The growths in e-mobility are the factor that impetus the research in lightweight material with improved mechanical properties, especially strength. The research concentrates on developing a novel metal matrix nano-composite of high-quality AA8011 aluminium alloy reinforced with varying weight percentages of nano-particles of B₄C (0, 0.3, 0.6, 0.9, 1.2 and 1.5 wt%). The high-energy electromagnetic frequency stir casting technique was used to fabricate nano-composite, which enhanced the wetting of matrix and reinforcement. The rupture strength of nano-composite primarily hinges on the structure and formation of nano-composite. The morphology and distribution of nano-particles in metal matrix nano-composites (MMNC) were characterized by using Field Emission Scanning Electron Microscope. The yield strength, yield point, tensile strength, elongation, and reduction of area of MMNC under uniaxial tensile stresses were determined by Universal Testing Machine. The machine learning algorithms automatically characterized the fractured material texture in conjunction with the described techniques. The unique textural information extracted from each fractured sample distinguished the surfaces as agglomeration, brittle and ductile texture. The fractography analysis of MMNCs revealed the transition of composite from cup and cone to cleavage fracture, which ensured the property change of matrix by the addition of nano-reinforced particles.

电动汽车的发展是推动轻质材料研究的因素，这些材料具有改进的机械性能，尤其是强度。_{该研究专注于开发一种新型金属基纳米复合材料，该复合材料由不同重量百分比的 B 4}纳米颗粒增强的高品质 AA8011 铝合金制成。C (0, 0.3, 0.6, 0.9, 1.2 和 1.5 wt%)。采用高能电磁频率搅拌铸造技术制备纳米复合材料，增强了基体和增强体的润湿性。纳米复合材料的断裂强度主要取决于纳米复合材料的结构和形成。利用场发射扫描电子显微镜对金属基纳米复合材料（MMNC）中纳米粒子的形态和分布进行了表征。MMNC在单轴拉伸应力下的屈服强度、屈服点、抗拉强度、伸长率和断面收缩率由万能试验机测定。机器学习算法结合所描述的技术自动表征断裂材料纹理。从每个断裂样品中提取的独特纹理信息将表面区分为团聚、脆性和延展性纹理。MMNCs的断口分析揭示了复合材料从杯锥向解理断裂的转变，保证了纳米增强颗粒的加入保证了基体的性能变化。