SAMBA: A Trainable Segmentation Web-App with Smart Labelling

Segmentation is the assigning of a semantic class to every pixel in an image and is a prerequisite for various statistical analysis tasks in materials science, like phase quantification, physics simulations or morphological characterization. The wide range of length scales, imaging techniques and materials studied in materials science means any segmentation algorithm must generalise to unseen data and support abstract, user-defined semantic classes. Trainable segmentation is a popular interactive segmentation paradigm where a classifier is trained to map from image features to user drawn labels. SAMBA is a trainable segmentation tool that uses Meta's Segment Anything Model (SAM) for fast, high-quality label suggestions and a random forest classifier for robust, generalizable segmentations. It is accessible in the browser (https://www.sambasegment.com/) without the need to download any external dependencies. The segmentation backend is run in the cloud, so does not require the user to have powerful hardware

Recent developments in X-ray diffraction/scattering computed tomography for materials science

X-ray diffraction/scattering computed tomography (XDS-CT) methods are a non-destructive class of chemical imaging techniques that have the capacity to provide reconstructions of sample cross-sections with spatially resolved chemical information. While X-ray diffraction CT (XRD-CT) is the most well-established method, recent advances in instrumentation and data reconstruction have seen greater use of related techniques like small angle X-ray scattering CT and pair distribution function CT. Additionally, the adoption of machine learning techniques for tomographic reconstruction and data analysis are fundamentally disrupting how XDS-CT data is processed. The following narrative review highlights recent developments and applications of XDS-CT with a focus on studies in the last five years. This article is part of the theme issue 'Exploring the length scales, timescales and chemistry of challenging materials (Part 2)'

Multiscale investigation of adsorption properties of novel 3D printed UTSA-16 structures

Structuring MOF materials is a fundamental step towards their commercialization. Herein we report intensive characterization of 3D-printed UTSA-16 monoliths, facilitated by the development of a new non-aqueous ink formulation, employing hydroxypropyl cellulose and boehmite to adjust the rheology of the ink. What makes this formulation and printing process different from the printed adsorbents and catalysts published previously, is that the resulting structures in this work were not sintered. The presence of the binder matrix not only produced the physical properties for printability but also ensured a homogeneous dispersion of UTSA-16 in the structures, as well as gas adsorption characteristics. The monoliths were tested for the adsorption of different gases (N2, CH4, CO2 and H2O) in order to apply them into separation processes that contribute to defossilizing energy and fuels production. Water is strongly adsorbed in this material (~14 mol/kg at 293 K) and is competing with CO2 for adsorption sites. Breakthrough curves showed that the retention time of CO2 decreases significantly when the feed stream is saturated with water. In this study, synchrotron XRD-CT data were collected in situ, in a non-destructive way, and phase distribution maps were reconstructed to, for the first time, gain insight into the spatial and temporal evolution of the UTSA-16 containing phases in the operating 3D printed monolith during the exposure to CO2.publishedVersio

μ-CT Investigation into the Impact of a Fuel-Borne Catalyst Additive on the Filtration Efficiency and Backpressure of Gasoline Particulate Filters

An investigation into the pre-ashing of new gasoline particulate filters (GPFs) has demonstrated that the filtration efficiency of such filters can be improved by up to 30% (absolute efficiency improvement) when preconditioned using ash derived from a fuel-borne catalyst (FBC) additive. The additive is typically used in diesel applications to enable diesel particulate filter (DPF) regeneration and can be added directly into the fuel tank of the vehicle. This novel result was compared with ash derived from lube oil componentry, which has previously been shown to improve filtration efficiency in GPFs. The lube oil-derived ash utilized in this work improved the filtration efficiency of the GPF by approximately 30%, comparable to the ash derived from the FBC additive. The undesirable impact of the ash deposit on backpressure increases was also investigated, and it was established that the use of the FBC additive resulted in a lower backpressure increase versus the equivalent ash loading from lube oil components. Following the real-world vehicle testing and GPF evaluation, the used, intact filters were further analyzed, using micro-focus computed tomography (μ-CT) to assess the ash distribution within the filters. It was established that the FBC-derived ash was predominantly deposited near the outlet plug region of the filter, whereas the lube oil-derived ash was also distributed within the channel walls, which resulted in a higher GPF backpressure. The μ-CT results were therefore key to establishing the differences between these two ash-providing sources and enabled a better understanding of the effect of filter microstructure on macroscopic performance, i.e., GPF efficiency and backpressure results.</p

Sustainable iron-based oxygen carriers for hydrogen production : real-time operando investigation

In this work, a spray-dried Fe-based oxygen carrier with an in situ generated Mg1-xAl2-yFex+yO4-support was investigated during packed-bed chemical looping operation with methane at 900 degrees C. The evolution of the solid-state chemistry taking place in the oxygen carrier material was investigated in real-time with synchrotron X-ray diffraction while the spatial distribution of the phases was investigated using X-ray diffraction computed tomography (XRD-CT). These measurements revealed that some Fe-cations were systematically taken up and released from the spinel support. This take-up and release was shown to be strongly related with the oxidation state of the active phase. Although this take-up and release of Fe-cations decreased the amount of Fe-oxides active in the chemical looping process, the oxygen transfer capacity was still sufficiently high. The microstructure of the oxygen carriers along the length of the packed reactor bed was also investigated with scanning electron microscopy (SEM). The experiments indicate that the MgFeAlOx support with an extra Fe-based active phase is a promising material for oxygen carriers, as it forms a sustainable non-toxic, stable and green alternative to the typical Ni-based oxygen carriers, for hydrogen generation by chemical looping

3D printed Ni/Al2O3 based catalysts for CO2 methanation : a comparative and operando XRD-CT study

Ni-alumina-based catalysts were directly 3D printed into highly adaptable monolithic/multi-channel systems and evaluated for CO2 methanation. By employing emerging 3D printing technologies for catalytic reactor design such as 3D fibre deposition (also referred to as direct write or microextrusion), we developed optimised techniques for tailoring both the support's macro-and microstructure, as well as its active particle precursor distribution. A comparison was made between 3D printed commercial catalysts, Ni-alumina based catalysts and their conventional counterpart, packed beds of beads and pellet. Excellent CO2 conversions and selectivity to methane were achieved for the 3D printed commercial catalyst (95.75% and 95.63% respectively) with stability of over 100 h. The structure-activity relationship of both the commercial and in-house 3D printed catalysts was explored under typical conditions for CO2 hydrogenation to CH4, using operando 'chemical imaging', namely X-Ray Diffraction Computed Tomography (XRD-CT). The 3D printed commercial catalyst showed a more homogenous distribution of the active Ni species compared to the in-house prepared catalyst. For the first time, the results from these comparative characterisation studies gave detailed insight into the fidelity of the direct printing method, revealing the spatial variation in physico-chemical properties (such as phase and size) under operating conditions

A multi-scale study of 3D printed Co-Al2O3 catalyst monoliths versus spheres

This study demonstrates the characteristics of two model packing configurations: 3D printed (3DP) catalyst monoliths on the one hand, and their conventional counterparts, packed beds of spheres, on the other. Cobalt deposited on alumina is selected as a convenient model system for this work, due to its wide spread use in many catalytic reactions. 3DP constructs were produced from alumina powder impregnated with cobalt nitrate while the alumina spheres were directly impregnated with the same cobalt nitrate precursor. The form of the catalyst, the impregnation process, as well as the thermal history, were found to have a significant effect on the resulting cobalt phases. Probing the catalyst bodies in situ by XRD-CT indicated that the level of dispersion of identified Co phases (Co3O4 reduced to CoO) across the support is maintained under reduction conditions. The packed bed of spheres exhibits a non-uniform distribution of cobalt phases, including a core-shell morphology with an average crystallite size of 10–14 nm across the sphere, while the 3DP monolith exhibits a uniform distribution of cobalt phases with an average crystallite size of 5–12 nm upon reduction from Co3O4 to CoO. Computational Fluid Dynamics (CFD) modelling was carried out to develop digital twins and assess the effect of the geometry of both configurations on the pressure drop and velocity profiles. Finally, the activity of both Cobalt-based catalyst geometries was assessed in terms of their conversion, selectivity and turn over frequencies under model multiphase (selective oxidation) reaction conditions, which showed that the desired 3D printed monolithic geometries can offer distinct advantages to the reactor design