Open AccessPrenormative verification and validation of a protocol for measuring magnetite–maghemite ratios in magnetic nanoparticles
Author(s) -
Lara K. Bogart,
Jeppe Fock,
Geraldo Magela da Costa,
Kerstin Witte,
JeanMarc Grenèche,
J. Żukrowski,
Marcin Sikora,
Drew E. Latta,
Michelle M. Scherer,
Mikkel Fougt Hansen,
Cathrine Frandsen,
Quentin A. Pankhurst
Publication year - 2021
Publication title -
metrologia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.637
H-Index - 79
eISSN - 1681-7575
pISSN - 0026-1394
DOI - 10.1088/1681-7575/ac36b6
Subject(s) - maghemite , repeatability , magnetite , statistic , statistics , computer science , analytical chemistry (journal) , nanoparticle , materials science , mathematics , chemistry , chromatography , nanotechnology , metallurgy
An important step in establishing any new metrological method is a prenormative interlaboratory study, designed to verify and validate the method against its stated aims. Here, the 57 Fe Mössbauer spectrometric ‘centre of gravity’ (COG) method was tested as a means of quantifying the magnetite/maghemite (Fe 3 O 4 /γ-Fe 2 O 3 ) composition ratio in biphasic magnetic nanoparticles. The study involved seven laboratories across Europe and North and South America, and six samples—a verification set of three microcrystalline mixtures of known composition, and a validation set of three nanoparticle samples of unknown composition. The spectra were analysed by each participant using in-house fitting packages, and ex post facto by a single operator using an independent package. Repeatability analysis was performed using Mandel’s h statistic and modified Youden plots. It is shown that almost all (83/84) of the Mandel h statistic values fall within the 0.5% significance level, with the one exception being borderline. Youden-based pairwise analysis indicates the dominance of random uncertainties; and in almost all cases the data analysis phase is only a minor contributor to the overall measurement uncertainty. It is concluded that the COG method is a robust and promising candidate for its intended purpose.