A Review of the Thermophysical Properties and Recent Development Trends on Liquid Desiccants for HVAC Applications
Bibliographic record
Abstract
The design of a liquid desiccant air conditioning (LDAC) system and its dehumidification and regeneration performance are significantly determined by the thermophysical properties of the liquid desiccant (LD) solution. The selection of a suitable LD depends largely on its vapor pressure, although other properties (e.g., viscosity, density, specific heat capacity, capital/operational cost, etc.) are equally important and should be carefully evaluated. Pure LDs, such as glycols (e.g., triethylene glycol (TEG) and polyethylene glycol (PEG)), halide salts (e.g., LiBr, LiCl, CaCl 2, and MgCl 2 ), and weak organic acid salts (e.g., HCO 2 K/Na, CH 3 CO 2 K/Na) have variable dehumidification and regeneration performances, as determined by the differences in thermophysical properties. Halide salt-based liquid desiccants are currently the most popular because they possess good thermodynamic properties and low volatility. However, such materials may be limited by low absorption efficiency, crystallization issues, and high cost. On the contrary, mixed desiccant solutions (e.g., LiCl-CaCl 2, LiBr-CaCl 2, LiCl-PEG, etc.) are characterized by lower vapor pressures, better dehumidification efficiency, and lower material cost and energy demands. The improved thermophysical properties of mixed desiccant solutions may relate to “elevation of boiling point” phenomenon imparted by the presence of impurities in the matrix. Ionic liquids (ILs) offer a potential alternative to halide salts and can address the drawbacks associated with conventional LD solutions, despite limited research in HVAC applications. Of particular interest are phase change material (PCM)-based LDs which represent a new direction in LDAC technology. PCM-LDs are characterized by (1) improved thermal properties due to “elevation of boiling point” by the PCM particles, and (2) lower regeneration requirements due to temperature control ability of the PCMs. This study compares the thermophysical properties (e.g., vapor pressure, density, viscosity, and specific heat capacity) and cost of common LD solutions and reviews recent development trends on alternative liquid desiccant solutions. Hybrid desiccant systems have stimulated significant research interest because of their potential to improve the dehumidification characteristics while addressing capital and operational costs.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".