The dry reforming of methane (DRM) offers a promising route for the simultaneous valorisation of CH4 and CO2 into syngas. However, practical implementation of Ni-based catalysts remains limited by carbon deposition and the restricted availability of catalytically active metallic Ni species. In this study, the effect of controlled strontium (Sr) promotion (1-3 wt.%) on a catalyst containing a fixed Ni loading of 5 wt.% supported on a MgOZrO2 mixed-oxide (MSZ) was systematically investigated to elucidate the role of Sr in modifying surface basicity and coke formation behaviour. Structural analysis revealed that Sr incorporation did not alter the bulk crystalline phases or porosity of the MSZ support. However, Sr significantly influenced the surface chemical properties of the catalyst, enhancing basicity and altering Ni reducibility at moderate loadings. The catalytic evaluation under DRM conditions at 700 degrees C (CH4/CO2/N2 = 3:3:1 and gas hourly space velocity (GHSV) = 42,000 mL g-1h-1) revealed that the catalyst with 1 wt.% Sr loading (5Ni-1Sr/MSZ) exhibited the most favourable performance, achieving 55.7% H2 yield, 68.3% CO yield and an H2/CO ratio of 0.83. Moreover, Sr promotion significantly improved resistance to carbon deposition compared to the unpromoted catalyst. Response surface methodology (RSM) applied to the optimal 5Ni-1Sr/MSZ catalyst identified a broad operating window with enhanced H2 yield, demonstrating the robustness of the optimized catalyst beyond single-point reaction conditions. These results highlight the beneficial role of Sr promotion in improving catalyst stability for DRM applications.
A computational fluid dynamics (CFD) model was developed and validated against experiments for a laboratory-scale 5-L bioreactor. Numerical simulation was performed to describe the bioreaction of Streptomyces atratus SCSIO ZH16 fermentation for ilamycin E production with the dynamic changes in viscosity of the fermentation broth due to biomass growth and decay. This model can account for the two-way coupling between the fermentation environment and medium, which enabled the analysis of the relationship between the broth viscosity, flow field, mass transfer, and macroscopic fermentation performance. This work represents the first integration of Streptomyces fermentation with CFD, enabling the simulation of flow field and mass transfer under varying stirring speed, aeration rate, and viscosity during Streptomyces fermentation. A suggested favorable range of fermentation broth viscosity (10–30 mPa s) was identified for ilamycin E production by S. atratus SCSIO ZH16 fermentation. Furthermore, the addition of sorbitol was used to adjust the viscosity of the fermentation broth in the later stages of fermentation. Experimental evidence, including elevated OUR/CER and up-regulated respiratory-chain gene transcription, suggested that the yield improvement was primarily associated with enhanced oxygen transfer resulting from reduced broth viscosity. This research offers a practical strategy for the process intensification and industrial scale-up for such bioreactors.
Compressed Sensing Magnetic Resonance Imaging (CS-MRI) enables the reconstruction of MR images from undersampled k-space data, thus accelerating the imaging process. However, most existing methods require training separate models for different sampling rates, resulting in low computational efficiency and limited generalization. To address this limitation, we propose DT-Net, a novel network that integrates Dynamic Prompts and Transformers for unified CS-MRI reconstruction across various sampling rates. Once trained, DT-Net can handle multiple sampling scenarios without the need for retraining. DT-Net comprises two key components: the Dynamic Prompt Module (DPM) and the Efficient Transformer-based Proximal Mapping Module (ETPM). The designed DPM dynamically generates degradation-aware prompts input features, enabling the model to adaptively recover images under varying degradation levels. The ETPM integrates a Dual-domain Feature Extraction Module (DFEM) and a High-efficiency Transformer Module (HTM) to jointly extract spatial and frequency domain features while enhancing long-range dependencies, thereby reducing information loss and improving reconstruction quality. Extensive experiments on the public IXI and FastMRI datasets demonstrate that DT-Net consistently outperforms state-of-the-art methods in both quantitative metrics and visual fidelity.
A graph is called F-free if it does not contain a copy of F. Let G(r,s) denote a K_r+1-free graph of order n with chromatic number at least s that maximizes the spectral radius. Nikiforov [Linear Algebra Appl., 2007] proved the spectral Turán theorem, which implies that G(r,s) is the r-partite Turán graph T_n,r for s≤ r. Lin, Ning, and Wu [Combin. Probab. Comput., 2021] characterized the unique spectral extremal graph G(2,3). This result was later extended by Li and Peng [SIAM J. Discrete Math., 2023] to all s=r+1≥ 3. In this paper, we push the characterization further by determining the unique extremal graph G(2,4) for all sufficiently large n. Specifically, we show that G(2,4) is precisely a blow-up of the Grötzsch graph. Interestingly, under the same conditions, G(2,4) also coincides with the unique edge-extremal graph identified by Ren, Wang, Wang, and Yang [arXiv:2404.07486v2].
This study investigates thermal plasma-assisted pyro-gasification as an intensified allothermal route for converting biomass-derived bio-oil and representative oxygenated compounds into H2- and CO-rich syngas. An integrated experimental–numerical framework combined bio-oil fractionation, model-oil formulation, gasification tests, optical shadowgraphy, and supporting plasma-droplet calculations. Gas-phase tests using methane, acetic acid, and ethanol showed that H2 and CO dominated the permanent gas and that conversion increased with plasma specific enthalpy and the dimensionless specific-enthalpy ratio. Shadowgraphy identified rapid comb-type primary jet breakup followed by stripping or tear-off secondary fragmentation. The numerical framework is defined as a steady, two-dimensional axisymmetric Eulerian-Lagrangian model employing temperature-dependent properties, RNG k-ε turbulence, an optically thin LTE plasma representation, and Kelvin-Helmholtz WAVE breakup. Quantitative comparisons gave experimental/simulated Sauter mean diameters of 110/121 μm after optical-cutoff correction and thermocouple temperature-rise deviations of 7.4–18.5%. The combined evidence indicates that intrinsic kinetics were not the sole limitation under the tested gas-phase conditions; plasma-reactant contact, energy transfer, effective exposure time, injection geometry, and liquid heat/mass transfer were also decisive.
