H Sorption Based Materials for the Hydrogenation of CO2 to Added Value Fuel Products
Bibliographic record
Abstract
Energy transformation through technological systems has always been a critical issue regarding how our society works. With the environmental consideration taking over these last years, the establishment of efficient energy conversion technology allowing storage of renewably produced electricity in simple non-environmentally harmful chemicals is one of the great challenges of our times. The interest in CO2 in this context is simple; it represents a largely distributed low-energy chemical available for green energy storage. The electrochemical reduction of CO2 to small fuel molecule has been largely investigated, but the reduction process inefficiency and the cost of the highly specialized catalysts act as drawback to the implementation of this technology to industrial applications. In this work, we explore bimetallic catalyst that moves away from the simple optimization of reaction rate by adjustment of adsorption energies of species (i.e. volcano plot). We propose to combine a material active for H adsorption to a conventional CO2 electrocatalyst to explore the effect of potential enhanced availability and transfer of H during the carbon species conversion. The Cu/Pd system has been selected as a model material for the studies. Although many structures are possible to combine the metals, we chose to plate the Cu on the Pd substrate by UPD technique [1] to reduce the large hydrogen evolution occurring at Pd. The system has been studied by conventional electrochemistry, including a diversity of potentiostatic measurements and cyclic voltammetry (CV). The isotherm of H sorption has been assessed using Lasia methodology [2] to insure that the H sorption on Pd and the CO2 reduction on Cu occur in the same potential region. The UPD has been optimized and combined to dilution method to allow CO2 reduction at Cu-free solution after the deposition of a designed monolayer (ML) content of Cu on Pd. CVs has been conducted to access the general behavior of the Cu/Pd system. Activity of the underlying substrate for H has been observed to occur at the 1ML Cu on Pd. Measurements point toward the preservation of some H sorption activity by the Pd through the Cu ML although activity of bare Pd in contact with the solution through ML defect is not to exclude. We propose that the preservation of the Pd structure and electronic effects at the 1 ML Cu explains the possibility of enhanced H adsorption after the reduction by Cu at the interface. Differential electrochemical mass spectrometry (DEMS) measurements are conducted to study the effect of different content of Cu ML at the surface of the catalyst on the product distribution during the electrolysis. The specific adsorption of the anion from the electrolyte being known to affect the reaction pathway by partial and scattered surface coverage [3], different electrolytes were used to gain insight on pathways that are privileged by the different Cu/Pd surfaces. To further rationalize the links between surface properties and reaction products, X-ray photoelectron spectroscopy at near-ambient pressures (APXPS) measurements has been collected. This technique uses X-rays that generate photoelectrons that enter a differentially pumped XPS analyzer with electronoptics that facilitate the characterization of a solid material that is exposed to gases to enable the observation of their interaction during the spectrum collection. This method has previously been used to highlight different modes of CO2 adsorption on Cu surface [4]. Several ML content of Cu over Pd has been exposed to CO2 and CO under H-present and H-absent regimes. The affinity of the CO for Pd dominant surfaces has been observed. The coverage of Cu on the Pd substrate also influences the charge transfer between the adsorbed CO and the surface. We believe that the close containment of domains active for H sorption and CO2 reduction can be used as a tool to control selectivity over CO2 reduction and to favor the production of small added value molecules. Acknowledgement The financial support of the Fonds de recherche du Québec – Nature et technologies (FRQNT), of the Natural Sciences and Engineering Research Council of Canada (NSERC) and of Rio Tinto Alcan are gratefully acknowledged. This research used resources of the Advanced Light Source, which is a DOE Office of Science User Facility under contract no. DE-AC02-05CH11231. References A. Kumar and D. A. Buttry, The Journal of Physical Chemistry C, 2015, 119(29), 16927-16933 H. Duncan and A. Lasia, J. Electroanal. Chem., 2008, 621(1), 62−68. P. Dubé, G. Brisard, J. Electroanal. Chem., 2008, 582(1-2), 230-240 M. Favaro, H. Xiao, T. Cheng, W. A. Goddard, J. Yano et E. J. Crumlin, PNAS, 2017, 201701405
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".