Novel Ketone-Based IPDA Phase Change Absorbents for Highly Efficient Wide-Concentration-Range CO2 Capture and Low-Energy Regeneration
Bibliographic record
Abstract
Carbon dioxide capture and storage (CCS) is an important technological path for realizing “carbon neutrality,” where carbon capture is one of the three key CCS technologies. At present, mature carbon capture technologies still have technical shortcomings and difficulties, such as low capture efficiency and high energy consumption, which limit their large-scale popularization and application. In this study, a solid–liquid phase change absorbent (PCA) system with isophorone diamine (IPDA) as the only carbon dioxide (CO 2 ) capture carrier and ketone-based organic molecules as the phase change medium was developed. The solid–liquid PCA system has a wide range of applicability, with highly efficient CO 2 capture (1.11 mol·mol −1 ) at concentrations ranging from typical values in air to those in coal-fired industrial emissions (400 to 150 000 ppm) and low-energy consumption regeneration, as revealed by a two-phase integrated engineering model. The CO 2 absorption product IPDA(NHCOO − ) 2 was characterized by materials science analysis, molecular dynamics (MD) calculations and quantum chemistry. The results indicate that in noncyclic ketone-based phase-change media, the hydrogen bonding in IPDA(NHCOO − ) 2 is modulated by noncovalent bond interaction (NCI) forces to form a small-scale hydrogen-bonding network. These properties ensure that the product can be easily regenerated by low-temperature thermal treatment (333 K, 60 °C), and characterization and calculations revealed a reaction mechanism different from that of the aqueous system. The technoeconomic evaluation (TEA) results show that this type of ketone-based PCA has an obvious low-cost advantage over traditional carbon capture technologies. This study provides a new perspective on the application and practical feasibility of PCAs for direct air capture of carbon dioxide.
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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 | 0.000 |
| 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) | 0.001 | 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".