Shifting To Renewable Furan Candidates: Synthesis and Study of New Optoelectronic Materials
Bibliographic record
Abstract
With climate concerns consistently growing, the chemical industry must shift away from petrochemicals and turn to sustainable feedstocks derived from lignocellulosic biomass. There is urgency to develop new synthetic methodologies that effectively convert biomass-derived starting materials into useful consumer products. The production of multi-arylated furans and 2,5-furan-based oligomers, has gained popularity as organic candidates for light-emitting diodes or field-effect transistors, owing to their favourable optoelectronic properties found in highly conjugated furan-based materials. Hydroxymethylfurfural and furfural are biomass-derived platform chemicals that have received attention as raw materials due to their chemical functionality, renewability, and capability to produce various furan-containing building blocks. In this work, we aim to develop a synthetic methodology starting from biomass-derived chemicals to design potential optoelectronics. Hydroxymethylfurfural was studied to develop multi-arylated furans; however, a rigid diol monomer was synthesized instead. Working with methyl-5-bromofuran-2-carboxylate led to three different multi-arylated furans via regioselective halogenations followed by Pd-catalyzed cross-coupling reactions. 5-Bromofurfural, a close derivative of biomass-derived furfural, was an ideal candidate to produce ten 2,5-furan-based oligomers and one 2,5-furan-based push-pull chromophore. To rapidly extend the π-conjugation of each material, a double Pd-catalyzed decarboxylative cross-coupling (DCC) reaction was utilized. This strategy fuses two nucleophilic arylated furan acids with a dihalogenated aryl linker to produce highly planar furan-based oligomers. Regarding overall yields of the double DCC, electron-neutral and electron-donating furan acids exhibited higher yields (32 – 74%) than electron-withdrawing acid derivatives (18 – 21%). All furan-based compounds were then characterized by NMR and their absorbance, photoluminescence and quantum yields were studied in dilute solution.
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) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".