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Record W3117249851 · doi:10.1149/ma2020-02623176mtgabs

In-Situ Soft X-Ray Spectromicroscopy Characterization of Electrochemical Processes

2020· article· en· W3117249851 on OpenAlexaffabout
Chunyang Zhang, Pablo Ingino, Martin Obst, Ladan Shahcheraghi, Hao Yuan, Haytham Eraky, Jian Wang, Drew Higgins, Adam P. Hitchcock

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldEnergy
TopicCO2 Reduction Techniques and Catalysts
Canadian institutionsCanadian Light Source (Canada)University of SaskatchewanMcMaster University
Fundersnot available
KeywordsElectrochemistryElectrochemical cellMaterials scienceElectrolyteXANESRedoxIn situElectrodeAnalytical Chemistry (journal)Chemical engineeringChemistrySpectroscopyMetallurgy

Abstract

fetched live from OpenAlex

Soft X-ray Scanning Transmission X-ray microscopy (STXM) is a synchrotron-based technique which can provide both spectroscopic characterization (near edge X-ray absorption fine structure, NEXAFS) and chemically selective imaging with high spatial resolution (~30 nm). Recently, we have developed in situ flow electrochemical devices [1,2] which allow control of the electrochemical environment while conducting STXM measurements, thus providing a platform for in-situ studies of electrochemical oxidation and reduction processes. This presentation reports results of in situ flow electrochemical STXM studies on three different systems to demonstrate the present capabilities. First, the ability to rapidly exchange the electrolyte is demonstrated by a STXM Fe 2p and in situ electrochemical study of the ferro/ferricyanide solution redox system. Second Cu and Ag-doped Cu catalysts for CO2 electrochemical reduction (CO2R) were successfully prepared using in situ electrodeposition. Third, the electrolyte was changed from CuSO4 to NaHCO3 (as substrate for CO2R) and the cell was operated under electrochemical CO2 reduction conditions, while monitoring the changes to the Cu deposited layer at various potentials, including –0.5 V where CO2 reduction is expected [3]. The figure shows a cyclic voltammogram (CV) and color-coded Cu oxidation state maps which were derived from Cu 2p stacks measured under chronoamperometric conditions at the indicated potentials. These results demonstrate that in situ flow electrochemical STXM measurements can be performed in our device under varying electrochemical reaction conditions, enabling visualization of the morphology changes from selective energy imaging, and quantitative tracking of electrochemical transformations from spectromicroscopy. This system will be used for in situ studies of CO2 electrochemical reduction catalysis with the goal of obtaining mechanistic insights to guide the development of catalysts with improved efficiency and selectivity. In addition, the system will be used to study a variety of material science, chemistry and environmental science related questions associated with oxidation or reduction processes, such as mechanisms of extra-cellular electron transport in marine sediment microbial biofilms [4]. This research is supported by NSERC (Canada). STXM measurements were performed at the ambient STXM facility at the Canadian Light Source, which is funded by the Canadian Foundation for Innovation. [1] V. Prabu et al., Rev. Sci. Inst. 89 (2018) 063702. [2] P. Ingino, et al., in preparation [3] L. Wang, D.C. Higgins, et al., Proc. Nat. Acad. Sci. (2020) 01821683. DOI: 10.1073/pnas.1821683117 [4] M. Obst, et al., Microsc. Microanal. 24 (S-2) (2018) 502-504. Figure 1

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.236
Teacher spread0.226 · 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 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

Citations1
Published2020
Admission routes2
Has abstractyes

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