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Direct conversion of EPR dipolar time evolution data to distance distributions

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons48107

Jeschke,  Gunnar
MPI for Polymer Research, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons48203

Koch,  A.
MPI for Polymer Research, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons48118

Jonas,  Ulrich
MPI for Polymer Research, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons47942

Godt,  Adelheid
MPI for Polymer Research, Max Planck Society;

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Zitation

Jeschke, G., Koch, A., Jonas, U., & Godt, A. (2002). Direct conversion of EPR dipolar time evolution data to distance distributions. Journal of Magnetic Resonance, 155(1), 72-82.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-6675-0
Zusammenfassung
Shallow electron spin echo envelope modulations due to dipole- dipole couplings between electron spins provide information on the radial distribution function of the spins in disordered systems while angular correlations between spin pairs are negligible. Under these conditions and in the absence of orientational selection, the dipolar time evolution data can be quantitatively simulated for arbitrary radial distribution functions by shell factorization, i.e., by performing the orientational average separately for thin spherical shells and multiplying the signals of all the shells. For distances below 5 nm, a linear superposition of the signals of the shells is sufficient. The dipolar time evolution data can be separated into this linear contribution and a nonlinear background. The linear contribution can then be converted directly to a radial distribution function. For a series of shape-persistent and flexible biradicals with end-to-end distances between 2 and 5 nm, shell factorization and direct conversion of the data are in good agreement with each other and with force-field computations of the end-to-end distances. The neglect of orientation selection does not cause significant distortions of the determined distance distributions. (C) 2002 Elsevier Science (USA).