Small particles, big impacts: A review of the diverse applications of nanofluids
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
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.
- Candidate categories
- none
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: Not applicableConsensus signal: none
- Genre
- Candidate signal: ReviewConsensus signal: Review
- Teacher disagreement score
- 0.946
- Threshold uncertainty score
- 0.726
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.214 · how far apart the two teachers sit on this one work
- Validation status
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
Abstract
Nanofluids—a simple product of the emerging world of nanotechnology—are suspensions of nanoparticles (nominally 1–100 nm in size) in conventional base fluids such as water, oils, or glycols. Nanofluids have seen enormous growth in popularity since they were proposed by Choi in 1995. In the year 2011 alone, there were nearly 700 research articles where the term nanofluid was used in the title, showing rapid growth from 2006 (175) and 2001 (10). The first decade of nanofluid research was primarily focused on measuring and modeling fundamental thermophysical properties of nanofluids (thermal conductivity, density, viscosity, heat transfer coefficient). Recent research, however, explores the performance of nanofluids in a wide variety of other applications. Analyzing the available body of research to date, this article presents recent trends and future possibilities for nanofluids research and suggests which applications will see the most significant improvement from employing nanofluids.
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.
The record
- Venue
- Journal of Applied Physics
- Topic
- Nanofluid Flow and Heat Transfer
- Field
- Engineering
- Canadian institutions
- McGill University
- Funders
- University of New South WalesDivision of Chemical, Bioengineering, Environmental, and Transport SystemsNatural Sciences and Engineering Research Council of CanadaU.S. Department of DefenseNational Science Foundation
- Keywords
- NanofluidMaterials scienceThermal conductivityViscosityNanotechnologyHeat transferNanoparticleThermodynamicsComposite materialPhysics
- Has abstract in OpenAlex
- yes