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Meteorites contain a record of their thermal and magnetic history, written in the intergrowths of iron-rich and nickel-rich phases that formed during slow cooling. Of intense interest from a magnetic perspective is the “cloudy zone,” a nanoscale intergrowth containing tetrataenite—a naturally occurring hard ferromagnetic mineral that has potential applications as a sustainable alternative to rare-earth permanent magnets. Here we use a combination of high-resolution electron diffraction, electron tomography, atom probe tomography (APT), and micromagnetic simulations to reveal the 3D architecture of the cloudy zone with subnanometer spatial resolution and model the mechanism of remanence acquisition during slow cooling on the meteorite parent body. Isolated islands of tetrataenite are embedded in a matrix of an ordered superstructure. The islands are arranged in clusters of three crystallographic variants, which control how magnetic information is encoded into the nanostructure. The cloudy zone acquires paleomagnetic remanence via a sequence of magnetic domain state transformations (vortex to two domain to single domain), driven by Fe–Ni ordering at 320 °C. Rather than remanence being recorded at different times at different positions throughout the cloudy zone, each subregion of the cloudy zone records a coherent snapshot of the magnetic field that was present at 320 °C. Only the coarse and intermediate regions of the cloudy zone are found to be suitable for paleomagnetic applications. The fine regions, on the other hand, have properties similar to those of rare-earth permanent magnets, providing potential routes to synthetic tetrataenite-based magnetic materials.

International audienceA fully integrated WirelessHD compatible 60-GHz transceiver module in 65-nm CMOS process is presented, covering the four standard channels. The silicon die is flip-chipped on top of a low-cost HTCC module which also includes an external 65-nm CMOS PA and large beamwidth antennas targeting industrial manufacturability. The module achieves a 16QAM OFDM modulation wireless link with 3.8 Gbps over 1 m. The transceiver consumption is 454 mW in RX mode (including PLL) and 1090 mW in TX mode (including PLL and external PA)

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Scanning precession electron diffraction involves the acquisition of a two-dimensional precession electron diffraction pattern at every probe position in a two-dimensional scan. The data typically comprise many more diffraction patterns than the number of distinct microstructural volume elements (e.g. crystals) in the region sampled. A dimensionality reduction, ideally to one representative diffraction pattern per distinct element, may then be sought. Further, some diffraction patterns will contain contributions from multiple crystals sampled along the beam path, which may be unmixed by harnessing this oversampling. Here, we report on the application of unsupervised machine learning methods to achieve both dimensionality reduction and signal unmixing. Potential artefacts are discussed and precession electron diffraction is demonstrated to improve results by reducing the impact of bending and dynamical diffraction so that the data better approximate the case in which each crystal yields a given diffraction pattern.