• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Acta Crystallographica, Section B. Structural Science >Theoretical prediction of bond-valence networks. II. Comparison of the graph-matrix and resonance-bond approaches
【24h】

Theoretical prediction of bond-valence networks. II. Comparison of the graph-matrix and resonance-bond approaches

机译：键价网络的理论预测。二。图矩阵和共振键方法的比较

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper provides a common framework for the bond-valence and resonance-bond-number methods, both of which explain the principal variations in inorganic bond lengths from the sum of radii, as arising from the connectivity of the structure, and therefore may apply graph information in conjunction with the Valence-Sum Rule. Under these constraints, possible predictions are limited to specific ranges of (M - N + 1) parameters, where M and N are the size and order of a multigraph describing the crystal motif. Further restrictions on these parameters may arise from non-crystallographic graph symmetries. Convenient graphtheoretical calculation schemes are described for both approaches. As it is possible to identify the best possible prediction within the limits described, which is that most closely corresponding to the experimental result, we have a means of making a direct comparison of the effectiveness of the various methods proposed, as well as being able to evaluate them against a statistically based prediction. The resonance-bond-number method proves to be the better predictor in most cases. Examples analysed in this way comprise KVO3 (potassium metavanadate), alpha-Ga2O3 (gallium oxide), TeI4 [tellurium(IV) iodide], Li2SiO3 (lithium metasilicate), Li2GeO3 (lithium metagermanate) and CaCrF5 (calcium chromium fluoride). [References: 24]
机译：本文为键合价和共振键数方法提供了一个通用框架，这两种方法都解释了由于结构的连通性而导致的，从半径之和得出的无机键长的主要变化，因此可以应用图信息结合价和规则。在这些约束下，可能的预测仅限于（M-N + 1）参数的特定范围，其中M和N是描述晶体图案的多重图形的大小和顺序。对这些参数的进一步限制可能源自非晶体学图的对称性。两种方法都描述了方便的图论计算方案。由于有可能在上述限制内确定最佳的预测，即与实验结果最接近，因此我们可以直接比较所提出的各种方法的有效性，并且能够根据基于统计的预测对它们进行评估。在大多数情况下，共振键数方法被证明是更好的预测指标。以此方式分析的实例包括KVO3（偏钒酸钾），α-Ga2O3（氧化镓），TeI4 [碘化碲（IV）]，Li2SiO3（偏硅酸锂），Li2GeO3（偏锗酸锂）和CaCrF5（氟化铬钙）。 [参考：24]

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号