Physicotechnical, spectroscopic and thermogravimetric properties of powdered cellulose and microcrystalline cellulose derived from groundnut shells
Bibliographic record
Abstract
α-Cellulose and microcrystalline cellulose powders, derived from agricultural waste products, that have for the pharmaceutical industry, desirable physical (flow) properties were investigated. α–Cellulose (GCN) was extracted from groundnut shell (an agricultural waste product) using a non-dissolving method based on inorganic reagents. Modification of this α -cellulose was carried out by partially hydrolysing it with 2N hydrochloric acid under reflux to obtain microcrystalline cellulose (MCGN). The physical, spectroscopic and thermal properties of the derived α-cellulose and microcrystalline cellulose powders were compared with Avicel® PH 101, a commercial brand of microcrystalline cellulose (MCCA), using standard methods. X-ray diffraction and infrared spectroscopy analysis showed that the α-cellulose had lower crystallinity. This suggested that treatment with 2N hydrochloric acid led to an increase in the crystallinity index. Thermogravimetric analysis showed quite similar thermal behavior for all cellulose samples, although the α- cellulose had a somewhat lower stability. A comparison of the physical properties between the microcrystalline celluloses and the α-cellulose suggests that microcrystalline cellulose (MCGN and MCCA) might have better flow properties. In almost all cases, MCGN and MCCA had similar characteristics. Since groundnut shells are agricultural waste products, its utilization as a source of microcrystalline cellulose might be a good low-cost alternative to the more expensive commercial brand.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".