Biobased foam composites of tannic acid-furfuryl alcohol- furfural or vanillin reinforced with wood fibers
Bibliographic record
Abstract
The preparation of conventional phenolic foams (PF) relies on non-renewable petroleum resources. Overuse leads to environmental pollution and resource depletion. In this study poplar, wood fiber (WF) reinforced PF were prepared based on tannic acid (TA), furfural (FU), furfuryl alcohol (FA) and vanillin (VA). So, two series of samples were produced: TA – FA – FU (TFU series) and TA – FA – VA (TVA series) biobased foams. While their properties were improved by adding WF. Fourier transform infrared spectroscopy (FTIR) revealed covalent cross-linking reactions between the components and hydrogen bonding between WF and the matrix. Viscosity measurements showed that higher values, the higher apparent densities and compressive strengths of the materials, while porosity and pulverization ratios were lower. Scanning electron microscopy (SEM) showed a homogeneous cell structure and small open cells, while two-dimensional (2D) images from computerized tomography (CT) showed small cell anisotropy and good binding between WF and the matrix. The TFU series foams exhibited excellent mechanical properties, with compression strengths up to 2.4 MPa and a minimum pulverization ratio of 1.3 %. In addition, thermogravimetric analysis (TGA), thermal conductivity , vertical combustion test and cone calorimeter test were conducted to evaluate the samples' thermal stability, thermal conductivity , and flammability . The TGA results showed that the material has good thermal stability and high residual carbon (37.1 % – 41.5 %). The cone calorimetry results confirmed a low heat release rate with a lowest peak heat release rate (pHRR) of 26.3 kW/m². At the same time, the vertical combustion tests showed that the materials were self-extinguishing and had excellent flame retardancy. For the TVA series, excellent thermal insulation was observed with a minimum thermal conductivity of 0.032 W/m·K. The addition of WF was found to reduce the foam's pulverization ratio, increase the specific compression strength, lower the heat release rate and increase the amount of residual carbon. All these results confirm that these new sustainable foams and composite foams have a high potential to replace conventional PF for construction, transportation, packaging, and insulation.
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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".