Time-resolved SANS visualization of hierarchical structures during thermochemical reactions
Bibliographic record
Abstract
Knowledge of structural changes to biomass during pretreatment will enable an informed approach to improving biomass conversion efficiencies. We developed a pressure reaction cell to monitor morphological changes in biomass using small-angle neutron scattering (SANS) during thermochemical pretreatment in real-time. This approach takes advantage of the non-destructive and high penetration properties of neutrons to perform in-situ studies. Recently, we have extended the capabilities of the Bio-SANS instrument at the High Flux Isotope Reactor at Oak Ridge National Laboratory by installation of an additional detector array. The upgrade makes it possible to capture neutrons scattered at higher angles simultaneously to the neutrons captured at smaller scattering angles by the main detector. As a result, data collection times are dramatically reduced and it is possible to obtain structural information at much shorter length scales than was previously possible. Here, we report on real-time SANS studies of native poplar and variant that is deficient in lignin synthesis, during dilute acid and alkali pretreatments. We observe significant differences in lignin aggregation patterns in the native and mutant poplar comparing the two pretreatment regimes. On the other hand, the scattering signature assigned to the cellulose microfibrils remains relatively unchanged in both pretreatments. A quantitative analysis of the structural changes in the native and mutant plants will be presented. Using this approach, it is possible to obtain molecular level insights into structural rearrangements of biomass polymers during pretreatment to better understand the consequences of genetic mutations on the overall digestability of biomass. http://www.ornl.
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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".