Materials Informatics Technique for Designing Strong-Adhesion Interfaces in Electronics Devices

T. Iwasaki
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Abstract

A materials-informatics technique for designing strong flat interfaces has been developed by use of advanced simulation that can calculate the delamination energy as the adhesion strength. In this study, this technique is applied to the design of metal (or alloy) with strong adhesion to polyimide, which is an example resin used for printed circuit boards. At the first stage, the interatomic spacings were selected as the important, dominant metal parameters from four metal parameters (the short-distance and long-distance interatomic spacings, electronegativity, and surface energy density) by using sensitivity analysis based on the design-of-experiments method with the delamination-energy data calculated from the advanced simulation. At the second stage, the adhesion strength (delamination energy) is expressed as a function of the important alloy parameters (i.e., the short-distance and long-distance interatomic spacings) by using Kriging-method-based artificial intelligence. At the third stage, by solving the maximum-value problem of the function, it was found that the metal that has the same short-distance and long-distance interatomic spacings as those of the resin has the strongest adhesion to the resin. Finally, it was confirmed that the metal (Ni-12%Mn) that satisfies this lattice-matching condition has the strongest adhesion by conducting a scratch test. Thus, lattice matching was found to be the most important factor in the adhesion.
电子器件中强粘附界面设计的材料信息学技术
利用先进的仿真技术,开发了一种设计强平面界面的材料信息学技术,该技术可以将分层能计算为粘附强度。在这项研究中,该技术被应用于设计与聚酰亚胺具有强附着力的金属(或合金),聚酰亚胺是用于印刷电路板的一种示例树脂。第一阶段采用基于实验设计的灵敏度分析方法,利用先进模拟计算的分层能数据,从近距离和远距离原子间间距、电负性和表面能密度四个金属参数中选择原子间间距作为重要的优势金属参数。在第二阶段,利用基于kriging方法的人工智能将粘接强度(分层能)表示为合金重要参数(即原子间短距离和远距离间距)的函数。在第三阶段,通过求解函数的最大值问题,发现与树脂具有相同短距离和长距离原子间间距的金属与树脂的附着力最强。最后,通过划痕试验证实,满足这种晶格匹配条件的金属(Ni-12%Mn)具有最强的附着力。因此,晶格匹配是影响粘附的最重要因素。
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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