Related papers: ABO3 Perovskites' Formability Prediction and Cryst…
Recent advances in materials informatics have expanded the number of synthesizable materials. However, screening promising candidates, such as semiconductors, based on defect properties remains challenging. This is primarily due to the lack…
Photoelectric conversion efficiency of organic-inorganic perovskite solar cells has been rapidly raised and attracted great attention in recent years. The quality of perovskite films is vital for the performance of devices. We used the…
The great tunability of the properties of halide perovskites presents new opportunities for optoelectronic applications as well as significant challenges associated with exploring combinatorial chemical spaces. In this work, we develop a…
Lead-free chalcogenide perovskites are emerging as game-changers in the race for sustainable, high-performance photovoltaics. These materials offer a perfect trifecta: non-toxic elemental composition, exceptional phase stability, and…
Fueled by the widespread adoption of Machine Learning (ML) and the high-throughput screening of materials, the data-centric approach to materials design has asserted itself as a robust and powerful tool for the in-silico prediction of…
Silver-based chalcohalide anti-perovskites (CAP), Ag$_{3}$BC (B = S, Se; C = Cl, Br, I), represent an emerging family of energy materials with intriguing optoelectronic, vibrational and ionic transport properties. However, the structural…
Novel photovoltaics, such as perovskites and perovskite-inspired materials, have shown great promise due to high efficiency and potentially low manufacturing cost. So far, solar cell R&D has mostly focused on achieving record efficiencies,…
To be able to increase the efficiency of perovskite solar cells which is one of the most substantial challenges ahead in photovoltaic industry, the structural and optical properties of perovskite CH3NH3PbI3-xBrx for values x=1-3 have been…
The inverse design of tailored organic molecules for specific optoelectronic devices of high complexity holds an enormous potential, but has not yet been realized1,2. The complexity and literally infinite diversity of conjugated molecular…
Machine learning has emerged as a potent computational tool for expediting research and development in solid oxide fuel cell electrodes. The effective application of machine learning for performance prediction requires transforming…
The active layer microstructure of organic solar cells is critical to efficiency. By studying the photovoltaic properties of organic solar cell's microstructure, it is possible to increase the efficiency of the solar cell. A graph-based…
Light Management (LM) is essential for metal-halide perovskite solar cells in their race for record performance. In this review, criteria on materials, processes and photonic engineering are established such as to enhance mainly the short…
With remarkable stability and exceptional optoelectronic properties, two-dimensional (2D) halide layered perovskites hold immense promise for revolutionizing photovoltaic technology. Presently, inadequate representations have substantially…
Distinct shortcomings of individual halide perovskites for solar applications, such as restricted range of band gaps, propensity of ABX3 to decompose into AX+BX2, or oxidation of 2ABX3 into A2BX6 have led to the need to consider alloys of…
Despite the promising optoelectronic properties of methylammonium lead iodide (MAPbI3)-based perovskite solar cells (PSCs), their commercial viability is hindered by interfacial energy misalignment, suboptimal light absorption, and thermal…
Machine learning (ML) is widely used to explore crystal materials and predict their properties. However, the training is time-consuming for deep-learning models, and the regression process is a black box that is hard to interpret. Also, the…
Two seemingly similar crystal structures of the low-temperature (~100 K) MAPbX$_3$ (X=I,Br,Cl) perovskites, but with different relative Methylammonium (MA) ordering, have appeared as representatives of this orthorhombic phase.…
Crystal structure prediction is a central problem of theoretical crystallography and materials science, which until mid-2000s was considered intractable. Several methods, based on either energy landscape exploration$^{1,2}$ or, more…
Organic-inorganic hybrid perovskites (OIHPs) have recently emerged as groundbreaking semiconductor materials owing to their remarkable properties. Transmission electron microscopy (TEM), as a very powerful characterization tool, has been…
The complex perovskite Pb2CoTeO6 (PCTO) has been prepared as polycrystalline powders by solid state reaction route, and the crystal structure and magnetic properties have been investigated using a combination of X-ray and neutron powder…