Application of corrosion-resistant Corning advanced-flow reactors for multiphase Bunsen reaction - Part two: investigation on multiphase reaction
Bibliographic record
Abstract
Bunsen reaction ( 2 H 2 O + I 2 + S O 2 → H 2 S O 4 + 2 H I ) is a key step for hydrogen production from either the H2S splitting cycle or the sulfur-iodine (S-I) cycle of water splitting. As pointed out in part one, when engineering this reaction, many challenges such as side reactions and corrosion impede scaling up this process. Using iodine-toluene solution to provide flowing iodine below the melting point of iodine renders the Bunsen reaction to be conducted at ambient temperature such that these challenges can be either overcome or eased. However, using toluene as the iodine solvent makes the Bunsen reaction a multiphase reaction system which includes gas, aqueous, and organic phases. Glass-made Corning® advanced-flowTM reactors (AFRs) can be used for Bunsen reaction because they are good at resisting corrosion, improving mixing efficiency of multiphase fluids, and allowing seamless scaling up. Part one has studied the absorption behavior of SO2 gas in the liquids used for Bunsen reaction (water, toluene and water-toluene mixture). Part two (this work) mainly studies the Bunsen reaction using the Corning® microscale (LF) and milliscale (G1) AFRs. When I2 was dissolved in toluene, the Bunsen reaction was conducted by feeding SO2 gas, water, and I2/toluene solution into the AFRs. SO2 and I2 were used as the limiting reactants in turn, and the effects of operating conditions such as gas and liquid flow rates, water to toluene ratio, and temperature in the range (22-80 oC) on the absorption rates of SO2 and the I2 reaction rate were studied. The results confirm the seamless scaling-up capability of the Corning reactors when the flow rates were increased twenty times from AFR-LF to AFR-G1.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".