聚类法对不同温度下不同有毒气体的响应及恢复时间分析

Amit Gupta, A.V.Nageswara varaha Rao, B. Raghavaiah, S. K. Dargar
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引用次数: 0

摘要

利用溅射热解技术制备了负载锡酸锌薄膜的二氧化氮传感器。考察了母质发热对二氧化氮反应的影响。在400℃下沉积的薄板以片状地貌为主,在表层内形成的毛坯增加了粗糙度。锡酸锌传感器在相对较低(300°C)的温度下,当二氧化氮浓度为40 ppm时,最大传感器反应为29.3。新型锡酸锌薄膜具有优异的气敏特性,表现出非凡的反应和恢复动力学,不受元素或表面活性剂的表面变化。建议的工作遵循使用蟒蛇软件的蜘蛛工具(spyder-3)操作与python编程语言。应用聚类技术的机器学习中的Python脚本重视有毒液体。在不同功能温度下的模拟结果与实时结果接近。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Clustering Method Response and Recovery Time Analysis with Different Temperature for different Toxic Gas
Nitrogen Dioxide sensors supported Zinc Stannate films were manufactured utilizing the splattering-pyrolysis technique. The impact of parent material pyrexia on Nitrogen Dioxide reaction was investigated. The sheets deposited at 400 °C dominate flakes like geomorphology that the blanks put forward within the superficial increase the roughness. The zinc Stannate sensor demonstrated maximum sensor reaction 29.3 at comparatively low (300 °C) functioning pyrexia regarding 40 ppm Nitrogen Dioxide concentration. The new Zinc Stannate films demonstrate excellent gas sensing characteristics and evidence extraordinary reaction and rehabilitation dynamics with no superficial variation by element or surface-active agent. The proposed work follows the use of anaconda software over spider tool (spyder-3) operation with python programming language. The Python scripts in machine learning with applied clustering techniques have valued toxic liquids. The results are close to real-time results with simulated ones at divergent functional temperatures.
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