Valence structures of aromatic bioactive compounds: a combined theoretical and experimental study.

Valence electronic structures of three recently isolated aryl bioactive compounds, namely 2-phenylethanol (2PE), p-hydroxyphenylethanol (HPE) and 4-hydroxybenzaldehyde (HBA), are studied using a combined theoretical and experimental method. Density functional theory-based calculations indicate that the side chains cause electron charge redistribution and therefore influence the aromaticity of the benzene derivatives. The simulated IR spectra further reveal features induced by the side chains. Solvent effects on the IR spectra are simulated using the polarizable continuum model, which exhibits enhancement of the O-H stretch vibrations with significant red-shift of 464 cm(-1) in 2PE. A significant spectral peak splitting of 94 cm(-1) between O(4)-H and O(8)-H of HPE is revealed in an aqueous environment. Experimental measurements for valence binding energy spectra for 2PE, HPE and HBA are presented and analyzed using outer-valence Green function calculations. The experimental (predicted) first ionization energies are measured as 9.19 (8.79), 8.47 (8.27) and 8.97 (8.82) eV for 2PE, HPE and HBA, respectively. The frontier orbitals (highest occupied molecular orbitals, HOMOs, and lowest unoccupied molecular orbitals, LUMOs) have similar atomic orbital characters although the HOMO-LUMO energy gaps are quite different

Three-Dimensional Shapes of Spinning Helium Nanodroplets

A significant fraction of superfluid helium nanodroplets produced in a free-jet expansion have been observed to gain high angular momentum resulting in large centrifugal deformation. We measured single-shot diffraction patterns of individual rotating helium nanodroplets up to large scattering angles using intense extreme ultraviolet light pulses from the FERMI free-electron laser. Distinct asymmetric features in the wide-angle diffraction patterns enable the unique and systematic identification of the three-dimensional droplet shapes. The analysis of a large dataset allows us to follow the evolution from axisymmetric oblate to triaxial prolate and two-lobed droplets. We find that the shapes of spinning superfluid helium droplets exhibit the same stages as classical rotating droplets while the previously reported metastable, oblate shapes of quantum droplets are not observed. Our three-dimensional analysis represents a valuable landmark for clarifying the interrelation between morphology and superfluidity on the nanometer scale

Deep neural networks for classifying complex features in diffraction images

Intense short-wavelength pulses from free-electron lasers and high-harmonic-generation sources enable diffractive imaging of individual nano-sized objects with a single x-ray laser shot. The enormous data sets with up to several million diffraction patterns represent a severe problem for data analysis, due to the high dimensionality of imaging data. Feature recognition and selection is a crucial step to reduce the dimensionality. Usually, custom-made algorithms are developed at a considerable effort to approximate the particular features connected to an individual specimen, but facing different experimental conditions, these approaches do not generalize well. On the other hand, deep neural networks are the principal instrument for today's revolution in automated image recognition, a development that has not been adapted to its full potential for data analysis in science. We recently published in Langbehn et al. (Phys. Rev. Lett. 121, 255301 (2018)) the first application of a deep neural network as a feature extractor for wide-angle diffraction images of helium nanodroplets. Here we present the setup, our modifications and the training process of the deep neural network for diffraction image classification and its systematic benchmarking. We find that deep neural networks significantly outperform previous attempts for sorting and classifying complex diffraction patterns and are a significant improvement for the much-needed assistance during post-processing of large amounts of experimental coherent diffraction imaging data.Comment: Published Version. Github code available at: https://github.com/julian-carpenter/airyne

Carbon and Nitrogen K-Edge NEXAFS Spectra of Indole, 2,3-Dihydro-7-azaindole, and 3-Formylindole

The near-edge X-ray absorption fine structure (NEXAFS) spectra of indole, 2,3-dihydro-7-azaindole, and 3-formylindole in the gas phase have been measured at the carbon and nitrogen K-edges. The spectral features have been interpreted based on density functional theory (DFT) calculations within the transition potential (TP) scheme, which is accurate enough for a general description of the measured C 1s NEXAFS spectra as well as for the assignment of the most relevant features. For the nitrogen K-edge, the agreement between experimental data and theoretical spectra calculated with TP-DFT was not quite satisfactory. This discrepancy was mainly attributed to the many-body effects associated with the excitation of the core electron, which are better described using the time-dependent density functional theory (TDDFT) with the range-separated hybrid functional CAM-B3LYP. An assignment of the measured N 1s NEXAFS spectral features has been proposed together with a complete description of the observed resonances. Intense transitions from core levels to unoccupied antibonding π* states as well as several transitions with mixed-valence/Rydberg or pure Rydberg character have been observed in the C and N K-edge spectra of all investigated indoles

Improved stabilization scheme for extreme ultraviolet quantum interference experiments

Interferometric pump-probe experiments in the extreme ultraviolet (XUV) domain are experimentally very challenging due to the high phase stability required between the XUV pulses. Recently, an efficient phase stabilization scheme was introduced for seeded XUV free electron lasers (FELs) combining shot-to-shot phase modulation with lock-in detection. This method stabilized the seed laser beampath on the fundamental ultraviolet wavelength to a high degree. Here, we extend this scheme including the stabilization of the XUV beampath, incorporating phase fluctuations from the FEL high gain harmonic generation process. Our analysis reveals a clear signal improvement with the new method compared to the previous stabilization scheme

High-Gain Harmonic Generation with temporally overlapping seed pulses and application to ultrafast spectroscopy

Collinear double-pulse seeding of the High-Gain Harmonic Generation (HGHG) process in a free-electron laser (FEL) is a promising approach to facilitate various coherent nonlinear spectroscopy schemes in the extreme ultraviolet (XUV) spectral range. However, in collinear arrangements using a single nonlinear medium, temporally overlapping seed pulses may introduce nonlinear mixing signals that compromise the experiment at short time delays. Here, we investigate these effects in detail by extending the analysis described in a recent publication (Wituschek et al., Nat. Commun., 11, 883, 2020). High-order fringe-resolved autocorrelation and wave-packet interferometry experiments at photon energies > $23\,$eV are performed, accompanied by numerical simulations. It turns out that both the autocorrelation and the wave-packet interferometry data are very sensitive to saturation effects and can thus be used to characterize saturation in the HGHG process. Our results further imply that time-resolved spectroscopy experiments are feasible even for time delays smaller than the seed pulse duration.Comment: This is accepted version of the article. The Version of Record is available online at https://doi.org/10.1364/OE.40124

Application of Matched-Filter Concepts to Unbiased Selection of Data in Pump-Probe Experiments with Free Electron Lasers

Pump-probe experiments are commonly used at Free Electron Lasers (FEL) to elucidate the femtosecond dynamics of atoms, molecules, clusters, liquids and solids. Maximizing the signal-to-noise ratio of the measurements is often a primary need of the experiment, and the aggregation of repeated, rapid, scans of the pump-probe delay is preferable to a single long-lasting scan. The limited availability of beamtime makes it impractical to repeat measurements indiscriminately, and the large, rapid flow of single-shot data that need to be processed and aggregated into a dataset, makes it difficult to assess the quality of a measurement in real time. In post-analysis it is then necessary to devise unbiased criteria to select or reject datasets, and to assign the weight with which they enter the analysis. One such case was the measurement of the lifetime of Intermolecular Coulombic Decay in the weakly-bound neon dimer. We report on the method we used to accomplish this goal for the pump-probe delay scans that constitute the core of the measurement; namely we report on the use of simple auto- and cross-correlation techniques based on the general concept of “matched filter”. We are able to unambiguously assess the signal-to-noise ratio (SNR) of each scan, which then becomes the weight with which a scan enters the average of multiple scans. We also observe a clear gap in the values of SNR, and we discard all the scans below a SNR of 0.45. We are able to generate an average delay scan profile, suitable for further analysis: in our previous work we used it for comparison with theory. Here we argue that the method is sufficiently simple and devoid of human action to be applicable not only in post-analysis, but also for the real-time assessment of the quality of a dataset