Related papers: Communication: Modeling layered mosaic perovskite …
Progress in the application of machine learning (ML) methods to materials design is hindered by the lack of understanding of the reliability of ML predictions, in particular for the application of ML to small data sets often found in…
Artificial intelligence (AI)-assisted workflows have transformed materials discovery, enabling rapid exploration of chemical spaces of functional materials. Endowed with extraordinary optoelectronic properties, two-dimensional (2D) hybrid…
2D layered hybrid organic-inorganic perovskites (HOIPs) have demonstrated improved stability and promising photovoltaic performance. The mechanical properties of such functional materials are both fundamentally and practically important to…
Inorganic halide perovskites have emerged as a promising platform in a wide range of applications from solar energy harvesting to computing, and light emission. The recent advent of epitaxial thin film growth of halide perovskites has made…
2D Ruddlesden Popper perovskites have been extensively studied for their exceptional optical and electronic characteristics while only a few studies have shed light on their mechanical properties. The existing literature mainly discusses…
Forming a hetero-interface is a materials-design strategy that can access an astronomically large phase space. However, the immense phase space necessitates a high-throughput approach for optimal interface design. Here we introduce a…
Increasing photovoltaic conversion efficiency, or PCE, has proven to be a critical factor in the transition to renewable energy. There exist strong interdependencies between the perovskite crystals and multijunction architectures within…
Leveraging strong optoelectronic responses to external stimuli, such as temperature and electric fields, is central to the development of advanced photonic technologies, including adaptive photodetectors and reconfigurable photovoltaic…
In this paper, we describe the unification and extension of multiple kinematic theories on the advection of colloidal particles through periodic obstacle lattices of arbitrary geometry and infinitesimally small obstacle size. We focus…
Ruddlesden-Popper hybrid halide perovskite are quasi-two-dimensional materials with a layered structure and structural dynamics that are determined by the interplay between the organic and inorganic layers. While their optical properties…
The multi-scale nature of architectured materials raises the need for advanced experimental methods suitable for the identification of their effective properties, especially when their size is finite and they undergo extreme deformations.…
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…
Asceding interest of the scientific community in layered hybrid halide perovskites (LHHPs) as materials for innovative photovoltaic and optoelectronic applications led to unprecedented expansion of this family of compounds, reaching now…
Amorphous and amorphous porous palladium are key materials for catalysis, hydrogen storage, and functional applications, but their complex structures present computational challenges. This study employs a deep neural network trained on…
Organohalide perovskite with a variety of surface structures and morphologies have shown promising potential owing to the choice of the type of heterostructure dependent stability. We systematically investigate and discuss the impact of…
We revisit the problem of polytypism in layered $\textit{MX}_2$ materials, with a view to reinterpreting the phase space accessible to this family. Our starting point is to develop a simple, constructive and compact label for the most…
The hybrid perovskite CH3NH3PbX3 (X= Cl, Br, I) is a promising material for developing novel optoelectronic devices. Owing to the intrinsic non-layer structure, it remains challenging to synthesize molecularly thin CH3NH3PbX3 with large…
The full optimization of the design and operation of instruments whose functioning relies on the interaction of radiation with matter is a super-human task, given the large dimensionality of the space of possible choices for geometry,…
Non-invasive imaging of the atomic arrangement in two-dimensional (2D) Ruddlesden-Popper hybrid Perovskites (RPPs), as well as understanding the related effects is challenging, due to the insulating nature and softness of the organic layers…
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…