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Record W3095192706 · doi:10.1021/acs.cgd.0c01152

Kinetics of Crystallization and Orientational Ordering in Dipolar Particle Systems

2020· article· en· W3095192706 on OpenAlexaff
Xianqi Xu, Brian B. Laird, J.J. Hoyt, Mark Asta, Yang Yang

Bibliographic record

VenueCrystal Growth & Design · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Thermodynamics and Statistical Mechanics
Canadian institutionsMcMaster University
FundersBasic Energy SciencesNational Natural Science Foundation of ChinaMinistry of Education of the People's Republic of ChinaNational Science Foundation
KeywordsCrystallizationChemical physicsKineticsMaterials scienceCrystal growthMagnetizationNanotechnologyChemistryThermodynamicsCrystallographyMagnetic fieldPhysicsClassical mechanics

Abstract

fetched live from OpenAlex

The kinetic mechanisms underlying the bottom-up assembly of colloidal particles have been widely investigated in efforts to control crystallization pathways and to direct growth into targeted superstructures for applications, including photonic crystals. Current work builds on recent progress in the development of kinetic theories for crystal growth of bcc crystals in systems with short-range interparticle interactions, accounting for a greater diversity of crystal structures (including fcc and noncubic crystals) and the role of the longer-ranged interactions and orientational degrees of freedom arising in polar systems. We address the importance of orientational ordering processes in influencing crystal growth in such polar systems, thus advancing the theory beyond the treatment of the translational ordering processes considered in previous investigations. The work employs comprehensive molecular dynamics simulations that resolve key crystallization processes and are used in the development of a quantitative theoretical framework based on ideas from time-dependent Ginzburg–Landau theory. The significant effect of orientational ordering (polarization or magnetization) on the crystallization kinetics could be potentially leveraged to achieve solidification kinetics steering through external electric or magnetic fields. Our combined theory/simulation approach provides opportunities for future investigations of more complex crystallization kinetics.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.911
Threshold uncertainty score0.334

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 head0.019
GPT teacher head0.231
Teacher spread0.212 · 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 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

Citations13
Published2020
Admission routes1
Has abstractyes

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