Multi-scale microscopy study of 3D morphology and structure of MoNi4/MoO2@Ni electrocatalytic systems for fast water dissociation

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Ehrenfried Zschech - , Dresden Center for Nanoanalysis (DCN) (Autor:in)
  • Emre Topal - , Dresden Center for Nanoanalysis (DCN) (Autor:in)
  • Kristina Kutukova - , Fraunhofer Institute for Ceramic Technologies and Systems (Autor:in)
  • Jürgen Gluch - , Fraunhofer Institute for Ceramic Technologies and Systems (Autor:in)
  • Markus Löffler - , Dresden Center for Nanoanalysis (DCN) (Autor:in)
  • Stephan Werner - , Helmholtz Centre Berlin for Materials and Energy (Autor:in)
  • Peter Guttmann - , Helmholtz Centre Berlin for Materials and Energy (Autor:in)
  • Gerd Schneider - , Helmholtz Centre Berlin for Materials and Energy, Humboldt University of Berlin (Autor:in)
  • Zhongquan Liao - , Fraunhofer Institute for Ceramic Technologies and Systems (Autor:in)
  • Janis Timoshenko - , Fritz Haber Institute of the Max Planck Society (Autor:in)

Abstract

The 3D morphology of hierarchically structured electrocatalytic systems is determined based on multi-scale X-ray computed tomography (XCT), and the crystalline structure of electrocatalyst nanoparticles is characterized using transmission electron microscopy (TEM), supported by X-ray diffraction (XRD) and spatially resolved near-edge X-ray absorption fine structure (NEXAFS) studies. The high electrocatalytic efficiency for hydrogen evolution reaction (HER) of a novel transition-metal-based material system – MoNi4 electrocatalysts anchored on MoO2 cuboids aligned on Ni foam (MoNi4/MoO2@Ni) – is based on advantageous crystalline structures and chemical bonding. High-resolution TEM images and selected-area electron diffraction patterns are used to determine the crystalline structures of MoO2 and MoNi4. Multi-scale XCT provides 3D information of the hierarchical morphology of the MoNi4/MoO2@Ni material system nondestructively: Micro-XCT images clearly resolve the Ni foam and the attached needle-like MoO2 micro cuboids. Laboratory nano-XCT shows that the MoO2 micro cuboids with a rectangular cross-section of 0.5 × 1 µm2 and a length of 10–20 µm are vertically arranged on the Ni foam. MoNi4 nanoparticles with a size of 20–100 nm, positioned on single MoO2 cuboids, were imaged using synchrotron radiation nano-XCT. The application of a deep convolutional neural network (CNN) significantly improves the reconstruction quality of the acquired data.

Details

OriginalspracheEnglisch
Aufsatznummer103262
FachzeitschriftMicron
Jahrgang158
PublikationsstatusVeröffentlicht - Juli 2022
Peer-Review-StatusJa

Externe IDs

Scopus 85127487085
unpaywall 10.1016/j.micron.2022.103262
Mendeley 7c075467-c0d6-3012-a052-25c4a03d42b6
WOS 000791264100001

Schlagworte

Forschungsprofillinien der TU Dresden

Fächergruppen, Lehr- und Forschungsbereiche, Fachgebiete nach Destatis

Schlagwörter

  • Morphology, Crystalline structure, X-ray microscopy, X-ray computed tomography, NEXAFS, TEM, Electrocatalyst, Convolutional neural network, Nexafs, Tem

Bibliotheksschlagworte