Combustion Kinetics and Mechanism of Pre-Oxidized Coal with Different Oxygen Concentrations

动力学 燃烧 机制(生物学) 氧气 化学 化学工程 环境化学 物理化学 有机化学 工程类 物理 量子力学
作者
Haohao Fan,Kai Wang,Xiaowei Zhai,Lihong Hu
出处
期刊:ACS omega [American Chemical Society]
卷期号:6 (29): 19170-19182 被引量:25
标识
DOI:10.1021/acsomega.1c02520
摘要

The phenomenon of spontaneous combustion of "oxidized coal" is common in mining processes of goafs, thick coal seams, and unsealing of closed fire areas. In order to study the reburning characteristics of coal with different oxidation degrees, the oxygen concentration in the pre-oxidation process was selected as the key influencing factor. Thermogravimetric analysis (TGA) and in situ Fourier-transform infrared (FT-IR) spectroscopy were used to study the macro- and microcharacteristics of raw and oxidized coal during the combustion stage. The results showed that the pre-oxidation treatment exhibited a dual effect on promoting and inhibiting the weight loss characteristics of oxidized coal. The apparent activation energy, Ea, of the combustion reaction for the utilized coal samples was calculated using the Flynn–Wall–Ozawa (FWO) and Kissinger–Akahira–Sunose (KAS) methods, and it was found that the average apparent activation energy (Ea̅) values of the oxidized coal samples were less in magnitude than that of the raw coal and that the coal sample with the pre-oxidized oxygen concentration of 15% was more prone to the combustion reaction. Using the correlation determination method of key active groups in the proposed coal combustion reaction, the key active groups affecting the weight change of the tested coal samples during the combustion stage were determined as −CH3 and C–O. The results can be helpful to prevent and control coal spontaneous combustion during re-mining and unsealing of closed fire areas.

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
独特的秋完成签到,获得积分10
9秒前
cxl完成签到,获得积分10
18秒前
hhh完成签到,获得积分10
21秒前
无悔完成签到 ,获得积分0
25秒前
Hua完成签到,获得积分10
28秒前
丰富睫毛膏完成签到,获得积分10
30秒前
海洋完成签到,获得积分10
33秒前
Ping完成签到,获得积分10
37秒前
思维隋完成签到 ,获得积分10
38秒前
伶俐书蝶完成签到 ,获得积分10
42秒前
小小完成签到 ,获得积分10
43秒前
唠叨的天亦完成签到 ,获得积分10
47秒前
悦耳的城完成签到 ,获得积分10
49秒前
zzxiao完成签到,获得积分10
53秒前
我找到月亮了完成签到 ,获得积分10
58秒前
可靠铸海应助顺心的梦容采纳,获得10
58秒前
蜗牛完成签到,获得积分10
1分钟前
FashionBoy应助科研通管家采纳,获得10
1分钟前
cdercder应助科研通管家采纳,获得30
1分钟前
cdercder应助科研通管家采纳,获得10
1分钟前
初昀杭完成签到 ,获得积分10
1分钟前
1分钟前
疯狂的海白完成签到,获得积分10
1分钟前
睡到十点半完成签到 ,获得积分10
1分钟前
淮安石河子完成签到 ,获得积分10
1分钟前
淡定的夜云完成签到 ,获得积分10
1分钟前
Tonald Yang完成签到 ,获得积分10
1分钟前
大鹏完成签到,获得积分10
1分钟前
机智的孤兰完成签到 ,获得积分10
1分钟前
大胆路人完成签到 ,获得积分10
2分钟前
Stayup_o9完成签到 ,获得积分10
2分钟前
leeyolo完成签到,获得积分10
2分钟前
2分钟前
2分钟前
again发布了新的文献求助10
2分钟前
Slemon完成签到,获得积分0
2分钟前
随风完成签到 ,获得积分10
2分钟前
jason完成签到 ,获得积分10
2分钟前
云梦泽完成签到,获得积分20
2分钟前
杨啸林完成签到 ,获得积分10
2分钟前
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
Health Psychology 600
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
When Is Two-Stage Sample Robust Optimization Asymptotically Optimal? 500
APA handbook of comparative psychology: Basic concepts, methods, neural substrate, and behavior 500
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7592454
求助须知:如何正确求助?哪些是违规求助? 9169713
关于积分的说明 19626130
捐赠科研通 7170507
什么是DOI,文献DOI怎么找? 3267514
关于科研通互助平台的介绍 2432371
邀请新用户注册赠送积分活动 2260009