|
|
|
|
|
|
FTIR Quantitative Analysis of Evolution and Interaction of Plastic Layer in Coking Process |
TIE Wei-bo1, WANG Qi1*, GAN Xiu-shi2, WANG Xu2, HUANG Jun-chen1, YANG Song-tao1, ZHANG Song1 |
1. Department of Metallurgical Engineering, College of Materials and Metallurgy, University of Science and Technology Liaoning, Anshan 114051, China
2. Anshan Iron & Steel Research Institute, Anshan 114009, China
|
|
|
Abstract The plastic layer is an important intermediate phase in the coking process. Its structure evolution and the interference between different structures in the coal blending process are of great significance for understanding coal's properties and the blending's interaction mechanism. This paper used self-made coking-related properties measuring device to conduct coking experiments on different blend ratios. The evolution products of the plastic layer were obtained by the interrupted cooling method, including the softening zone (SFZ), melting zone (MPBZ), flow zone (MZ), and resolidification zone (RSZ). FTIR determined the raw materials that were obtained. FTIR was divided into four bands of 3 600~3 000, 3 000~2 800, 1 800~1 000 and 900~700 cm-1 for peak fitting analysis. I-aromatization, DOC-polycondensation degree, —CH2— aliphatic structure, A'-hydrocarbon generation capacity, and C-oxygen-containing functional group were used to explore the changes in the coking process and the interaction among the same evolution products of blends with different mass ratios. The results show that I and DOC increased gradually in the special temperature field, and the changes were particularly significant from MZ to RSZ. With the release of volatiles and tar, the aliphatic group —CH2 and A' as a whole showed a downward trend. The content of C fluctuates slightly in MPBZ and MZ, but the overall trend is also downward. The condensation of aromatic carbon structure induces the decomposition of aliphatic structure and oxygen-containing functional groups. MZ to RSZ in the plastic layer is an important part of coking process. TheI1 and DOC of the same evolution products of mixed coals with different mass ratios have good additive properties in SFZ, MPBZ, and MZ, with the degree of fitting R2 reaching 0.744, 0.71, 0.775 and 0.74, 0.266, 0.773 respectively. The interaction of other structures is influenced by many factors of the process of pyrolysis and bonding, so these do not have additivity. Therefore, the aromatic carbon structure at the resolidification zone and the lack of additivity of the aliphatic structure and heteroatoms are important factors affecting the different properties of coke.
|
Received: 2023-02-21
Accepted: 2024-01-17
|
|
Corresponding Authors:
WANG Qi
E-mail: wangqi8822@sina.com
|
|
[1] Díez M A, Alvarez R, Barriocanal C. International Journal of Coal Geology, 2002, 50(1):389.
[2] Marsh H, Menendez R. Fuel Processing Technology, 1988, 20:269.
[3] YANG Zhi-rong, MENG Qing-yan, HUANG Jie-jie, et al(杨志荣,孟庆岩,黄戒介,等). Journal of Fuel Chemistry and Technology(燃料化学学报), 2018, 46(6):641.
[4] Hu W J, Wang Q, Zhao X F, et al. Fuel, 2019, 253:199.
[5] Wang Q, Cheng H, Zhao X F, et al. Energy & Fuels, 2018, 32(7):7438.
[6] LI Xia,ZENG Fan-gui,WANG Wei,et al(李 霞,曾凡桂,王 威,等). Journal of China Coal(煤炭学报), 2015, 40(12):2900.
[7] Marzec A. Fuel Processing Technology, 2002, 77:25.
[8] Solomon P R, Carangelo R M. Fuel, 1982, 61:663.
[9] Solomon P R, Carangelo R M. Fuel, 1988, 67:949.
[10] Morga R. International Journal of Coal Geology, 2010, 84(1):1.
[11] Tian B, Qiao Y Y, Tian Y Y, et al. Fuel Processing Technology, 2016, 154:210.
[12] Ibarra J V, Munoz E, Moliner R. Organic Geochemistry, 1996, 24(6-7):725.
[13] Chen Y, Mastalerz M, Schimmelmann A. International Journal of Coal Geology, 2012, 104(1):22.
[14] Meng F R, Yu J L, Tahmasebi A, et al. Energy & Fuels, 2014, 28:275.
|
[1] |
SHAO Yan1, 2, 3, LÜ Jin-guang1, 2*, LIN Jing-jun4, ZHENG Kai-feng1, 2, ZHAO Bai-xuan1, 2, ZHAO Ying-ze1, 2, CHEN Yu-peng1, 2, QIN Yu-xin1, 2, WANG Wei-biao1, 2, LIN Xiao-mei5, LIANG Jing-qiu1, 2*. Determination of Metal Elements in Lubricant Oil by Beeswax Sample Preparation Assisted Laser-Induced Breakdown Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(12): 3321-3326. |
[2] |
WU Zhuo1, 2, SU Xiao-hui3, FAN Bo-wen4, ZHU Hui-hui1, 2, ZHANG Yu-bo1, 2, FANG Bin3, WANG Yi-fan1, 2, LÜ Tao1, 2*. Different Feature Selection Methods Combined With Laser-Induced Breakdown Spectroscopy Were Used to Quantify the Contents of Nickel, Titanium and Chromium in Stainless Steel[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(12): 3339-3346. |
[3] |
HAN Mei1, 2, 3, JIA Yun-hai1*, DAI Lian-shuang4, HU Jing-yu1, ZHAO Lei1, ZHANG Xi5*, WEI Chen2, 3, WANG Hai-zhou1. In Situ Quantitative Analysis of Elements in X80 Pipeline Steel Welds[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(12): 3406-3413. |
[4] |
WANG Xiao-yan1, 2, JIANG Zhe-zhen1, JI Ren-dong1, 2*, BIAN Hai-yi1, 2, HE Ying1, CHEN Xu1, XU Chun-xiang3. Detection and Analysis of Mixed Organic Pesticides Based on
Three-Dimensional Fluorescence Spectroscopy and PARAFAC[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(11): 3082-3089. |
[5] |
WANG Xue1, 2, 4, WANG Zi-wen1, ZHANG Guang-yue1, MA Tie-min1, CHEN Zheng-guang1, YI Shu-juan3, 4, WANG Chang-yuan2. A Universal Model for Quantitative Analysis of Near-Infrared
Spectroscopy Based on Transfer Component Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(11): 3213-3221. |
[6] |
LIU Rong-xiang1, YANG Zhan-feng1, 2*, LI Jie3*, CAO Zhao1, LI Qiang2, LI Ji-chuan1. FTIR and XPS Studies on the Effect of Ca2+ on the Fotation of Monazite by Octyl Hydroxamic Acid[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(10): 2959-2967. |
[7] |
HUANG Xiao-hong1, 2, LIU Xiao-chen1, 2, LIU Yan-li3*, SONG Chao1, 2, SUN Yong-chang1, 2, ZHANG Qing-jun4. Element Detection in Scrap Steel Using Portable LIBS and Sparrow Search Algorithm-Kernel Extreme Learning Machine (SSA-KELM)[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(09): 2412-2419. |
[8] |
PENG Jiao-yu1, 2, YANG Ke-li1, 2, DONG Ya-ping1, 2, FENG Hai-tao1, 2, ZHANG Bo1, 3, LI Wu1, 3. Research on the Chemical Species of Borates in Salt Lake Brine and Its Quantitative Analysis by Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(09): 2514-2522. |
[9] |
MA Qin-yong1, 2*, CUI Yong-qiang1, 2, WANG Zhi-wei1, KONG Ling-fu1, 2. Saturation Intensity Analysis of LIF Received Optical Power of
Oil-In-Water Emulsion in Emulsified Oil Spill on Sea Surface[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(08): 2192-2197. |
[10] |
YAN Xia1, HU Cong-cong1, YANG Zhi-yuan2, ZHAO Hang2*, SHI Xiao-feng2, MA Jun2*. SERS Detection of Carbendazim Based on Convex Polyhedrons Shaped Au@4-ATP@Au Nanoparticle[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(07): 1843-1851. |
[11] |
LÜ Shu-bin1, 2, YANG Wan-qi1, 2, LI Fu-sheng1, 2*. Quantitative Analysis of Lead and Cadmium Heavy Metal Elements in Soil Based on Principal Component Analysis and Broad Learning System[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(07): 1852-1857. |
[12] |
WANG An1, CUI Jia-cheng2, SONG Wei-ran2, HOU Zong-yu2, 3*, CHEN Xiang4, CHEN Fei4. Quantitative Analysis of Coal Properties Using Laser-Induced Breakdown Spectroscopy and Semi-Supervised Learning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(07): 1940-1945. |
[13] |
XIANG Zi-han1, YIN Zuo-wei2, 3, ZHANG Zhi-qing1*, WANG Wen-wei2, 3*. Quantitative Study of Borax Filler in Heat-Treated Rubies[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(07): 2024-2028. |
[14] |
YU Shui1, HUAN Ke-wei1*, LIU Xiao-xi2, WANG Lei1. Quantitative Analysis Modeling of Near Infrared Spectroscopy With
Parallel Convolution Neural Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(06): 1627-1635. |
[15] |
DAI Yu-jia1, GAO Xun2*, LIU Zi-yuan1*. Accuracy Improvement of Mn Element in Aluminum Alloy by the
Combination of LASSO-LSSVM and Laser-Induced Breakdown
Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(04): 977-982. |
|
|
|
|