An overview of the temperature dependence of the zeta potential of aqueous suspensions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Zeta potential is a crucial parameter in colloid and surface science which reflects the electrokinetic potential at the slipping plane of particles in suspensions. Despite the broad range of interests and applications of the temperature dependence of zeta potential, the relationship between temperature and zeta potential is not entirely understood. Understanding the temperature dependence of zeta potential is essential for applications in various fields, from colloidal stability in drug delivery to flotation recovery in mineral processing. Although the concept has been around for nearly two centuries, dedicated high-temperature zeta potential measurements are a relatively recent development. Challenges have been arising due to the limitations of traditional measurement techniques at elevated temperatures and the influence of temperature on other factors affecting zeta potential. As a result, the zeta potential values of many materials at various conditions relevant to natural or desired settings are not known accurately. This review comprehensively explores the influence of temperature on zeta potential, detailing how thermal variations affect the electrokinetic properties of suspensions. The present knowledge of the temperature dependence of zeta potential and its relationship with the physicochemical characteristics of suspensions, such as pH, type and concentration of the background electrolyte, dissolved ions, surface composition, and dissolution of the particles as key points in understanding and predicting the behavior of colloidal particles in processes are discussed.
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.
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 it