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Record W1425040100 · doi:10.1149/ma2015-02/43/1688

Solar-to-Hydrogen Production on Multi-Band Photoelectrodes: Surpassing the Current Matching Requirements of Conventional Tandem Devices

2015· article· en· W1425040100 on OpenAlexaff
Zetian Mi, Bandar AlOtaibi, Shizhao Fan

Bibliographic record

VenueECS Meeting Abstracts · 2015
Typearticle
Languageen
FieldMaterials Science
TopicGa2O3 and related materials
Canadian institutionsMcGill University
Fundersnot available
KeywordsOptoelectronicsMaterials scienceNanowireHeterojunctionWaferTandemPhotovoltaic systemSemiconductorBand gap

Abstract

fetched live from OpenAlex

In a photoelectrochemical (PEC) system, to harvest a wider wavelength range of sunlight, a relatively narrow bandgap photoelectrode is often used, which, however, requires an external bias to produce hydrogen, due to its insufficient photovoltage. One of the solutions to overcome the low photovoltage of single-photoelectrodes is to implement a buried junction below the photocatalyst (known as photovoltaic-PEC or PV-PEC). However, the design and performance of PV-PEC is severely limited by the stringent requirement of current matching between the buried PV and the top complementary light absorption photocatalyst. In this context, by exploiting the lateral carrier extraction scheme of 1-dimensional nanowire structures, we have developed an adaptive PV-PEC photocathode, consisting of monolithically integrated GaN/ p -InGaN nanowire arrays on a planar Si solar cell wafer, that can surpass the current matching requirements of conventional tandem electrode. An applied bias photon-to-current efficiency of 8.7% is measured. The Si/GaN/ p -InGaN PV-PEC device heterostructure consists of a planar n + -p Si solar cell wafer, ~ 150 nm n -GaN and ~ 600 nm p -InGaN nanowire segments along the axial direction. The top p -InGaN nanowire arrays are designed to absorb the ultraviolet and a large portion of the visible solar spectrum. The remaining photons with wavelengths up to 1.1 µm are absorbed by the underlying planar Si p-n junction. In contrary to conventional semiconductor photocatalysts, InGaN can uniquely straddle water oxidation and hydrogen reduction potentials under deep visible light irradiation. The n -GaN and p -InGaN are connected via an n ++ - GaN / InGaN/ p ++ - GaN polarization-enhanced tunnel junction, which enables the transport of photo-excited holes from the p -InGaN to the n -GaN within each single nanowire. The presented device differs from conventional PV-PEC electrodes in that both the top p -InGaN and the bottom GaN/Si light absorbers can simultaneously drive proton reduction due to the lateral carrier extraction scheme of nanowires. That is, due to the relatively small offset between the n + -Si and n -GaN conduction band edges, photo-excited electrons of the bottom Si solar cell can readily inject into the n -GaN nanowire segment. A large fraction of the injected electrons can drive proton reduction on GaN surfaces, with the rest recombining with holes from the p -InGaN in the tunnel junction. It is seen that such a novel design, with the use of Si/GaN-nanowire as the bottom light absorber, can surpass the restriction of current matching in conventional dual absorber devices and simultaneously provide energetic photo-excited electrons to the hydrogen-evolution-reaction (HER) catalyst. Compared to the conventional PEC-PV, such adaptive junction can reduce chemical loss by allowing charge carriers with different overpotentials to be utilized for HER. Such a monolithically integrated photocathode shows an applied bias photon-to-current efficiency of 8.7% at a potential of 0.33 V vs. normal hydrogen electrode. The Faradaic efficiency for hydrogen generation is also measured to be nearly unity.

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)0.003
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 score0.024
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.060
GPT teacher head0.312
Teacher spread0.253 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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