3D geometallurgical characterization of coal mine waste rock piles for their reprocessing purpose
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Jerada coal mining generates extensive coal mine waste rock (CMWR) piles rich in valuable minerals, posing environmental challenges and economic opportunities. This study examines reprocessing feasibility through 3D geometallurgical characterization. Sampling used down the hole hammer drilling technique (DTH) and drone surveys for topographical precision. Over 620 samples from (T01, T02, T08) underwent comprehensive analyses including particle size distribution, x-ray fluorescence (XRF), total sulfur/carbon analysis (S/C), and inductively coupled plasma mass spectrometry (ICP-MS) for physical–chemical characterization. Mineralogical aspects were explored via optical microscopy (OM), X-ray diffraction (XRD), scanning electron microscopy (SEM), electron probe microanalysis (EPMA), and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). Quantitative mineral evaluation by scanning electron microscope (QEMSCAN) provided mineral insights. Chemical data was used in a 3D block model to quantify residual coal. Results for the three examined CMWR piles (T01, T02, and T08) showed varying D 80 from 160 to 300 µm, notable carbon content averaged 12.5 wt% (T01), 16 wt% (T02), and 8.5 wt% (T08). Sulfur presence exceeded 1 wt% in T08, and potential environmental concerns due to iron sulfides. Anthracite liberation was below 30 wt%. 3D modeling estimated a total volume of 7 Mm 3 , mainly from T08, equaling 11.2 Mt. With its high carbon content and substantial tonnages, re-exploitation or alternative applications could minimize these CMWR piles environmental impact.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it