Lan Yang, Xiao Zhou, Xudong Ni, Li Huang, Lianduan Zeng, Zhongyang Wang, Jun Song, Tongxiang Fan
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引用次数: 0
Abstract
The optical static refractive index, a critical intrinsic property of materials, plays a vital role in advanced optoelectronic applications. Accurate prediction of this index is essential for the efficient design and optimization of materials with tailored optical properties. Here, we present a robust predictive model that accurately forecasts the optical static refractive indices of complex oxides across diverse crystal structures and compositions. By leveraging chemical bond theory, our model elucidates the influence of intrinsic physical properties, including chemical bonds and d-electron bands, on the refractive index. Through rigorous analysis of 41 complex oxide systems and 5 doped systems, we demonstrate that our predictions align closely with experimental data, showcasing the model’s high accuracy and broad applicability. This work not only accelerates the development of novel materials and spectral design but also provides profound physical insights for optimizing and customizing optical properties.
期刊介绍:
npj Computational Materials is a high-quality open access journal from Nature Research that publishes research papers applying computational approaches for the design of new materials and enhancing our understanding of existing ones. The journal also welcomes papers on new computational techniques and the refinement of current approaches that support these aims, as well as experimental papers that complement computational findings.
Some key features of npj Computational Materials include a 2-year impact factor of 12.241 (2021), article downloads of 1,138,590 (2021), and a fast turnaround time of 11 days from submission to the first editorial decision. The journal is indexed in various databases and services, including Chemical Abstracts Service (ACS), Astrophysics Data System (ADS), Current Contents/Physical, Chemical and Earth Sciences, Journal Citation Reports/Science Edition, SCOPUS, EI Compendex, INSPEC, Google Scholar, SCImago, DOAJ, CNKI, and Science Citation Index Expanded (SCIE), among others.