The advancement of spintronic technology depends on the efficient generation and control of spin-polarized currents. However, traditional approaches relying on magnetic materials are susceptible to external magnetic interference, thereby limiting their practical applications. Andreev reflection spectroscopy has emerged as a powerful tool for detecting material-specific properties such as spin polarization (P) and superconducting gap (∆), but its theoretical basis is usually based on simplified models that assume isotropic interface scattering. In this assumption, the ubiquitous spin-dependent anisotropic scattering observed in real-world interfaces is neglected, which can lead to significant misinterpretations of intrinsic material characteristics. To solve this problem, our study develops a comprehensive theoretical framework that combines anisotropic spin scattering effects, thereby enabling a systematic investigation of how interface anisotropy modulates Andreev reflection spectra. This study aims to resolve the precision issues in the characterization of spin-polarized materials, particularly for emerging quantum systems such as topological insulators, where accurate measurement of spin polarization is crucial but challenging.

Methodologically, we employ the basic Blonder-Tinkham-Klapwijk (BTK) model and its extension by Chen-Tesanovic-Chien (CTC) by introducing spin-dependent scattering parameters Z_↑ and Z_↓ to describe the different interface scattering intensities for spin-up and spin-down electrons, thereby enabling the construction of a unified theoretical model applicable to a wide range of interface systems, from normal metals (P = 0) to half-metals (P = ±1). We conduct the detailed numerical calculations and three-dimensional image analysis to simulate the differential conductance spectra under varying conditions of spin polarization and interface anisotropy. Specifically, the model accounts for the probability amplitudes of Andreev reflection and normal reflection by solving the Bogoliubov-de Gennes equations with generalized boundary conditions. The current formulae are derived by integrating over energy-dependent transmission probabilities, incorporating a judgment function to realistically handle dominant spin channels.

Our key results reveal several important physical insights. For non-magnetic metals (P = 0), interface anisotropic scattering (e.g., Z_↑ ≠ Z_↓) can induce highly spin-polarized currents through a transmission spin polarization mechanism. This is demonstrated by the suppression of Andreev reflection and the decrease in normalized differential conductance within the superconducting gaps (e.g., decreasing from 2 to 0 as Z_↑ increases while Z_↓ is fixed). This effect is sensitive even to small values of Z (around 0.25–0.5), highlighting the importance of precise interface engineering. For magnetic materials with positive spin polarization (P > 0), such as those with P = 0.25, anisotropy at the interface non-linearly modulates the current polarization. For instance, when Z_↓ is fixed at 0.5, increasing it initially enhances Andreev reflection due to balanced spin transmission but suppresses it beyond a critical point, illustrating the tunability of polarization rates. Conversely, for negatively polarized materials (P < 0), the spectra exhibit different features, such as the absence of peaks under certain conditions, enabling a novel method to determine the sign of P by comparing differential conductance behaviors. Experimental validation using pure Co films shows close agreement with our model, confirming both its accuracy and the presence of minor anisotropy in typical magnetic interfaces.

In summary, this theoretical framework not only deepens the understanding of Andreev reflection spectra by considering anisotropic scattering, but also provides practical tools for characterizing quantum materials and designing spintronic devices. Furthermore, this study provides a new approach for developing ant-interference spin sources based on non-magnetic materials and optimizes interface engineering in magnetoresistance devices. Future work will focus on experimental extension to low-dimensional systems and algorithmic improvement for parameter analysis, so as to further bridge the gap between theory and application in quantum information science.