Autofit and the Spectrum of Eugenol New College of Florida: Erika Riffe, Sawyer Welden, Emma Cockram, Katherine Ervin, Steven Shipman Coker College: Cameron M. Funderburk, Gordon G. Brown Emory University: Susanna L. Widicus Weaver

Cloves and Clove Oil (Eugenol) Image from https://en.wikipedia.org/wiki/Eugenol Images from https://en.wikipedia.org/wiki/Clove

Eugenol Structures and Energies (B3LYP/6-311+G(d,p)) 0 cm-1 130 cm-1 343 cm-1 A = 1420.8 B = 617.3 C = 445.2 A = 1733.3 B = 524.5 C = 414.3 A = 2185.6 B = 480.3 C = 410.3 Methoxy Scan (from minimum) Alkene Scan (from minimum)

Coker College Spectrometer

Eugenol Spectrum Sample T = 80 °C, Expansion T = 5 K 20 μs FID, 10k averages, S/N: 53:1 106 peaks with S/N > 3:1

Autofit

Previous Autofit Results

Cluster Computing Main Challenges: Image from https://en.wikipedia.org/wiki/Computer_cluster Main Challenges: Need to port code to very different environment No interactive scripts – submit job and log out Images from http://www.emerson.emory.edu/

Non-interactive Scripts Most parameters read in from input file or command line. Most significant: automated selection of fitting / scoring transitions Process Simulate based on type (a-type, b-type, etc.) and initial constants Find 10 most-intense peaks from .cat file in frequency range Choose 3 fit transitions based on weighted combination of: linear independence sensitivity to rotational constants overall intensity Remaining 7 are scoring transitions

Grid-Based Search A = 1781, B = 721, C = 514 505 – 404: 5730 533 – 432: 6248 514 – 413: 6548 505 – 404: 7372 533 – 432: 7393 514 – 413: 7476 Transitions move dramatically with rotational constants. Use larger search windows or grid of initial guesses (or both). Sampling volume defined by A ≥ B ≥ C. What’s the most efficient method, given transition sensitivity? Equal spacing for now. A A B B C C

Tests with Hexanal Dominant conformers identified as expected. For blind search: many autofit jobs! Wrote scripts to summarize output from hundreds of jobs. # jobs = [(1/2) (n3 + n2)] x 6 (a-, b-, c-, ab-, ac-, bc-type spectra)

Summary Eugenol extracted via steam distillation in high yield and purified. Cluster-ready autofit with grid-based search works. Eugenol autofit jobs are on-going (perhaps already completed!) Future Work Revamp code using Open MPI to run on multiple compute nodes (currently limited to one). Easy routes for further parallelization. Consider automatically classifying spectrum by type to reduce number of jobs – machine learning? Bulk of run time is spent on SPCAT and SPFIT – possible to optimize? Investigate alternate optimization methods (swarm algorithms)

Acknowledgements Anne-Lise Emig, Oliver Gray, Wes Harper, Maggie Swerdloff Luyao Zhou, Cherry L. Emerson Center for Scientific Computation

Eugenol Spectrum Sample T = 80 °C Expansion T = 5 K 20 μs FID, 10k averages S/N: 53:1 220 peaks with S/N > 3:1