MétaCan
Menu
Back to cohort
Record W4387702532 · doi:10.26434/chemrxiv-2023-f3rzv

Competitive CO2/H2O Adsorption on CALF-20

2023· preprint· en· W4387702532 on OpenAlexafffund
Tai Nguyen, Bhubesh Murugappan Balasubramaniam, Nicholas Fylstra, Racheal P. S. Huynh, George K. H. Shimizu, Arvind Rajendran

Bibliographic record

VenueChemRxiv · 2023
Typepreprint
Languageen
FieldChemistry
TopicMetal-Organic Frameworks: Synthesis and Applications
Canadian institutionsUniversity of CalgaryUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates
KeywordsAdsorptionRelative humidityThermogravimetric analysisDesorptionLangmuirLangmuir adsorption modelThermogravimetryFlue gasChemistryGravimetric analysisMaterials scienceAnalytical Chemistry (journal)ThermodynamicsChromatographyOrganic chemistryInorganic chemistry

Abstract

fetched live from OpenAlex

The equilibrium and breakthrough studies of the H2O adsorption and the competition of CO2/H2O on a physisorbent MOF CALF-20, commercialized for CO2 capture from cement plants, are reported. Volumetric measurements and thermogravimetry were used to measure the water isotherm at various temperatures and relative humidity (RH) values. A Cubic-Langmuir model was used to describe the water isotherms at different temperatures. Both adsorption and desorption dynamic column breakthrough experiments were performed at different RH values to examine different transitions in the isotherm. To quantify the competitive adsorption of CO2 and H2O, both thermogravimetric analysis and dynamic column breakthrough techniques were required. A wide range of relative humidity (RH) values was considered, i.e., 10% to 90% RH. CALF-20 showed high CO2 loadings for RH was smaller than 47%; showing its exceptional capacity to be deployed for CO2 capture from industrial flue gas. Beyond 70% RH, water was strongly adsorbed, resulting in a significant loss of CO2 capacity. In the presence of CO2, CALF-20 showed an unique phenomena where water adsorption was suppressed making it more favourable for practical applications. The modified Langmuir isotherm model was used to describe the competitive CO2 loading as a function of water loadings and temperatures. A one-dimensional column model simulates the water dynamic column breakthrough and competitive CO2/H2O breakthroughs. Both concentration profiles and temperature histories agreed with the experimental results.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.036
GPT teacher head0.270
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueChemRxivSame topicMetal-Organic Frameworks: Synthesis and ApplicationsFrench-language works237,207