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Record W1963975005 · doi:10.1103/physrevb.90.115428

Investigation of transient heat current from first principles using complex absorbing potential

2014· article· en· W1963975005 on OpenAlexaff
Zhizhou Yu, Lei Zhang, Yanxia Xing, Jian Wang

Bibliographic record

VenuePhysical Review B · 2014
Typearticle
Languageen
FieldEngineering
TopicMolecular Junctions and Nanostructures
Canadian institutionsMcGill University
FundersUniversity of Hong KongNational Science Foundation
KeywordsHeat currentNon-equilibrium thermodynamicsTransient (computer programming)PhysicsMolecular electronicsVoltageMaterials scienceThermalQuantum mechanicsMoleculeThermodynamicsComputer science

Abstract

fetched live from OpenAlex

We report on a first-principles investigation of transient heat current through molecular devices under steplike pulse of external and gate voltages. Using the nonequilibrium Green's function (NEGF) approach, an exact solution of transient heat current is obtained that goes beyond the wide-band limit. Combining with density-functional theory (DFT), we propose a time-dependent NEGF-DFT formalism to study the transient heat current under a steplike pulse for molecular devices from first principles. Anticipating the huge computational cost in the transient regime, we develop an algorithm to speed up the calculation using the complex absorbing potential (CAP). By adding the CAP to replace the Hamiltonian of leads, the effective self-energy of the Green's function becomes independent of energy, allowing analytic calculation of the triple integrations in the exact solution of transient heat current using the theorem of residue. With this linear scaling algorithm, the computational complexity is greatly reduced, and a first-principles calculation of transient heat current of molecular devices becomes possible. As an example, we apply our NEGF-DFT-CAP formalism for a molecular device, the Di-thiol benzene molecule connected by two semi-infinite aluminum leads, and we calculate the transient heat current under an upward gate voltage pulse. The enhancement of heat current is observed.

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: Empirical
Teacher disagreement score0.791
Threshold uncertainty score0.351

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 head0.039
GPT teacher head0.263
Teacher spread0.224 · 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

Citations16
Published2014
Admission routes1
Has abstractyes

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