Rare high-3He/4He signatures in ocean island basalts (OIB) erupted at volcanic hotspots derive from deep-seated domains preserved in Earth’s interior. Only high-3He/4He OIB exhibit anomalous182W—an isotopic signature inherited during the earliest history of Earth—supporting an ancient origin of high3He/4He. However, it is not understood why some OIB host anomalous182W while others do not. We provide geochemical data for the highest-3He/4He lavas from Iceland (up to 42.9 times atmospheric) with anomalous182W and examine how Sr-Nd-Hf-Pb isotopic variations—useful for tracing subducted, recycled crust—relate to high3He/4He and anomalous182W. These data, together with data on global OIB, show that the highest-3He/4He and the largest-magnitude182W anomalies are found only in geochemically depleted mantle domains—with high143Nd/144Nd and low206Pb/204Pb—lacking strong signatures of recycled materials. In contrast, OIB with the strongest signatures associated with recycled materials have low3He/4He and lack anomalous182W. These observations provide important clues regarding the survival of the ancient He and W signatures in Earth’s mantle. We show that high-3He/4He mantle domains with anomalous182W have low W and4He concentrations compared to recycled materials and are therefore highly susceptible to being overprinted with low3He/4He and normal (not anomalous)182W characteristic of subducted crust. Thus, high3He/4He and anomalous182W are preserved exclusively in mantle domains least modified by recycled crust. This model places the long-term preservation of ancient high3He/4He and anomalous182W in the geodynamic context of crustal subduction and recycling and informs on survival of other early-formed heterogeneities in Earth’s interior.
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Computational 3D surface microscopy from terabytes of data with a self-supervised reconstruction algorithm
We present a computational 3D profilometric microscope employing an array of 54 cameras and 3-axis scanning to produce multi-TB datasets per sample. Using stereo and sharpness cues, our self-supervised reconstruction algorithm generates 6-gigapixel reconstructions with micron-scale resolution across >110 cm2.
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- Award ID(s):
- 2238845
- PAR ID:
- 10482404
- Publisher / Repository:
- Optica Publishing Group
- Date Published:
- ISBN:
- 978-1-957171-28-9
- Page Range / eLocation ID:
- JM1B.2
- Format(s):
- Medium: X
- Location:
- Boston, Massachusetts
- Sponsoring Org:
- National Science Foundation
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