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Record W4205517464 · doi:10.1021/acs.analchem.1c03624

Raman Spectroscopy as a Simple yet Effective Analytical Tool for Determining Fermi Energy and Temperature Dependent Fermi Shift in Silicon

2022· article· en· W4205517464 on OpenAlexaff
Chanchal Rani, Manushree Tanwar, Tanushree Ghosh, Suchita Kandpal, Devesh K. Pathak, Anjali Chaudhary, Priyanka Yogi, Shailendra K. Saxena, Rajesh Kumar

Bibliographic record

VenueAnalytical Chemistry · 2022
Typearticle
Languageen
FieldMaterials Science
TopicSilicon Nanostructures and Photoluminescence
Canadian institutionsUniversity of Alberta
FundersScience and Engineering Research BoardCouncil of Scientific and Industrial Research, IndiaIndian Institute of Technology IndoreUniversity Grants CommissionDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsRaman spectroscopyChemistryFermi energyFermi levelFermi Gamma-ray Space TelescopeFermi–Dirac statisticsCondensed matter physicsSiliconDopingAtomic physicsPhysicsOpticsQuantum mechanicsElectron

Abstract

fetched live from OpenAlex

The Fermi energy is known to be dependent on doping and temperature, but finding its value and corresponding thermal Fermi shift experimentally is not only difficult but is virtually impossible if one attempts their simultaneous determination. We report that temperature dependent Raman spectromicroscopy solves the purpose easily and proves to be a powerful technique to determine the position and temperature associated Fermi shift in an extrinsic semiconductor as demonstrated for silicon in the present study. The typical asymmetrically broadened Raman spectral line-shape from sufficiently doped n- and p-type silicon contains the information about the Fermi level position through its known association with the Fano coupling strength. Thus, Raman line-shape parameters, the terms quantify the Fano-coupling, have been used as experimental observables to reveal the value of the Fermi energy and consequent thermal Fermi shift. A simple formula has been developed based on existing established theoretical frameworks that can be used to calculate the position of the Fermi level. The proposed Raman spectroscopy-based formulation applies well for n- and p-type silicon. The calculated Fermi level position and its temperature dependent variation are consistent with the existing reports.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score1.000

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)0.0010.000

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 head0.006
GPT teacher head0.261
Teacher spread0.255 · 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.

Study designBench or experimental
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

Citations28
Published2022
Admission routes1
Has abstractyes

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