Carboxymethylated lignin incorporated chitosan aerogel as thermal insulator
Bibliographic record
Abstract
Aerogels have been used in many applications, including thermal insulation. However, most of these aerogels were produced using petrochemical materials with adverse environmental footprints. Biodegradable materials, such as chitosan (CH) and lignin, can promote the green manufacturing of sustainable aerogels. In this work, aerogels were produced from carboxymethylated lignin (CM). The NMR and XPS confirmed the crosslinking of CM and CH, as indicated by an increase in the intensity of the O C–N bond in the lignin-chitosan composite network. This work assessed a hypothesis that carboxymethylated lignin derivatives would improve the critical characteristics of aerogels required for insulation purposes. As the charge density of CM increased, the crosslinking bond between CM and CH intensified, reducing porosity and compression strength while increasing thermal conductivity. In addition, the increment in the charge density of CM increased the elasticity and hardness of the induced aerogels. The least charged CM (CM1) fabricated aerogel with a surface area of 211.2 (m 2 /g), pore volume of 0.198 (cm 3 /g), and pore size of 1.9 (nm). This aerogel had the lowest thermal conductivity, 0.035 (W/mk), and the highest compression strength, 3.87 (MPa). Moreover, the addition of CM increased the biodegradability of the aerogels. The results of this work present a promising strategy for fabricating a sustainable and biodegradable aerogel using only green materials and employing water-based, environmentally friendly processes that eliminate the use of toxic organic solvents.
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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".