Technique for Concentration of Carbonaceous Material from Aerogel Collectors Using HF-Vapor Etching
Bibliographic record
Abstract
COLLECTORS USING HF-VAPOR ETCHING. A. J. Westphal, A. L. Butterworth, C. J. Snead, G. Dominguez, P. K. Weber, I. D. Hutcheon, G. R. Huss, C. V. Nguyen, G. A. Graham, F. Ryerson, and J. P. Bradley. Space Sciences Laboratory, University of California at Berkeley, Berkeley, CA 94720, USA (westphal@ssl.berkeley.edu), Lawrence Livermore National Laboratory, 7000 East Avenue, L-395, Livermore, CA 94550, USA, 3 Department of Geological Sciences and Center for Meteorite Studies, Arizona State University, P. O. Box 871404, Tempe, AZ 85287-1404, ELORET, NASA Ames Research Center, MS 229-1, Moffett Field, CA 94035-1000, Institute for Geophysics and Planetary Physics, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA 94550, USA. Introduction: Extraction of fine residues of hypervelocity impacts in aerogel collectors is a major challenge. The problem is likely to be especially severe for the Stardust mission. If cometary dust particles are similar to IDPs, they are unlikely to survive as structurally intact particles, but will instead break up into their fine-grained (micron to sub-micron) constituents. Large, refractory grains (e.g., olivines) that can be extracted relatively easily are likely to survive completely intact. But recovery of fine-grained material, distributed along the impact tracks[1,2], is required for comprehensive analysis of cometary material. The recovery and analysis of organics and carbonaceous material is a particular priority for Stardust. Etching in HF liquid has been used for many years to remove silicates and to isolate organics and carbon from chondritic materials[3-6]. Etching of aerogel collectors to remove silicate aerogel has been suggested previously[7], but the large background of contaminants and inclusions in the aerogel collectors has discouraged this approach. Here we describe our first steps in the development of a technique for isolating certain types of non-silicate chondritic grains, and, potentially, partially etched larger silicate grains from aerogel collectors. This technique may be a useful addition to the analytical toolbox available to the Stardust community. Specifically, we describe two key innovations. First, the use of HF vapor instead of liquid for removing the aerogel matrix takes advantage of the enormous contrast (at least two orders of magnitude) in surface area, and thus etch-rate, between aerogel and ordinary silicates, and the rate can be readily controlled and monitored. Second, etching extracted aerogel keystones minimizes the volume of aerogel matrix and therefore the background of terrestrial organics and particulates. Technique: For this development effort, we used particle impacts from the “chondritic swarm” population from the ODCE aerogel collector, which was deployed externally on the Russian space station Mir for 18 months in 1996-1997[8]. First, we extracted complete particle impact tracks in aerogel keystones with total volume ~0.01 mm. We describe this technique in detail elsewhere [1]. We placed the aerogel keystone on a graphite disk, then placed the disk in a small (~25 cm) closed polystyrene box with a optically clear and flat CR-39 plastic window so that the keystone could be optically imaged.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".