Performance evaluation and cost analysis of MOF-303-based adsorption desalination and cooling systems using experimental dynamic data
Bibliographic record
Abstract
Climate change and population growth intensify the challenges of limited energy and water resources. Desalination, while providing fresh water from seawater, is energy-intensive and resource-demanding. Therefore, this study is the first to investigate the feasibility of MOF-303 as an adsorbent in a two-bed adsorption cooling desalination system (ACDS). Based on the literature, a series of dynamic experiments was conducted to evaluate the performance of MOF-303 across regeneration temperatures ranging from 40 °C to 80 °C, revealing its high kinetic responsiveness and superior thermal behavior. Moreover, Detailed analyses of heat capacity and effective diffusion coefficients across different cycle times and operating conditions provide new insights into the thermal and mass transfer dynamics of the ACDS system. A thermodynamic model of the system (ACDS) using MOF-303 measured properties was developed, validated, and used to investigate its performance under various operating conditions. The results of the parametric study and the radar charts indicated that the optimal conditions are a 700-s cycle time and regeneration temperature of 85 °C, yielding a coefficient of performance (COP) of 0.584, more 13 % than silica gel, specific daily water productivity (SDWP) of 13.02 m 3 /ton.day, and a water production cost of 0.0909 $/kg. Further, the techno-economic feasibility of the ACDS using MOF-303 has the potential to enhance the water productivity and cooling performance while reducing energy and economic costs. MOF-303 shows potential as a key material in the development of eco-friendly cooling and desalination systems.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".