Spin diffusion transfer difference (SDTD) NMR: An advanced method for the characterisation of water structuration within particle networks.
Spin diffusion transfer difference (SDTD) NMR: An advanced method for the characterisation of water structuration within particle networks.
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自旋扩散传递差 (SDTD) NMR:一种表征颗粒网络内水结构的先进方法。
DOI:
10.1016/j.jcis.2021.02.094
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发表时间:
2021
影响因子:
9.9
通讯作者:
Gabrielli V
中科院分区:
文献类型:
--
作者:
Gabrielli V
HypothesisThe classical STD NMR protocol to monitor solvent interactions in gels is strongly dependent on gelator and solvent concentrations and does not report on the degree of structuration of the solvent at the particle/solvent interface. We hypothesised that, for suspensions of large gelator particles, solvent structuration could be characterised by STD NMR when taking into account the particle-to-solvent1H–1H spin diffusion transfer using the 1D diffusion equation.ExperimentsWe have carried out a systematic study on effect of gelator and solvent concentrations, and gelator surface charge, affecting the behaviour of the classical STD NMR build-up curves. To do so, we have characterised solvent interactions in dispersions of starch and cellulose-like particles prepared in deuterated water and alcohol/D2O mixtures.FindingsThe Spin Diffusion Transfer Difference (SDTD) NMR protocol is independent of the gelator and solvent concentrations, hence allowing the estimation of the degree of solvent structuration within different particle networks. In addition, the simulation of SDTD build-up curves using the general one–dimensional diffusion equation allows the determination of minimum distances (r) and spin diffusion rates (D) at the particle/solvent interface. This novel NMR protocol can be readily extended to characterise the solvent(s) organisation in any type of colloidal systems constituted by large particles.
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DOI:
--
发表时间:
1998
期刊:
影响因子:
--
作者:
N. Fatkullin;G. Yatsenko;R. Kimmich;E. Fischer
通讯作者:
E. Fischer
DOI:
10.1002/chem.201700793
发表时间:
2017-06-12
期刊:
Chemistry (Weinheim an der Bergstrasse, Germany)
影响因子:
--
作者:
Ramalhete SM;Nartowski KP;Sarathchandra N;Foster JS;Round AN;Angulo J;Lloyd GO;Khimyak YZ
通讯作者:
Khimyak YZ
影响因子:
56.9
作者:
J. Alexander
通讯作者:
J. Alexander
影响因子:
3.4
作者:
Martinez-Sanz, Marta;Gidley, Michael J.;Gilbert, Elliot P.
通讯作者:
Gilbert, Elliot P.
影响因子:
6.1
作者:
Foston, Marcus;Katahira, Rui;Ragauskas, Arthur J.
通讯作者:
Ragauskas, Arthur J.