MétaCan
Menu
Back to cohort
Record W4416529942 · doi:10.1016/j.asr.2025.11.079

An aluminum production chain for the Moon: Experimental demonstration of aluminum metal extraction for in-situ resource utilization

2025· article· en· W4416529942 on OpenAlexafffund
Xavier Walls, Alex Ellery, Katherine Marczenko, Priti Wanjara

Bibliographic record

VenueAdvances in Space Research · 2025
Typearticle
Languageen
FieldEngineering
TopicBauxite Residue and Utilization
Canadian institutionsCarleton UniversityNatural Sciences and Engineering Research Council of Canada
FundersNational Research Council Canada
KeywordsAluminiumAlloyProduction (economics)Work (physics)MetalExtraction (chemistry)Process (computing)Resource (disambiguation)

Abstract

fetched live from OpenAlex

The possibility of a sustained human presence on the Moon is getting closer every day. A prolonged human presence will require the utilization of lunar resources to minimize the transportation of materials from Earth. Aluminum, an abundant, widespread element found in both lunar highlands and mare, offers significant potential for structural and manufacturing applications. However, conventional terrestrial methods such as the Bayer and Hall-Héroult processes are not well suited for lunar implementation due to their environmental and material constraints. This study presents and experimentally validates an alternative lunar-compatible pathway for aluminum production. A lunar highlands simulant (LHS-1), was beneficiated and subsequently leached with hydrochloric acid to refine it to alumina. The refined alumina was electrochemically reduced to aluminum afterwards. The reaction products were analyzed and imaged using a series of analytical techniques. The aluminum produced was ⩾ 99 % pure falling within alloy 1100 standards. The aluminum produced was successfully shaped into a wire spool that can be used for electron beam additive manufacturing on the Moon. The present work shows that the critical steps for a lunar aluminum production chain are feasible. A review of the key operational and material requirements for implementing each stage of the process under lunar conditions is also presented.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.054
GPT teacher head0.405
Teacher spread0.350 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueAdvances in Space ResearchSame topicBauxite Residue and UtilizationFrench-language works237,207