A review of rubidium: Resources, technologies, and applications
Bibliographic record
Abstract
Rubidium (Rb), as a rare alkali metal, exhibits unique physicochemical properties, such as ease of ionization, ultra-precise stability of atomic transition frequencies, and excellent photoelectric response, which have led to its significant application in various cutting-edge fields, including photocatalysis, photovoltaic materials, magnetohydrodynamic (MHD) power generation, rubidium atomic clocks, specialty glass, pharmaceuticals, pyrotechnics, and quantum computer. With advancements in technology and industrial upgrades, the global demand for rubidium is rapidly increasing, driving the development of rubidium resources, innovation in extraction technologies, and the expansion of applications. This paper provides a systematic review of rubidium's fundamental properties, mineral types, resource occurrence, global distribution, technological progress, and market landscape, offering a full industrial-chain overview over time. It particularly evaluates the characteristics of solid and liquid rubidium resources and the challenges encountered in their development and utilization. In terms of metallurgical technologies, the paper summarizes the current mainstream extraction and separation processes, including acid leaching, roasting, hydrothermal treatment, ion exchange, solvent extraction, and electrochemical separation. These methods are analyzed comprehensively from the perspectives of technical feasibility, energy consumption, environmental impact, and economic efficiency, while also reflecting on interdisciplinary integration, technological convergence, cross-field learning, and future development directions. Additionally, this paper outlines the current status and development trends of rubidium applications in various high-tech fields, exploring the interrelationships among resources, technology, and applications and their role in supporting the sustainable development of the rubidium industry. Through interdisciplinary analysis, this study aims to provide scientific guidance and practical reference for the strategic planning and technological evolution of the global rubidium industry. • Reviewed rubidium's physicochemical properties and related application fields. • Global distribution and types of rubidium resources, along with market status. • Comprehensive assessment of technological advancements in rubidium metallurgy. • Comparison of advantages, disadvantages, and applicability of different technologies. • Outlook on the future development direction of rubidium resource extraction.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".