Situation of Utilization and Geological Occurrences of Critical Minerals(Graphite, REE, Ni, Li, and V) Used for a High-tech Industry
Bibliographic record
Abstract
Recently, there has been a rapid response from mineral-demanding countries for securing critical minerals in a high tech industries.Graphite, while overwhelmingly dominated by China in production, is changing in global supply due to the exponential growth in EV battery sector, with active exploration in East Africa.Rare earth elements are essential raw materials widely used in advanced industries.Globally, there are ongoing developments in the production of REEs from three main deposit types: carbonatite, laterite, and ion-adsorption clay types.While China's production has decreased somewhat, it still maintains overwhelming dominance in this sector.Recent changes over the past few years include the rapid emergence of Myanmar and increased production in Vietnam.Nickel has been used in various chemical and metal industries for a long time, but recently, its significance in the market has been increasing, particularly in the battery sector.Worldwide, nickel deposits can be broadly classified into two types: laterite-type, which are derived from ultramafic rocks, and ultramafic hosted sulfide-type.It is predicted that the development of sulfide-type, primarily in Australia, will continue to grow, while the development of laterite-type is expected to be promoted in Indonesia.This is largely driven by the growing demand for nickel in response to the demand for lithium-ion batteries.The global lithium ores are produced in three main types: brine lake (78%), rock/mineral (19%), and clay types (3%).Rock/mineral type has a slightly higher grade compared to brine lake type, but they are less abundant.Chile, Argentina, and the United States primarily produce lithium from brine lake deposits, while Australia and China extract lithium from both brine lake and rock/mineral sources.Canada, on the other hand, exclusively produces lithium from rock/mineral type.Vanadium has traditionally been used in steel alloys, accounting for approximately 90% of its usage.However, there is a growing trend in the use for vanadium redox flow batteries, particularly for large-scale energy storage applications.The global sources of vanadium can be broadly categorized into two main types: vanadium contained in iron ore (81%) produced from mines and vanadium recovered from by-products (secondary sources, 18%).The primary source, accounting for 81%, is vanadiumiron ores, with 70% derived from vanadium slag in the steel making process and 30% from ore mined in primary sources.Intermediate vanadium oxides are manufactured from these sources.Vanadium deposits are classified into four types: vanadiferous titanomagnetite (VTM), sandstone-hosted, shale-hosted, and vanadate types.Currently, only the VTM-type ore is being produced.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".