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Record W2613734451 · doi:10.1021/acs.jctc.6b00998

A New Split Charge Equilibration Model and REPEAT Electrostatic Potential Fitted Charges for Periodic Frameworks with a Net Charge

2017· article· en· W2613734451 on OpenAlexafffund
Mykhaylo Krykunov, Christopher Demone, Jason Wai-Ho Lo, Tom K. Woo

Bibliographic record

VenueJournal of Chemical Theory and Computation · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Ottawa
KeywordsCharge (physics)Net (polyhedron)Chemical physicsFixed chargePhysicsStatistical physicsElectrostaticsComputer scienceMathematicsQuantum mechanics

Abstract

fetched live from OpenAlex

Periodic frameworks that possess a net charge, such as zeolites, are an important class of materials in wide use. For guest–host interactions to be simulated in these materials, partial atomic charges are often used. In this work, we investigate two methods for the generation of partial atomic charges in periodic systems having a net framework charge. We first examine the validity of generating REPEAT electrostatic potential fitted charges derived from periodic electronic structure calculations, where a constant background charge is added to neutralize the net charge on the framework. The constant background charge obviates the need to add neutralizing counterions, which may induce artifacts such as polarization in the infinite periodic system. The second method we explore is the split charge equilibration (SQE) method for the rapid generation of partial atomic charges. The original formulation of the SQE method cannot be applied to systems with a net charge. In this work, we reformulate the SQE method by transforming the split charges into an atomic charge basis that allows for non-neutral systems to be treated. The new SQE model, which we call SQE AB (for atomic basis), was validated with a series of tests using both charged and neutral metal organic frameworks and zeolites. It was shown that SQE AB gives equivalent results to those of the original SQE model for neutral systems. We then demonstrated that the SQE AB method is able to “capture” the chemical structure of a charged framework better than that of the charge equilibration model by comparing to REPEAT electrostatic potential fitted charges.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.728
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.264
Teacher spread0.256 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations15
Published2017
Admission routes2
Has abstractyes

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