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Record W2325027196 · doi:10.1103/physrevb.90.035121

<i>Ab initio</i>model of optical properties of two-temperature warm dense matter

2014· article· en· W2325027196 on OpenAlexafffund
B. Holst, V. Recoules, S. Mazevet, Marc Torrent, A. Ng, Zhijiang Chen, Sean E. Kirkwood, V. Sametoglu, M. Reid, Ying Y. Tsui

Bibliographic record

VenuePhysical Review B · 2014
Typearticle
Languageen
FieldEngineering
TopicLaser Material Processing Techniques
Canadian institutionsUniversity of OttawaUniversity of Northern British ColumbiaUniversity of AlbertaUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaAgence Nationale de la Recherche
KeywordsWarm dense matterFemtosecondAb initioRelaxation (psychology)Ultrashort pulseIonLaserMaterials scienceElectronAb initio quantum chemistry methodsMolecular physicsCondensed matter physicsThermodynamicsPhysicsAtomic physicsOpticsQuantum mechanicsMolecule

Abstract

fetched live from OpenAlex

We present a model to describe thermophysical and optical properties of two-temperature systems consisted of heated electrons and cold ions in a solid lattice that occur during ultrafast heating experiments. Our model is based on ab initio simulations within the framework of density functional theory. The optical properties are obtained by evaluating the Kubo-Greenwood formula. By applying the material parameters of our ab initio model to a two-temperature model we are able to describe the temperature relaxation process of femtosecond-laser-heated gold and its optical properties within the same theoretical framework. Recent time-resolved measurements of optical properties of ultrafast heated gold revealed the dynamics of the interaction between femtosecond laser pulses and solid state matter. Different scenarios obtained from simulations of our study are compared with experimental data [Chen, Holst, Kirkwood, Sametoglu, Reid, Tsui, Recoules, and Ng, Phys. Rev. Lett. 110, 135001 (2013)].

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.018
GPT teacher head0.254
Teacher spread0.236 · 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

Citations73
Published2014
Admission routes2
Has abstractyes

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