The low-dimensional (LD) perovskites are proven to be capable of blocking moisture erosion and thereby improving the photovoltaic device stability. In this review, the low-dimensional (LD) perovskite materials are carefully summarized that are induced by A-position organic substituents, starting from the crystal microstructure and electronic structure of LD (2D, 1D, and 0D) perovskite materials with regulating dimensions, combined with first principles calculation (DFT). By further studying the thermodynamics and dynamics of crystallization nucleation and growth of LD-3D perovskite thin films in the heterojunction region, LD-3D heterojunction perovskite thin films and solar cells with controllable dimensions can be in situ prepared. Various LD-3D perovskite structure photovoltaic devices are systematically summarized, which shows flexible regulation of the energy band structure and carrier transport characteristics, locks the water oxygen corrosion channel with close-fitting conjugated structure, and improves the long-term stability of the LD-3D perovskite solar cells. This review is expected to provide some guidance for the perovskite development and multipurpose use through in depth understanding of the structurally dimensional engineering in perovskite photovoltaics.

Despite inorganic CsPbI3−xBrx perovskite solar cells (PSCs) being promising in thermal stability, the perovskite degradation and severe nonradiative recombination at the interface hamper their further development. Herein, the typical MXene material, that is, Ti3C2Tx, is employed to be the buried interface prior to the perovskite absorber layer in the device, which multi‐functionalizes the as‐prepared electron‐transfer layers by means of both fascinating preferential crystallization of perovskite and/or accelerating the charge extraction with respect to an ideal energy‐level alignment and suppressed trap states. Accordingly, the power conversion efficiency of the modified PSC device is substantially enhanced by as high as 19.56% in comparison to their counterparts with only the pristine CsPbI3−xBrx active layer. More importantly, MXene modification is favorable to improve the wettability of perovskite precursor solution with enhanced grain size and crystallinity, thereby increasing the UV long‐term stability of solar cells. This work provides a new paradigm toward alleviating the severe nonradiative recombination at the interface in the device whilst enhancing the long‐term stability via the preferential crystallization process.

Low-dimensional perovskites (LDPs) have enormous potential for the development of advanced optoelectronic devices and tackling the stability issue for the commercial application of perovskites. However, quantified structural dimensionality prediction for LDPs is still an intractable issue. Herein, we develop a self-established machine learning (ML)-assisted approach to predict the dimensionality of LDPs based on 195 reported amines that are classified as two-dimensional, one-dimensional, and zero-dimensional. The optimal K-nearest neighbor model allows us to realize an accuracy rate of 92.3% for the test data set containing 39 reported amines. Two features, i.e., ATSC1pe and SlogP_VSA2, associated with polarity and electrostatic potential on the van der Waals surface of an organic spacer, are identified from >1800 descriptors as key controlling factors determining the structure dimensionality. This work develops a typical paradigm for the application of a multiple-classification strategy of ML with an extremely high accuracy rate, which would thereby motivate the development of new types of LDPs.