Multi-scale X-ray tomography and machine learning algorithms to study MoNi4 electrocatalysts anchored on MoO2 cuboids aligned on Ni foam

Topal, Emre; Liao, Zhongquan; Löffler, Markus; Gluch, Jürgen; Zhang, Jian; Feng, Xinliang; Zschech, Ehrenfried

doi:10.1186/s42833-020-00011-0

Cited by 16 publications

(18 citation statements)

References 48 publications

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“…Highly performant and durable systems for electrochemical energy storage and conversion require the design and synthesis of materials with optimized hierarchical 3D morphology and surface structures with high activity. In addition to the intrinsic properties of the constituent components that determine chemical activity and conductivity, the material's 3D morphology is crucial to prevent agglomeration of particles and to promote mass transfer (i.e., reactant diffusion and product release) [8]. The design and synthesis of robust 3D structures, e.g., electrocatalysts, with an optimized hierarchical morphology, are of particular interest for the upscaling of processes and for the development of technologies to fabricate advanced energy conversion devices.…”

Section: Synthesis and Characterization Of The Moni 4 /Moo 2 @Ni Materials Systemmentioning

confidence: 99%

“…A novel computer vision methodology combined with a deep neural network approach provides estimates for motion by tracking features through adjacent projections. This tomographic-reconstruction algorithm is empowered by sophisticated correction modules that autonomously estimate and effectively suppress artifacts and random errors using gradient descent and deep learning algorithms (examples see [8,9]). Another development to shorten the data acquisition time for XCT was reported by Bulatov et al [10].…”

Section: Introductionmentioning

confidence: 99%

“…The chosen example, a high performance and durable electrocatalytic system with a tailored morphology, is a novel transition-metal-based materials system for fast water dissociation: MoNi4 electrocatalysts anchored on MoO 2 cuboids aligned on Ni foam (MoNi 4 /MoO 2 @Ni) [11]. XCT, both nano-XCT and micro-XCT, are suitable techniques to provide the morphology of the (sub-)structures of such hierarchically structured materials and systems [8]. Since individual projections, i.e., 2D slices of the investigated object, include very different individual features, we used several different 2D slices of one object for evaluation.…”

Section: Introductionmentioning

confidence: 99%

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Monitored Tomographic Reconstruction—An Advanced Tool to Study the 3D Morphology of Nanomaterials

et al. 2021

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Detailed and accurate three-dimensional (3D) information about the morphology of hierarchically structured materials is derived from multi-scale X-ray computed tomography (XCT) and subsequent 3D data reconstruction. High-resolution X-ray microscopy and nano-XCT are suitable techniques to nondestructively study nanomaterials, including porous or skeleton materials. However, laboratory nano-XCT studies are very time-consuming. To reduce the time-to-data by more than an order of magnitude, we propose taking advantage of a monitored tomographic reconstruction. The benefit of this new protocol for 3D imaging is that the data acquisition for each projection is interspersed by image reconstruction. We demonstrate this new approach for nano-XCT data of a novel transition-metal-based materials system: MoNi4 electrocatalysts anchored on MoO2 cuboids aligned on Ni foam (MoNi4/MoO2@Ni). Quantitative data that describe the 3D morphology of this hierarchically structured system with an advanced electrocatalytically active nanomaterial are needed to tailor performance and durability of the electrocatalyst system. We present the framework for monitored tomographic reconstruction, construct three stopping rules for various reconstruction quality metrics and provide their experimental evaluation.

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Section: Synthesis and Characterization Of The Moni 4 /Moo 2 @Ni Materials Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Monitored Tomographic Reconstruction—An Advanced Tool to Study the 3D Morphology of Nanomaterials

et al. 2021

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“…The exposure time per image was 120 s. The acquired projections were reconstructed using a Filtered Back Projection (FBP) algorithm [39]. The applied reconstruction methodology provides highly accurate 3D morphological data by enabling corrections for imaging artefacts of high-resolution XCT though the compensation of acquisition inaccuracies such as misalignment and motions of samples and tool components [40,41]. The reconstructed image stacks are fused into one stack that includes whole 3D morphological information of the frustule.…”

Section: Structure Characterizationmentioning

confidence: 99%

Numerical and Experimental Study of the Mechanical Response of Diatom Frustules

et al. 2020

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Diatom frustules, with their hierarchical three-dimensional patterned silica structures at nano to micrometer dimensions, can be a paragon for the design of lightweight structural materials. However, the mechanical properties of frustules, especially the species with pennate symmetry, have not been studied systematically. A novel approach combining in situ micro-indentation and high-resolution X-ray computed tomography (XCT)-based finite element analysis (FEA) at the identical sample is developed and applied to Didymosphenia geminata frustule. Furthermore, scanning electron microscopy and transmission electron microscopy investigations are conducted to obtain detailed information regarding the resolvable structures and the composition. During the in situ micro-indentation studies of Didymosphenia geminata frustule, a mainly elastic deformation behavior with displacement discontinuities/non-linearities is observed. To extract material properties from obtained load-displacement curves in the elastic region, elastic finite element method (FEM) simulations are conducted. Young’s modulus is determined as 31.8 GPa. The method described in this paper allows understanding of the mechanical behavior of very complex structures.

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“…Computed tomography has important applications in such fields as industry, physics, chemistry [3], biology [4], medicine, and others. Analysis of a three-dimensional internal structure of objects is required for the study of multimaterial components [5], for characterization of object's properties [6], or to analyze nanostructures [7], [8].…”

Section: Introduction a Computed Tomography And Its Applicationsmentioning

confidence: 99%

Monitored Reconstruction: Computed Tomography as an Anytime Algorithm

et al. 2020

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Computed tomography is an important technique for non-destructive analysis of an object's internal structure, relevant for scientific studies, medical applications, and industry. Pressing challenges emerging in the field of tomographic imaging include speeding up reconstruction, reducing the time required to obtain the X-ray projections, and reducing the radiation dose imparted to the object. In this paper, we introduce a model of a monitored reconstruction process, in which the acquiring of projections is interspersed with image reconstruction. This model allows to examine the tomographic reconstruction process as an anytime algorithm and consider a problem of finding the optimal stopping point, corresponding to the required number of X-ray projections for the currently scanned object. We outline the theoretical framework for the monitored reconstruction, propose ways of constructing stopping rules for various reconstruction quality metrics and provide their experimental evaluation. Due to stopping at different times for different objects, the proposed approach allows to achieve a higher mean reconstruction quality for a given mean number of X-ray projections. Conversely, fewer projections on average are used to achieve the same mean reconstruction quality. INDEX TERMS Anytime algorithms, computed tomography, dose reduction, monitored reconstruction, optimal stopping, x-ray tomography.

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Multi-scale X-ray tomography and machine learning algorithms to study MoNi4 electrocatalysts anchored on MoO2 cuboids aligned on Ni foam

Cited by 16 publications

References 48 publications

Monitored Tomographic Reconstruction—An Advanced Tool to Study the 3D Morphology of Nanomaterials

Monitored Tomographic Reconstruction—An Advanced Tool to Study the 3D Morphology of Nanomaterials

Numerical and Experimental Study of the Mechanical Response of Diatom Frustules

Monitored Reconstruction: Computed Tomography as an Anytime Algorithm

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