Modeling the Distribution of Iron-oxides in Basalt by combining FIB-SEM
and MicroCT Measurements
Abstract
Micromagnetic tomography (MMT) aims to go beyond paleomagnetic
measurements on bulk samples by obtaining magnetic moments for
individual iron-oxide grains present in a sample. To obtain accurate MMT
results all magnetic sources and all their magnetic signals should be
known. Small particles (<<1 µm) are often not
detected by MicroCT analyses, but do have a magnetic signal, and
therefore hamper obtaining reliable MMT results. Currently it is unknown
how many of these small ‘ghost grains’ are present in basaltic samples.
Here we aim to obtain a realistic grain-size distribution for
iron-oxides in a typical Hawaiian basalt. We characterize the entire
grain-size range of interest to paleomagnetism, from the
superparamagnetic threshold of ∼40 nm to multidomain grains with sizes
up to 10 μm. This requires a combination of FIB-SEM slice-and-view and
MicroCT techniques: FIB-SEM characterizes the grains between 20 nm and 1
μm and MicroCT detects iron-oxides >750 nm. The FIB-SEM and
MicroCT data are combined through normalizing the grain-size
distribution using the surface area of non-magnetic minerals that are
characterised in both datasets. Then, a lognormal-like grain-size
distribution is acquired for the entire grain-size range. Our dataset
enables future studies to populate (MMT) models with a realistic
distribution of even the smallest iron-oxide grains, which ultimately
may shed light on the confounding influence of such ghost grains on MMT
results.