An Eco-Friendly Method to Get a Bio-Based Dicarboxylic Acid Monomer 2,5-Furandicarboxylic Acid and Its Application in the Synthesis of Poly(hexylene 2,5-furandicarboxylate) (PHF)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Recently, we have developed an eco-friendly method for the preparation of a renewable dicarboxylic acid 2,5-furandicarboxylic acid (FDCA) from biomass-based 5-hydroxymethylfrufural (HMF). In the present work, we optimized our reported method, which used phosphate buffer and Fe(OH)₃ as the stabilizer to improve the stability of potassium ferrate, then got a purified FDCA (up to 99%) in high yield (91.7 wt %) under mild conditions (25 °C, 15 min, air atmosphere). Subsequently, the obtained FDCA, along with 1,6-hexanediol (HDO), which was also made from HMF, were used as monomers for the synthesis of poly(hexylene 2,5-furandicarboxylate) (PHF) via direct esterification, and triphenyl phosphite was used as the antioxidant to alleviate the discoloration problem during the esterification. The intrinsic viscosity, mechanical properties, molecular structure, thermal properties, and degradability of the PHFs were measured or characterized by Koehler viscometer, universal tensile tester, Nuclear Magnetic Resonance (NMR), Fourier-transform Infrared (FTIR), X-ray diffraction (XRD), Differential Scanning Calorimeter (DSC), Derivative Thermogravimetry (DTG), Scanning Electron Microscope (SEM), and weight loss method. The experimental evidence clearly showed that the furan-aromatic polyesters prepared from biomass-based HMF are viable alternatives to the petrochemical benzene-aromatic polyesters, they can serve as low-melting heat bondable fiber, high gas-barrier packaging material, as well as specialty material for engineering applications.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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