Decoding solute-vacancy binding in transition metals via first-principles and machine learning

Traditional solute-vacancy binding energy (SVBE) models based on atomic radii or electronegativity fail for transition metals. Through first-principles analysis, we show SVBE comprises solute-host bond energy and vacancy relaxation energy. For main-group solutes, both components align with parabolic trends, yielding predictable SVBE. In transition metals, solute-host bond energy remains parabolic, but vacancy relaxation energy shifts its peak due to d-orbital splitting-induced lattice distortion asymmetry, leading to non-parabolic SVBE. This coupling resolves historical discrepancies across alloy systems. A complementary data-driven approach identifies key electronic descriptors. The framework provides a universal principle for solute selection in diffusion-controlled alloy design.

基于原子半径或电负性的传统溶质-空位结合能（solute-vacancy binding energy, SVBE）模型，对于过渡金属体系不再适用。本研究通过第一性原理分析，证明SVBE由溶质-宿主键能与空位弛豫能两部分构成。对于主族溶质而言，上述两个分量均符合抛物线变化趋势，因此SVBE具备可预测性。而在过渡金属体系中，溶质-宿主键能仍保持抛物线特性，但空位弛豫能因d轨道分裂引发的晶格畸变不对称性，其峰值发生偏移，最终导致SVBE呈现非抛物线变化规律。该耦合机制解决了不同合金体系间长期存在的模型偏差问题。本研究辅以数据驱动方法，识别出关键电子描述符。所提出的框架为扩散控制合金设计中的溶质筛选提供了普适性原理。