Exploring Correlations Between Properties Using Artificial Neural Networks
文献类型：会议论文
| 作者 | Zhang, Yiming; Evans, Julian R. G.; Yang, Shoufeng |
| 出版日期 | 2020 |
| 会议日期 | JUL 21-25, 2019 |
| 关键词 | WORK FUNCTION ELECTRONEGATIVITY POLARIZABILITY VAPORIZATION PREDICTION TUNGSTEN |
| 卷号 | 51 |
| 期号 | 1 |
| DOI | 10.1007/s11661-019-05502-8 |
| 英文摘要 | The traditional aim of materials science is to establish the causal relationships between composition, processing, structure, and properties with the intention that, eventually, these relationships will make it possible to design materials to meet specifications. This paper explores another approach. If properties are related to structure at different scales, there may be relationships between properties that can be discerned and used to make predictions so that knowledge of some properties in a compositional field can be used to predict others. We use the physical properties of the elements as a dataset because it is expected to be both extensive and reliable and we explore this method by showing how it can be applied to predict the polarizability of the elements from other properties. |
| 学科主题 | Materials Science ; Metallurgy & Metallurgical Engineering |
| ISSN号 | 1073-5623 |
| 源URL | [http://ir.nimte.ac.cn/handle/174433/23310]  |
| 专题 | 会议专题 会议专题_会议论文 |
| 推荐引用方式 GB/T 7714 | Zhang, Yiming,Evans, Julian R. G.,Yang, Shoufeng. Exploring Correlations Between Properties Using Artificial Neural Networks[C]. 见:. JUL 21-25, 2019. |
入库方式： OAI收割
来源：宁波材料技术与工程研究所
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