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Record W1999107057 · doi:10.1021/es071724e

Laboratory Tests on Mercury Emission Monitoring with Resonating Gold-coated Silicon Cantilevers

2008· article· en· W1999107057 on OpenAlexaff
Jarosław Drelich, C.L. White, Zhenghe Xu

Bibliographic record

VenueEnvironmental Science & Technology · 2008
Typearticle
Languageen
FieldMaterials Science
TopicDiamond and Carbon-based Materials Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMercury (programming language)CantileverEnvironmental chemistrySiliconEnvironmental scienceNanotechnologyMaterials scienceOptoelectronicsChemistryComposite materialComputer science

Abstract

fetched live from OpenAlex

To measure extremely low concentrations of mercury vapor in gases as encountered in flue gases of coal-fired power plants, accurate and reliable online and/or portable mercury detection systems are needed. As discussed in this communication, resonating silicon-based cantilevers coated with thin films of gold change their resonant frequency when exposed to mercury vapors and could serve as the basis for such sensing devices. Two different types of commercial AFM cantilevers, which differed by physical dimensions and surface finish, were coated with a 10 nm film of gold and were tested in streams of argon containing mercury. The argon flow rates ranged from 5.7 to 57.4 ml/min, carrying mercury vapors at concentrations between 37 and 700 microg/m3. The results show that smaller cantilevers (approximately 140 microm x 40 microm x 4 microm) with a resonant frequency of 270-275 kHz were sensitive to less than 10 picograms of mercury, whereas larger cantilevers (approximately 245 microm x 50 microm x 7 microm) with a resonant frequency of 155-165 kHz have a sensitivity about 10 times lower. The results indicate that the kinetics of mercury capture by the gold coating follows a simple power law-correlation with the mass change (delta m) being proportional to t(n), where t is the capture time and n depends strongly on the concentration of mercury in the gas. It is also demonstrated that the mercury can be stripped off the gold coating by heating to 350 degrees C, which would allowthe cantilevers to be regenerated and reused.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.010
GPT teacher head0.239
Teacher spread0.229 · 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 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

Citations25
Published2008
Admission routes1
Has abstractyes

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