title: Diffusion coefficient distribution from NMR-DOSY experiments using Hopfield neural network.
abstract: Diffusion ordered spectroscopy (DOSY) is a powerful two-dimensional NMR method to study molecular translation in various systems. The diffusion coefficients are usually retrieved, at each frequency, from a fit procedure on the experimental data, considering a unique coefficient for each molecule or mixture. However, the fit can be improved if one regards the decaying curve as a multiexponential function and the diffusion coefficient as a distribution. This work presents a computer code based on the Hopfield neural network to invert the data. One small-molecule binary mixture with close diffusion coefficients is treated with this approach, demonstrating the effectiveness of the method.
authors.affiliation: Depto. de Química-ICEx, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil. ritacos@gmail.com
authors.forename: Rita C O
authors.initials: RC
authors.lastname: Sebastião
authors.forename: Carlos N
authors.initials: CN
authors.lastname: Pacheco
authors.forename: J P
authors.initials: JP
authors.lastname: Braga
authors.forename: Dorila
authors.initials: D
authors.lastname: Piló-Veloso
mesh_terms: D001643:Bridged Bicyclo Compounds / Q000737:chemistry*; D004058:Diffusion; D016571:Neural Networks, Computer; D019906:Nuclear Magnetic Resonance, Biomolecular / Q000379:methods*; D011422:Propionates / Q000737:chemistry*; D013331:Strychnine / Q000031:analogs & derivatives* / Q000737:chemistry
chemical_list: D001643:Bridged Bicyclo Compounds; D011422:Propionates; C096242:isopinocampheyl 2-methyl-2-(3-pyridyl)propanoate; C083806:brucine; D013331:Strychnine