High-energy radiation from T Tauri stars (TTS) influences the amount and longevity of gas in disks, thereby playing a crucial role in the creation of gas giant planets. Here we probe the high-energy ionizing radiation from TTS using high-resolution mid-infrared (MIR) Spitzer IRS Neon forbidden line detections in a sample of disks from IC 348, NGC 2068, and Chamaeleon. We report three new detections of [Ne III] from CS Cha, SZ Cha, and T 54, doubling the known number of [Ne III] detections from TTS. Using [Ne III]-to-[Ne II] ratios in conjunction with X-ray emission measurements, we probe high-energy radiation from TTS. The majority of previously inferred [Ne III]/[Ne II] ratios based on [Ne III] line upper limits are significantly less than 1, pointing to the dominance of either X-ray radiation or soft Extreme-Ultraviolet (EUV) radiation in producing these lines. Here we report the first observational evidence for hard EUV dominated Ne forbidden line production in a T Tauri disk: [Ne III]/[Ne II]∼1 in SZ Cha. Our results provide a unique insight into the EUV emission from TTS, by suggesting that EUV radiation may dominate the creation of Ne forbidden lines, albeit in a minority of cases.
The three-dimensional characterization of internal features, via metrics such as orientation, porosity, and connectivity, is important to a wide variety of scientific questions. Many spatial and morphological metrics only can be measured accurately through direct in situ three-dimensional observations of large (i.e., big enough to be statistically representative) volumes. For samples that lack material contrast between phases, serial grinding and imaging—which relies solely on color and textural characteristics to differentiate features—is a viable option for extracting such information. Here, we present the Grinding, Imaging, Reconstruction Instrument (GIRI), which automatically serially grinds and photographs centimeter-scale samples at micron resolution. Although the technique is destructive, GIRI produces an archival digital image stack. This digital image stack is run through a supervised machine-learning-based image processing technique that quickly and accurately segments data into predefined classes. These classified data then can be loaded into three-dimensional visualization software for measurement. We share three case studies to illustrate how GIRI can address questions with a significant morphological component for which two-dimensional or small-volume three-dimensional measurements are inadequate. The analyzed metrics include: the morphologies of objects and pores in a granular material, the bulk mineralogy of polyminerallic solids, and measurements of the internal angles and symmetry of crystals.
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