{"title":"通过 QSPR 方法设计表面改性剂控制氧化铝分散树脂的粘度","authors":"","doi":"10.1016/j.apt.2024.104701","DOIUrl":null,"url":null,"abstract":"<div><div>In order to dissipate heat in electronic devices, particle-dispersed resins are commonly used to fill gaps between components. It is crucial to reduce the viscosity of the particle-dispersed resin to ensure complete filling. To achieve low viscosity, surface-modified particles using silane coupling agents have been developed to enhance compatibility with the resin. In this study, we focused on the Hansen solubility parameter (HSP) indicating compatibility of substances. We established a method to accurately predict HSP values using a combination of quantum chemical calculations and machine learning techniques known as the quantitative structure property relationships method (QSPR-method). Using this method, we calculated the HSP values of various silane coupling agents for modifying alumina particles and investigated their correlation with the viscosity of the alumina particle-dispersed resin. This study aimed to verify whether the QSPR method can be used to design silane coupling agents that can significantly reduce viscosity of particle-dispersed resins.</div></div>","PeriodicalId":7232,"journal":{"name":"Advanced Powder Technology","volume":null,"pages":null},"PeriodicalIF":4.2000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Viscosity control of alumina dispersed resin through design of surface modifier by a QSPR-method\",\"authors\":\"\",\"doi\":\"10.1016/j.apt.2024.104701\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In order to dissipate heat in electronic devices, particle-dispersed resins are commonly used to fill gaps between components. It is crucial to reduce the viscosity of the particle-dispersed resin to ensure complete filling. To achieve low viscosity, surface-modified particles using silane coupling agents have been developed to enhance compatibility with the resin. In this study, we focused on the Hansen solubility parameter (HSP) indicating compatibility of substances. We established a method to accurately predict HSP values using a combination of quantum chemical calculations and machine learning techniques known as the quantitative structure property relationships method (QSPR-method). Using this method, we calculated the HSP values of various silane coupling agents for modifying alumina particles and investigated their correlation with the viscosity of the alumina particle-dispersed resin. This study aimed to verify whether the QSPR method can be used to design silane coupling agents that can significantly reduce viscosity of particle-dispersed resins.</div></div>\",\"PeriodicalId\":7232,\"journal\":{\"name\":\"Advanced Powder Technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2024-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Powder Technology\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0921883124003777\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Powder Technology","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0921883124003777","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
Viscosity control of alumina dispersed resin through design of surface modifier by a QSPR-method
In order to dissipate heat in electronic devices, particle-dispersed resins are commonly used to fill gaps between components. It is crucial to reduce the viscosity of the particle-dispersed resin to ensure complete filling. To achieve low viscosity, surface-modified particles using silane coupling agents have been developed to enhance compatibility with the resin. In this study, we focused on the Hansen solubility parameter (HSP) indicating compatibility of substances. We established a method to accurately predict HSP values using a combination of quantum chemical calculations and machine learning techniques known as the quantitative structure property relationships method (QSPR-method). Using this method, we calculated the HSP values of various silane coupling agents for modifying alumina particles and investigated their correlation with the viscosity of the alumina particle-dispersed resin. This study aimed to verify whether the QSPR method can be used to design silane coupling agents that can significantly reduce viscosity of particle-dispersed resins.
期刊介绍:
The aim of Advanced Powder Technology is to meet the demand for an international journal that integrates all aspects of science and technology research on powder and particulate materials. The journal fulfills this purpose by publishing original research papers, rapid communications, reviews, and translated articles by prominent researchers worldwide.
The editorial work of Advanced Powder Technology, which was founded as the International Journal of the Society of Powder Technology, Japan, is now shared by distinguished board members, who operate in a unique framework designed to respond to the increasing global demand for articles on not only powder and particles, but also on various materials produced from them.
Advanced Powder Technology covers various areas, but a discussion of powder and particles is required in articles. Topics include: Production of powder and particulate materials in gases and liquids(nanoparticles, fine ceramics, pharmaceuticals, novel functional materials, etc.); Aerosol and colloidal processing; Powder and particle characterization; Dynamics and phenomena; Calculation and simulation (CFD, DEM, Monte Carlo method, population balance, etc.); Measurement and control of powder processes; Particle modification; Comminution; Powder handling and operations (storage, transport, granulation, separation, fluidization, etc.)