Biomass‐water interactions correlate to recalcitrance and are intensified by pretreatment: An investigation of water constraint and retention in pretreated spruce using low field NMR and water retention value techniques
Why this work is in the frame
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Bibliographic record
Abstract
The underlying mechanisms of the recalcitrance of biomass to enzymatic deconstruction are still not fully understood, and this hampers the development of biomass based fuels and chemicals. With water being necessary for most biological processes, it is suggested that interactions between water and biomass may be key to understanding and controlling biomass recalcitrance. This study investigates the correlation between biomass recalcitrance and the constraint and retention of water by the biomass, using SO 2 pretreated spruce, a common feedstock for lignocellulosic biofuel production, as a substrate to evaluate this relationship. The water retention value (WRV) of the pretreated materials was measured, and water constraint was assessed using time domain Low Field Nuclear Magnetic Resonance (LFNMR) relaxometry. WRV increased with pretreatment severity, correlating to reduced recalcitrance, as measured by hydrolysis of cellulose using commercial enzyme preparations. Water constraint increased with pretreatment severity, suggesting that a higher level of biomass‐water interaction is indicative of reduced recalcitrance in pretreated materials. Both WRV and water constraint increased significantly with reductions in particle size when pretreated materials were further milled, suggesting that particle size plays an important role in biomass water interactions. It is suggested that WRV may be a simple and effective method for measuring and comparing biomass recalcitrance. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 33:146–153, 2017
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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 | 0.000 | 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) | 0.000 | 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