid (TMA-azo). Using variable-temperature single-crystal X-ray diffraction (SC-XRD), low-frequency Raman spectroscopy, and terahertz time-domain spectroscopy (THz-TDS), we observe significant temperature-induced shifting and broadening of the vibrational absorption features, indicating changes in the intermolecular potential. Our findings reveal that thermal expansion is driven by anharmonic interactions and the potential energy topography, rather than increased molecular dynamics.

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Accelerating the development of π-conjugated molecules for applications such as energy generation and storage, catalysis, sensing, pharmaceuticals, and (semi)conducting technologies requires rapid and accurate evaluation of the electronic, redox, or optical properties. While high-throughput computational screening has proven to be a tremendous aid in this regard, machine learning (ML) and other data-driven methods can further enable orders of magnitude reduction in time while at the same time providing dramatic increases in the chemical space that is explored. However, the lack of benchmark datasets containing the electronic, redox, and optical properties that characterize the diverse, known chemical space of organic π-conjugated molecules limits ML model development.

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Article Synopsis
  • Materials discovery has traditionally relied on slow, costly trial-and-error methods, but new advances in computational power and data science are changing this approach.
  • The OCELOT infrastructure offers a Python-based application and database to facilitate rapid exploration of crystalline organic semiconductors.
  • With a database of over 56,000 experimental crystal structures linked to 47,000 unique molecular structures, OCELOT provides open-access tools for efficient materials screening.
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