相关论文: Geometric Parameter Estimations of Perovskite Sola…
Perovskite stability is of the core importance and difficulty in current research and application of perovskite solar cells. Nevertheless, over the past century, the formability and stability of perovskite still relied on simplified factor…
The inverse design of tailored organic molecules for specific optoelectronic devices of high complexity holds an enormous potential, but has not yet been realized1,2. The complexity and literally infinite diversity of conjugated molecular…
Eclipsing binaries provide one of the most direct mechanisms for measuring stellar properties such as mass and radius, but historically, determining these properties has been non-trivial and computationally prohibitive. As such, only a…
To be able to increase the efficiency of perovskite solar cells which is one of the most substantial challenges ahead in photovoltaic industry, the structural and optical properties of perovskite CH3NH3PbI3-xBrx for values x=1-3 have been…
The discovery of effective molecular modulators is essential for advancing perovskite solar cells (PSCs), but the research process is hindered by the vastness of chemical space and the time-consuming and expensive trial-and-error…
We propose a novel semantic segmentation algorithm by learning a deconvolution network. We learn the network on top of the convolutional layers adopted from VGG 16-layer net. The deconvolution network is composed of deconvolution and…
Solution combustion synthesized hole transport layer of co-doped spinel nickel cobaltite were fabricated using doctor-blading technique for planar inverted perovskite solar cells. Perovskite solar cells incorporating Co-doped spinel nickel…
In recent years, convolutional neural networks (CNNs) have experienced an increasing interest in their ability to perform a fast approximation of effective hydrodynamic parameters in porous media research and applications. This paper…
The 2D/3D construction of hybrid perovskite interfaces is gaining increasing attention due to their enhanced stability towards degradation without compromising the corresponding solar cell efficiency. Much of it is due to the interfacial…
In perovskite solar cells, photovoltaic action is created by charge transport layers (CTLs) either side of the light-absorbing metal halide perovskite semiconductor. Hence, the rates for desirable charge extraction and unwanted interfacial…
Automatic detection and segmentation of cells and nuclei in microscopy images is important for many biological applications. Recent successful learning-based approaches include per-pixel cell segmentation with subsequent pixel grouping, or…
The dynamics in the photosphere is governed by the multi-scale turbulent convection termed as granulation and supergranulation. It is important to derive 3-dimensional velocity vectors to understand the nature of the turbulent convection.…
Perovskite/Si tandem solar cells have the potential to considerably out-perform conventional solar cells. Under standard test conditions, perovskite/Si tandem solar cells already outperform the Si single junction. Under realistic…
Geophysical inversion attempts to estimate the distribution of physical properties in the Earth's interior from observations collected at or above the surface. Inverse problems are commonly posed as least-squares optimization problems in…
Machine learning enables rapid estimation of material parameters in solar cells via neural-network-based surrogate models. However, the reliability of extracted parameters depends on underlying assumptions such as the choice of…
Halide perovskite solar cells based on CH3NH3PbI3 and related materials have emerged as the most exciting development in the next generation photovoltaic technologies, yet the microscopic phenomena involving photo-carriers, ionic defects,…
Traditional inorganic semiconductors can be electronically doped with high precision. Conversely, there is still conjecture regarding the assessment of the electronic doping density in metal-halide perovskites, not to mention of a control…
The last five years have witnessed a remarkable progress in the field of lead halide perovskite materials and devices. Examining the existing body of literature reveals staggering inconsistencies in the reported results among different…
In this work, we characterize the performance of a deep convolutional neural network designed to detect and quantify chemical elements in experimental X-ray photoelectron spectroscopy data. Given the lack of a reliable database in…
Electroluminescence (EL) imaging is a powerful and established technique for assessing the quality of photovoltaic (PV) modules, which consist of many electrically connected solar cells arranged in a grid. The analysis of imperfect…