Measurements and Model Estimations of Viscosities of the MnO-CaO-SiO 2 -MgO-Al 2 O 3 Melts

热力学 分析化学(期刊)
作者
Baijun Yan,Yixiang Liu,Qifeng Shu,Tengfei Deng,Björn Glaser
出处
期刊:Metallurgical and Materials Transactions B-process Metallurgy and Materials Processing Science [Springer Nature]
卷期号:50 (1): 376-384 被引量:4
标识
DOI:10.1007/s11663-018-1454-x
摘要

The viscosities of the MnO (0 to 55 mass pct)-CaO-SiO2-MgO (5 mass pct)-Al2O3 (20 mass pct) melts were measured by rotating cylinder method in the temperature range from 1573 K to 1873 K (1300 °C to 1600 °C). The measurements were carried out in the atmosphere of flowing CO/CO2 gas mixture with a volume ratio of 99/1, and molybdenum crucible and spindle were adopted. The results reveal that MnO is a viscosity reducing component, and the effect of MnO is more notable in the melts with higher ratio of CaO to SiO2. For example, in the melts with the mass ratio of CaO to SiO2 equal to 0.6, the addition of 5 mass pct MnO only slightly reduced the viscosities. Comparatively, the addition of 5 mass pct MnO made the viscosities of the melts with the mass ratio of CaO to SiO2 equal to 1.0 and 1.5 decrease remarkably. Based on the measured data, the viscosities estimation model proposed in our previous study was extended to the system containing MnO, and the model parameters were determined. The model can estimate and predict the viscosities of the aluminosilicate melts containing MnO well, and then some iso-viscosity contours of this system were calculated. From the iso-viscosity contours, it can be seen that MnO is almost equivalent to CaO in reducing the viscosities in the melt with high SiO2 content, while with the decrease of the SiO2 content MnO becomes more effective than CaO.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
顾矜应助111采纳,获得10
1秒前
1秒前
完美世界应助renovel采纳,获得10
2秒前
3秒前
3秒前
宸一发布了新的文献求助30
5秒前
欢喜的夜天完成签到,获得积分10
5秒前
科研通AI6.1应助Nyh采纳,获得10
5秒前
6秒前
6秒前
斯文败类应助风之旅人采纳,获得10
6秒前
飞龙在天完成签到,获得积分10
8秒前
8秒前
彭于晏应助zhounini1989采纳,获得10
8秒前
完美世界应助闪闪落雁采纳,获得10
10秒前
寒食完成签到,获得积分0
10秒前
10秒前
Akim应助Amelk采纳,获得10
12秒前
mmzz发布了新的文献求助10
12秒前
derherzog发布了新的文献求助10
13秒前
凉小远完成签到,获得积分10
13秒前
1234567发布了新的文献求助10
14秒前
火星弟弟完成签到,获得积分10
14秒前
15秒前
15秒前
小巫发布了新的文献求助10
16秒前
17秒前
17秒前
发的不太好完成签到,获得积分10
17秒前
xiao完成签到,获得积分10
17秒前
derherzog完成签到,获得积分20
18秒前
陈千里发布了新的文献求助10
19秒前
科研通AI2S应助睡不醒的网采纳,获得10
19秒前
别摆发布了新的文献求助10
20秒前
尘曦完成签到,获得积分10
20秒前
风之旅人发布了新的文献求助10
21秒前
SCI发布了新的文献求助10
21秒前
21秒前
23秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Molecular Biology of Cancer: Mechanisms, Targets, and Therapeutics 3000
VASCULITIS(血管炎)Rheumatic Disease Clinics (Clinics Review Articles) —— 《风湿病临床》(临床综述文章) 1000
Feldspar inclusion dating of ceramics and burnt stones 1000
What is the Future of Psychotherapy in a Digital Age? 801
The Psychological Quest for Meaning 800
Digital and Social Media Marketing 600
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5977450
求助须知:如何正确求助?哪些是违规求助? 7338065
关于积分的说明 16010164
捐赠科研通 5116845
什么是DOI,文献DOI怎么找? 2746683
邀请新用户注册赠送积分活动 1715088
关于科研通互助平台的介绍 1623852