Micronaut: Sphingomonas desiccabilis for Space Mining and Sustainable Space Development
Bibliographic record
Abstract
The roles of biotechnologies in support of human exploration of celestial bodies have evolved from mere theoretical concepts to tangible realities, driven by the development of cutting-edge biotechnologies. Among these advancements, biomining has emerged as a promising alternative for on-site mining and resource extraction (ISRU) (Linne et al., 2017). Widely employed on Earth, this technology, known as biohydrometallurgy, utilizes single microorganisms or microbial consortia to extract resources from ores or mine waste, with minimal or limited human intervention (Habibi et al., 2020). While numerous microbial species on Earth are typically involved in such processes, specifically classified as iron-oxidizers, studies have demonstrated similar abilities in certain species of fungi and organisms not conventionally associated with extraction processes (Chaerun et al., 2017). Notably, Sphingomonas desiccabilis, a heterotrophic Gram-negative bacterium, has shown remarkable potential as a candidate for supporting space exploration (Santomartino et al., 2022). It has actively extracted industrially significant metals from basaltic rocks under both terrestrial conditions and microgravity environments, such as those found on the International Space Station (ISS) (Loudon et al., 2018). Here we present the results obtained from a ground-based biomining experiment using S. desiccabilis to extract precious and critical elements, such as Rare Earth Elements (REEs) and Platinum Group Elements (PGEs), from seven different rocky substrates. Five of these were collected from Canadian mining sites known to contain PGEs, Icelandic basalt previously used on the ISS, and an eucrite, a type of meteorite whose origin is commonly attributed to Vesta, one of the biggest asteroids in the asteroid belt. Our results demonstrate the active extraction of metals of industrial interest from all the used substrates. Specifically we were able to extract Cr, Pd, Pt, U, V, Sc, Ge and other elements that can be used in-situ in space to support human settlement in a sustainable future on other celestial bodies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".