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Enregistrement W3024979507 · doi:10.1149/ma2020-015626mtgabs

N-Doped Nanoporous Carbon Scaffold As an Electrocatalyst for CO<sub>2</sub> Reduction

2020· article· en· W3024979507 sur OpenAlexaff
Jialang Li, Erwan Bertin, Viola Birss

Notice bibliographique

RevueECS Meeting Abstracts · 2020
Typearticle
Langueen
DomaineEnergy
ThématiqueCO2 Reduction Techniques and Catalysts
Établissements canadiensSt. Francis Xavier UniversityUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésCatalysisElectrocatalystMaterials scienceCarbon fibersRenewable energyNanotechnologyElectrochemical energy conversionElectrochemistryChemistryChemical engineeringOrganic chemistryPhysical chemistry

Résumé

récupéré en direct d'OpenAlex

The rising level of CO2 in the atmosphere poses a major threat to our global climate [1]. Renewable energy are promising alternatives but the utilization of renewable energy is challenging because of its intermittency. The key solution is to develop an energy storage system that can store energy and then release it as needed. CO2 reduction reaction (CO2RR) uses abundant CO2 present in the atmosphere and renewable energy as the input power. Therefore, increasing interest has been focused on electrochemical routes to transform CO2 into useful products. However, the reduction of CO2 is thermodynamically and kinetically unfavorable. To overcome the energy barrier of CO2RR, the development of high efficiency and high selectivity catalysts is a key goal of CO2RR research. Metallic catalysts have attracted much attention for CO2RR and have achieved some successes. However, most metallic catalysts exhibit large CO2RR overpotentials and insufficient selectivity. Also, the high price of noble metals is a key obstacle to scale-up and commercialization of these materials for CO2RR. Carbon is a very promising candidate to advance CO2RR due to its high specific surface areas and good conductivity. However, carbon atoms are electrically neutral and therefore it is difficult to activate the CO2 molecules and adsorb the intermediate. Therefore, it is necessary to develop novel carbon catalysts to enhance their catalytic activity for CO2RR. Nitrogen is the most commonly used carbon doping atom due to its high electronegativity, which leads to polarization of the adjacent carbon atoms, thus enhancing the electronic/ionic conductivity [2]. Many carbon materials, such as carbon nanotubes and graphene, have been doped with N and investigated as CO2RR catalysts [3][4], with some N-doped materials exhibiting a 85% Faradaic efficiency towards CO production[5]. In this work, a nitrogen-doped templated nanoporous carbon scaffold (N-doped NCS) was investigated as a catalyst material for electrochemical CO2 reduction. The NCS is a novel, templated, binder-free, self-supported, fully tunable mesoporous carbon material[6] that gives a high active site density and good conductivity. NCS material, having a pore size of either 12, 50 or 85 nm, was heated in NH3 gas at 700 °C for 7 hours to prepare N-doped NCS. SEM and TEM were used to confirm the NCS morphology, while XPS, EDX and elemental analysis were used to determine the N content of the NCS material. The electrochemical performance of the N-doped NCS was carried out first using CV in CO2 sat. 0.1 M KHCO3 in a glass cell. After that, a membrane electrode assembly (MEA) CO2 electrolyzer was used to determine the CO2 reduction activity. An N-doped NCS (IrO2-coated) was used as the anode and an anion exchange membrane (AEM) was used as the separator during CO2 electrolysis, with humidified CO2 gas used at the cathode side. The gas products were collected from the cathode outlet and injected into a gas chromatography system for analysis. No liquid products were observed in the solution that was released to the cell outlet. The performance of N-doped NCS will be presented based on the results obtained in various solution-flow cell configurations. Effect of N-doped NCS preparation optimization will also be discussed. Based on both the CV results and the MEA CO2 electrolyzer data, the onset potential of CO2RR was comparable to what has been reported by others for N-doped carbons, but the high internal surface area of the NCS, combined with its high extent of N doping, may give the N-doped NCS some advantages. A maximum 90% FECO was achieved and the stability of the catalytic material was also studied in the flow cell systems. References [1] C. Costentin, M. Robert, and J.-M. Savéant, “Catalysis of the electrochemical reduction of carbon dioxide,” Chem. Soc. Rev., 2013. [2] T. Zheng, K. Jiang, and H. Wang, “Recent Advances in Electrochemical CO2 -to-CO Conversion on Heterogeneous Catalysts,” Adv. Mater., vol. 30, no. 48, p. 1802066, Nov. 2018. [3] X. Wang et al., “Emerging Nanostructured Carbon-based Non-precious Metal Electrocatalysts for Selectively Electrochemical CO2 Reduction to CO,” J. Mater. Chem. A, 2019. [4] H. Cui, Y. Guo, L. Guo, L. Wang, Z. Zhou, and Z. Peng, “Heteroatom-doped carbon materials and their composites as electrocatalysts for CO2 reduction,” J. Mater. Chem. A, vol. 6, no. 39, pp. 18782–18793, 2018. [5] T. Ma et al., “Heterogeneous electrochemical CO2 reduction using nonmetallic carbon-based catalysts: current status and future challenges,” Nanotechnology, vol. 28, no. 47, p. 472001, Nov. 2017. [6] Birss, Viola, L. I. Xiaoan, and Dustin Banham. "Porous carbon films." U.S. Patent Application No. 15/124,847.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,003

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,016
Tête enseignante GPT0,253
Écart entre enseignants0,237 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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