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Related papers: ABO3 Perovskites' Formability Prediction and Cryst…

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Deposition of perovskite thin films by antisolvent engineering is one of the most common methods employed in perovskite photovoltaics research. Herein, we report on a general method that allows the fabrication of highly efficient perovskite…

Determining the stability of chemical compounds is essential for advancing material discovery. In this study, we introduce a novel deep neural network model designed to predict a crystal's formation energy, which identifies its stability…

Materials Science · Physics 2026-04-21 V. Torlao , E. A. Fajardo

Hybrid organic inorganic formate perovskites, AB(HCOO)$_3$, is a large family of compounds which exhibit variety of phase transitions and diverse properties. Some examples include (anti)ferroelectricity, ferroelasticity,…

Perovskite solar cells have drawn much attention in recent years, owing to its world-record setting photovoltaic performances. Despite its promising use in tandem applications and flexible devices, its practicality is still limited by its…

Third-generation photovoltaic (PV) materials combine many advantageous properties, including a high optical absorption together with a large charge carrier mobility, facilitated by small effective masses. Halide perovskites (ABX3, where X…

Photovoltaics (PV) are widely used to harvest solar energy, an important form of renewable energy. Photovoltaic arrays consist of multiple solar panels constructed from solar cells. Solar cells in the field are vulnerable to various…

Applications · Statistics 2024-08-13 Xinyi Song , Kennedy Odongo , Francis G. Pascual , Yili Hong

Materials property predictions have improved from advances in machine learning algorithms, delivering materials discoveries and novel insights through data-driven models of structure-property relationships. Nearly all available models rely…

Materials Science · Physics 2022-04-13 Yiqun Wang , Xiao-Jie Zhang , Fei Xia , Elsa A. Olivetti , Ram Seshadri , James M. Rondinelli

It is well known that if a crystal structure has no inversion symmetry, it may allow for Dzyaloshinskii-Moriya magnetic interactions, operating between different crystallographic unit cells, which in turn should lead to the formation of…

Materials Science · Physics 2012-03-19 I. V. Solovyev

A novel stable crystallographic structure is discovered in a variety of ABO3, ABF3 and A2O3 compounds (including materials of geological relevance, prototypes of multiferroics, exhibiting strong spin-orbit effects, etc...), via the use of…

Materials Science · Physics 2015-01-20 Changsong Xu , Bin Xu , Yurong Yang , Huafeng Dong , A. R. Oganov , Shanying Wang , Wenhui Duan , Binglin Gu , L. Bellaiche

In this study, we present a novel approach along with the needed computational strategies for efficient and scalable feature engineering of the crystal structure in compounds of different chemical compositions. This approach utilizes a…

Materials Science · Physics 2021-05-25 Prathik R. Kaundinya , Kamal Choudhary , Surya R. Kalidindi

Hybrid organic-inorganic halide perovskites for photovoltaics have attracted research interest due to their unique material properties, but suffered from poor material stability. In this work, we investigated the surface phase diagrams of…

Applied Physics · Physics 2021-09-30 Yun-Sim Kim , Chol-Hyok Ri , Yun-Hyok Kye , Un-Gi Jong , Chol-Jun Yu

Owing to their high energy-conversion efficiency and inexpensive fabrication routes, solar cells based on metal-organic halide perovskites have rapidly gained prominence as a disruptive technology. An attractive feature of perovskite…

Materials Science · Physics 2015-02-17 Marina R. Filip , Giles E. Eperon , Henry J. Snaith , Feliciano Giustino

Predicting the stability of the perovskite structure remains a longstanding challenge for the discovery of new functional materials for many applications including photovoltaics and electrocatalysts. We developed an accurate, physically…

With the consideration of photon recycling effect, the efficiency limit of methylammonium lead iodide (CH3NH3PbI3) perovskite solar cells is predicted by a detailed balance model. To obtain convincing predictions, both AM 1.5 spectrum of…

Materials Science · Physics 2015-07-01 Wei E. I. Sha , Xingang Ren , Luzhou Chen , Wallace C. H. Choy

We have developed an efficient and reliable methodology for crystal structure prediction, merging ab initio total-energy calculations and a specifically devised evolutionary algorithm. This method allows one to predict the most stable…

Materials Science · Physics 2009-11-18 A. R. Oganov , C. W. Glass

Machine learning has emerged as a promising approach for estimating material parameters in solar cells. Traditional methods for parameter extraction often rely on time-consuming numerical simulations that fail to capture the full complexity…

Materials Science · Physics 2025-06-17 Eunchi Kim , Paula Hartnagel , Barbara Urbano , Leonard Christen , Thomas Kirchartz

We propose a method for crystal structure prediction based on a new structure generation algorithm and on-lattice machine learning interatomic potentials. Our algorithm generates the atomic configurations assigning atomic species to sites…

Materials Science · Physics 2023-06-08 Vadim Sotskov , Alexander V. Shapeev , Evgeny V. Podryabinkin

Metal halide perovskite solar cells have achieved dramatic improvements in their power conversion efficiency in the recent past. Since compositional engineering plays an important role in optimizing material properties, we investigate the…

Inorganic-organic perovskites semiconductors are becoming increasingly interesting due to their remarkable optical properties, such as a high photoluminescence quantum yield and the possibility to show optical gain in a broad range of…

Optics · Physics 2021-03-30 Michele Bellingeri , Francesco Scotognella

The spectacular performance of halide perovskites in optoelectronic devices is rooted in their tolerance to defects. Previous studies showed that defects in these materials generate shallow electronic states. However, how these shallow…

Materials Science · Physics 2025-05-20 Frederico P. Delgado , Frederico Simões , Leeor Kronik , Waldemar Kaiser , David A. Egger