Experimentation of a novel sequential moving-bed DAC System
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
Solid sorbent Direct Air Capture (DAC) technologies face significant challenges due to the high energy demands associated with adsorption and regeneration phases. Overcoming these limitations is essential to improve the scalability and sustainability of carbon removal solutions. This study investigates the performance of a novel sequential moving-bed (SMB) DAC architecture that utilizes solid sorbent cells circulating through three distinct zones: adsorption, regeneration, and heat exchange, in order to increase system duty cycle and allow for heat recovery between sorption and desorption. The primary objective is to evaluate the energy and capture performance of this configuration in comparison to a conventional fixed-bed system, using the same sorbent under the same operating conditions. Compared to a conventional fixed-bed system, the SMB configuration increased CO 2 uptake by nearly 30% while reducing total energy intensity by more than 35%, to just over 1000 Wh/kgCO 2 . These gains are attributed to reduced sorbent working mass, lower pressure drops, and efficient heat recovery. The findings highlight the potential of the SMB approach to enhance the performance and energy efficiency of DAC systems, offering a pathway toward more sustainable and scalable carbon removal solutions. • CO 2 uptake increased by more than 30% with the sequential moving-bed process. • Energy intensity decreased by over 35% with the sequential moving-bed process. • Energy intensity reduced to near 1000 Wh/kgCO 2 with the sequential moving-bed.
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.
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 | 0.000 | 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 | 0.000 |
| 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 it