KINETIC STUDY OF CHEMICAL LOOPING COMBUSTION USING IRON AS AN OXYGEN CARRIER
Bibliographic record
Abstract
Over the past few decades, combustion of fossil fuels has released greenhouse gases such as CO2 and NOx into the atmosphere. It has been realized that a mean temperature increase of the Earth, also known as global warming, has resulted from the increase of CO2 concentration in the air. Hence, there is a growing tendency to establish novel methods of burning fossil fuels in order to mitigate CO2 concentration. Chemical Looping Combustion (CLC) is a method of burning fuel with inherent separation of CO2 while curbing the formation of NOx, typically by circulating an oxygen carrier between an air (oxidation) reactor and a fuel (reduction) reactor. An oxygen carrier, mainly a metal oxide, circulates between the reactors providing the oxygen for conversion of fuel to CO2 and H2O. Thus, having a pure CO2 stream, CO2 sequestration becomes economically feasible. Fe2O3, due to its availability and properties, could be an apposite oxygen carrier for CLC. Reaction kinetics of reduction of Hematite with methane, in the absence of gaseous oxidant, was studied. Temperature Program Reduction (TPR) experiments were carried out in a fixed bed tubular reactor. Reduction gas was composed of 15% methane and 85% argon. Thermogravimetric Analysis (TGA) was carried out on TPR products using air as the oxidant. Iron oxide samples were analyzed through X-ray diffraction (XRD) analysis and scanning electron microscopy. Two-stage reduction of iron oxide was observed: Fe2O3 reduced to Fe3O4 and then reduced to FeO. The activation energy of each stage was calculated from Kissinger’s method. For the first and second stage of reduction the activation energies were 10.58±0.86 and 25.77±0.83 kJ/mol, respectively. In addition, different kinetic models were assumed and compared to the actual data. A random nucleation mechanism can be assigned to the first stage and a two-dimensional diffusion mechanism can be assigned to the second stage of the reduction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".