Geometric Effects on Non-DLVO Forces: Relevance for Nanosystems
Bibliographic record
Abstract
In this paper, the surface element integration (SEI) method was used derive analytical force/potential versus distance profiles for two non-DLVO forces: Lewis acid-base and solvation forces. These forces are highly relevant in a variety of systems, from bacterial adhesion, nanoparticle suspension stability to atomic force microscopy (AFM) profiles. The SEI-derived expressions were compared with the more commonly utilized Derjaguin approximations in order to assess the effect of curvature on the resulting interaction for the test cases of sphere-flat plate and equally sized spheres. For acid-base interactions, the deviation was found to be significant for particles up to 40 nm in diameter for the conventionally used decay length (λ = 1 nm) for water. The resulting expressions show that accounting in curvature for acid-base interactions is important even for simple smooth geometric shapes, recovering the Derjaguin expression at smaller values of λ/R. These results allow for correction of the acid-base force/potential versus distance from the Derjaguin-derived expressions using simple functions of λ/R. Conversely, for the solvation force the deviation was far less significant due to the oscillatory nature of the potential damping out effects and the smaller order of magnitude range of the solvation decay length, indicating that for solvation forces the Derjaguin approximation is suitable for most conceivable cases.
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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".