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Double perovskite halides are emerging as promising materials for a wide range of applications, particularly in renewable energy technologies such as solar cell devices, thereby contributing to addressing global energy demands. In this…

Materials Science · Physics 2026-04-10 Huda A. Alburaih , Sikander Azam , N. A. Noor , A. Laref , Sohail Mumtaz

Metal halide perovskites are attracting tremendous interest for a variety of optoelectronic applications. The ability to tune the perovskite bandgap by tweaking the chemical compositions opens up new applications as coloured emitters and as…

My study is about Halide Perovskites (HaPs) and focuses the fundamental structural, chemical and dielectric properties of HaPs in reference to their PV-related properties. * I present my main research model: HaP single-crystals - their…

Materials Science · Physics 2018-10-01 Yevgeny Rakita , David Cahen , Gary Hodes

The optimization of properties of perovskite oxides has drawn interest on account of their diverse areas of application. In this work, the hierarchical clustering technique is used to reduce the multi-collinearity among selected features…

Materials Science · Physics 2022-03-01 George Stephen Thoppil , Alankar Alankar

Density functional theory (DFT) calculations are performed to predict the structural, electronic and magnetic properties of electrically neutral or charged few-atomic-layer (AL) oxides whose parent systems are based on polar perovskite…

Finding new superconductors with a high critical temperature ($T_c$) has been a challenging task due to computational and experimental costs. We present a diffusion model inspired by the computer vision community to generate new…

Superconductivity · Physics 2023-07-28 Daniel Wines , Tian Xie , Kamal Choudhary

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…

This study mainly emphasis the fascinating features of inverse perovskites Na3AgO using density functional theory (DFT). Inverse perovskite (IP) Na3AgO structural features have been examined, and the space group and cubic structure of Pm-3m…

Materials Science · Physics 2025-09-19 Vipan Kumar , Shyam Lal Gupta , Sumit Kumar , Ashwani Kumar , Pooja Rana , Diwaker

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…

Materials Science · Physics 2018-12-31 Gustavo M. Dalpian , Xingang Zhao , Lawrence Kazmerski , Alex Zunger

The term defect tolerance (DT) is used often to rationalize the exceptional optoelectronic properties of Halide Perovskites (HaPs) and their devices. Even though DT lacked direct experimental evidence, it became a "fact" in the field. DT in…

Materials Science · Physics 2024-02-23 Naga Prathibha Jasti , Igal Levine , Yishay Feldman , Gary Hodes , Sigalit Aharon , David Cahen

Since perovskite solar cells have attracted a lot of attentions over the past years, the enhancement of their optical absorption and current density are among the basic coming challenges. For this reason, first, we have studied structural…

The structural, electrical, optical, and mechanical characteristics of the lead-free halide double perovskites Cs2NaTlX6 X = F, Cl, Br are calculated by utilizing PBE functional within generalized gradient approximation GGA under the…

Materials Science · Physics 2023-02-07 Mohammed Mehedi Hasan , Nazmul Hasan , Alamgir Kabir

Accelerated discovery with machine learning (ML) has begun to provide the advances in efficiency needed to overcome the combinatorial challenge of computational materials design. Nevertheless, ML-accelerated discovery both inherits the…

Materials Science · Physics 2022-05-09 Chenru Duan , Fang Liu , Aditya Nandy , Heather J. Kulik

Metal halide perovskite (MHP) optoelectronics may become a viable alternative to standard Si-based technologies, but the current lack of long-term stability precludes their commercial adoption. Exposure to standard operational stressors…

Halide double perovskites are an emerging class of semiconductors with tremendous chemical and electronic diversity. While their bandstructure features can be understood from frontier-orbital models, chemical intuition for optical…

Materials Science · Physics 2023-09-04 Raisa-Ioana Biega , Yinan Chen , Marina R. Filip , Linn Leppert

We performed density functional calculations to estimate the formation energies of intermetallic alloys. We used two semilocal approximations, the generalized gradient approximation (GGA) by Perdew-Burke-Ernzerhof (PBE) and the strongly…

Materials Science · Physics 2020-11-25 Niraj K. Nepal , Santosh Adhikari , Bimal Neupane , Adrienn Ruzsinszky

The predictive accuracy of density functional theory (DFT) for alloy formation enthalpies is often limited by intrinsic energy resolution errors, particularly in ternary phase stability calculations. In this work, we present a machine…

Materials Science · Physics 2025-03-10 Sergei I. Simak , Erna K. Delczeg-Czirjak , Olle Eriksson

Streamlined prediction of the electronic properties of photoactive materials warrants a Density Functional Theory (DFT) based approach that (i) yields reliable bandgaps, (ii) is free of empirically tuned parameters, and (iii) exhibits low…

Materials Science · Physics 2025-12-17 Andrew C. Burgess , Lórien MacEnulty , Ethan D'Arcy , David Gavin , David D. O'Regan

This paper presents the phase stability, opto-electronic and thermo-electric behavior of X2AuYZ6 (X = Cs, Rb; Z = Cl/Br/I) double perovskite halides by using the DFT method. The compounds belong to the cubic arrangement and are verified by…

Materials Science · Physics 2024-04-25 S. Mahmud , M. A. Ali , M. M. Hossain , M. M. Uddin

We develop new transfer learning algorithms to accelerate prediction of material properties from ab initio simulations based on density functional theory (DFT). Transfer learning has been successfully utilized for data-efficient modeling in…

Computational Physics · Physics 2020-07-01 Schuyler Krawczuk , Daniele Venturi
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