Crosslinking of polyamides using dianhydrides, diacid chloride and dialdehyde: a promising approach for water treatment
Bibliographic record
Abstract
Abstract New crosslinked polyamides were successfully produced from the condensation of pre‐synthesized monomer, 5‐(2,2,2‐trifluoroacetamido)isophthaloylchloride (TFAIAC) and diamines at low temperature. These polyamides were used as promising metal‐chelating adsorbents due to the presence of O and N donor sites on the crosslinked polyamides. For this purpose, trifluoroacetic anhydride was used to protect the amino group of 5‐aminoisophthalic acid, thus generating 5‐(2,2,2‐trifluoroacetamido)isophthalic acid (TFAIA). TFAIA was converted into TFAIAC using oxalyl chloride, which was exploited as a suitable monomer for the synthesis of aromatic polyamides. Amino groups were then set free under basic conditions and the crosslinking was carried out through amino groups present on the polyamide chains with different dianhydrides, isophthaloyl chloride and 2,5‐thiophenedicarboxaldehyde. The synthesis of monomers and polymers was confirmed by Fourier transform infrared, 1 H and 13 C NMR spectroscopy and molar masses of the polyamides were measured by gel permeation chromatography. The crosslinked macromolecules were found to possess enough chain alignment as depicted by their XRD patterns. The thermal stability of the crosslinked polyamides was increased as their decomposition temperatures were improved from 420 to 619 °C. Metal ion uptake was scrutinized through atomic absorption spectroscopy with 83%–85% adsorption capacity at optimized parameters, i.e. a contact time of 3 h at pH 6. The mechanism of adsorption was further investigated through the Freundlich and Langmuir adsorption isotherms. The results reveal that uptake of metal ions followed monolayer adsorption of cations owing to coordination to electronegative centers on the macromolecules, confirming the Langmuir adsorption model. © 2019 Society of Chemical Industry
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 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) | 0.001 | 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 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".