序列分布导向的CGC催化乙烯与1-辛烯共聚过程建模

doi:10.11949/0438-1157.20190930

摘要/Abstract

摘要：

限制几何构型催化剂(constrained geometry catalyst，CGC)特别适用于乙烯与α-烯烃溶液聚合法制备高性能聚烯烃弹性体POE(polyolefin elastomer)。基于CGC催化乙烯与1-辛烯共聚反应机理，建立了乙烯与1-辛烯共聚反应动力学模型并确定了动力学参数。采用前期实验获得的乙烯消耗速率曲线与催化剂平均活性验证了动力学模型的准确性。基于动力学模型和面向序列结构的共聚机理，建立了乙烯与1-辛烯共聚过程序列分布模型。模型可准确预测序列分布与短支链含量及其随反应条件的变化趋势。结果表明，随着1-辛烯浓度的增加，乙烯序列长度逐渐减小，其平均序列长度线性降低，而1-辛烯平均序列平均长度呈线性增加的趋势。所建模型可为从聚合过程角度调控POE链结构提供理论参考。

关键词: 序列分布, 聚烯烃弹性体, 聚合, 动力学模型, 预测

Abstract:

Constrained geometry catalyst (CGC) is particularly suitable for the preparation of high performance polyolefin elastomer (POE) using ethylene and α-olefin solution polymerization process. Based on the reaction mechanism of ethylene copolymerization with 1-octene catalyzed by CGC, a kinetic model was established and its kinetic parameters were determined. The kinetic model was validated by the consumption rate of ethylene and catalyst activity. Based on the kinetic model and sequence structure oriented copolymerization mechanism, a sequence distribution model of ethylene and 1-octene copolymerization was established. The model can accurately predict the sequence distribution, the content of short branch chains and their changing trend with reaction conditions. The results show that with the increase of 1-octene concentration, the average sequence length of ethylene decreases gradually and linearly, while the average sequence length of 1-octene increases linearly. The model can provide a theoretical reference for regulating the structure of the POE chain from the perspective of polymerization process.

Key words: sequence distribution, polyolefin elastomer, polymerization, kinetic modeling, prediction

中图分类号:

TQ 316.3

田洲, 焦栋, 王金强, 刘柏平. 序列分布导向的CGC催化乙烯与1-辛烯共聚过程建模[J]. 化工学报, 2020, 71(2): 651-659.

Zhou TIAN, Dong JIAO, Jinqiang WANG, Boping LIU. Sequence distribution oriented modeling of ethylene and 1-octene copolymerization process catalyzed by CGC[J]. CIESC Journal, 2020, 71(2): 651-659.

图/表 11

表1 主要动力学参数及竞聚率

Table 1 Kinetic parameters and reactivity ratios

k_pAA/

(L/(mol·s))

k_pAB/

(L/(mol·s))

k_pBA/

(L/(mol·s))

k_pBB/

(L/(mol·s))

k_d/

(L/(mol·s))

r_A^①

r_B^②

图1 乙烯消耗速率曲线的模型预测与实验结果对比

Fig.1 Comparison of ethylene consumption rate from model prediction and experimental results

图2 催化剂活性的模型预测与实验结果对比

Fig.2 Comparison of catalyst activity from model prediction and experimental results

图3 1-辛烯浓度为1.04 mol/L时的序列分布

Fig.3 Model prediction of sequence distribution (the concentration of 1-octene is 1.04 mol/L)

图4 1-辛烯浓度为0.08 mol/L与0.56 mol/L时的序列分布

Fig.4 Model prediction of sequence distribution (concentration of 1-octene are 0.08 and 0.56 mol/L, respectively)

表2 平均序列长度模型预测与实验结果对比

Table 2 Comparison of average sequence length from model prediction and experimental results

1-辛烯浓度/(mol/L)	序列	乙烯	1-辛烯
0.08	n_A,exp	36.16	1.08
	n_A,model	—	1.04
	error	—	3.70%
0.56	n_A,exp	6.86	1.23
	n_A,model	6.83	1.3
	error	0.44%	5.69%
1.04	n_A,exp	4.72	1.33
	n_A,model	4.78	1.38
	error	1.27%	3.76%

表 3 SCB含量模型预测与实验结果对比

Table 3 Comparison of content of SCB from model prediction and experimental results

Concentration/(mol/L)	Item	SCB
0.56	SCB_A,exp	48.1
	SCB_A,model	52.1
	error	8.30%
1.04	SCB_A,exp	61.7
	SCB_A,model	67
	error	8.6

图5 模型预测的序列分布

Fig.5 Model prediction of sequence distribution

图6 1-辛烯平均序列长度模型预测与实验结果对比

Fig.6 Comparison of average sequence length of 1-octene from model prediction and experimental results

图7 乙烯平均序列长度模型预测与实验结果对比

Fig.7 Comparison of average sequence length of ethylene from model prediction and experimental results

图8 短支链含量模型预测结果和实验结果对比

Fig.8 Comparison of content of SCB from model prediction and experimental results

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