An empirical model for deriving information on ion dynamics from μSR data via the conventional Kubo-Toyabe function analysis
Abstract
We present an empirical model that analytically relates the parameters of the extended Kubo-Toyabe (KT) function GzEA(t;Δ,νi,Q), which describes muon spin relaxation (μSR) induced by jump diffusion of ions using the Edwards-Anderson parameter Q, to those of the conventional KT function GzKT(t;ΔKT,νKT) that serves as an approximation of GzEA(t). The proposed formulae successfully reproduce the anomalous temperature dependences of the linewidth ΔKT(T) and the fluctuation rate νKT(T) which are artifacts observed upon analyzing μSR data on ion diffusion using GzKT(t). Applying this model to ΔKT and νKT published in the literature of battery materials yields activation energy Ei and pre-exponential factor νi0 in the Arrhenius equation for ion diffusion, νi(T)=νi0 e−Ei/kT, that are in excellent agreement with those deduced using other techniques, transforming peculiar artifacts into a powerful diagnostic tool.
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BibTeX
@misc{kadono2026empirical,
title = {{An empirical model for deriving information on ion dynamics from $μ$SR data via the conventional Kubo-Toyabe function analysis}},
author = {Ryosuke Kadono},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.16006},
eprint = {2610.16006},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.16006},
note = {CC BY-SA 4.0},
}
RIS
TY - UNPB
TI - An empirical model for deriving information on ion dynamics from μSR data via the conventional Kubo-Toyabe function analysis
AU - Ryosuke Kadono
PY - 2026
DA - 2026/10/12
PB - arXiv
DO - 10.48550/arxiv.2610.16006
UR - https://arxiv.org/abs/2610.16006
AB - We present an empirical model that analytically relates the parameters of the extended Kubo-Toyabe (KT) function G_z^EA(t;Δ,ν_i,Q), which describes muon spin relaxation (μSR) induced by jump diffusion of ions using the Edwards-Anderson parameter Q, to those of the conventional KT function G_z^KT(t;Δ_KT,ν_KT) that serves as an approximation of G_z^EA(t). The proposed formulae successfully reproduce the anomalous temperature dependences of the linewidth Δ_KT(T) and the fluctuation rate ν_KT(T) which are artifacts observed upon analyzing μSR data on ion diffusion using G_z^KT(t). Applying this model to Δ_KT and ν_KT published in the literature of battery materials yields activation energy E_i and pre-exponential factor ν_i0 in the Arrhenius equation for ion diffusion, ν_i(T)=ν_i0 e^−E_i/kT, that are in excellent agreement with those deduced using other techniques, transforming peculiar artifacts into a powerful diagnostic tool.
ER -