UV‐ignited frontal polymerization of an epoxy resin

By combining frontal polymerization and radical‐induced cationic polymerization, it was possible to cure thick samples of an epoxy monomer bleached by UV light. The effect of the relative amounts of cationic photoinitiator and radical initiator was thoroughly investigated and was related to the front's velocity and its maximum temperature. The materials obtained were characterized by quantitative conversion also in the deeper layers, not reached by UV light. © 2004 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 42: 2066–2072, 2004     

Fluoride effect on the palladium–phenanthroline catalyzed carbonylation of nitroarenes to carbamates

Fluorides promote the palladium–phenanthroline catalyzed carbonylation of nitroarenes to carbamates. The effect is more evident on the rate of the reaction at short reaction times, but a positive effect on selectivity is also observed under certain conditions. The effect is observed even under conditions under which chloride inhibits the reaction. Tetraethylammonium is a better countercation than sodium. Copyright © 2007 John Wiley & Sons, Ltd.     

Reaction-based machine learning representations for predicting the enantioselectivity of organocatalysts

Hundreds of catalytic methods are developed each year to meet the demand for high-purity chiral compounds. The computational design of enantioselective organocatalysts remains a significant challenge, as catalysts are typically discovered through experimental screening. Recent advances in combining quantum chemical computations and machine learning (ML) hold great potential to propel the next leap forward in asymmetric catalysis. Within the context of quantum chemical machine learning (QML, or atomistic ML), the ML representations used to encode the three-dimensional structure of molecules and evaluate their similarity cannot easily capture the subtle energy differences that govern enantioselectivity. Here, we present a general strategy for improving molecular representations within an atomistic machine learning model to predict the DFT-computed enantiomeric excess of asymmetric propargylation organocatalysts solely from the structure of catalytic cycle intermediates. Mean absolute errors as low as 0.25 kcal mol⁻¹ were achieved in predictions of the activation energy with respect to DFT computations. By virtue of its design, this strategy is generalisable to other ML models, to experimental data and to any catalytic asymmetric reaction, enabling the rapid screening of structurally diverse organocatalysts from available structural information.

A machine learning model for enantioselectivity prediction using reaction-based molecular representations.     

Die Reduktion von Cu2+-Ionen durch Fe2+-Ionen

The conditions, under which in aqueous solution Cu^II ist reduced by Fe^II, are discussed. The conditions for the formation of Cu₂O and metallic Cu, respectively, are determined by means of potentiometric measurements and other experiments.     

Bestimmung des Chiralitätssinns der enantiomeren 2,6-Adamantandiole

Determination of the Chirality Sense of the Enantiomeric 2,6-Adamantanediols The enantiomers of 2,6-adamantanediol ( 1 ) are resolved via the diastereoisomeric camphanoates. The (2R,6R)-chirality sense for (?)- 1 and (2S,6S) for (+)- 1 was determined by chemical correlation with (?)-(1R,5R)-bicyclo[3.3.1]nonan-2,6-dion ((1R,5R)- 3 ) of known absolute configuration in the following way: alkylation of the bis(pyrrolidine enamine) of (?)-(1R,5R)- 3 with CD₂I₂ and hydrolysis of the product gives the enantiomer 4 of (4,4-D₂)-2,6-adamantanedione. Reduction of 4 with LiAlH₄ leads to one enantiomer (Scheme 2) of each of the three diols 5 – 7 of known absolute configuration. The three diols are themselves configurational isomers due to the presence of the CD₂ group, but correspond otherwise entirely to the enantiomeric diols 1 . Accordingly, they can also be separated by means of their diastereoisomeric camphanoates to give the diols 5 / 6 and 7 . These samples are easily distinguished and identified by their characteristic ¹H-NMR spectra (cf. Fig. 2). This allows to identify the (2R,6R)- and (2S,6S)-enantiomer of 1 on the basis of their behavior in the resolution experiment analogous to that of the diols 5 / 6 and 7 , respectively. The diol (?)- 1 must have the (2R,6R)-configuration because it forms, like the diols 5 / 6 , with (?)-camphanic acid the diastereoisomeric ester less soluble in benzene. The diol (+)- 1 has (2S,6S)-configuration, because it forms, like 7 , with (+)-camphanic acid the diastereoisomeric ester less soluble in benzene. The bis(4-methoxybenzoate) of (?)-(2R,6R)- 1 shows chiroptical properties which are in accordance with Nakanishi's rule for two chromophores having coupled electric dipol transition moments arranged with a left-handed torsion angle.     

Synthese des Dysidins

Synthesis of Dysidin The synthesis of dysidin ((?)- 1 ), the enantiomer of a metabolite of the marine sponge Dysidea herbacea, is described. To effect the synthesis, (±)-5-isopropyl-4-methoxy-3-pyrrolin-2-one ( 7 ) is converted to its lithium salt and reacted with (?)-(5R,2E)-3-methoxy-5-trichloromethyl-2-hexenoyl chloride ((-)- 11 ) to give (?)- 1 and its diastereoisomer (+)-5-epidysidin ((+)- 12 ) epimeric at C(5) of the pyrrolinone ring. The (?)-acyl chloride (?)- 11 has been synthesized from (+)-(R)-3-(trichloromethyl)butanoic acid ((+)- 8 ) via the intermediates (+)- 9 and (?)- 10 , the pyrrolinone 7 from N-benzyl-oxycarbonyl-L-valine via the intermediate 5 . The enantiomers of acid 8 have been resolved by fractional crystallization of their diastereoisomeric N-(1-phenylethyl)amides. The (R)-chirality of (+)- 8 was determined by comparing the ¹H-NMR spectra of the diastereoisomeric N-(1-phenylethyl)amides 16 and 17 , made from (+)- 8 by substituting deuterium for chlorine, with the spectra of the N-(1-phenylethyl)amides 14 and 15 of known absolute configuration. This correlation shows that literature value (R) for (?)- 8 is in error. Therefore, the structural formulae of (?)-dysidenin and (+)-isodysidenin, two other metabolites of D.herbacea, have to be changed to their mirror images as shown in formulae (?)- 3 and (+)- 4 , respectively.     

Molecular mechanics (MM2) calculations and cone angles of phosphine ligands

Molecular mechanics (MM2) calculations were performed on 54 conformations of 18 phosphines (PH₃; PH_3−nR_n, where n = 1,…3, and R = Me and Et, n = 1 or 2 and R =ⁱPr, and n = 1 and R =^tBu, PMe₂Et, PMeEt₂, and PPhMe₂, and PPh₂R where R = Me, Et, ⁱPr, ^tBu and Ph). The results are compared to those previously obtained from MINDO/3 and MNDO calculations, and to experimental data. Single conformer cone angles and weighted average cone angles were calculated from MM2 optimized geometries employing Tolman's general definition, and they are compared to Tolman's values, MINDO/3 results, and T.L. Brown's E_R values. Of the cone angle definitions used, the weighted average values are suggested as the best single representation of phosphine ligand sizes. The steric parameters (cone angle and E_R values) alone, and in conjunction with electronic parameters, are correlated with experimental data.