Concurrent optimization of fracture toughness, thermal conductivity, and tribological behavior in Cf/Si3N4 composites via phase driven selection Saeed Hoseinzadeh, Mohammad Reza Loghman Estarki, Ali Ghasemi, Saeed Zahabi, Gholamreza Gordani, Ehsan Mohammad Sharifi Scientific Reports, 2026 Carbon fiber–reinforced silicon nitride (C f /Si 3 N 4 ) composites were fabricated by spark plasma sintering (SPS) using α-, β-, and γ-Si 3 N 4 powders to clarify the influence of the initial Si 3 N 4 phase on microstructural evolution and functional properties. The results show that the starting phase significantly affects densification behavior, phase transformation, and mechanical and tribological performance. The composite derived from α-Si 3 N 4 achieved the highest relative density (96.53%) and exhibited an optimal balance of fracture toughness (10.87 MPa m 0.5 ), thermal conductivity (66 W/m K), and stable friction behavior (COF ≈ 0.46). This performance is attributed to the in-situ formation of a self-reinforced β-Si 3 N 4 microstructure during the α → β phase transformation, which promotes crack deflection, crack bridging, and effective load transfer in synergy with carbon fibers. In contrast, β- and γ-Si 3 N 4 –based composites showed lower densification or excessive hardness associated with increased porosity and secondary phase formation. These findings demonstrate that controlling the initial Si 3 N 4 phase provides an effective microstructural design strategy for developing high-performance C f /Si 3 N 4 composites for thermostructural applications such as aerospace brake discs.
Improving resilience of networked multi-energy carrier microgrids through proactive scheduling Ali Akbar Ghasemi, Mohsen Gitizadeh, Mohammadali Norouzi International Journal of Electrical Power and Energy Systems, 2025 The interdependence of various energy carriers within networked multi-energy carrier microgrids (NMECMs) enhances resilience against high-impact low-probability (HILP) events. However, these interdependences can also increase vulnerability to disruptions. This paper introduces a proactive scheduling model designed to bolster NMECM resilience during sudden outages in upstream gas and electricity networks. The proposed method adjusts microgrid scheduling to secure feasible islanding, maximize preparedness, and minimize operating costs and load shedding. The optimization problem is modeled as a two-stage mixed-integer linear programming. In the first stage, scheduling of the microgrids is programmed in normal mode. In the second stage, the schedule of the microgrids is modeled in the mode of disconnection from both the gas and electricity networks. Furthermore, to consider both normal and contingency uncertainties, stochastic and deterministic models of proactive resilient scheduling for the NMECMs are presented. Moreover, the benefits of responsive electrical and heat loads are considered. Finally, by performing simulations, the efficiency of the proposed method in improving the resilience of the test NMECMs is evaluated. Numerical results demonstrate the superior performance of the proposed model over the other scheduling models. In particular, the unpreparedness index of the proposed stochastic proactive scheduling model reduces by 68% compared with the normal scheduling, while ensuring uninterrupted power supply to critical electrical and heat loads even in islanding conditions.
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