Correlations between the constituent molecules, crystal structures, and dielectric constants in organic crystals

IF 3.7 2区化学 Q2 AUTOMATION & CONTROL SYSTEMS

Chemometrics and Intelligent Laboratory Systems Pub Date : 2025-03-11 DOI:10.1016/j.chemolab.2025.105376

Yuya Shiraki, Hiromasa Kaneko

引用次数: 0

Abstract

Organic crystals are crystals composed of molecules of organic compounds. Materials made from organic crystals are used in devices, such as capacitors and ferroelectric memories. It is desirable to develop new materials with improved physical properties such as the dielectric constant (DC). However, the relationship between the constituent molecule (CM), crystal structure (CS), and DC of the organic crystals is not clearly understood. In this study, we investigated the relationship between CM, CS, and DC with existing data and machine learning. Using regression analysis, we could construct machine learning models between CM and DC, between CS and DC, and between CM and CS, and could predict DC from CM, DC from CS, and CS from CM using the constructed models.

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有机晶体中组成分子、晶体结构和介电常数之间的关系

有机晶体是由有机化合物分子组成的晶体。由有机晶体制成的材料用于电容器和铁电存储器等器件。开发具有改善介电常数（DC）等物理性能的新材料是可取的。然而，有机晶体的组成分子（CM）、晶体结构（CS）和DC之间的关系尚不清楚。在这项研究中，我们研究了CM、CS和DC与现有数据和机器学习之间的关系。通过回归分析，我们可以构建CM和DC之间、CS和DC之间、CM和CS之间的机器学习模型，并可以使用构建的模型预测CM的DC、CS的DC和CM的CS。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Chemometrics and Intelligent Laboratory Systems 工程技术-分析化学

CiteScore

7.50

自引率

7.70%

发文量

169

审稿时长

3.4 months

期刊介绍： Chemometrics and Intelligent Laboratory Systems publishes original research papers, short communications, reviews, tutorials and Original Software Publications reporting on development of novel statistical, mathematical, or computer techniques in Chemistry and related disciplines. Chemometrics is the chemical discipline that uses mathematical and statistical methods to design or select optimal procedures and experiments, and to provide maximum chemical information by analysing chemical data. The journal deals with the following topics: 1) Development of new statistical, mathematical and chemometrical methods for Chemistry and related fields (Environmental Chemistry, Biochemistry, Toxicology, System Biology, -Omics, etc.) 2) Novel applications of chemometrics to all branches of Chemistry and related fields (typical domains of interest are: process data analysis, experimental design, data mining, signal processing, supervised modelling, decision making, robust statistics, mixture analysis, multivariate calibration etc.) Routine applications of established chemometrical techniques will not be considered. 3) Development of new software that provides novel tools or truly advances the use of chemometrical methods. 4) Well characterized data sets to test performance for the new methods and software. The journal complies with International Committee of Medical Journal Editors'' Uniform requirements for manuscripts.