相关论文: Efficiently charting the space of mixed vacancy-or…
Compared to first principles studies like DFT (physically accurate, computationally expensive), the TB approach allows the disentanglement of the region of interest, to wit the fermi level. This allows the creation of simplified, highly…
Quantum wells made of two-dimensional organic-inorganic hybrid perovskites (2D-PKs) offer a high degree of flexibility in tailoring optoelectronic properties through carrier confinement and functional interlayers. Compared to their 3D…
Hybrid halide perovskites are currently under intense investigation due to their potential applications in optoelectronics and solar cells. Among them, MAPbI$_3$ where MA stands for the methylammonium cation, exhibits ideal properties for…
The unprecedented structural flexibility and diversity of inorganic frameworks of layered hybrid halide perovskites (LHHPs) rise up a wide range of useful optoelectronic properties thus predetermining the extraordinary high interest to this…
We performed ab initio simulations aimed at identifying the atomistic and electronic structure origin of the high valence and conduction band, and band gap tunability of halide perovskites. We found that the two key ingredients are the…
Preparation of solid solutions represents an effective means to improve the photocatalytic properties of semiconductor-based materials. Nevertheless, the effects of site-occupancy disorder on the mixing stability and electronic properties…
Two-dimensional (2D) halide perovskites are emerging as promising candidates for nano-electronics and optoelectronics. To realize their full potential, it is important to understand the role of those defects that can strongly impact…
With their celebrated structural and chemical flexibility, perovskite oxides have served as a highly adaptable material platform for exploring emergent phenomena arising from the interplay between different degrees of freedom. Molecular…
Halide perovskites perform remarkably in optoelectronic devices including tandem photovoltaics. However, this exceptional performance is striking given that perovskites exhibit deep charge carrier traps and spatial compositional and…
Hybrid organic-inorganic halide perovskites have emerged as a disruptive new class of materials, exhibiting optimum properties for a broad range of optoelectronic applications, most notably for photovoltaics. The first report of highly…
The electronic structure evolution of deficient halide perovskites with a general formula $(A,A')_{1+x}M_{1-x}X_{3-x}$ was investigated using the density functional theory. The focus is placed on characterization of changes in the band gap,…
Efficient visual data processing by neuromorphic networks requires volatile artificial synapses that detect and process light inputs, ideally in the same device. Here, we demonstrate microscale back-contacted optoelectronic halide…
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…
Two-dimensional (2D) halide perovskites (HPs) are promising materials for various optoelectronic applications, yet a comprehensive understanding of their dynamics is still elusive. Here, we offer insight into the dynamics of prototypical 2D…
We investigate the structural, electronic and optical properties of mixed bromide-iodide lead perovskite solar cell CH$_3$NH$_3$Pb(I$_{1-x}$Br$_x$)$_3$ by means of the virtual crystal approximation (VCA) within density functional theory…
Understanding and controlling charge carrier recombination dynamics is essential for enhancing the performance of metal halide perovskite optoelectronic devices. In this study, we present a machine learning-assisted intensity-modulated…
With the availability of extensive databases of inorganic materials, data-driven approaches leveraging machine learning have gained prominence in materials science research. In this study, we propose an innovative adaptation of data-driven…
Halide vacancies are the dominant point defects in perovskites with VCl identified as a detrimental trap for the optoelectronic performance of CsPbCl3, with applications ranging from photodetectors to solar cells. Understanding these…
Pinpointing the origin of inefficiency can expedite the process of optimizing the efficiency of perovskite photovoltaics. However, it is challenging to discern and quantify the different loss pathways in a complete perovskite photovoltaic…
Graph-based neural networks and, specifically, message-passing neural networks (MPNNs) have shown great potential in predicting physical properties of solids. In this work, we train an MPNN to first classify materials through density…