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Record W2921644063 · doi:10.1002/celc.201900249

Highly Sensitive Method to Isolate Photocurrent Signals from Large Background Redox Currents on Protein‐Modified Electrodes

2019· article· en· W2921644063 on OpenAlexaff
Daniel Jun, J. Thomas Beatty, Dan Bizzotto

Bibliographic record

VenueChemElectroChem · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhotosynthetic Processes and Mechanisms
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRhodobacter sphaeroidesRedoxPhotocurrentPhotosynthetic reaction centreElectrodeChemistryElectrochemistryElectron transferPhotoelectrochemistryAnalytical Chemistry (journal)ExcitationMaterials sciencePhotochemistryOptoelectronicsPhotosynthesisInorganic chemistryPhysics

Abstract

fetched live from OpenAlex

Abstract The high quantum efficiency in converting light energy into a charge‐separated state is a major advantage in using photosynthetic proteins in biophotovoltaic applications. Photocurrents are typically measured at open circuit potential (OCP), where the electrochemical redox or faradaic currents are minimized. However, at potentials far from the OCP, the photocurrents produced by the proteins may be impossible to measure against the large background current, owing to electrochemical redox reactions of charge‐transfer mediators and/or sacrificial electron donors. Demonstrated here is a highly sensitive method using a sinusoidal‐modulated intensity of an LED excitation light source to isolate the protein‐based photocurrent component from the total current irrespective of electrode surface coverage. Using a genetically modified photochemical reaction center from Rhodobacter sphaeroides as a proof‐of‐concept, photocurrents up to 10 4 –10 5 orders of magnitude smaller than the background electrochemical redox current (due to redox reactions directly on the electrode surface) were measured at applied voltages >0.4 V from the OCP. The phase relationship between the optical excitation and photocurrent response was also measured and shown to be analytically useful.

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)
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 score0.051
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)0.0000.000

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 head0.011
GPT teacher head0.281
Teacher spread0.270 · 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

Citations5
Published2019
Admission routes1
Has abstractyes

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