Exploring the Infiltration Features of Perovskite within Mesoporous Carbon Stack Solar Cells Using Broad Beam Ion Milling

Quantifying Infiltration for Quality Control in Printed Mesoscopic Perovskite Solar Cells: A Microscopic Perspective

Mesoscopic carbon-based perovskite solar cells (CPSCs) are often cited as a potential frontrunner to perovskite commercialization. Infiltration, the extent to which perovskite fills the mesoporous scaffold, is critical for optimum performance and stability. However, infiltration data are usually presented as qualitative photographic comparisons of samples with extreme infiltration variation. This work examines how small infiltration defects impact performance using an optical microscopy examination of the base TiO2 layer to identify issues and develop targeted techniques for infiltration enhancement. Critically, the uninfiltrated area at the base of the stack was found to correlate well with PCE across multiple batches of varied print quality and ZrO2 thickness. Through reduction of mesh mark defects and improvement of print quality in the ZrO2 and carbon layers, a champion PCE of 15.01% is attained. It follows that this facile, multiscaled, nondestructive technique could enable targeted performance enhancement and quality control in future scale-up initiatives.

Methods to expose subsurface objects of interest identified from 3D imaging: The intermediate sample preparation stage in the correlative microscopy workflow

The correlative imaging workflow is a method of combining information and data across modes (e.g. SEM, X-ray CT, FIB-SEM), scales (cm to nm) and dimensions (2D-3D-4D), providing a more holistic interpretation of the research question. Often, subsurface objects of interest (e.g. inclusions, pores, cracks, defects in multilayered samples) are identified from initial exploratory nondestructive 3D tomographic imaging (e.g. X-ray CT, XRM), and those objects need to be studied using additional techniques to obtain, for example, 2D chemical or crystallographic data. Consequently, an intermediate sample preparation step needs to be completed, where a targeted amount of sample surface material is removed, exposing and revealing the object of interest. At present, there is not one singular technique for removing varied thicknesses at high resolution and on a range of scales from cm to nm. Here, we review the manual and automated options currently available for targeted sample material removal, with a focus on those methods which are readily accessible in most laboratories. We summarise the approaches for manual grinding and polishing, automated grinding and polishing, microtome/ultramicrotome, and broad-beam ion milling (BBIM), with further review of other more specialist techniques including serial block face electron microscopy (SBF-SEM), and ion milling and laser approaches such as FIB-SEM, Xe plasma FIB-SEM, and femtosecond laser/LaserFIB. We also address factors which may influence the decision on a particular technique, including the composition, shape and size of the samples, sample mounting limitations, the amount of surface material to be removed, the accuracy and/or resolution of peripheral parts, the accuracy and/or resolution of the technique/instrumentation, and other more general factors such as accessibility to instrumentation, costs, and the time taken for experimentation. It is hoped that this study will provide researchers with a range of options for removal of specific amounts of sample surface material to reach subsurface objects of interest in both correlative and non-correlative workflows.