اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدFull spectrum optical constant interface to the Materials Project
312
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
Optical constants characterize the interaction of materials with light and are important properties in material design. Here we present a Python-based Corvus workflow for simulations of full spectrum optical constants from the UV-VIS to hard x-ray wavelengths based on the real-space Greens function code FEFF10 and structural data from the Materials Project (MP). The Corvus workflow manager and its associated tools provide an interface to FEFF10 and the MP database. The workflow parallelizes the FEFF computations of optical constants over all absorption edges for each material in the MP database specified by a unique MP-ID. The workflow tools determine the distribution of computational resources needed for that case. Similarly, the optical constants for selected sets of materials can be computed in a single-shot. To illustrate the approach, we present results for nearly all elemental solids in the periodic table, as well as a sample compound, and compared with experimental results. As in x-ray absorption spectra, these results are interpreted in terms of an atomic-like background and fine-structure contributions.
قيم البحث
اقرأ أيضاً
The application of PhotoEmission Electron Microscopy (PEEM) and Low Energy Electron Microscopy (LEEM) techniques to the study of the electronic and chemical structure of ferroelectric materials is reviewed. Electron optics in both techniques gives sp
atial resolution of a few tens of nanometres. PEEM images photoelectrons whereas LEEM images reflected and elastically backscattered electrons. Both PEEM and LEEM can be used in direct and reciprocal space imaging. Together, they provide access to surface charge, work function, topography, chemical mapping, surface crystallinity and band structure. Examples of applications for the study of ferroelectric thin films and single crystals are presented.
The full monolayer of pentacene adsorbed on rutile TiO$_2$(110) provides an intriguing model to study charge-transfer excitations where the optically excited electrons and holes reside on different sides of the internal interface between the pentacen
e monolayer and the TiO$_2$ surface. In this work we investigate the electronic properties of this system with density functional theory, and compute its excitonic and optical properties making use of emph{ab initio} matrix elements. The pentacene molecules are found to lie flat on the surface, head to tail, and slightly tilted towards the troughs of the oxygen rows of the surface --- in agreement with experiment. Molecular states appear in the band gap of the clean TiO$_2$ surface which enable charge transfer excitations directly from the molecular HOMO to the TiO$_2$ conduction band. The calculated optical spectrum shows a strong polarization dependence and displays excitonic resonances corresponding to the charge-transfer states. We characterize the computed excitons by their symmetry and location in k-space and use this information to explain the polarization dependence of the optical spectrum.
Triggered by the revival of multiferroic materials, a lot of effort is presently undergoing as to find a coupling between a capacitance and a magnetic field. We show in this report that interfaces are the right way of increasing such a coupling provi
ded free charges are localized on these two-dimensional defects. Starting from commercial diodes at room temperature and going to grain boundaries in giant permittivity materials and to ferroelectric domain walls, a clear magnetocapacitance is reported which is all the time more than a few percent for a magnetic field of 90kOe. The only tuning parameter for such strong coupling to arise is the dielectric relaxation time which is reached on tuning the operating frequency and the temperature in many different materials.
Lattice constants such as unit cell edge lengths and plane angles are important parameters of the periodic structures of crystal materials. Predicting crystal lattice constants has wide applications in crystal structure prediction and materials prope
rty prediction. Previous work has used machine learning models such as neural networks and support vector machines combined with composition features for lattice constant prediction and has achieved a maximum performance for cubic structures with an average $R^2$ of 0.82. Other models tailored for special materials family of a fixed form such as ABX3 perovskites can achieve much higher performance due to the homogeneity of the structures. However, these models trained with small datasets are usually not applicable to generic lattice parameter prediction of materials with diverse compositions. Herein, we report MLatticeABC, a random forest machine learning model with a new descriptor set for lattice unit cell edge length ($a,b,c$) prediction which achieves an R2 score of 0.979 for lattice parameter $a$ of cubic crystals and significant performance improvement for other crystal systems as well. Source code and trained models can be freely accessed at https://github.com/usccolumbia/MLatticeABC
The increase in the temperature of photovoltaic (PV) solar cells affects negatively their power conversion efficiency and decreases their lifetime. The negative effects are particularly pronounced in concentrator solar cells. Therefore, it is crucial
to limit the PV cell temperature by effectively removing the excess heat. Conventional thermal phase change materials (PCMs) and thermal interface materials (TIMs) do not possess the thermal conductivity values sufficient for thermal management of the next generation of PV cells. In this paper, we report the results of investigation of the increased efficiency of PV cells with the use of graphene-enhanced TIMs. Graphene reveals the highest values of the intrinsic thermal conductivity. It was also shown that the thermal conductivity of composites can be increased via utilization of graphene fillers. We prepared TIMs with up to 6% of graphene designed specifically for PV cell application. The solar cells were tested using the solar simulation module. It was found that the drop in the output voltage of the solar panel under two-sun concentrated illumination can be reduced from 19% to 6% when graphene-enhanced TIMs are used. The proposed method can recover up to 75% of the power loss in solar cells.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
