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Record W7111290247 · doi:10.1021/acs.est.5c09948.s001

TheNext Lithium Boom? Assessment of U.S. DomesticProduction Pathways through Economic and Environmental Lenses

2025· article· W7111290247 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2025
Typearticle
Language
FieldEngineering
TopicExtraction and Separation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityOperating expensePayback periodInternal rate of returnCapital costProduction (economics)Capital expenditureLithium (medication)

Abstract

fetched live from OpenAlex

This study examines current and future lithium production from primary resources in the United States, with a focus on economic viability and environmental sustainability using factory-level data. Four production methods/resources were evaluated: conventional brine extraction from Silver Peak, direct lithium extraction from Clayton Valley, sedimentary rock in Thacker Pass, and hard-rock spodumene sourced from Canada and refined in Texas. The key economic performance indicators include capital and operational expenditures (CAPEX and OPEX), net present value (NPV), internal rate of return (IRR), and payback period (PBP) across 21 lithium carbonate price scenarios ($10,000 to $50,000/ton LCE) over 20 years. DLE shows the lowest CAPEX but the highest OPEX due to higher energy use. Estimated OPEX per ton LCE is $6350 for Thacker Pass, $4600 for Silver Peak, $7850 for DLE, and $6100 for Hard Rock. Environmental assessments show CO<sub>2</sub> emissions (tons per ton LCE) of 10 for Thacker Pass, 4.3 for Silver Peak, 17.4 for DLE, and 17.6 for Hard Rock. While DLE and hard rock methods have higher emissions, Silver Peak stands out as the most environmentally efficient due to its use of solar evaporation and low chemical usage.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.908
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0670.000

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 head0.026
GPT teacher head0.274
Teacher spread0.248 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations0
Published2025
Admission routes1
Has abstractyes

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