How much can novel solid sorbents reduce the cost of post-combustion <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e555" altimg="si168.svg"> <mml:msub> <mml:mrow> <mml:mi mathvariant="normal">CO</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>2</mml:mn> </mml:mrow> </mml:msub> </mml:math> capture? A techno-economic investigation on the cost limits of pressure–vacuum swing adsorption
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper focuses on identifying the cost limits of two single-stage pressure–vacuum swing adsorption (PVSA) cycles for post-combustion CO2 capture if the “ideal” zero-cost adsorbent can be discovered. Through an integrated techno-economic optimisation, we simultaneously optimise the adsorbent properties (adsorption isotherms and particle morphology) and process design variables to determine the lowest possible cost of CO2 avoided (excluding the CO2 conditioning, transport and storage) for different industrial flue gas CO2 compositions and flow rates. The CO2 avoided cost for PVSA ranges from 87.1 to 10.4 € per tonne of CO2 avoided, corresponding to CO2 feed compositions of 3.5 mol% to 30 mol %, respectively. The corresponding costs for a monoethanolamine based absorption process, using heat from a natural gas plant, are 76.8 to 54.8 € per tonne of CO2 avoided, respectively showing that PVSA can be attractive for flue gas streams with high CO2 compositions. The “ideal” adsorbents needed to attain the lowest possible CO2 avoided costs have a range of CO2 affinities with close to zero N2 adsorption, demonstrating promise for adsorbent discovery and development. The need for simultaneously optimising the particle morphology and the process conditions are emphasised.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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 it