MétaCan
Menu
Back to cohort
Record W2641155589 · doi:10.1149/ma2017-02/35/1498

(Invited) Platinum Group Metal-Free Oxygen Reduction Reaction Electrocatalysts from Fe-N-C Family: Activity, Durability and Manufacturability

2017· article· en· W2641155589 on OpenAlexaff
Alexey Serov, Barr Zulevi, Kateryna Artyushkova, Plamen Atanassov, Gaixia Zhang, Régis Chenitz, Michel Lefèvre, Jean‐Pol Dodelet, Shuhui Sun, Serge Pann, Sanjeev Mukerjee

Bibliographic record

VenueECS Meeting Abstracts · 2017
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsCatalysisPyrolysisPlatinumMaterials scienceMetalChemical engineeringCathodeChemistryInorganic chemistryOrganic chemistryMetallurgyPhysical chemistry

Abstract

fetched live from OpenAlex

PEM fuel cells have been recognized as one of the most promising candidates for motive and stationary power source. Among the PGM-free catalysts known today, Fe-N-C catalysts (especially made by high temperature pyrolysis) are considered the most viable candidates for platinum substitution from cathode side of fuel cell. There are several ways for synthesis of highly active M-N-C electrocatalysts which involved dispersion of organic N-C precursor and metal salts on support (carbon, MOF or silica), followed by high temperature pyrolysis and post pyrolysis treatments. Among them imidazole-based materials have been the most promising. In this talk we will describe GPGM-free catalysts materials derived from imidazoles using 3 different synthesis methods. The INRS team has developed a MOF-based Fe/N/C catalyst (synthesized using FeAc+Phen+ZIF-8 precursors) with catalyst initial mass activity of 10.6 mA/mg at 0.9 V and maximum initial performance (0.91 W/cm 2 ) [1]. The long term stability of the catalyst was also evaluated and compared with the best literature value (LANL catalyst, which was measured at 0.4 V and 80 o C) [2]. As shown earlier by the Mukerjee group at NEU, encapsulation of Fe chelates within the confines of a MOF as a part of wet chemical synthesis results in formation of highly active and durable M-N-C electrocatalysts [3]. This presentation will provide synthetic, mechanistic and steady state polarization results measured both at a PEM and PAFC single cell. Some aspects of durability and immunity towards anions will also be presented. The UNM team used Sacrificial Support Method (SSM) for preparation of highly active electrocatalysts derived from different imidazole precursors. The influence of imidazole precursors, SSM synthetic parameters (number of post treatments, duration of treatment, heat treatment temperature etc) on the final activity of ORR electrocatalysts was studied in Rotating Ring Disc Electrode as well as in Membrane Electrode Assembly set ups [4-5]. Pajarito Powder performed an extensive R&D on scaling up of the Fe-N-C catalysts made from imidazole MOFs. Such parameters, which will influence the catalyst activity and durability as heat treatment temperature, post treatment conditions, catalyst layer fabrication in MEA were optimized for the materials on the level of 25-50g per batch. It was shown that VariPore ™ allows to reproducibly synthesize commercial amount of ORR PGM-free catalysts with improved activity matching smaller lab scale batches and improve the durability of imidazole-derived catalysts [6]. [1] E. Proietti, F. Jaouen, M. lefèvre, N. Larouche, J. Tian, J. Herranz, J. P. Dodelet “Iron-based cathode catalyst with enhanced power density in polymer electrolyte membrane fuel cells”, Nature Communications 2 (2011) 416. [2] G. Wu, K.L. More,C.M. Johnston, P. Zelenay "High-performance electrocatalysts for oxygen reduction derived from polyaniline, iron, and cobalt" Science 332 (2011) 443-447. [3] K. Strickland, E. Miner, Q. Jia, U. Tylus, N. Ramaswamy, W. Liang, M.-T. Sougrati, F. Jaouen. S. Mukerjee "Highly active oxygen reduction non-platinum group metal electrocatalyst without direct metal–nitrogen coordination" Nature Comm. 6, Article number: 7343 (2015) [4] D. Sebastian, A. Serov, K. Artyushkova, J. Gordon, P. Atanassov, A. S. Arico, V. Baglio "High Performance and Cost‐Effective Direct Methanol Fuel Cells: Fe‐N‐C Methanol‐Tolerant Oxygen Reduction Reaction Catalysts" ChemSusChem 9 (15) (2016) 1986-1995. [5] D. Sebastian, A. Serov, K. Artyushkova, P. Atanassov, A. S. Arico, V. Baglio "Performance, methanol tolerance and stability of Fe-aminobenzimidazole derived catalyst for direct methanol fuel cells", J. Power Sources 319 (2016), 235–246. [6] A. Serov, M. J. Workman, K. Artyushkova, P. Atanassov, G. McCool, S. McKinney, H. Romero, B. Halevi, T. Stephenson "Highly stable precious metal-free cathode catalyst for fuel cell application", J. Power Sources 327 (2016) 557-564.

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)0.001
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 score0.304
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.013
GPT teacher head0.216
Teacher spread0.203 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueECS Meeting AbstractsSame topicFuel Cells and Related MaterialsFrench-language works237,207