Development of biobased building blocks, polymers and coatings
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
Coatings are omnipresent in daily life, indispensable in construction and applied everywhere around us to enhance the durability and aesthetics of numerous products ranging from cars to wood to electronics. One of the most conventional sets of building blocks used to build these polymer chains, justified by their high reactivity and broad versatility, are the petrochemical feedstock derived acrylates. Despite their promise, the high demand and the resulting large-scale production from fossil fuels contribute heavily to an unsustainable ecological footprint. As a result of the growing environmental awareness and the desire for a green future, sustainable production of acrylates and the development of acrylate alternatives derived from biorenewable resources have gained increased attention over the last decades. Although great progress has been made, the commercialization of a competing sustainable process has not yet been achieved due techno-economic challenges arising from the underdeveloped larger scale syntheses and expensive starting materials and reagents. In this thesis we implemented both strategies and present several new developments towards sustainable acrylate alternatives (alkoxybutenolides) and biobased acrylic acid, all starting from furfural and using oxygen and visible light for sustainable chemical transformations. In order to account for a larger scale synthesis, a photochemical reactor was developed for the continuous production of our sustainable building blocks. The resulting biobased coatings obtained from these alkoxybutenolides are hard, transparent and resistant to solvent and water, similar to commercial coatings. Above all, the coatings are functional and have tunable properties, based on the different building blocks we developed.
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 | 0.001 | 0.001 |
| 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 it