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Record W3204881305 · doi:10.1021/acs.jcim.1c01181

Fine-Tuning the Polarizable CL&Pol Force Field for the Deep Eutectic Solvent Ethaline.

2021· preprint· en· W3204881305 on OpenAlexafffund
Rafael Maglia de Souza, Mikko Karttunen, Mauro C. C. Ribeiro

Bibliographic record

VenuePubMed · 2021
Typepreprint
Languageen
FieldChemical Engineering
TopicIonic liquids properties and applications
Canadian institutionsWestern University
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaMinistry of Education and Science of the Russian FederationCanada Research Chairs
KeywordsPolarizabilityDipoleForce field (fiction)Eutectic systemMolecular dynamicsIonic liquidAnisotropyChemical physicsDeep eutectic solventField (mathematics)ChemistryAb initioComputational chemistryMoleculeMaterials sciencePhysicsMathematicsQuantum mechanicsOrganic chemistryAlloy

Abstract

fetched live from OpenAlex

) in the partial components of the structure factors. In physical terms, this is equivalent to overestimated spatial nanoscale heterogeneity. To correct these problems, we adjusted the chloride-hydroxyl radial distribution functions against ab initio data and then extended the use of the Tang-Toennis damping function for the chlorides' induced dipoles. These adjustments correct the problems without losing the robustness of the CL&Pol force field. The results were also compared with the nonpolarizable version, the CL&P force field. We expect that the corrections will facilitate reliable use of the CL&Pol force field for other types of DESs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.035
GPT teacher head0.238
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes2
Has abstractyes

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