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Nørskov, Jens K.

Publications and source records attributed to Nørskov, Jens K..

24 records · Page 2

Two-Dimensional Conductive Ni-HAB as a Catalyst for the Electrochemical Oxygen Reduction Reaction

Catalytic systems whose properties can be systematically tuned via changes in synthesis conditions are highly desirable for the next-generation catalyst design and optimization. Herein, we present a two-dimensional (2D) conductive metal–organic framework consisting of M-N 4 units (M = Ni, Cu) and a hexaaminobenzene (HAB) linker as a catalyst for the oxygen reduction reaction. By varying synthetic conditions, we prepared two Ni-HAB catalysts with different crystallinities, resulting in catalytic systems with different electric conductivities, electrochemical activity, and stability. We show that crystallinity has a positive impact on conductivity and demonstrate that this improved crystallinity/conductivity improves the catalytic performance of our model system. Additionally, density functional theory simulations were performed to probe the origin of M-HAB’s catalytic activity, and they suggest that M-HAB’s organic linker acts as the active site with the role of the metal being to modulate the linker sites’ binding strength.

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Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction

The discovery of high-performing and stable materials for sustainable energy applications is a pressing goal in catalysis and materials science. Understanding the relationship between a material’s structure and functionality is an important step in the process, such that viable polymorphs for a given chemical composition need to be identified. Machine-learning-based surrogate models have the potential to accelerate the search for polymorphs that target specific applications. Herein, we report a readily generalizable active-learning (AL) accelerated algorithm for identification of electrochemically stable iridium oxide polymorphs of IrO 2 and IrO 3 . The search is coupled to a subsequent analysis of the electrochemical stability of the discovered structures for the acidic oxygen evolution reaction (OER). Structural candidates are generated by identifying all 956 structurally unique AB2 and AB3 prototypes in existing materials databases (more than 38000). Next, using an active learning approach, we find 196 IrO 2 polymorphs within the thermodynamic amorphous synthesizability limit and reaffirm the global stability of the rutile structure. We find 75 synthesizable IrO 3 polymorphs and report a previously unknown FeF 3 -type structure as the most stable, termed α-IrO 3 . To test the algorithms performance, we compare to a random search of the candidate space and report at least a 2-fold increase in the rate of discovery. Additionally, the AL approach can acquire the most stable polymorphs of IrO 2 and IrO 3 with fewer than 30 density functional theory optimizations. Analysis of the structural properties of the discovered polymorphs reveals that octahedral local coordination environments are preferred for nearly all low-energy structures. Subsequent Pourbaix Ir–H 2 O analysis shows that α-IrO3 is the globally stable solid phase under acidic OER conditions and supersedes the stability of rutile IrO 2 . Calculation of theoretical OER surface activities reveal ideal weaker binding of the OER intermediates on α-IrO 3 than on any other considered iridium oxide. We emphasize that the proposed AL algorithm can be easily generalized to search for any binary metal oxide structure with a defined stoichiometry.

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A cyclic electrochemical strategy to produce acetylene from CO 2 , CH 4 , or alternative carbon sources

This paper presents the first combined measurement of the double-differential muon neutrino and antineutrino charged-current cross sections with no pions in the final state on hydrocarbon at the off-axis near detector of the T2K experiment. The data analyzed in this work comprise 5.8 × 10$^{20}$ and 6.3 × 10$^{20}$ protons on target in neutrino and antineutrino mode respectively, at a beam energy peak of 0.6 GeV. Using the two measured cross sections, the sum, difference, and asymmetry were calculated with the aim of better understanding the nuclear effects involved in such interactions. The extracted measurements have been compared with the prediction from different Monte Carlo generators and theoretical models showing that the difference between the two cross sections have interesting sensitivity to nuclear effects.

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Nitride or Oxynitride? Elucidating the Composition–Activity Relationships in Molybdenum Nitride Electrocatalysts for the Oxygen Reduction Reaction

Molybdenum nitride (Mo–N) catalysts have shown promising activity and stability for the oxygen reduction reaction (ORR) in acid. However, the effect of oxygen (O) incorporation (from synthesis, catalysis, or exposure to air) on their activity remains elusive. Here, we use reactive sputtering to synthesize three compositions of thin-film catalysts and use extensive materials characterization to investigate the depth-dependent structure and incorporated O. We show that the as-deposited Mo–N films are highly oxidized both at the surface (>30% O) and in the bulk (3–21% O) and that the ORR performance is strongly correlated with the bulk structure and composition. Activity for 4e– ORR is highest for compositions with the highest N/O and N/Mo ratio. Furthermore, H 2 O 2 production for the films with moderate O content is comparable to or higher than the most H 2 O 2 -selective nonprecious metal catalysts in acidic electrolyte, on a moles per mass or surface area of catalyst basis. Density functional theory provides insight into the energetics of O incorporation and vacancy formation, and we hypothesize that activity trends with O/N ratios can be traced to the varying crystallite phases and their interactions with ORR adsorbates. This work demonstrates the prevalence and significance of O in metal nitride electrocatalysts and motivates further investigation into the role of O in other nonprecious metal materials.

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