Levantamento de etnobotânica aplicada à veterinária na região Alentejo
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
Excess protons in water exhibit unique transport properties because they can rapidly hop along H-bonded water wires. Considerable progress has been made in unraveling this Grotthuss diffusion mechanism using quantum mechanical-based computational techniques. Unfortunately, high computational cost tends to restrict those techniques to small systems and short times. Molecular dynamics (MD) simulations can be applied to much larger systems and longer time windows. However, standard MD methods do not permit the dissociation/formation of covalent bonds, such that Grotthuss diffusion cannot be captured. Here, we bridge this gap by combining atomistic MD simulations (using Gromacs and TIP4P/2005 water) with proton hopping. Excess protons are modeled as hydronium ions that undergo H<sub>3</sub>O<sup>+</sup> + H<sub>2</sub>O → H<sub>2</sub>O + H<sub>3</sub>O<sup>+</sup> transitions. In accordance with ab initio MD data, these Grotthuss hopping events are executed in "bursts" with quasi-instantaneous hopping across one or more waters. The bursts are separated by regular MD periods during which H<sub>3</sub>O<sup>+</sup> ions undergo Brownian diffusion. The resulting proton diffusion coefficient agrees with the literature value. We apply this Grotthuss MD technique to highly charged water droplets that are in a size regime encountered during electrospray ionization (5 nm radius, ∼17,000 H<sub>2</sub>O). The droplets undergo rapid solvent evaporation and occasional H<sub>3</sub>O<sup>+</sup> ejection, keeping them at ca. 81% of the Rayleigh limit. The simulated behavior is consistent with phase Doppler anemometry data. The Grotthuss MD technique developed here should be useful for modeling the behavior of various proton-containing systems that are too large for high-level computational approaches. In particular, we envision future applications related to electrospray processes, where earlier simulations used metal cations while in reality excess protons dominate.
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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 | 0.001 | 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