The first HyDRA challenge for computational vibrational spectroscopy.
Taija L FischerMargarethe BödeckerSophie M SchweerJennifer DupontValéria LepèreAnne Zehnacker-RentienMartin A SuhmBenjamin SchröderTobias HenkesDiego M AndradaRoman M BalabinHaobam Kisan SinghHimangshu Pratim BhattacharyyaManabendra SarmaSilvan KäserKai TöpferLuis Itza Vazquez-SalazarEric D BoittierMarkus MeuwlyGiacomo MandelliCecilia LanziRiccardo ConteMichele CeottoFabian DietrichVicente CisternasRamachandran GnanasekaranMichael F A HipplerMahmoud JarrayaMajdi HochlafNarasimhan ViswanathanThomas NevolianisGabriel RathWassja A KoppKai LeonhardRicardo A MataPublished in: Physical chemistry chemical physics : PCCP (2023)
Vibrational spectroscopy in supersonic jet expansions is a powerful tool to assess molecular aggregates in close to ideal conditions for the benchmarking of quantum chemical approaches. The low temperatures achieved as well as the absence of environment effects allow for a direct comparison between computed and experimental spectra. This provides potential benchmarking data which can be revisited to hone different computational techniques, and it allows for the critical analysis of procedures under the setting of a blind challenge. In the latter case, the final result is unknown to modellers, providing an unbiased testing opportunity for quantum chemical models. In this work, we present the spectroscopic and computational results for the first HyDRA blind challenge. The latter deals with the prediction of water donor stretching vibrations in monohydrates of organic molecules. This edition features a test set of 10 systems. Experimental water donor OH vibrational wavenumbers for the vacuum-isolated monohydrates of formaldehyde, tetrahydrofuran, pyridine, tetrahydrothiophene, trifluoroethanol, methyl lactate, dimethylimidazolidinone, cyclooctanone, trifluoroacetophenone and 1-phenylcyclohexane- cis -1,2-diol are provided. The results of the challenge show promising predictive properties in both purely quantum mechanical approaches as well as regression and other machine learning strategies.
Keyphrases
- energy transfer
- density functional theory
- molecular dynamics
- machine learning
- molecular dynamics simulations
- single molecule
- high resolution
- quantum dots
- big data
- molecular docking
- high frequency
- electronic health record
- artificial intelligence
- healthcare
- monte carlo
- risk assessment
- human health
- magnetic resonance imaging
- data analysis
- health insurance