Exploring the ultrafast and isomer-dependent photodissociation of iodothiophenes via site-selective ionization.

C-I bond extension and fission following ultraviolet (UV, 262 nm) photoexcitation of 2- and 3-iodothiophene is studied using ultrafast time-resolved extreme ultraviolet (XUV) ionization in conjunction with velocity map ion imaging. The photoexcited molecules and eventual I atom products are probed by site-selective ionization at the I 4d edge using intense XUV pulses, which induce multiple charges initially localized to the iodine atom. At C-I separations below the critical distance for charge transfer (CT), charge can redistribute around the molecule leading to Coulomb explosion and charged fragments with high kinetic energy. At greater C-I separations, beyond the critical distance, CT is no longer possible and the measured kinetic energies of the charged iodine atoms report on the neutral dissociation process. The time and momentum resolved measurements allow determination of the timescales and the respective product momentum and kinetic energy distributions for both isomers, which are interpreted in terms of rival 'direct' and 'indirect' dissociation pathways. The measurements are compared with a classical over the barrier model, which reveals that the onset of the indirect dissociation process is delayed by ∼1 ps relative to the direct process. The kinetics of the two processes show no discernible difference between the two parent isomers, but the branching between the direct and indirect dissociation channels and the respective product momentum distributions show isomer dependencies. The greater relative yield of indirect dissociation products from 262 nm photolysis of 3-iodothiophene (cf. 2-iodothiophene) is attributed to the different partial cross-sections for (ring-centred) π∗ ← π and (C-I bond localized) σ∗ ← (n/π) excitation in the respective parent isomers.

Imaging of Chemical Kinetics at the Water-Water Interface in a Free-Flowing Liquid Flat-Jet.

We present chemical kinetics measurements of the luminol oxidation chemiluminescence (CL) reaction at the interface between two aqueous solutions, using liquid jet technology. Free-flowing liquid microjets are a relatively recent development that have found their way into a growing number of applications in spectroscopy and dynamics. A variant thereof, called flat-jet, is obtained when two cylindrical jets of a liquid are crossed, leading to a chain of planar leaf-shaped structures of the flowing liquid. We here show that in the first leaf of this chain, the fluids do not exhibit turbulent mixing, providing a clean interface between the liquids from the impinging jets. We also show, using the example of the luminol CL reaction, how this setup can be used to obtain kinetics information from friction-less flow and by circumventing the requirement for rapid mixing by intentionally suppressing all turbulent mixing and instead relying on diffusion.

Low-energy constraints on photoelectron spectra measured from liquid water and aqueous solutions.

We report on the effects of electron collision and indirect ionization processes, occurring at photoexcitation and electron kinetic energies well below 30 eV, on the photoemission spectra of liquid water. We show that the nascent photoelectron spectrum and, hence, the inferred electron binding energy can only be accurately determined if electron energies are large enough that cross sections for quasi-elastic scattering processes, such as vibrational excitation, are negligible. Otherwise, quasi-elastic scattering leads to strong, down-to-few-meV kinetic energy scattering losses from the direct photoelectron features, which manifest in severely distorted intrinsic photoelectron peak shapes. The associated cross-over point from predominant (known) electronically inelastic to quasi-elastic scattering seems to arise at surprisingly large electron kinetic energies, of approximately 10-14 eV. Concomitantly, we present evidence for the onset of indirect, autoionization phenomena (occurring via superexcited states) within a few eV of the primary and secondary ionization thresholds. These processes are inferred to compete with the direct ionization channels and primarily produce low-energy photoelectrons at photon and electron impact excitation energies below ∼15 eV. Our results highlight that vibrational inelastic electron scattering processes and neutral photoexcitation and autoionization channels become increasingly important when photon and electron kinetic energies are decreased towards the ionization threshold. Correspondingly, we show that for neat water and aqueous solutions, great care must be taken when quantitatively analyzing photoelectron spectra measured too close to the ionization threshold. Such care is essential for the accurate determination of solvent and solute ionization energies as well as photoelectron branching ratios and peak magnitudes.

Creating ground truth for nanocrystal morphology: a fully automated pipeline for unbiased transmission electron microscopy analysis.

Control over colloidal nanocrystal morphology (size, size distribution, and shape) is important for tailoring the functionality of individual nanocrystals and their ensemble behavior. Despite this, traditional methods to quantify nanocrystal morphology are laborious. New developments in automated morphology classification will accelerate these analyses but the assessment of machine learning models is limited by human accuracy for ground truth, causing even unsupervised machine learning models to have inherent bias. Herein, we introduce synthetic image rendering to solve the ground truth problem of nanocrystal morphology classification. By simulating 2D images of nanocrystal shapes via a function of high-dimensional parameter space, we trained a convolutional neural network to link unique morphologies to their simulated parameters, defining nanocrystal morphology quantitatively rather than qualitatively. An automated pipeline then processes, quantitatively defines, and classifies nanocrystal morphology from experimental transmission electron microscopy (TEM) images. Using improved computer vision techniques, 42 650 nanocrystals were identified, assessed, and labeled with quantitative parameters, offering a 600-fold improvement in efficiency over best-practice manual measurements. A classification algorithm was trained with a prediction accuracy of 99.5%, which can successfully analyze a range of concave, convex, and irregular nanocrystal shapes. The resulting pipeline was applied to differentiating two syntheses of nominally cuboidal CsPbBr3 nanocrystals and uniquely classifying binary nickel sulfide nanocrystal phase based on morphology. This pipeline provides a simple, efficient, and unbiased method to quantify nanocrystal morphology and represents a practical route to construct large datasets with an absolute ground truth for training unbiased morphology-based machine learning algorithms.