透過Python進行磁性薄膜量測及數據分析

Measurements and Data Analysis of Magnetic Thin Films Using Python

謝佑剛(Neil Murray)

指導教授 ： 白奇峰

國立臺灣大學/工學院/材料科學與工程學研究所/碩士(2019年)

https://doi.org/10.6342/NTU202000052

摘要

磁阻式隨機存取記憶體（MRAM）是一種非揮發性記憶體，由於其具有高密度和低能耗的潛力，MRAM近年來受到了廣泛關注。通過調製材料系統來優化MRAM元件仍然是一個活躍的研究課題，尤其是對於寫入方法為自旋軌道矩（SOT）的MRAM元件。當為了MRAM的應用而表徵元件的性質時，有幾項品質因數對於確定其可行性至關重要。對於SOT器件，這些性質包括類阻尼自旋軌道矩(DL-SOT)效率，熱穩定性和臨界翻轉電流。研究用於優化這些材料系統的品質因數之工作流程可能會非常漫長，需要花費大量時間進行材料沉積，元件製備，測量以及最終的數據分析。一般而言，一篇文獻將需要來自大量元件的多次測量數據，因此擁有完善的系統來收集和分析數據非常重要。本工作中，我呈現出精簡的測量及數據分析程序之Python程式碼，其縮短了大量消耗於嘗試萃取品質因素之時間。這些測量程式碼提供一個彈性的編譯腳本於快速開發客製化量測程式。利用此程式，可以提供用來尋找SOT元件中品質因素之標準量測，如異常霍爾效應，各向異性磁阻和電致SOT翻轉量測。利用Jupyter notebook之量測結果進而進行數據分析，允許使用者批量處理這些大量的數據樣本。根據數據分析的結果，比較不同元件的品質因數被簡化為一件微不足道的事。利用這些測量腳本和數據分析notebook，使用者應該能夠將更多的時間專注於理解結果的含義上，而不是專注於收集所述結果上。

關鍵字

自旋軌道矩 ； MRAM ； python ； 自旋軌道矩效率 ； 數據分析 ； 臨界電流 ； 熱穩定性

並列摘要

Magnetoresistive random access memory (MRAM) is a type of non-volatile memory that has attracted significant attention in recent years due to its potential for high density and low power consumption. Optimization of MRAM devices through tailoring the material systems still remains a lively topic of research, especially for MRAM devices utilizing spin-orbit torques (SOT) as a write method. When characterizing device properties for MRAM applications, there are several figures of merit that are of key importance to determining their viability. For SOT devices, these properties include the damping-like SOT efficiency, thermal stability and the critical switching current.
The workflow for researching material systems that optimize these figures of merit can be quite lengthy, with significant time being spent on material deposition, device fabrication, measurement and finally data analysis. Typically, a single paper will require data from multiple measurements for a large number of devices. Therefore it is important to have well built systems for collecting and analyzing data.
In this work I present python code that streamlines the measurement and data analysis process to minimize the amount of time spent on trying to extract figures of merit. The measurement code presented in this work provides a flexible scripting format to quickly develop measurements per user specifications. Using this code, standard anomalous Hall effect, anisotropic magnetoresistance and current induced SOT switching measurements used for finding figures of merit from SOT devices are presented. Data analysis on the results of these measurements using Jupyter notebooks written to allow for batch processing of large datasets. From the results of the data analysis, comparison of figures of merit for different devices becomes a trivial task. Utilizing these measurement scripts and data analysis notebooks, users should be able to focus more of their time on understanding the meaning of results instead of on collecting said results.

並列關鍵字

spin-orbit torque ； MRAM ； python ； SOT switching ； data analysis ； spin-orbit torque efficiency ； critical current ； thermal stability

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