Synthesis of phthalide derivatives using nickel-catalyzed cyclization of o-haloesters with aldehydes

The reaction of o-bromobenzoate (1 b) with benzaldehyde (2 a) in the presence of [NiBr(2)(dppe)] (dppe=1,2-bis(diphenylphosphino)ethane) and zinc powder in THF (24 hours, reflux temperature), afforded 3-phenyl-3H-isobenzofuran-1-one (3 a) in an 86 % yield. Similarly, o-iodobenzoate reacts with 2 a to give 3 a, but in a lower yield (50 %). A series of substituted aromatic and aliphatic aldehydes (2 b, 4-MeC(6)H(4)CHO; 2 c, 4-MeOC(6)H(4)CHO; 2 d, 3-MeOC(6)H(4)CHO; 2 e, 2-MeOC(6)H(4)CHO; 2 f, 4-CNC(6)H(4)CHO; 2 g, 4-(Me)(3)CC(6)H(4)CHO; 2 h, 4-C(6)H(5)C(6)H(4)CHO; 2 i, 4-ClC(6)H(4)CHO; 2 j, 4-CF(3)C(6)H(4)CHO; 2 k, CH(3)(CH(2))(5)CHO; 2 l, CH(3)(CH(2))(2)CHO) also underwent cyclization with o-bromobenzoate (1 b) producing the corresponding phthalide derivatives in moderate to excellent yields and with high chemoselectivity. Like 1 b, methyl 2-bromo-4,5-dimethoxybenzoate (1 c) reacts with tolualdehyde (2 b) to give the corresponding substituted phthalide 3 m in a 71 % yield. The methodology can be further applied to the synthesis of six-membered lactones. The reaction of methyl 2-(2-bromophenyl)acetate (1 d) with benzaldehyde under similar reaction conditions afforded six-membered lactone 3 o in a 68 % yield. A possible catalytic mechanism for this cyclization is also proposed.     

Synthesis and characterization of cobalt(II), nickel(II), copper(II), palladium(II) and dioxouranium(VI) complexes of the antipyrine Schiff base of 3-formylsalicylic acid

A new Schiff base has been synthesized from 4-aminoantipyrine and 3-formylsalicylic acid. The ligand has a dianionic tetradentate compartmental OONO donor system. The cobalt(II), nickel(II), copper(II) and dioxouranium(VI) complexes exist in phenolato-bridged dinuclear species, while palladium(II) gives a mononuclear complex with free –COOH groups. The complexes have been characterized by elemental analyses, i.r., u.v.-vis, thermal and magnetic measurements.     

Molybdenum complexes of bioinorganic interest. New dioxomolybdenum(VI) complexes of schiff bases derived from salicylaldehydes and salicylhydrazide

Summary New dioxomolybdenum(VI) complexes MoO₂L · H₂O (LH₂=Schiff base) derived from Salicylhydrazide and salicylaldehyde, 5-chloro-, 5-bromo-, 5-nitro-, 3-methoxy, 3-ethoxy-, 3,5-dichlorosalicylaldehyde and 2-hydroxy-1-naphthaldehyde have been synthesized and characterized, together with the MoO₂L · THF adducts. The complexes are monomers, nonelectrolytes and diamagnetic, and contain acis O=Mo=O     

Chloride, -Hydride and -Borohydride Derivatives of Difluorenyl Thallium(III)

Chloride¹), borohydrides²) and hydrides³) of dicyclopentadienyl thallium (III) and diindenyl thallium (III) have already been reported. The present communication deals with a study on the preparation and characterization of difluorenyl thallium (III) chloride, -hydride and -borohydride.     

An efficient route to regioselective opening of N-tosylaziridines with zinc(II) halides

An efficient route for the regio- and stereoselective ring opening of N-tosylaziridines with zinc dihalides (ZnX₂, X = Cl, Br, I) is described. Depending on the solvent and Zn(II) halide, β-halo amines or imidazolines are obtained selectively in good to excellent yields.     

Cu-nanoparticles: a chemoselective catalyst for the aza-Michael reactions of N-alkyl- and N-arylpiperazines with acrylonitrile

A novel method for effecting the aza-Michael reactions of N-alkyl- and N-arylpiperazines with acrylonitrile using Cu-nanoparticles is described. The method features the use of 10 mol % Cu (14-17 nm) nanoparticles under mild reaction conditions to afford the addition products in good to excellent yields. The Cu-nanoparticles selectively catalysed the aza-Michael reaction of N-alkyl- and N-arylpiperazines in the presence of aromatic amino or aliphatic hydroxy groups.     

Sc(OTf)3-catalyzed alkylation of indoles with propargyl alcohols: an expeditious synthesis of 3-substituted indoles

Indoles undergo smooth alkylation with propargylic alcohols in the presence of 10 mol % of scandium triflate under mild conditions to produce 3-propargylated indoles in excellent yields with high selectivity.     

Facile reduction of aromatic nitro/azido functionality on solid support employing Al/NiCl2·6H2O and Al/NH4Cl: synthesis of pyrrolo[2,1-c][1,4]benzodiazepines

An efficient and mild method for the reduction of aromatic nitro and azido groups on solid support using Al/NiCl₂·6H₂O and Al/NH₄Cl is described. This solid phase reduction technique has been applied towards the synthesis of DNA binding pyrrolo[2,1-c][1,4]benzodiazepine antitumour antibiotics.     

Conversion of ammonia to dinitrogen in wastewater by Nitrosomonas europaea

Because Nitrosomonas europaea contains ammonia-oxidizing enzyme, nitrite reductase, and nitrous oxide reductase, the conversion of ammonia to dinitrogen was tried with different reaction conditions. In aerobic reaction conditions, ammonium was converted to nitrite (NO ₂ ⁻ ), while under oxygen-limiting or oxygen-free conditions, NO ₂ ⁻ -N formed from ammonia oxidation by N. europaea was reduced to N₂O and dinitrogen with 22% conversion. During denitrification, optimal pH for the production of N₂O and dinitrogen was found to be 7.0–8.0. Dinitrogen was not produced in acidic pH<7.0. A low partial oxygen pressure as well as oxygen-free conditions are favorable for high production of dinitrogen.     

BonDNet: a graph neural network for the prediction of bond dissociation energies for charged molecules

A broad collection of technologies, including e.g. drug metabolism, biofuel combustion, photochemical decontamination of water, and interfacial passivation in energy production/storage systems rely on chemical processes that involve bond-breaking molecular reactions. In this context, a fundamental thermodynamic property of interest is the bond dissociation energy (BDE) which measures the strength of a chemical bond. Fast and accurate prediction of BDEs for arbitrary molecules would lay the groundwork for data-driven projections of complex reaction cascades and hence a deeper understanding of these critical chemical processes and, ultimately, how to reverse design them. In this paper, we propose a chemically inspired graph neural network machine learning model, BonDNet, for the rapid and accurate prediction of BDEs. BonDNet maps the difference between the molecular representations of the reactants and products to the reaction BDE. Because of the use of this difference representation and the introduction of global features, including molecular charge, it is the first machine learning model capable of predicting both homolytic and heterolytic BDEs for molecules of any charge. To test the model, we have constructed a dataset of both homolytic and heterolytic BDEs for neutral and charged (−1 and +1) molecules. BonDNet achieves a mean absolute error (MAE) of 0.022 eV for unseen test data, significantly below chemical accuracy (0.043 eV). Besides the ability to handle complex bond dissociation reactions that no previous model could consider, BonDNet distinguishes itself even in only predicting homolytic BDEs for neutral molecules; it achieves an MAE of 0.020 eV on the PubChem BDE dataset, a 20% improvement over the previous best performing model. We gain additional insight into the model''s predictions by analyzing the patterns in the features representing the molecules and the bond dissociation reactions, which are qualitatively consistent with chemical rules and intuition. BonDNet is just one application of our general approach to representing and learning chemical reactivity, and it could be easily extended to the prediction of other reaction properties in the future.

Prediction of bond dissociation energies for charged molecules with a graph neural network enabled by global molecular features and reaction difference features between products and reactants.