论文标题
从统计设计中识别高dielectric常数化合物
Identification of High-Dielectric Constant Compounds from Statistical Design
论文作者
论文摘要
高降压材料的发现对于提高电子设备和电池的效率至关重要。 Here, we report three previously unexplored materials with very high dielectric constants (69 $<$ $ε$ $<$ 101) and large band gaps (2.9$<$ $E_{\text{g}}$(eV) $<$ 5.5) obtained by screening materials databases using statistical optimization algorithms aided by artificial neural networks (ANN).其中两个新的介电介质是混合化合物（欧盟$ _5 $ sicl $ _6 $ o $ _4 $和hoclo），并且显示通过相位数字分析对公共半导体具有热力学稳定。我们还发现了其他四种具有相对较大的电介质常数（20 $ <$ <$ <ε$ <$ 40）和频段差距（2.3 $ <$ <$ <$ <$ <$ e _ {\ text {g}} $（ev）$ <$ 2.7）的其他四种材料。虽然ANN训练数据是从材料项目中获得的，但搜索空间由开放量子材料数据库（OQMD）的材料组成 - 证明了跨数据库材料设计的成功实施。总体而言，我们报告了使用AB-Initio计算计算的17种材料的介电性能，这些材料是在我们的设计工作流中选择的。在这项工作中预测具有高介电性能的介电材料为进一步的实验研究机会提供了。
The discovery of high-dielectric materials is crucial to increasing the efficiency of electronic devices and batteries. Here, we report three previously unexplored materials with very high dielectric constants (69 $<$ $ε$ $<$ 101) and large band gaps (2.9$<$ $E_{\text{g}}$(eV) $<$ 5.5) obtained by screening materials databases using statistical optimization algorithms aided by artificial neural networks (ANN). Two of these new dielectrics are mixed-anion compounds (Eu$_5$SiCl$_6$O$_4$ and HoClO), and are shown to be thermodynamically stable against common semiconductors via phase-diagram analysis. We also uncovered four other materials with relatively large dielectric constants (20$<$$ε$$<$40) and band gaps (2.3$<$$E_{\text{g}}$(eV)$<$2.7). While the ANN training data is obtained from Materials Project, the search-space consists of materials from Open Quantum Materials Database (OQMD) - demonstrating a successful implementation of cross-database materials design. Overall, we report dielectric properties of 17 materials calculated using ab-initio calculations, that were selected in our design workflow. The dielectric materials with high dielectric properties predicted in this work open up further experimental research opportunities.
