DOI: 10.5061/dryad.3ffbg79q3
title: Revisiting the paradigm of reaction optimization in flow with a priori computational reaction intelligence

description: The use of micro/meso-fluidic reactors has resulted in both new scenarios
 for chemistry and new requirements for chemists. Through flow chemistry,
 large-scale reactions can be performed in drastically reduced reactor
 sizes and reaction times. This obvious advantage comes with the
 concomitant challenge of re-designing long-established batch processes to
 fit these new conditions. The reliance on experimental trial-and-error to
 perform this translation frequently makes flow chemistry unaffordable,
 thwarting initial aspirations to revolutionize chemistry. By combining
 computational chemistry and machine learning, we have developed a model
 that provides predictive power tailored specifically to flow reactions. We
 show its applications to translate batch to flow, to provide mechanistic
 insight, to contribute reagent descriptors, and to synthesize a library of
 novel compounds in excellent yields after executing a single set of
 conditions.
description: This data set concerns the characterization and identification of
 new organic compounds reported in this manuscript. 
 Please refer to the Supplementary Materials for
 details. <strong>NMR
 data</strong> <sup>1</sup>H and
 <sup>13</sup>C NMR spectra were recorded with a Bruker Avance
 III 400 MHz NMR spectrometer using residual solvent peaks as an internal
 standard (1H NMR: CDCl<sub>3</sub> at 7.26 ppm, TMS at 0.00
 ppm. <sup>13</sup>C NMR: CDCl<sub>3</sub> at 77.16
 ppm). Chemical shifts (δ) were reported in ppm and coupling constants (J)
 were reported in Hertz (Hz). Multiplicities were reported as singlet (s),
 doublet (d), triplet (t), q (quadruplet) and multiplet (m).
 <strong>HPLC</strong>
 Quantification of yields and conversions were done through HPLC
 analyses that were performed on a Shimadzu LC-2050C system equipped with a
 Diode Array Detector (DAD). The eluents used were: A: Water; B:
 Acetonitrile. <strong>X-ray
 Diffraction</strong> X-ray intensity data were
 collected at 100 K, on a Rigaku Oxford Diffraction Supernova Dual Source
 (Cu at zero) diffractometer equipped with an Atlas CCD detector using w
 scans and CuKa (l = 1.54184 Å) radiation. Using Olex2, the structures were
 solved by direct methods using the ShelXT structure solution program using
 Intrinsic Phasing and refined with the SHELXL refinement package using
 Least Squares minimisation. <strong>High
 Resolution Mass Spectra </strong> HRMS data were
 collected on a Thermo Scientific Q-Exactive Orbitrap (Full MS - ESI
 positive mode; Resolution: 140000).
description: <strong>NMR data</strong> Topsin
 or Mestrenova <strong>X-ray Diffraction</strong> enCIFer <strong>All other files</strong> All other files are pdf or Word files
description: # Nitrosoarenes, Silyl Enol Ethers and Silylated α-Hydroxylaminated
 Ketones Characterization ## DOI: 10.5061/dryad.3ffbg79q3 Each folder
 contains structural and identification data of novel compounds prepared
 during the following related work:
 [https://onlinelibrary.wiley.com/doi/10.1002/anie.202311526](https://onlinelibrary.wiley.com/doi/10.1002/anie.202311526). The chemical species can be either nitrosoarenes, silyl enol ethers or silylated α-hydroxylaminated ketones (please refer to the manuscript for compound numbering). For each compound, we provide (a) unprocessed NMR data, (b) HPLC reports, (c) optionally HRMS data for new compounds and (d) optionally X-ray diffraction structure determination for compounds 1g and 3a (please also refer to the Cambridge Crystallographic Data Centre (CCDC 2279232-2279233)). ## Description of the data and file structure Each folder is characterized with the following description. Name of the folder: Compound numbering from the manuscript Subfolder: unprocessed NMR data (folder #10 for 1H and #11 for 13C analyses) as well as processed NMR spectra as MNOVA format files. N.B.: Even empty, each file of this subfolder is necessary to ensure an in-depth analysis of the unprocessed data PDF file: HPLC chromatograms at 190 nm and the maximum absorption wavelength of the compound, as well as its UV spectrum DOCX file: HRMS chromatographs as well as elemental composition results CIF file (optional): X-ray diffraction structure information ## Methods NMR: 1H and 13C NMR spectra were recorded with a Bruker Avance III 400 MHz NMR spectrometer using residual solvent peaks as an internal standard (1H NMR: CDCl3 at 7.26 ppm, TMS at 0.00 ppm. 13C NMR: CDCl3 at 77.16 ppm). Chemical shifts (δ) were reported in ppm and coupling constants (J) were reported in Hertz (Hz). Multiplicities were reported as singlet (s), doublet (d), triplet (t), q (quadruplet) and multiplet (m). HPLC: Quantification of yields and conversions were done through HPLC analyses that were performed on a Shimadzu LC-2050C system equipped with a Diode Array Detector (DAD). Eluents: A = Water; B = Acetonitrile. Flow rate: 1 mL min-1. Column: C18, 100 x 4.6 mm, 3 μm. Oven Temperature: 40 °C. Diode Array Detector: 180-800 nm. Wavelength for analysis: maximum wavelength of each compound. SCXRD: X-ray intensity data were collected at 100 K, on a Rigaku Oxford Diffraction Supernova Dual Source (Cu at zero) diffractometer equipped with an Atlas CCD detector using  scans and CuK ( = 1.54184 Å) radiation. Using Olex2, the structures were solved by direct methods using the ShelXT structure solution program using Intrinsic Phasing and refined with the SHELXL refinement package using Least Squares minimisation. CCDC 2279232-2279233 (respectively for 3a and 1g) contains the supplementary crystallographic data for this paper. These data can be obtained free of charge from the Cambridge Crystallographic Data Centre via [www.ccdc.cam.ac.uk/structures](http://www.ccdc.cam.ac.uk/structures). ## Code/Software Unprocessed NMR data can be accessed with either MestReNova or TopSpin software. MestReNova is required to read processed NMR spectra. These were analyzed using version 14.2. Any PDF viewer can be used to view HPLC chromatograms. Any word processor can be employed for reading HRMS reports. Crystallographic structures can be visualized by reading the corresponding Crystallographic Information File with any text editor or crystallographic program.