The monolithic integration of perovskite top cells on textured crystalline silicon affords efficient tandem devices with strong prospects for large-scale applications. Such integration has primarily relied on state-of-the-art recombination junctions, which typically comprise transparent conductive oxides and molecular self-assembled monolayer (SAM) contacts. However, the potential influence of bottom cell nanoroughness, which may vary based on specific processing routes and technologies, has received far less attention. Here, we systematically engineered the top surface nanoroughness of silicon heterojunction solar cells to examine its impact on monolithic perovskite–silicon tandem solar cells. We employed two approaches: (i) varying the thickness of (n)-type hydrogenated nanocrystalline silicon ((n)nc-Si:H) layers or (ii) applying a plasma treatment using a hydrogen and carbon dioxide gas mixture before the deposition of (n)nc-Si:H layers. Both methods enhanced the conductivity and crystallinity of (n)nc-Si:H layers and increased the surface nanoroughness, with plasma treatment enabling the efficient realization of distinct nanoroughness in thin (n)nc-Si:H (15-nm-thick) layers. Our results reveal that the surface nanoroughness imposed by (n)nc-Si:H layers influences the SAM anchoring, leading to increased work function shifts and improved SAM/perovskite interface quality, thereby impacting the overall tandem device performance. Notably, tandem devices incorporating higher-nanoroughness bottom cells achieved increased fill factors, dominating the observed tandem efficiency enhancements, with a peak efficiency of 32.6% enabled by a 30-second-long plasma treatment.

The aerodynamic pressure load on the aircraft is vital for structural design and safety evaluation. A new method capable of identifying the pressure load on the complex surface of a three-dimensional structure is proposed. To achieve this goal, the pressure load identification technique based on subregion interpolation, which is theoretically suitable for identifying the distributed load on flat surface with arbitrary shape, will be combined with the surface fattening technique. A transfer matrix describing the relationship between pressure load on the subregion of three-dimensional structural surface and structural strain data at local measurement points is constructed, and then the pressure load on the whole surface can be identified from the strain data via a simple matrix inversion procedure. A numerical example of the pressure load identification on a curve panel is firstly used to verified the proposed method. Different noise levels in structural response, sensor placement schemes and regularization methods which may affect the accuracy of the proposed method are further investigated. Finally, the proposed method is applied on the aerodynamic pressure load identification of a 3D wing structure, which aims to demonstrate the applicability of the proposed method on real three-dimensional structures.