One story as part of the Global Conversation on Sustainability: dye adsorption studies using a novel bio-derived calcite material
Bibliographic record
Abstract
Abstract Many of the United Nations’ Sustainable Development Goals (SDGs) can be addressed through chemistry. Researchers at Memorial University of Newfoundland, Canada, have been sharing their stories on September 25 for the past two years through the Global Conversation on Sustainability. This article describes the details of one of these stories. As the global population increases, food production including aquaculture is increasing to provide for this. At the same time, this means more waste is produced. Waste from aquaculture is often overlooked as a source of valuable chemicals. By-products from farming blue mussels ( Mytilus edulis ) is dominated by shells rich in calcite. A ‘soft’ calcite material prepared from waste mussels, via a combination of heat and acetic acid treatment, was investigated for its adsorptive properties and its possible use in wastewater remediation. The adsorption of two cationic dyes, methylene blue and safranin-O, on this material were evaluated through isothermal and kinetic modelling. The adsorption systems for both methylene blue and safranin-O can best be described using Langmuir isotherms and the respective adsorption capacities were 1.81 and 1.51 mg/g. The adsorption process was dominated by pseudo-second order rate kinetics. Comparisons are made with other mollusc-derived materials reported to date.
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 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 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".