11 Conversion of glycerolglycerol and bio-renewable carbon to acrylic acidacrylic acid
Bibliographic record
Abstract
Acrylic acid (AA) is an extraordinary compound that serves as a monomer for adhesives and sealants, plastic additives, surface coatings and paint, absorbents in diapers and personal care products, and water treatment. Annual worldwide production surpassed 6–7 million tons as of 2022–2023, valued at $12–13 billion, and is growing at a rate close to 4–6% per year (between 2023 and 2030). Propylene’s propylene partial oxidation to AA is the predominant process, as there is no real competitive alternative. In this gas-phase process, oxygen partially oxidizes propylene to acrolein above 300 °C, which in turn is oxidized in tandem to AA, where propylene is derived from petroleum. Society and governments motivate industry and academia to develop innovative technologies to reduce the environmental footprint related to AA synthesis. A biobased feedstock is a compelling alternative to propylene to approach a carbon-neutral AA process. Glycerol, a coproduct from biodiesel and oleochemistry derived from vegetable oil and animal fat, which dehydrates to acrolein at 300 °C, is one such bio-feedstock. However, crude glycerol crude glycerol (also called glycerin glycerine ) contains salts (such as NaCl), fatty acids (FA) and their salts, methanol, as well as various non-glyceric organic matter that add distillation costs. Consequently, many companies choose to combust it for its fuel value, while a few convert it to epichlorohydrin rather than refining it, and larger companies react it to methanol. BioMCN produces methanol from glycerol, and Solvay and others produce epichlorohydrin. Furthermore, excluding AA, there was insufficient market demand for glycerol, which made this product of low value for industry; therefore, its prices dropped from $0.43 kg −1 in 2003 to $0.18 kg −1 and $0.02 kg −1 for refined and crude glycerol, respectively, in 2010 [ 1 ]. By the mid-2010s, glycerol prices began to stabilize but remained low due to continued biodiesel biodiesel production. In the late 2010s and early 2020s, technological advances in refining glycerol into higher-value products, such as epichlorohydrin and propylene glycol, helped stabilize the market for refined glycerol. During the COVID-19 pandemic, disruptions in supply chains and the economic slowdown affected the glycerol market. Industrial activity slowed, reducing demand for both crude and refined glycerol. However, the demand for pharmaceutical-grade glycerol (used in hand sanitizer) increased, temporarily raising prices in those specific sectors. By 2021–2023, glycerol prices began to see modest increases due to growing 2 demand for sustainable chemicals and bio-based products and increased consumption in pharmaceutical, food, and personal care sectors. Therefore, the price of crude glycerol and refined glycerol has remained around $0.1–$0.2 kg −1 and 0.7–1.5 kg −1 , respectively. Here, we discuss commercial and potential processes to produce AA.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.009 |
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".