High performance electromagnetic (EM) interference shielding composites are of high demand due to increasing EM wave radiation pollution. In this work, GO/NiNCs/PMMA microcellular foams with different GO/NiNCs gradient and 3D conductive filler framework were fabricated by thermal reduction and supercritical CO 2 foaming process. With the crosslink of 1D NiNCs and 2D GO sheets, GO/NiNCs framework with electrical conductivity varied from 1.15 Â 10 À4 to highest 1.09 Â 10 À1 S/m is fabricated, exhibiting absorptiondominated electromagnetic interference shieling effectiveness (EMI SE) of 53.62 dB and specific EMI SE of 48.44 dB g À1 cm 3 in X-band. The density of GO/NiNCs/PMMA microcellular foams achieved lowest value of 0.623 g/cm 3 . Moreover, the foams showed excellent thermal conductivity and compressive strength of 178.76 MPa, indicating excellent application potential in aerospace and electronic field. The thermoplastic polymer matrix also indicates great potential in recycle of the foam material.

Offshore pipelines are hailed as the “lifeline” of an offshore oil and gas production system and are essential for offshore oil and gas development. Component tracing technologies for the oil and gas multiphase transmission pipeline networks need to be urgently developed to predict the fluid composition changes in pipeline networks. Instead of assuming the fluid components are constant, we consider they varied with flow. The component conservation equations and a phase change model are established. The equation of state of the fluid is adopted to determine the equilibrium state of each component in real time. Considering the macroscopic flow calculation, microscopic fluid components, and phase equilibrium, the component tracking algorithm is established for natural gas condensate pipeline networks, which can dynamically track the fluid composition in pipeline networks and calculate the phase exchange amount and related flow parameters in real time. Three case studies are performed to verify the effectiveness of the algorithm. These findings are of great practical significance for understanding the gas–liquid two-phase flow in pipeline networks, promoting further engineering applications of component tracking on pipeline networks.