Exploring high pressure slurry ablation as a mineral processing technology
Bibliographic record
Abstract
In order to achieve economic operation and enable efficient separation of valuable components, most mineral processing facilities require comminution technologies. These machines liberate valuable minerals from the associated gangue by reducing the size of individual particles, or, in some operations, by removing loosely adhered particles from the hard mineral matrix. Due to the stochastic nature of particle-particle and particle-wall collisions, as well as the intrinsic inefficiencies associated with the low fraction of energy spent on particle breakage, these technologies require enormous amounts of energy to function and, therefore, research into the development and implementation of more efficient technologies is continuously ongoing. This study assesses the performance of high pressure slurry ablation, a new size reduction, particle liberation, and slurry conditioning technology, against current industry standards. Various materials were tested with the equipment, and product samples were collected and analyzed for size distribution and size-based assaying. Where applicable, separation technologies such as gravity separation and froth flotation were used to provide further insights into the amenability of HPSA products to beneficiation. The results were then compared to the expected outcomes of typical grinding and scrubbing-attrition technologies. The results concluded that the technology can achieve size reduction for all considered materials, can selectively liberate soft and loosely attached materials into a fraction of the original mass, and can provided elevated gravity separation recoveries in precious metals applications. However, due to the mechanical components of the pilot-scale unit used in this study limiting the percentage of solids that the unit could handle, the observed unit efficiencies are found to be lower than those of conventional size reduction units. By upgrading the pumps associated with the testing rig these limitations could be eliminated, thus, identifying areas for future work.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".