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Article Abstract

Conventional packed-bed catalysts suffer from single-scale porosity, insufficient mechanical strength, and suboptimal mass transfer efficiency. Inspired by the fractal structure of the lung bronchi, a design and 3D printing method for gradient meta-structural catalysts is proposed by integrating synthesized LaFeNiO (LFN) perovskite with pseudo-boehmite, achieving ultralow pressure drop and high catalytic efficiency. Computational fluid dynamics and reaction simulations guide the design of uniform and gradient-structured catalysts with hierarchical woodpile channels (0.5-3 mm). Compared with homogeneous catalysts, the gradient design theoretically exhibits 1.5-fold and 1.1-fold increases in flow velocity and hydrogen production, respectively. Meta-structural catalysts are fabricated with gradient multi-peak pore distribution (9.32 nm, 103.75 nm) by regionally modulating unit cell sizes and LFN content (11-35%) combined with the dehydroxylation of pseudo-boehmite. 3D-printed perovskite catalysts demonstrate a 78.7-fold increase in specific surface area (102.26 m g) and compressive strength of 8.48 MPa. In dry reforming of methane (DRM) tests, it achieves 82.13% CH conversion, and 9.69 mmol g syngas yield, outperforming conventional powder-packed beds by 10% efficiency. This study achieves mass transfer and catalytic performance coupling by tuning gradient hierarchical pores and tailoring flow dynamics, offering a paradigm for robust, high-efficiency catalyst design across diverse applications.

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http://dx.doi.org/10.1002/adma.202508078DOI Listing

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