Liquid Phase Oxidation of Hydrocarbons to High‐Value Chemicals in Microfluidic Reactors – Prospects and Challenges
Bibliographic record
Abstract
Liquid phase oxidation (LPO) of hydrocarbon is an industrially important process to produce petrochemicals and pharmaceuticals. It follows a free radical path having initiation, propagation and termination. The initiation step is slow while the propagation and termination steps are fast. The main challenge of such process is to control product selectivity at an appreciable conversion level. With the advancement of microfluidic reactor technology, it is possible to control the free radical steps. The present contribution critically reviewed the reaction engineering aspects of LPO of hydrocarbon, the influence of microfluidic reactor design and operation on reaction mechanism, conversion and product selectivity. It also outlines the challenges associated with microfluidic reactor operation, and prospects to apply the understanding from microfluidic reactors in few sectors. The understanding from the free radical oxidation process can also be applied to any other free radical processes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".