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Abstract. Polished geological samples are frequently used in geoscientific research to investigate the chemical and physical characteristics of rocks. A broad range of imaging techniques is available to analyze such samples, but when combining datasets from multiple imaging techniques, an accurate co-registration of the datasets is often challenging. In this study, we investigate this issue in the context of Micromagnetic Tomography (MMT; De Groot et al., 2018, 2021). MMT combines surface magnetometry data with computed tomography (CT) data to analyze the magnetic state of rock samples. By combining the spatial (position) and dimensional (size) information of the magnetic grains in the samples with their magnetic surface expression, the individual magnetic moments per grain can be determined. This information can be used for paleomagnetic and rock-magnetic studies. Calculating the magnetic moments of the grains strongly depends on the correct co-registration of the two datasets, which proves to be challenging. In this study, we used two test samples for the application of micro-sized marker structures, to further develop the methodology of MMT. The marker structures are applied by microlithography and Nb-sputter coating, which are standard techniques used in the semiconductor industry. We determined that the marker structure application is possible on typical MMT samples. Marker structures larger than ca. 10 µm are clearly visible under the Quantum Diamond Microscope (QDM) used for the surface magnetometry. Given a sufficient marker structure thickness, they can also be observed in the CT scans used for determining the positions and shapes of the magnetic carriers. The marker structures are useful for identifying the orientation and location of the samples during measurements and can be used for scaling and mapping of the two datasets during data processing. Nb-marker structures do not fluoresce under the QDM, which means that no magnetic interference occurs during measurements. The application procedure is time-consuming but is valuable when a sample is lacking natural marker features, it makes the data processing time in MMT significantly faster, and more precise. This method can be useful for MMT, for Quantum Diamond Microscopy in general, and for broader geological applications that require visible anchor points for sample placement or marker structures for the co-registration of multiple datasets.
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High‐Sensitivity Moment Magnetometry With the Quantum Diamond Microscope
Abstract Interest in magnetic fields on the ancient Earth and other planetary bodies has motivated the paleomagnetic analysis of complex rocks such as meteorites that carry heterogeneous magnetizations at <<1 mm scales. The net magnetic moment of natural remanent magnetization (NRM) in such small samples is often below the detection threshold of common cryogenic magnetometers. The quantum diamond microscope (QDM) is an emerging magnetic imaging technology with ~1 μm resolution and can, in principle, recover magnetizations as weak as 10−17 Am2. However, the typically 1–100 μm sample‐to‐sensor distance of QDM measurements can result in complex (nondipolar) magnetic field maps, from which the net magnetic moment cannot be determined using a simple algorithm. Here we generate synthetic magnetic field maps to quantify the errors introduced by sample nondipolarity and by map processing procedures such as upward continuation. We find that inversions based on least squares dipole fits of upward continued data can recover the net moment of complex samples with <5% to 10% error for maps with signal‐to‐noise ratio (SNR) in the range typical of current generation QDMs. We validate these error estimates experimentally using comparisons between QDM maps and between QDM and SQUID microscope data, concluding that, within the limitations described here, the QDM is a robust technique for recovering the net magnetic moment of weakly magnetized samples. More sophisticated net moment fitting algorithms in the future can be combined with upward continuation methods described here to improve accuracy.
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- PAR ID:
- 10374351
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Geochemistry, Geophysics, Geosystems
- Volume:
- 21
- Issue:
- 8
- ISSN:
- 1525-2027
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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