Li Zhang

Joule heating coupled with porous media offers rapid in situ heat generation and a more uniform temperature distribution for DRM reactions, whereas the strong coupling of structural and operating parameters renders conventional trial-and-error optimization inefficient and costly. To tackle this challenge, a multi-physics numerical model for a centrally resistively heated DRM reactor is constructed by coupling Joule heating, flow and heat transfer, multicomponent species transport, and apparent reaction kinetics. A fully connected feedforward neural network (FC-FNN) surrogate model is further established to enable rapid prediction of reactor performance. Seven critical input variables are selected, including reaction temperature, gas hourly space velocity (GHSV), etc., and 9216 simulation samples are generated via numerical simulations for surrogate model training and parametric analysis. The results demonstrate that the Bayesian-optimized FC-FNN model exhibits high predictive accuracy for the core reactor performance metrics, achieving coefficients of determination (R²) above 0.960 for CH₄ conversion, CO₂ conversion, energy efficiency, and the H₂/CO molar ratio. Subsequently, an unknown-constrained alternating Bayesian optimization (UCA-BO) algorithm is adopted to maximize the average reactant conversion under the constraints of H₂/CO molar ratio ≥ 0.9 and bed-temperature non-uniformity ≤ 5%. Under the optimized operating conditions, the average reactant conversion reaches 94.12%, accompanied by a H₂/CO molar ratio of 0.98, a bed-temperature non-uniformity of 4.53%, and a system energy efficiency of 74.83%. Posterior verification with the trained surrogate model gives slightly lower values (91.28%, 0.91, 4.86%, and 72.36%), all of which remain within the imposed constraints, confirming feasibility. Overall, the proposed integrated framework of numerical simulation, surrogate modeling, and Bayesian optimization enables efficient parameter screening and comprehensive performance optimization of resistively heated porous-media DRM systems, providing a methodological basis for the structural design and operating-parameter optimization of related reactor systems.

Optical‐based additive manufacturing offers a promising approach for the precise fabrication of monolithic carbon electrodes with complex geometries. However, the conventional fabrication process, which involves three sequential steps—3D printing, pyrolysis, and chemical activation—is both time‐intensive and technically challenging. In this study, a photosensitive resin incorporating K ₂ CO ₃ as a pore‐forming templates is developed and subsequently photocured into the desired structures via a digital light processing 3D printer. By employing this resin, the chemical activation step is effectively integrated into the pyrolysis process, thereby reducing the overall fabrication procedure from three steps to two. The resulting monolithic carbon structures exhibit hierarchical porosity across four distinct length scales, spanning from the nanometer to the sub‐millimeter range. The electrochemical surface area of the 3D‐printed monolithic carbon electrode is 7.2 times greater than that of the commercial carbon paper. When applied in a vanadium redox flow cell, the monolithic electrodes demonstrate an energy efficiency improvement of 20.7% compared to solid‐wall electrodes and 2.6 times that of the carbon paper electrode.

In this paper, three shear modes of a dual-mode passive shear structure are investigated. Three shear modes of the structure are verified by simulations and experiments. This structure can produce droplets of a wide range of viscosities, with the maximum viscosity exceeding 0.1 Pa·s, and for low-viscosity systems with a shear viscosity less than 0.1 Pa·s, a wider range of droplet sizes can be achieved. The coefficient of variation value of droplet sizes is all less than 8%, and the flow rate ratio of the dispersed phase to the continuous phase can be greater than 1, significantly enhancing the effectiveness of the shearing process. Considering the production flow velocity of the dispersed phase and the viscosity of the droplets, an index number R A ∗ for evaluating the efficient shearing structure by passive shearing structures is proposed. Compared with the single passive shear structure, the dual-mode shear structure has a significantly universality.

Substituting the traditional fuel combustion heating mode in hydrogen production reactors with electric heating demonstrates a significant potential for reducing carbon dioxide emissions. An Ni/Al₂O₃/Ceramic Foam Electric Heating Catalyst was created using a replication template method and a slurry method. On a reactor with dimensions of Φ25 × 800 mm, the differences in the heating rate, axial temperature variance, radial temperature variance, and energy consumption between internal and external heating were analyzed. The results show that: (1) By optimizing the structure of the electric heating wires, the temperature uniformity in the catalyst is enhanced; (2) At 650 °C, 3000 h⁻¹, and S/C = 3, compared to traditional granular catalysts, the internal electric heating reduces the axial temperature variance by 69.4% and the radial temperature variance by 95%; and (3) Achieving a temperature of 650 °C using electric heating only requires 23 min, resulting in a 56.82% reduction in energy consumption compared to external heating.

Excellent coating adhesion is a crucial requirement for monolithic catalysts. Within this investigation, a Design of Experiments (DOEs) Taguchi approach was leveraged to construct a 9-factor-3-level matrix encompassing 27 parallel experiments. This framework was employed to scrutinize the pivotal elements influencing the adhesion of FeCrAl metal-based integral coatings, which were prepared using the slurry method. Moreover, an unprecedented endeavor was made to scrutinize the mechanism of coating delamination from the vantage points of macroscopic slurry, microscopic coatings, and nanoscale interfaces. The findings reveal the following: (1) The inclusion of a high-acidity additive (>5%) emerges as one of the pivotal factors in achieving superior adhesion, particularly when the boehmite content exceeds 1%. (2) The existence of binder-filled interstices within the coating, smaller by 1–2 orders of magnitude than the carrier particles, significantly contributes to heightened adhesion. (3) A bonding region of approximately 5 nm is present at the interfaces between carrier particles, resulting in augmented adhesion.

An additive manufacturing method (digital light procession) is proposed to fabricate carbon-based monolithic catalysts and is applied to nitrobenzene (NB) hydrogenation in a packed-bed micro-reactor. The geometric model of the integrated catalyst is gyroid, a triply periodic minimal surface structure without a dead zone and a large surface area. Compared with particle catalysts, monolithic catalysts have higher porosity and regular pore structure, which can achieve better conversion and selectivity in hydrogenation reactions at high flow rates. The flow characteristics of the monolithic catalyst in the packed-bed micro-reactor were compared between gas–liquid upward and gas–liquid downward flow. It was found that, in the reactor with an inner diameter of 12 mm, the downward gas–liquid process exhibits Taylor flow characteristics, while the upward process for gas–liquid shows bubble flow. Both modes exhibit higher activity in the NB hydrogenation reaction compared with that reported in the literature. Under room temperature and pressure, the gas flow rate was 0.6 mL min⁻¹ and the liquid flow rate was 15 mL min⁻¹, and the gas–liquid downward residence time was 0.83 min. The conversion reached 99% and the selectivity was 98.2%. The three-dimensional printed carbon-based monolithic catalyst has a hierarchical porous structure and a large specific surface area, which can effectively enhance organic hydrogenation reactions.