Synthesis, characterization and evaluation of sodium doped lithium zirconate as a high temperature CO{sub 2} absorbent
Bibliographic record
Abstract
The world economy relies on the use of fossil fuels to produce affordable energy. However, the burning of fossil fuels results in the release of significant amounts of carbon dioxide (CO{sub 2}) into the atmosphere. Newer technologies are needed in order to remove CO{sub 2} at the high temperatures where energy is produced. One example of these new technologies involves a novel modification of the steam methane reforming process (SMR) for the production of hydrogen, where the reforming, water gas shift and solid CO{sub 2} capture reactions are combined in one single process step known as Sorption Enhanced Reforming (SER) which can lead to the production of high purity hydrogen. An essential part of this process is the CO{sub 2} solid acceptor, which must possess adequate absorption capacity and fast absorption/regeneration kinetics. Due to its high thermal stability, lithium zirconate (Li{sub 2}ZrO{sub 3}) has been proposed as a CO{sub 2} acceptor. However, CO{sub 2} absorption kinetics for this material is extremely slow. The objective of this study was to dope Li{sub 2}ZrO{sub 3} with sodium (Na) in order to increase its CO{sub 2} absorption capacity and kinetics. It was concluded that as a result of the Na doping process, an important improvement was found in the absorption kinetics and capacity with respect to pure Li{sub 2}ZrO{sub 3}. 31 refs., 2 tabs., 5 figs.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".