Oxygen Reduction Activities of Strained Platinum Core–Shell Electrocatalysts Predicted by Machine Learning

Rück, Marlon; Garlyyev, Batyr; Mayr, Felix; Bandarenka, Aliaksandr S.; Gagliardi, Alessio

doi:10.1021/acs.jpclett.0c00214

Cited by 35 publications

(24 citation statements)

References 55 publications

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“…713,714 In recent years, ML has proven to be a powerful tool to accelerate the screening of catalysts for energy conversion, without the need for conducting actual experiments nor a deep understanding of the underlying mechanism of the output properties. 714,715 ML has been mostly used to predict the function/activity of new materials of various complexities, e.g., single-component systems for a CO 2 RR photocathode, 716 bimetallic core−shell electrocatalysts for ORR, 717 Cu-Al electrocatalysts for CO 2 RR, 718 and graphene-supported single-atom electrocatalysts with different M-N-C coordination patterns. 719 The obtained relationships between the targeted functions/ activities, compositions, and characteristics can further guide the synthesis of optimal materials.…”

Section: Designing Optimized and Scalable Reactorsmentioning

confidence: 99%

Noble-Metal-Free Multicomponent Nanointegration for Sustainable Energy Conversion

et al. 2021

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Global energy and environmental crises are among the most pressing challenges facing humankind. To overcome these challenges, recent years have seen an upsurge of interest in the development and production of renewable chemical fuels as alternatives to the nonrenewable and high-polluting fossil fuels. Photocatalysis, photoelectrocatalysis, and electrocatalysis provide promising avenues for sustainable energy conversion. Single-and dual-component catalytic systems based on nanomaterials have been intensively studied for decades, but their intrinsic weaknesses hamper their practical applications. Multicomponent nanomaterial-based systems, consisting of three or more components with at least one component in the nanoscale, have recently emerged. The multiple components are integrated together to create synergistic effects and hence overcome the limitation for outperformance. Such higher-efficiency systems based on nanomaterials will potentially bring an additional benefit in balance-of-system costs if they exclude the use of noble metals, considering the expense and sustainability. It is therefore timely to review the research in this field, providing guidance in the development of noble-metal-free multicomponent nanointegration for sustainable energy conversion. In this work, we first recall the fundamentals of catalysis by nanomaterials, multicomponent nanointegration, and reactor configuration for water splitting, CO 2 reduction, and N 2 reduction. We then systematically review and discuss recent advances in multicomponent-based photocatalytic, photoelectrochemical, and electrochemical systems based on nanomaterials. On the basis of these systems, we further laterally evaluate different multicomponent integration strategies and highlight their impacts on catalytic activity, performance stability, and product selectivity. Finally, we provide conclusions and future prospects for multicomponent nanointegration. This work offers comprehensive insights into the development of cost-competitive multicomponent nanomaterial-based systems for sustainable energy-conversion technologies and assists researchers working toward addressing the global challenges in energy and the environment.

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Section: Designing Optimized and Scalable Reactorsmentioning

confidence: 99%

Noble-Metal-Free Multicomponent Nanointegration for Sustainable Energy Conversion

et al. 2021

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“…169 Furthermore, it was suggested very recently that the optimal strain for high ORR performance can vary, depending on the type of core and shell materials and on the particle size. 170 While most core−shell structures have a spherical or polyhedral shape, it was demonstrated that low-dimensional core−shell structures could attain much higher ORR perform- ance. Bu et al reported noticeable improvement of ORR activity in the PtPb/Pt core−shell nanoplate structure with a Pt shell thickness of ∼1 nm, as shown in Figure 14g,h.…”

Section: Orr Catalysis On Metal-based Materialsmentioning

confidence: 99%

Atomic-Level Manipulations in Oxides and Alloys for Electrocatalysis of Oxygen Evolution and Reduction

et al. 2020

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As chemical reactions and charge-transfer simultaneously occur on the catalyst surface during electrocatalysis, numerous studies have been carried out to attain an in-depth understanding on the correlation among the surface structure and composition, the electrical transport, and the overall catalytic activity. Compared with other catalysis reactions, a relatively larger activation barrier for oxygen evolution/reduction reactions (OER/ORR), where multiple electron transfers are involved, is noted. Many works over the past decade thus have been focused on the atomic-scale control of the surface structure and the precise identification of surface composition change in catalyst materials to achieve better conversion efficiency. In particular, recent advances in various analytical tools have enabled noteworthy findings of unexpected catalytic features at atomic resolution, providing significant insights toward reducing the activation barriers and subsequently improving the catalytic performance. In addition to summarizing important surface issues, including lattice defects, related to the OER and ORR in this Review, we present the current status and discuss future perspectives of oxide- and alloy-based catalysts in terms of atomic-scale observation and manipulation.

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“…56 The compressive strain results in a modified GCN that is larger than the original GCN. 57 On the other hand, the ligand effect has not been discussed in literature. During the study of core−shell NPs, preparing a few Pt layers near the surface of the NPs prevents the ligand effect on atomic or molecular adsorption.…”

Section: ■ Introductionmentioning

confidence: 99%

An Element-Based Generalized Coordination Number for Predicting the Oxygen Binding Energy on Pt₃M (M = Co, Ni, or Cu) Alloy Nanoparticles

Koyama

2021

ACS Omega

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We studied the binding energies of O species on face-centered-cubic Pt3M nanoparticles (NPs) with a Pt-skin layer using density functional theory calculations, where M is Co, Ni, or Cu. It is desirable to express the property by structural parameters rather than by calculated electronic structures such as the d-band center. A generalized coordination number (GCN) is an effective descriptor to predict atomic or molecular adsorption energy on Pt-NPs. The GCN was extended to the prediction of highly active sites for oxygen reduction reaction. However, it failed to explain the O binding energies on Pt-skin Pt150M51-NPs. In this study, we introduced an element-based GCN, denoted as GCNA–B, and considered it as a descriptor for supervised learning. The obtained regression coefficients of GCNPt–Pt were smaller than those of the other GCNA–B. With increasing M atoms in the subsurface layer, GCNPt–M, GCNM–Pt, and GCNM–M increased. These factors could reproduce the calculated result that the O binding energies of the Pt-skin Pt150M51-NPs were less negative than those of the Pt201-NPs. Thus, GCNA–B explains the ligand effect of the O binding energy on the Pt-skin Pt150M51-NPs.

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Oxygen Reduction Activities of Strained Platinum Core–Shell Electrocatalysts Predicted by Machine Learning

Cited by 35 publications

References 55 publications

Noble-Metal-Free Multicomponent Nanointegration for Sustainable Energy Conversion

Noble-Metal-Free Multicomponent Nanointegration for Sustainable Energy Conversion

Atomic-Level Manipulations in Oxides and Alloys for Electrocatalysis of Oxygen Evolution and Reduction

An Element-Based Generalized Coordination Number for Predicting the Oxygen Binding Energy on Pt₃M (M = Co, Ni, or Cu) Alloy Nanoparticles

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Oxygen Reduction Activities of Strained Platinum Core–Shell Electrocatalysts Predicted by Machine Learning

Cited by 35 publications

References 55 publications

Noble-Metal-Free Multicomponent Nanointegration for Sustainable Energy Conversion

Noble-Metal-Free Multicomponent Nanointegration for Sustainable Energy Conversion

Atomic-Level Manipulations in Oxides and Alloys for Electrocatalysis of Oxygen Evolution and Reduction

An Element-Based Generalized Coordination Number for Predicting the Oxygen Binding Energy on Pt3M (M = Co, Ni, or Cu) Alloy Nanoparticles

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An Element-Based Generalized Coordination Number for Predicting the Oxygen Binding Energy on Pt₃M (M = Co, Ni, or Cu) Alloy Nanoparticles