Electronegativity-Based QSPR Analysis for Understanding Structure–Property Relationships of Glass Materials

Glass materials have been widely used from daily life applications to high technology areas. However, the growing demands from applications, especially those with critical requirements, make it challenging to develop new functional glass materials through the traditional trial and error method. Recently, a methodology by combining molecular dynamics (MD) simulation and quantitative structure-property relationship (QSPR) analysis has shown its ability to correlate the structure and properties of glass, thus promising in predicting unknown glass properties. However, the established MD-QSPR method usually relies on experimental inputs, which limits its capability for applicable systems. In this work, a general-purpose analytical method combined with electronegativity was proposed without experimental inputs in the descriptor construction process. The descriptor in the new method consists of three parts, counting for contributions from composition, structure, and energy, respectively. Experimentally measured glass properties including density, hardness, glass transition temperature (<i>T</i><sub>g</sub>), and elemental leaching rates (η) have been correlated with descriptors based on different structure inputs. In addition, various types of glass have been employed to validate the generality of this method. The results show that the new method can help construct general-purpose models of the structure-property relationship and provide new ideas to design new functional glass.

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Publication Details

Journal
The Journal of Physical Chemistry B
Published
2025-05-09
DOI
https://doi.org/10.1021/acs.jpcb.5c00345
Citations
1
Primary Topic
Cultural Heritage Materials Analysis
Type
article
Field-Weighted Citation Impact
8.27

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article

Electronegativity-Based QSPR Analysis for Understanding Structure–Property Relationships of Glass Materials

Fangling Jiang, Lu Deng, Lili Hu, Shubin Chen et al.
1 citations
The Journal of Physical Chemistry B
Cultural Heritage Materials Analysis
8.27
article

Electronegativity-Based QSPR Analysis for Understanding Structure–Property Relationships of Glass Materials

Fangling Jiang, Lu Deng, Lili Hu, Shubin Chen, Jingping Yan, Tianfeng Xue, Yajiao Zhang, Jiawei Liu, Feimei Wang, Boyuan Li
article en
1 citations

Abstract

Glass materials have been widely used from daily life applications to high technology areas. However, the growing demands from applications, especially those with critical requirements, make it challenging to develop new functional glass materials through the traditional trial and error method. Recently, a methodology by combining molecular dynamics (MD) simulation and quantitative structure-property relationship (QSPR) analysis has shown its ability to correlate the structure and properties of glass, thus promising in predicting unknown glass properties. However, the established MD-QSPR method usually relies on experimental inputs, which limits its capability for applicable systems. In this work, a general-purpose analytical method combined with electronegativity was proposed without experimental inputs in the descriptor construction process. The descriptor in the new method consists of three parts, counting for contributions from composition, structure, and energy, respectively. Experimentally measured glass properties including density, hardness, glass transition temperature (<i>T</i><sub>g</sub>), and elemental leaching rates (η) have been correlated with descriptors based on different structure inputs. In addition, various types of glass have been employed to validate the generality of this method. The results show that the new method can help construct general-purpose models of the structure-property relationship and provide new ideas to design new functional glass.

The Journal of Physical Chemistry BVol. 129(20)
University of Science and Technology of China (CN), Chinese Academy of Sciences (CN), Shanghai Institute of Optics and Fine Mechanics (CN), University of Chinese Academy of Sciences (CN), Shanghai Institute of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 5%
Cultural Heritage Materials Analysis
8.27
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