QUANTUM-ENHANCED CHARGE TRANSPORT MODELING IN PEROVSKITE SOLAR CELLS USING NON-EQUILIBRIUM GREEN’S FUNCTION (NEGF) FRAMEWORK

Abstract

Perovskite solar cells (PSCs) can reach high efficiencies, yet semiclassical modeling can under-resolve transport losses at interfaces and contacts, limiting mechanism-level diagnosis. This study tested whether NEGF-parameterized transport factors explain cross-case variation in PSC performance and whether experts perceive the framework as credible and usable. A quantitative, cross-sectional, case-study–based design analyzed 12 modeled PSC cases and an expert survey (n = 42). Predictors were trap density (X1), interface barrier height (X2), scattering index (X3), and contact coupling (X4); outcomes were Jsc, Voc, FF, and PCE. Analyses comprised descriptives, Pearson correlations, multiple regression predicting PCE, and survey reliability plus one-sample tests against the neutral midpoint. Case outputs ranged from Jsc 19.8–25.4 mA·cm⁻² and PCE 11.7–21.8%. Trap density was negatively associated with PCE (r = −0.76, p = 0.004), barrier height was negatively associated with Jsc (r = −0.79, p = 0.002), and contact coupling was positively associated with PCE (r = +0.69, p = 0.014). The multivariate PCE model was significant (R² = 0.861, F(4,7) = 10.86, p = 0.004), with trap density (β = −0.46, p = 0.018), barrier height (β = −0.39, p = 0.031), scattering (β = −0.28, p = 0.044), and coupling (β = +0.33, p = 0.027). Experts rated the approach positively (Accuracy M = 4.12, α = 0.87; Usefulness M = 4.28, α = 0.90; p < 0.001). These findings imply NEGF can function as a decision-support layer for interface and contact engineering, and should be deployed in auditable compute pipelines for enterprise or cloud/HPC execution.