The remarkable rise of metal halide perovskite photovoltaics and optoelectronics has revealed semiconductive polarity as a central yet insufficiently understood determinant of device performance and stability. The soft ionic-covalent lattice of halide perovskites hosts highly mobile ions and low-formation-energy defects that spontaneously self-dope and dynamically shift the Fermi level. This unique defect-lattice interplay profoundly affects band alignment, quasi-Fermi-level splitting, interfacial recombination, and ultimately the attainable open-circuit voltage. In this review, we establish a hierarchical framework for polarity regulation spanning bulk defect thermodynamics, compositional tuning, additive coordination chemistry, and interfacial electronic design. We first elucidate how lattice geometry, orbital hybridization, and intrinsic defect equilibria dictate bulk carrier density and Fermi-level position. We then discuss how targeted A/B/X-site substitution, alloying strategies, and stoichiometric control modulate defect landscapes and stabilize desired electronic character. Based on these principles, we highlight how interfacial polarity engineering, including charge-transfer interlayers and selective-contact design, enables continuity of quasi-Fermi levels and minimizes nonradiative losses at both p- and n-type contacts. These insights unify defect physics and interfacial electrostatics, guiding polarity-balanced, defect-regulated perovskite optoelectronics, and highlighting opportunities in electrostatic modulation, heterovalent doping, surface reconstruction, and polarity engineering for perovskite solar cells.
Metal halide perovskite solar cells have been developed as a front runner in next generation photovoltaic technology. However, such rapid development is hampered by complex relationships among material compositions, process routes, device architectures, and environmental conditions. The fabrication system is strongly coupled with many variables, which implies that existing empirical optimization methods are less capable to explore design space in high dimensions. Additionally, perovskite materials have sensitive intrinsic properties to environmental factors hence facilitating reproducible optimization across the composition space is notoriously difficult. Now, in this coupled system, artificial intelligence and machine learning have driven progress toward the understanding of the nonlinear composition–process–property relationships. But their predictive reliability is limited by patchy data and low reproducibility in manual experiments. Therefore, controlling lab environments and generating reproducible data with help from autonomous laboratories is paramount to accelerate predictive design. This review highlights recent progress in data driven materials discovery and closed loop experiments in perovskite research. We also report that AI guided process optimization is capable of identifying reproducible manufacturing windows. In parallel, robotic manipulation, high throughput synthesis with in situ monitoring and autonomous characterization are enabling systematic exploration of the multi-dimensional process space.
Despite the high stability of 2D perovskites, high-efficiency perovskite solar cells (PSCs) have predominantly been fabricated using pure 3D perovskites as the light-absorbing layer. Introducing 2D perovskites into the 3D perovskite bulk typically leads to the formation of insulating spacer layers between conductive inorganic slabs, limiting the conductivity and charge transport of the 3D perovskite, thereby reducing device efficiency. This study demonstrates that these disadvantages associated with introducing 2D perovskites can be eliminated by tilting the 2D perovskite orientation. The thermodynamically stable tilted 2D perovskite orientation enhances the conductivity of 3D perovskites, improves film uniformity, and reduces defect concentration through grain boundary passivation. Additionally, the method used to induce this tilted 2D perovskite orientation does not influence the crystallization process of the highly optimized 3D perovskite. As a result, the best-performing PSCs exhibit an efficiency of 26.6% (certified efficiency of 26.3%) under simulated solar illumination. Furthermore, encapsulated devices retain ≈90% of their initial efficiency even after 1100 h of operation under maximum power point tracking. These findings provide critical insights into overcoming the inherent limitations of conventional 2D perovskites, offering a pathway toward high-efficiency and stable PSCs.
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