1. Relationship between Atomic Structure, Composition, and Dielectric Constant in Zr-SiO2 Glasses
- Author
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Hegoi Manzano, Jon López-Zorrilla, Andre Ivanov, S. Arash Sheikholeslam, and Saamaan Pourtavakoli
- Subjects
Work (thermodynamics) ,Materials science ,Silica glass ,Semiconductor technology ,General Chemical Engineering ,02 engineering and technology ,Dielectric ,algorithms ,01 natural sciences ,deposition ,Article ,Molecular dynamics ,0103 physical sciences ,010306 general physics ,QD1-999 ,Static dielectric constant ,diffusion ,General Chemistry ,Material Design ,dynamics ,021001 nanoscience & nanotechnology ,Engineering physics ,total energies ,reaxff ,Chemistry ,CMOS ,reactive force-field ,set model chemistry ,simulations ,0210 nano-technology ,optimization - Abstract
[EN]Computational methods, or computer-aided material design (CAMD), used for the analysis and design of materials have a relatively long history. However, the applicability of CAMD has been limited by the scales of computational resources generally available in the past. The surge in computational power seen in recent years is enabling the applicability of CAMD to unprecedented levels. Here, we focus on the CAMD for materials critical for the continued advancement of the complementary metal oxide semiconductor (CMOS) semiconductor technology. In particular, we apply CAMD to the engineering of high-permittivity dielectric materials. We developed a Reax forcefield that includes Si, O, Zr, and H. We used this forcefield in a series of simulations to compute the static dielectric constant of silica glasses for low Zr concentration using a classical molecular dynamics approach. Our results are compared against experimental values. Not only does our work reveal numerical estimations on ZrO2-doped silica dielectrics, it also provides a foundation and demonstration of how CAMD can enable the engineering of materials of critical importance for advanced CMOS technology nodes. This research was enabled in part by support provided by Compute Canada (www.computecanada.ca). Computations were performed on the Niagara supercomputer at the SciNet HPC Consortium. SciNet is funded by the Canada Foundation for Innovation, the Government of Ontario, Ontario Research Fund.Research Excellence, and the University of Toronto.
- Published
- 2021