Numerical Optimization of a Divergence-Beam Surface Plasmon Resonance Sensor with CaF2/ZnO/Ag/ZnTe Multilayers for Alpha-Fetoprotein-Associated Refractive Index Sensing

Abstract

This study presents a numerical investigation of a five-layer surface plasmon resonance (SPR) sensor employing a CaF₂/ZnO/Ag/ZnTe configuration, optimized through the transfer matrix method at an excitation wavelength of 633 nm. The primary objective is to numerically maximize angular refractive index (RI) sensitivity relevant to alpha-fetoprotein (AFP)-associated RI sensing. Unlike conventional SPR configurations, the proposed structure employs a sub-conventional silver film thickness of 40 nm combined with a 4 nm ZnTe protective/field-enhancing capping layer and a 6 nm ZnO adhesion layer. A rigorous theoretical analysis shows that, within the ZnO/ZnTe multilayer environment, 40 nm is the optimum Ag thickness that simultaneously minimizes ohmic losses and maximizes radiative coupling efficiency, rather than the conventional 50 nm associated with single-layer configurations. The simulation predicts a maximum angular sensitivity of 575.715°/RIU (RI unit), a figure of merit (FOM) of 125 RIU⁻¹, and a theoretical digitization-limited resolution of 3.55×10⁻¹⁰ RIU (an ideal lower bound under noise-free conditions) using a 3648-pixel charge-coupled device detector with a 12-bit analog to digital converter. The modeled RI range (1.3300–1.3353) corresponds to AFP concentrations of 0–125 ng/mL, following established bulk RI calibration references. A divergence-beam (Powell lens) interrogation system eliminates mechanical scanning by capturing all angles simultaneously. The sensor numerically indicates strong potential for high RI sensitivity in the AFP-relevant range; experimental validation with functionalized surfaces and noise characterization is required to establish real-world performance. 

Received: 17 December 2025 | Revised: 30 June 2026 | Accepted: 19 August 2026

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analyzed in this study.

Author Contribution Statement

Jordan H. Hossea: Conceptualization, Methodology, Software, Writing – original draft, Supervision. Athuman Mfinanga: Validation, Formal analysis, Investigation, Data curation, Writing – review & editing, Visualization. Vitalis Mwinyi: Validation, Formal analysis, Resources, Data curation, Writing – review & editing, Visualization, Project administration.