The preparation of highly conductive media and the construction of conducting channels play a crucial role in improving the electrical conductivity of electrically conductive adhesives. Therefore, a new MXene structure is reported in this paper, and the improved structure is rationally designed by computational modeling, which greatly prevents the buildup of MXene nanosheets, improves the stability of the structure, and creates a wide electron transfer channel, and the capacitance contribution of this structure is up to 86.3%. By mixing MXene modified with Ag-plated copper powder in a quantitative relationship to form high conductive media, the electrical conductivity is largely improved and the defect of low electron transfer rate of conventional conductive fillers is broken. The potential value of high conductive media is largely exploited using high throughput and machine learning methods, and here we show that the resistivity has reached 9.668 × 10-7 Ω m. The first principles investigate the conductive channels and electron transfer pathways of high-conductive media at the atomic level, further revealing the mechanism of action of high-conductive media. This study is also the first report on the application of MXene to high-conductive media.
Keywords: composites; conducting channels; high conductive media; machine learning; mxene.
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