Ultra‐Strong and Tough Bio‐Based Polyester Elastomer with Excellent Photothermal Shape Memory Effect and Degradation Performance
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
Abstract The exploitation of bio‐based materials derived from renewable resources represents a pivotal strategic approach in addressing environmental pollution and alleviating the scarcity of fossil resources. 2,5‐Furandicarboxylic acid (FDCA) is the most potential substitute for terephthalic acid. Lignin is the most abundant aromatic biomass resource. However, the preparation of high‐performance lignin/FDCA‐based bio‐polyesters remains a formidable challenge. Herein, a multifunctional lignin‐modified polyester elastomer (LFPEe) is designed using FDCA‐based polyester oligomer (PPeF) and lignin (AOH) as building blocks. The LFPEe exhibits superior mechanical properties with the optimum tensile strength, fracture strain, and elastic recovery ratio up to 58.9 MPa, 610% and 88.9%, respectively, attributing to the formation of dual cross‐linking network with nanophase separation structure. Furthermore, leveraging the inherent characteristics of lignin, the LFPEe demonstrates excellent light‐controlled shape memory and excellent UV shielding performance. This innovative work not only breaks the performance dependence of FDCA‐based polyester on high molecular weight but also highlights a novel paradigm for value‐added utilization of lignin in sustainable bio‐polyesters.
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 | 0.000 | 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 | 0.000 |
| 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 it