Fourier Transform Infrared and Solid State 13C Nuclear Magnetic Resonance Spectroscopic Characterization of Defatted Cottonseed Meal-Based Biochars
Bibliographic record
Abstract
Conversion to biochar may be a value-added approach to recycle defatted cottonseed meal, a major byproduct from the cotton industry. In this work, complete slow pyrolysis at seven peak temperatures ranging from 300 to 600°C in batch reactors was implemented to process cottonseed meal into biochar products. Elemental analysis, attenuated total reflection Fourier transform infrared (ATR FT-IR) spectroscopy and quantitative solid state 13C nuclear magnetic resonance (NMR) spectroscopy were applied to characterize raw meal and its derived biochar products. The biochar yield and organic C and total N recoveries decreased as the peak pyrolysis temperatures was elevated. However, most of the mineral elements including P in cottonseed meal were retained during pyrolysis and became enriched in biochar as a result of the decreased mass yield. The spectral data showed that pyrolysis removed the functional groups of biopolymers in cottonseed meal, producing highly aromatic structures in biochars. With increasing pyrolysis temperature, alkyl structures decreased progressively in the biochar products and became negligible at higher temperatures (550 and 600°C). Quantitative analysis of FT IR data revealed that the values of a simple 3-band (1800,1700, and 650 cm-1)-based R reading of the biochars were linearly related to the pyrolysis temperature, and showed strong correlations with decreasing aromaticity and increasing alkyl, aliphatic C-O/N and carbonyl signal intensities in the 13C NMR spectra. Therefore, the cheaper and faster FT-IR measurement could be used as a routine conversion indicator of pyrolysis of lignocellulosic biomass instead of the more expensive and time-consuming NMR spectroscopy.
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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 | 0.000 |
| 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".