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Thin film deposition is a fundamental technology for the discovery, optimization, and manufacturing of functional materials. Deposition by molecular beam epitaxy (MBE) typically employs reflection high-energy electron diffraction (RHEED) as a real-time in situ probe of the growing film. However, the state-of-the-art for RHEED analysis during deposition requires human observation. Here, we present an approach using machine learning (ML) methods to monitor, analyze, and interpret RHEED images on-the-fly during thin film deposition. In the analysis workflow, RHEED pattern images are collected at one frame per second and featurized using a pretrained deep convolutional neural network. The feature vectors are then statistically analyzed to identify changepoints; these changepoints can be related to changes in the deposition mode from initial film nucleation to a transition regime, smooth film deposition, and in some cases, an additional transition to a rough, islanded deposition regime. The feature vectors are additionally analyzed via graph analysis and community classification. The graph is quantified as a stabilization plot, and we show that inflection points in the stabilization plot correspond to changes in the growth regime. The full RHEED analysis workflow is termed RHAAPsody and includes data transfer and output to a visual dashboard. We demonstrate the functionality of RHAAPsody by analyzing the precaptured RHEED images from epitaxial depositions of anatase TiO2 on SrTiO3(001) and show that the analysis workflow can be executed in less than 1 s. Our approach shows promise as one component of ML-enabled real-time feedback control of the MBE deposition process. 

The catalytic uses of metal carbenes for addition, insertion, and cycloaddition reactions are dependent on their carbene precursor. The limited methods available for the preparation of diazo esters, which are the most common carbene precursors, restricts their ability to impart structural diversity in metal carbene reactions. Here we report a new methodology for the preparation of diverse vinyldiazoacetate esters and their effective uses in highly enantiocontrolled cyclopropanation, N-H bond insertion, O-H bond insertion, and [3+2] cycloaddition reactions. 1,2,3-Triazine 1-oxides with a sp3-C-H bond at the 5-position undergo base catalyzed Dimroth-type rearrangement to form multiply substituted oximidovinyldiazoacetates in high yields at or below room temperature, and these diverse vinyldiazo compounds undergo catalytic metal carbene transformations to produce oximidovinylcyclopropanes, α-oximidovinyl-α-amino acids and α-hydroxy acids, as well as tricyclic indole derivatives in high yields and enantioselectivities. The new access to vinyldiazo compounds has applicability to a vast array of metal carbene transformations. 

The cinchona thiourea moiety in the self-assembled modularly designed organocatalysts (MDOs) switches off the iminium catalysis of these catalysts. In this study, it was found that the inhibited iminium catalysis could be switched on by using an appropriate weak acid and that, once the iminium catalysis was switched on, these catalysts could be applied for the highly stereoselective and diastereodivergent synthesis of 4-oxocyclohexanecarbaldehydes via a domino reaction between ketones and α,β-unsaturated aldehydes.