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Understanding the formation of lead halide (LH) perovskite solution precursors is crucial to gain insight into the evolution of these materials to thin films for solar cells. Using density-functional theory in conjunction with the…

Perovskite photovoltaics (PV) have achieved rapid development in the past decade in terms of power conversion efficiency of small-area lab-scale devices; however, successful commercialization still requires further development of low-cost,…

Machine Learning (ML) techniques are revolutionizing the way to perform efficient materials modeling. Nevertheless, not all the ML approaches allow for the understanding of microscopic mechanisms at play in different phenomena. To address…

Discovering new materials that efficiently catalyze the oxygen reduction and evolution reactions is critical for facilitating the widespread adoption of solid oxide fuel cell and electrolyzer (SOFC/SOEC) technologies. Here, we develop…

We demonstrate a machine learning (ML) approach that accurately predicts the current-voltage behavior of 3D/2D-structured (FAMA)Pb(IBr)3/OABr hybrid organic-inorganic halide perovskite (HOIP) solar cells under AM1.5 illumination. Our neural…

Machine learning (ML) is increasingly becoming a helpful tool in the search for novel functional compounds. Here we use classification via random forests to predict the stability of half-Heusler (HH) compounds, using only experimentally…

Recent developments in materials informatics and artificial intelligence has led to the emergence of foundational energy models for material chemistry, as represented by the suite of MACE-based foundation models, bringing a significant…

Lead-halide perovskites (LHPs) have shot to prominence as efficient energy conversion materials that can be processed using cost-effective fabrication methods. A widely-quoted reason for their exceptional performance is their ability to…

Halide perovskites make efficient solar cells due to their exceptional optoelectronic properties, but suffer from several stability issues. The characterization of the degradation processes is challenging because of the limitations in the…

We present a machine learning framework for predicting the structural dimensionality of hybrid metal halides (HMHs), including organic-inorganic perovskites, using a combination of chemically-informed feature engineering and advanced…

Hybrid organic-inorganic perovskites are exceedingly interesting candidates for new solar energy technologies, for both ground-based and space applications. However, their large-scale production is hampered by the lack of long-term…

A key challenge for the practical application of metal halide perovskites (MHPs) is the instability of the desired perovskite phase relative to the optically non-active $\delta$ phase. To determine the phase stability, we previously…

Stability is one of the key issues in mixed-halide perovskite alloys which are promising in emergent optoelectronics. Previous density-functional-theory (DFT) and machine learning studies indicate that the formation-energy convex hulls of…

Among emerging energy materials, halide and chalcogenide perovskites have garnered significant attention over the last decade owing to the abundance of their constituent species, low manufacturing costs, and their highly tunable…

Hybrid perovskite solar cells, with their power conversion efficiency (PCE) exceeding 22%, have been representing a revolutionary concept for future energy power generation. Although listed among the Top 10 Emerging Technologies of 2016,…

Mixing iodide and bromide in halide perovskite semiconductors is an effective strategy to tune their bandgap, therefore mixed-halide perovskites hold great promise for color-tunable LEDs and tandem solar cells. However, the bandgap of…

We describe a first open-access database of experimentally investigated hybrid organic-inorganic materials with two-dimensional (2D) perovskite-like crystal structure. The database includes 515 compounds, containing 180 different organic…

Metal halide perovskites (MHPs) have become a promising candidate in a myriad of applications, such as light-emitting diodes, solar cells, lasing, photodetectors, photocatalysis, transistors, etc. This is related to the synergy of their…

Perovskite solar cells (PSCs) are attracting great attention as the most promising candidate for the next generation solar cells. This is due to their low cost and high power conversion efficiency in spite of their relatively short period…

The organic-inorganic hybrid perovskite CH3NH3PbI3 has attracted significant interest for its high performance in converting solar light into electrical power with an efficiency exceeding 20%. Unfortunately, chemical stability is one major…