莊信萬豐股份有限公司

Efficient mixing of binary particle systems is essential in process engineering, as it directly impacts product quality, stability, and cost. Traditional evaluation methods rely on empirical modeling from the theoretical assumptions or macroscale characterizations, both remaining time- and cost-intensive. In this study, X-ray computed tomography (XCT) is employed to perform non-destructive three-dimensional imaging of particulate systems. This advanced technique enables detailed characterization of microstructural features and spatial arrangements, yielding critical insights into mixing conditions at the microscale, and is quantified by tailored evaluation metrics. Machine learning-enhanced image segmentation enables efficient particle identification in 2D cross-sections from 3D XCT data. This framework enhances XCT-based feature extraction, enabling simultaneous qualitative observation and quantitative analysis to optimize and improve chemical engineering processes and product quality.

One-dimensional models of Particulate Filters (PFs) typically involve the numeric solution of the balance equations. However, for isothermal conditions and axially uniform soot and ash deposits, the mass and momentum balance equation can be solved analytically. Analytic models have the advantage of faster solution and easier identification of trends.This work builds on earlier analytic PF models and presents a model that for the first time includes all the following: i) compressible flow; ii) soot- and ash-loaded PFs; iii) momentum flux correction factors; and iv) asymmetric PFs, including those where inlet and outlet channels have different shape, e.g. octo-square PFs. The analytic model can predict flow and pressure profiles along the channels, in addition to backpressure. There are different options for formulating the analytic model; these are examined with a view to finding the best model.The analytic model has been validated against both measured backpressure data and the predictions of a numeric model; the latter allows model testing over a wider range of conditions.The analytic solution requires some approximations; the impact of these on the accuracy of prediction is assessed. The analytic model is exact for lower flow rates, where inertial contributions to backpressure are negligible. Analytic model error against the numeric model for pressure prediction tends to increase with increasing mass flow, PF asymmetry, wall permeability and temperature. However, analytic model error is generally low/acceptable for conditions encountered in real-world applications. Pressure profiles along the channels are well predicted under conditions where the backpressure is well predicted.

A reliable estimate of the impact of recycling is crucial for a fact-based assessment of the current and future sustainability of platinum group metal (PGM)-based catalysts. Recycling rates in the literature are usually calculated based on published market data, notably from Johnson Matthey, but as these reported data exclude "closed-loop" recycling, this method leads to a significant underestimation of recycling volumes. Harnessing Johnson Matthey's primary PGM market research and its proprietary suite of supply/demand/recycling models, we publish here an estimate of closed-loop recycling volumes. We find that closed-loop recycling volumes are much larger than open-loop recycling (which is reported in market data as secondary PGM supply) and that it is likely that between 50 and 60% of the metal used on new products is now sourced from recycling (globally on average). The significant reduction in global warming potential (GWP) of recycled (secondary) PGMs compared to newly mined (primary) metal means that an estimate of the proportion of recycled metal in a catalytic process or PGM-based product must be properly factored into LCA models. Our data and scenarios suggest that the GWP impact of PGMs can be reduced by 1 order of magnitude when a recycling "closed loop" is put in place within a process, underscoring the sustainability benefit of implementing routine recycling wherever practicable and ensuring that the recovered metal is retained.

The increasing demand for advanced materials in oil and gas exploration has driven renewed interest in modified Ti-6Al-4V alloys, particularly those doped with noble metals such as palladium and ruthenium. This study investigates the microstructural and corrosion behaviour of palladium- and ruthenium-modified commercial purity titanium (cp-Ti) and Ti-6Al-4V alloys fabricated via hot isostatic pressing (HIP) of 150–500 µm powders. Results reveal a non-uniform distribution of the noble metals, with enrichment at interparticle boundaries under the applied HIP conditions. Tailoring of microstructures was achieved by varying powder size and HIP parameters, with distinct β-phase morphologies observed between palladium- and ruthenium-modified samples. Palladium additions demonstrated superior corrosion resistance compared to ruthenium, highlighting the influence of dopant selection on alloy performance. The findings underscore the importance of powder metallurgical approaches for noble metal doping, offering pathways to microstructures and properties unattainable through conventional melt and wrought processing. This work emphasises the need for continued development of simulant protocols to bridge laboratory studies with field applications.