five

Materials Data on LiNbO3 by Materials Project|材料科学数据集|晶体结构数据集

收藏
Mendeley Data2024-01-31 更新2024-06-28 收录
材料科学
晶体结构
下载链接:
https://www.osti.gov/servlets/purl/1731774/
下载链接
链接失效反馈
资源简介:
LiNbO3 crystallizes in the monoclinic P2_1/c space group. The structure is three-dimensional. there are two inequivalent Li1+ sites. In the first Li1+ site, Li1+ is bonded to five O2- atoms to form distorted LiO5 trigonal bipyramids that share corners with four NbO6 octahedra, corners with two equivalent LiO5 trigonal bipyramids, edges with two NbO6 octahedra, and edges with two LiO5 trigonal bipyramids. The corner-sharing octahedra tilt angles range from 29–65°. There are a spread of Li–O bond distances ranging from 2.05–2.23 Å. In the second Li1+ site, Li1+ is bonded to five O2- atoms to form distorted LiO5 trigonal bipyramids that share corners with two NbO6 octahedra, corners with two equivalent LiO5 trigonal bipyramids, edges with four NbO6 octahedra, and an edgeedge with one LiO5 trigonal bipyramid. The corner-sharing octahedra tilt angles range from 23–52°. There are a spread of Li–O bond distances ranging from 1.97–2.20 Å. There are two inequivalent Nb5+ sites. In the first Nb5+ site, Nb5+ is bonded to six O2- atoms to form distorted NbO6 octahedra that share corners with two equivalent NbO6 octahedra, corners with two LiO5 trigonal bipyramids, edges with three NbO6 octahedra, and edges with three LiO5 trigonal bipyramids. The corner-sharing octahedra tilt angles range from 20–23°. There are a spread of Nb–O bond distances ranging from 1.88–2.19 Å. In the second Nb5+ site, Nb5+ is bonded to six O2- atoms to form distorted NbO6 octahedra that share corners with two equivalent NbO6 octahedra, corners with four LiO5 trigonal bipyramids, edges with two equivalent NbO6 octahedra, and edges with three LiO5 trigonal bipyramids. The corner-sharing octahedra tilt angles range from 20–23°. There are a spread of Nb–O bond distances ranging from 1.83–2.33 Å. There are six inequivalent O2- sites. In the first O2- site, O2- is bonded in a distorted rectangular see-saw-like geometry to one Li1+ and three Nb5+ atoms. In the second O2- site, O2- is bonded to three Li1+ and one Nb5+ atom to form distorted edge-sharing OLi3Nb trigonal pyramids. In the third O2- site, O2- is bonded in a T-shaped geometry to one Li1+ and two Nb5+ atoms. In the fourth O2- site, O2- is bonded in a distorted rectangular see-saw-like geometry to two Li1+ and two Nb5+ atoms. In the fifth O2- site, O2- is bonded in a rectangular see-saw-like geometry to two Li1+ and two Nb5+ atoms. In the sixth O2- site, O2- is bonded in a trigonal planar geometry to one Li1+ and two Nb5+ atoms.
创建时间:
2024-01-31
用户留言
有没有相关的论文或文献参考?
这个数据集是基于什么背景创建的?
数据集的作者是谁?
能帮我联系到这个数据集的作者吗?
这个数据集如何下载?
点击留言
数据主题
具身智能
数据集  4099个
机构  8个
大模型
数据集  439个
机构  10个
无人机
数据集  37个
机构  6个
指令微调
数据集  36个
机构  6个
蛋白质结构
数据集  50个
机构  8个
空间智能
数据集  21个
机构  5个
5,000+
优质数据集
54 个
任务类型
进入经典数据集
热门数据集

MeSH

MeSH(医学主题词表)是一个用于索引和检索生物医学文献的标准化词汇表。它包含了大量的医学术语和概念,用于描述医学文献中的主题和内容。MeSH数据集包括主题词、副主题词、树状结构、历史记录等信息,广泛应用于医学文献的分类和检索。

www.nlm.nih.gov 收录

中国1km分辨率逐月降水量数据集(1901-2024)

该数据集为中国逐月降水量数据,空间分辨率为0.0083333°(约1km),时间为1901.1-2024.12。数据格式为NETCDF,即.nc格式。该数据集是根据CRU发布的全球0.5°气候数据集以及WorldClim发布的全球高分辨率气候数据集,通过Delta空间降尺度方案在中国降尺度生成的。并且,使用496个独立气象观测点数据进行验证,验证结果可信。本数据集包含的地理空间范围是全国主要陆地(包含港澳台地区),不含南海岛礁等区域。为了便于存储,数据均为int16型存于nc文件中,降水单位为0.1mm。 nc数据可使用ArcMAP软件打开制图; 并可用Matlab软件进行提取处理,Matlab发布了读入与存储nc文件的函数,读取函数为ncread,切换到nc文件存储文件夹,语句表达为:ncread (‘XXX.nc’,‘var’, [i j t],[leni lenj lent]),其中XXX.nc为文件名,为字符串需要’’;var是从XXX.nc中读取的变量名,为字符串需要’’;i、j、t分别为读取数据的起始行、列、时间,leni、lenj、lent i分别为在行、列、时间维度上读取的长度。这样,研究区内任何地区、任何时间段均可用此函数读取。Matlab的help里面有很多关于nc数据的命令,可查看。数据坐标系统建议使用WGS84。

国家青藏高原科学数据中心 收录

HazyDet

HazyDet是由解放军工程大学等机构创建的一个大规模数据集,专门用于雾霾场景下的无人机视角物体检测。该数据集包含383,000个真实世界实例,收集自自然雾霾环境和正常场景中人工添加的雾霾效果,以模拟恶劣天气条件。数据集的创建过程结合了深度估计和大气散射模型,确保了数据的真实性和多样性。HazyDet主要应用于无人机在恶劣天气条件下的物体检测,旨在提高无人机在复杂环境中的感知能力。

arXiv 收录

DNS-Challenge

深度噪声抑制挑战数据集,包含干净的语音和噪声剪辑,用于训练和评估在有噪声环境下增强语音的模型。

huggingface 收录

FER2013

FER2013数据集是一个广泛用于面部表情识别领域的数据集,包含28,709个训练样本和7,178个测试样本。图像属性为48x48像素,标签包括愤怒、厌恶、恐惧、快乐、悲伤、惊讶和中性。

github 收录