ReviewFrontiers in chemistry2024
Computational applications for the discovery of novel antiperovskites and chalcogenide perovskites: a review.
Review in Frontiers in chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
5 authors.
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Abstract
Novel perovskites pertain to newly discovered or less studied variants of the conventional perovskite structure, characterized by distinctive properties and potential for diverse applications such as ferroelectric, optoelectronic, and thermoelectric uses. In recent years, advancements in computational methods have markedly expedited the discovery and design of innovative perovskite materials, leading to numerous pertinent reports. However, there are few reviews that thoroughly elaborate the role of computational methods in studying novel perovskites, particularly for state-of-the-art perovskite categories. This review delves into the computational discovery of novel perovskite materials, with a particular focus on antiperovskites and chalcogenide perovskites. We begin with a discussion on the computational methods applied to evaluate the stability and electronic structure of materials. Next, we highlight how these methods expedite the discovery process, demonstrating how rational simulations contribute to researching novel perovskites with improved performance. Finally, we thoroughly discuss the remaining challenges and future outlooks in this research domain to encourage further investigation. We believe that this review will be highly beneficial both for newcomers to the field and for experienced researchers in computational science who are shifting their focus to novel perovskites.
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