kMC simulations for publication "Control of Cu morphology on TaN barrier and combined Ru-TaN barrier/liner substrates for nanoscale interconnects from atomistic kinetic Monte Carlo simulations""

Kinetic Monte Carlo Simulations of Cu Metal Growth Growth direction: (111) Processes: Homoepitaxial growth on TaN and TaN modified with Ru (TaN, Ru25 and Ru50 modelled by modifying the activation energies), and post-deposition thermal vacuum annealing 📄 Overview This repository and dataset accompany the manuscript, containing the source code, input parameters, simulation outputs, and analysis scripts required to reproduce the results: "Control of Cu morphology on TaN barrier and combined Ru-TaN barrier/liner substrates for nanoscale interconnects from atomistic kinetic Monte Carlo simulations" Authors: Samuel Aldana, Cara-Lena Nies and Michael Nolan Journal: Nanoscale, Royal Society of Chemistry DOI: 10.1039/d4nr04505j arXiv: 2410.06133 The simulations utilize an open-source kinetic Monte Carlo simulator (kMC) simulator developed in Python by Dr. Samuel Aldana Delgado, designed to model thin-film growth and thermal vacuum annealing dynamics. Code repository: https://github.com/aldanads/Kinetix Code version (commit): 1a4689f This dataset is structured to support reproducibility and multiscale modeling in nanofabrication and materials design. 📂 Directory Structure Outputs/├── DFT/ # DFT data (activation energies)└── kMC/ # kMC data ├── time_evolution/ # Simulation for time evolution ├── partial_pressure/ # Simulation under high pressure conditions ├── annealing/ # Thermal vacuum annealing after deposition └── statistical_10sim/ # 10 runs per condition for statistics └── <Substrate>/ # e.g., TaN, Ru25, Ru50 └── <P=X>/ # Pressure (Pa): P=0.1, P=0.5, etc └── <TXXX>/ # Temperature (K): T = 300, 500, 700K (for annealing or deposition: check metadata) └── Sim_*/ # Individual simulation folders ├── metadata.json # Metadata summary ├── Program/ │ ├── *.py # Source code │ └── variables.pkl│ # Last state when simulation finishes├── Figures/│ ├── *.ipynb # Jupyter notebooks to reproduce manuscript figures│ └── Processed_data/│ │ ├── *.csv files with processed data │├── manuscript/│ ├── manuscript.pdf│ └── Supporting_information/ # Additional data and methods│└── README.md 🔑 Key Files for Reuse File Purpose Format metadata.json Standardized simulation parameters (domain size, process type) JSON Figure.csv Summary table linking simulations to high-level metrics CSV 📜 Licensing Simulation code: MIT License Dataset (metadata, results, trajectories): CC BY 4.0 → You are free to share and adapt the data, provided you give appropriate credit. 🙏 Acknowledgments M. N. and S. A. received support from the ASCENT + Access tothe European Infrastructure Nanoelectronics Program, fundedthrough the EU Horizon Europe Programme, grant no 871130.C-L. N. and M. N. were supported through the ScienceFoundation Ireland SFI–NSF China Partnership Program, grantnumber 17/NSFC/5279. 📬 Contact For questions or collaboration: Dr. Samuel Aldana Delgado Tyndall National Institute / University College Cork 📧 [e-mail] Monte Carlo（动力学蒙特卡洛，KMC）模拟铜金属生长 生长晶向：(111) 工艺：在氮化钽（TaN）以及经钌修饰的氮化钽（通过修改活化能建模的TaN、Ru25与Ru50）上的同质外延生长，以及沉积后热真空退火 📄 研究概况 本仓库与数据集配套于学术论文，包含复现论文结果所需的源代码、输入参数、模拟输出与分析脚本，论文标题为《基于原子级动力学蒙特卡洛模拟调控氮化钽阻挡层与钌-氮化钽复合阻挡/衬底上的铜微观形貌，用于纳米级互连》，作者为Samuel Aldana、Cara-Lena Nies与Michael Nolan，发表于英国皇家化学会期刊《Nanoscale》。 DOI：10.1039/d4nr04505j arXiv：2410.06133 本模拟使用由Samuel Aldana Delgado博士基于Python开发的开源动力学蒙特卡洛模拟器，用于模拟薄膜生长与热真空退火动力学过程。 代码仓库地址：https://github.com/aldanads/Kinetix 代码版本（提交哈希）：1a4689f 本数据集旨在支持纳米制造与材料设计领域的可复现研究与多尺度建模。 📂 目录结构 Outputs/ ├── DFT/ # 密度泛函理论（Density Functional Theory, DFT）数据（活化能相关） └── kMC/ # 动力学蒙特卡洛模拟数据 ├── time_evolution/ # 时间演化模拟 ├── partial_pressure/ # 高压条件下的模拟 ├── annealing/ # 沉积后的热真空退火模拟 └── statistical_10sim/ # 每种条件下10次重复模拟以获取统计数据 └── <Substrate>/ # 衬底类型，例如TaN、Ru25、Ru50 └── <P=X>/ # 压强（单位：帕斯卡）：P=0.1、P=0.5等 └── <TXXX>/ # 温度（单位：开尔文）：T=300、500、700K（退火或沉积的具体温度请查看元数据） └── Sim_*/ # 单个模拟结果文件夹 ├── metadata.json # 元数据摘要 ├── Program/ │ ├── *.py # 源代码文件 │ └── variables.pkl # 模拟结束时的最终状态 ├── Figures/ │ ├── *.ipynb # 用于复现论文图表的Jupyter Notebook文件 │ └── Processed_data/ │ ├── *.csv # 包含处理后数据的CSV文件 ├── manuscript/ │ ├── manuscript.pdf # 论文原稿 │ └── Supporting_information/ # 补充数据与方法说明 └── README.md 🔑 可复用关键文件 | 文件 | 用途说明 | 格式 | |---------------------|-------------------------------------------|-------| | metadata.json | 标准化模拟参数（模拟域尺寸、过程类型等） | JSON | | Figure.csv | 关联模拟与高阶评估指标的汇总表 | CSV | 📜 许可协议 模拟代码：采用MIT许可协议 数据集（元数据、结果、轨迹文件）：采用CC BY 4.0许可协议 → 您可自由共享与改编本数据集，但需标注恰当的引用来源。 🙏 致谢 M.N.与S.A.获得ASCENT+欧洲纳米电子基础设施获取计划的资助，该项目由欧盟地平线欧洲计划资助，项目编号871130。C-L.N.与M.N.获得爱尔兰科学基金会（Science Foundation Ireland, SFI）与中国国家自然科学基金委员会（NSFC）合作项目的资助，项目编号17/NSFC/5279。 📬 联系方式 如有疑问或合作意向，请联系：Samuel Aldana Delgado博士 廷德尔国家研究所 / 科克大学学院 📧 [e-mail]