Fast-Field-Cycling (FFC) NMR relaxometry probes the molecular dynamics of paramagnetic systems through Nuclear Magnetic Relaxation Dispersion (NMRD) profiles, from which structural, dynamic and electronic parameters can be extracted by model fitting. No existing software combines all paramagnetic relaxation models, from Solomon-Bloembergen-Morgan (SBM) to the (modified) Florence models for systems with static Zero-Field-Splitting. fiRelax (https://firelax.cerm.unifi.it) is a free, web-based fitting application that fills this gap. Its intuitive interface requires no programming or theoretical expertise, and it runs on the open-source One-Fit-Engine (OFE), which other programs have also adopted. The platform handles inner-sphere, outer-sphere and fast internal mobility contributions. It also supports simultaneous multi-dataset fitting through shared parameters or Arrhenius-based temperature dependencies.

fiRelax – Novel fitting platform for relaxivity data of paramagnetic systems / Adam Krzysztof Kubrak , Pedro Sebastião, Giacomo Parigi. - ELETTRONICO. - (2026), pp. 0-0. (Euromar 2026 ).

fiRelax – Novel fitting platform for relaxivity data of paramagnetic systems

Adam Krzysztof Kubrak;Giacomo Parigi
2026

Abstract

Fast-Field-Cycling (FFC) NMR relaxometry probes the molecular dynamics of paramagnetic systems through Nuclear Magnetic Relaxation Dispersion (NMRD) profiles, from which structural, dynamic and electronic parameters can be extracted by model fitting. No existing software combines all paramagnetic relaxation models, from Solomon-Bloembergen-Morgan (SBM) to the (modified) Florence models for systems with static Zero-Field-Splitting. fiRelax (https://firelax.cerm.unifi.it) is a free, web-based fitting application that fills this gap. Its intuitive interface requires no programming or theoretical expertise, and it runs on the open-source One-Fit-Engine (OFE), which other programs have also adopted. The platform handles inner-sphere, outer-sphere and fast internal mobility contributions. It also supports simultaneous multi-dataset fitting through shared parameters or Arrhenius-based temperature dependencies.
2026
Abstract book - Euromar 2026
Euromar 2026
Adam Krzysztof Kubrak ;Pedro Sebastião;Giacomo Parigi
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1488692
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