A Discussion of the Temperature Maximum for Sulfur Capture Efficiency in Fluidized Bed Combustion Systems
Bibliographic record
Abstract
For over 20 years, it has been known that there is a sulfur capture maximum around 850°C for limestone sorbents in FBC systems, albeit that this maximum appears to depend both on the characteristics of the FBC unit and the sorbent itself. Numerous explanations have been given for the temperature maximum at higher temperatures, including reducing reaction of CaSO4 with CO, sintering of sorbent particles which results in lower porosity and surface area. Other explanations include equilibrium between SO2 and SO3 with higher temperatures reducing the availability of SO3 for reaction with CaO, blocked sorbent pores at higher temperatures, and depletion of oxygen in the dense phase of the bed at higher temperatures. The most plausible explanation is that the temperature maximum results from a competition between sulfation and reduction of the sorbent, with reduction becoming more important at higher temperatures. Clear elucidation of the factors that affect the temperature dependence and an explicit relationship for the temperature maximum ought to permit improvements in sulfur capture efficiency to be achieved. Currently, no explicit relation appears to exist, and hence we provide an analysis for the temperature maximum based on the competition between sulfation and reduction, and derive an expression for the sulfur capture efficiency as a function of gas composition, sorbent residence time and apparent reaction rate coefficients, all of which are dependent on temperature. The expression relates operation conditions and sorbent activity to the temperature maximum, and may serve as a stepping-stone for future studies in this area.
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.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".