EFFECT OF PRETREATMENT CONDITIONS ON STRUCTURAL CHARACTERISTICS OF WHEAT STRAW
Bibliographic record
Abstract
Structural characteristics of lignocellulosic biomass such as surface area, pore volume, crystallinity, hemicellulose, and lignin content significantly affect the yield of fermentable sugars for bioethanol production. In the present work, the effect of dilute acid pretreatment was studied on structural characteristics of wheat straw, using different combinations of process variables (temperature, time, and acid concentration). Pretreated wheat straw (PWS) exhibited higher available surface area and pore volume along with low hemicellulose and lignin content. Crystallinity index (CrI) of biomass at different pretreatment conditions showed an increased trend followed by sharp decrease at high temperature (190°C) conditions. Maximum increase in surface area (7.1 m2/g compared to 4.0 m2/g for untreated wheat straw) was obtained at pretreatment conditions of 180°C temperature, 0.5% (v/v) acid, and 7 min time. SEM imaging of biomass revealed that pore breaking, compression of pores, and partial pore blocking in the case of high temperature (190°C) pretreatment conditions may be the reason behind decreased surface area of biomass. FT-IR analysis showed almost complete hemicellulose removal and acid-soluble lignin removal after dilute acid pretreatment but insufficient removal of acid insoluble lignin. [Supplementary material is available for this article. Go to the publisher's online edition of Chemical Engineering Communications for the following free supplemental resource: figure showing XRD pattern of biomass with respect to different pretreatment conditions.]
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".