离子液体-二氧化碳体系UNIFAC模型的构建

doi:10.16085/j.issn.1000-6613.2025-0541

摘要/Abstract

摘要：

离子液体（ILs）具有高稳定性、溶解性能好、可设计性、易回收等优点，尤其因高 CO₂溶解度在碳捕集方面显示了巨大潜力。但由于ILs种类繁多且价格昂贵，依靠实验研究耗时费力，因此构建 ILs 体系的热力学预测模型至关重要。UNIFAC 模型在 ILs 气体分离工艺设计与优化领域具有重要的理论价值和工程应用意义，基于此，本研究构建了应用于 ILs-CO₂ 体系活度系数预测的 UNIFAC 模型。本文系统收集了 CO₂ 在ILs中的溶解度实验数据，并结合相平衡计算出活度系数，建立了ILs-CO₂体系活度系数数据库。采用COSMO方法和van der Waals规则分别获得了 UNIFAC 模型中基团的重要参数（R_k 和Q_k ）。基于实验值，拟合了 UNIFAC 相互作用参数。通过平均相对误差（AARD），比较了两种方法建立的 UNIFAC 模型的预测效果。结果表明：通过 COSMO 方法（AARD=7.68%）建立的 UNIFAC 模型对 ILs-CO₂ 体系的活度系数预测误差比van der Waals方法（AARD=12.57%）降低了4.89个百分点。并在此基础上建立了ILs-CO₂体系 UNIFAC 模型，获得了近100 对基团的相互作用参数数据库。由于 UNIFAC 模型的基团贡献特点，本工作建立的 UNIFAC 模型可预测数据库中包含的基团组成的新型 ILs 与 CO₂ 体系的活度系数，从而为后续 ILs 法气体吸收的分子设计奠定了扎实基础。

关键词: 离子液体, UNIFAC 模型, 基团贡献法, 活度系数

Abstract:

Ionic liquids (ILs) possess the merits of high stability, excellent solubility, designability, facile recovery, and environmental friendliness. Particularly, they exhibit remarkable potential in carbon capture on account of their high solubility for CO₂. However, due to the wide variety and expensive price of ILs, it is time-consuming and laborious to rely on experimental research, and it is crucial to construct a thermodynamic prediction model for ILs systems. Since the UNIFAC predictive model was of great value for ILs selection and convenient for subsequent selection of gas separation tasks and process design and optimization, the UNIFAC model was proposed to predict the activity coefficient of the ILs-CO₂ system. In this work, the experimental data of CO₂ absorption by ILs were collected, the activity coefficient was calculated by combining the phase equilibrium, and the activity coefficient database of ILs-CO₂ system was established. The parameters of UNIFAC model (R_k and Q_k ) were calculated by COSMO method and van der Waals rule, respectively. Based on the experimental values, the UNIFAC interaction parameters were fitted. The prediction performance of the UNIFAC model established by the two methods was compared by the average relative error (AARD). The results showed that the UNIFAC model established by COSMO method (AARD=7.68%) could reduce the prediction error of activity coefficient of ILs-CO₂system by 4.89 percentage points compared with van der Waals method (AARD=12.57%). On this basis, the activity coefficient UNIFAC model of ILs-CO₂ system was established, and a database of interaction parameters for nearly 100 pairs of groups was obtained. In addition, based on the group contribution characteristics of the UNIFAC model, all group fragments contained in the interaction parameter database could be extended to new ionic liquid systems, so that the established UNIFAC model could be used to predict the activity coefficients of new kinds of ILs-CO₂ systems. Due to the group contribution feature of the UNIFAC model, the UNIFAC model developed in this work could predict the activity coefficients of ILs-CO₂binary system composed of the groups included in the database, providing a solid basis for the molecular design of the subsequent ILs method for gas absorption.

Key words: ionic liquids, UNIFAC model, group contribution method, activity coefficient

中图分类号:

TQ05

付映雪, 雷杨, 陈毓秋, 刘芯妍. 离子液体-二氧化碳体系UNIFAC模型的构建[J]. 化工进展, 2025, 44(8): 4862-4870.

FU Yingxue, LEI Yang, CHEN Yuqiu, LIU Xinyan. Construction of UNIFAC model for ionic liquid-carbon dioxide binary system[J]. Chemical Industry and Engineering Progress, 2025, 44(8): 4862-4870.

图/表 10

图1 ILs划分方式示意图

表1 IL-CO2体系所含ILs基团

基团序号	基团化学式	基团结构式
1	Im⁺
2	Pyr⁺
3	N⁺
4	P⁺
5	[BF₄]^-
6	[PF₆]^-
7	[Cl]^-	---Cl
8	[Br]^-	---Br
9	[NO₃]^-
10	—CN
11	—SO₂—
12	—CH₃

表2 基于van der Waals和COSMO量化计算方法计算出的基团片段体积与表面积

序号	基团片段	基团体积/Å³		基团表面积/Å²		序号	基团片段	基团体积/Å³		基团表面积/Å²
序号	基团片段	van der Waals	COSMO	van der Waals	COSMO	序号	基团片段	van der Waals	COSMO	van der Waals	COSMO
a1	Im⁺	76.5673	78.8425	67.0491	74.8054	a31	—H (non-ring)	3.22×10^-9	2.88×10^-12	1.17×10^-13	1.84×10^-12
a2	Pyr⁺	93.0945	88.6008	68.7745	79.1905	a32	—S或[—S—]^-	41.4690	32.5233	26.0029	24.5613
a3	Py⁺	94.1034	95.2286	77.7260	86.4588	a33	BF₃	56.1993	54.4049	46.7044	51.8305
a4	Pip⁺	112.8097	104.8166	82.1951	93.3278	a34	benzene ring	95.5647	88.1758	75.9492	78.9774
a5	N⁺	18.7142	24.7863	7.1353	16.7011	a35	[—N—]^-或>N—	20.1460	15.9473	17.9156	16.7650
a6	P⁺	37.0570	40.4472	20.1218	35.8658	a36	C $̿$ O	25.3835	24.9039	25.0013	25.6094
a7	S⁺	33.2359	39.1128	27.9854	36.0758	a37	—CF₂—	31.4475	33.5980	25.3543	30.3875
a8	[BF₄]^-	61.2174	62.2874	47.1405	55.6563	a38	—CF₃	40.5394	44.4884	33.0376	41.7422
a9	[PF₆]^-	87.1326	89.2392	67.7333	82.2673	a39	pyraz	80.8593	81.3180	65.7994	74.4410
a10	[Cl]^-	40.4777	27.0595	22.8040	16.5167	a40	F (ring)	0	5.4318	1.1015	5.0601
a11	[Br]^-	48.1779	33.5811	29.3039	22.7081	a41	quin	152.0713	149.0973	121.1241	130.8098
a12	[NO₃]^-	55.6096	46.2657	40.2931	40.6047	a42	thiaz	85.7933	90.0874	70.8378	80.9204
a13	[Aces]^-	159.4382	142.2671	128.8563	130.6366	a43	[ASF₆]^-	93.7932	95.5519	74.5103	89.9849
a14	[BMB]^-	203.5653	187.1462	168.1461	171.9940	a44	Guan	73.5587	73.1337	59.2302	69.4544
a15	[BMLB]^-	250.6386	221.2287	203.8728	209.2854	a45	[BCl₄]^-	133.6517	118.2315	103.1094	107.6575
a16	[BOB]^-	160.6194	150.2053	136.9377	139.2503	a46	[BClF₃]^-	80.5704	76.6895	63.2229	69.5261
a17	—CN	28.3720	27.8822	25.8283	26.2420	a47	—COO	50.9436	41.4938	39.5836	37.1174
a18	—SO₂—	48.4627	44.2438	38.6278	41.2222	a48	>POO	66.2032	53.0061	52.0701	51.9813
a19	[GaCl₄]^-	151.8823	133.3315	121.8828	127.5031	a49	[BBPhB]^-	449.3889	410.0913	343.7077	358.4873
a20	[AlCl₄]^-	150.1398	140.3866	120.2852	119.1695	a50	[ClO₄]^-	75.6789	64.7725	57.7302	59.8847
a21	—CH₃	22.5282	20.2353	17.1410	18.4048	a51	isoquin	153.6530	149.9763	125.8740	134.9791
a22	—CH₂—	23.7306	20.3829	21.2030	21.1868	a52	morph	102.4235	97.5111	74.6057	86.0866
a23	>CH—或[—CH—]^-	24.1542	20.2246	18.0718	19.6552	a53	[BSB]^-	302.9004	280.0698	245.5971	248.8058
a24	>C<或 [>C]^-	23.0386	18.4646	9.7866	12.9116	a54	—SO₃	70.8050	59.4857	56.4512	55.8970
a25	. $̿$ CH₂	17.4088	17.8537	12.0279	15.5348	a55	—SO₄	82.1872	70.4684	67.1649	66.5858
a26	. $̿$ CH-	19.7661	18.1608	17.4641	18.0304	a56	[Imidphf]^-	130.9107	123.9470	112.3453	122.4850
a27	$̿$ C<	20.3524	17.8412	20.6311	19.6341	a57	[salicylate]^-	155.9603	140.0384	122.5853	123.0451
a28	—H (ring)	0.3479	0.5889	0	0	a58	[B(CN)₄]^-	144.2575	136.6109	126.7380	128.0408
a29	—O—或[—O]^-	11.8365	11.3277	12.1500	11.8530	a59	I^-	61.4400	37.3200	43.4100	36.1700
a30	—OH	9.7960	9.8020	7.0168	8.3065	b₀	拟合常数	11.3393	8.8960	44.4916	36.1650

表2 基于van der Waals和COSMO量化计算方法计算出的基团片段体积与表面积

序号	基团片段	基团体积/Å³		基团表面积/Å²		序号	基团片段	基团体积/Å³		基团表面积/Å²
序号	基团片段	van der Waals	COSMO	van der Waals	COSMO	序号	基团片段	van der Waals	COSMO	van der Waals	COSMO
a1	Im⁺	76.5673	78.8425	67.0491	74.8054	a31	—H (non-ring)	3.22×10^-9	2.88×10^-12	1.17×10^-13	1.84×10^-12
a2	Pyr⁺	93.0945	88.6008	68.7745	79.1905	a32	—S或[—S—]^-	41.4690	32.5233	26.0029	24.5613
a3	Py⁺	94.1034	95.2286	77.7260	86.4588	a33	BF₃	56.1993	54.4049	46.7044	51.8305
a4	Pip⁺	112.8097	104.8166	82.1951	93.3278	a34	benzene ring	95.5647	88.1758	75.9492	78.9774
a5	N⁺	18.7142	24.7863	7.1353	16.7011	a35	[—N—]^-或>N—	20.1460	15.9473	17.9156	16.7650
a6	P⁺	37.0570	40.4472	20.1218	35.8658	a36	C $̿$ O	25.3835	24.9039	25.0013	25.6094
a7	S⁺	33.2359	39.1128	27.9854	36.0758	a37	—CF₂—	31.4475	33.5980	25.3543	30.3875
a8	[BF₄]^-	61.2174	62.2874	47.1405	55.6563	a38	—CF₃	40.5394	44.4884	33.0376	41.7422
a9	[PF₆]^-	87.1326	89.2392	67.7333	82.2673	a39	pyraz	80.8593	81.3180	65.7994	74.4410
a10	[Cl]^-	40.4777	27.0595	22.8040	16.5167	a40	F (ring)	0	5.4318	1.1015	5.0601
a11	[Br]^-	48.1779	33.5811	29.3039	22.7081	a41	quin	152.0713	149.0973	121.1241	130.8098
a12	[NO₃]^-	55.6096	46.2657	40.2931	40.6047	a42	thiaz	85.7933	90.0874	70.8378	80.9204
a13	[Aces]^-	159.4382	142.2671	128.8563	130.6366	a43	[ASF₆]^-	93.7932	95.5519	74.5103	89.9849
a14	[BMB]^-	203.5653	187.1462	168.1461	171.9940	a44	Guan	73.5587	73.1337	59.2302	69.4544
a15	[BMLB]^-	250.6386	221.2287	203.8728	209.2854	a45	[BCl₄]^-	133.6517	118.2315	103.1094	107.6575
a16	[BOB]^-	160.6194	150.2053	136.9377	139.2503	a46	[BClF₃]^-	80.5704	76.6895	63.2229	69.5261
a17	—CN	28.3720	27.8822	25.8283	26.2420	a47	—COO	50.9436	41.4938	39.5836	37.1174
a18	—SO₂—	48.4627	44.2438	38.6278	41.2222	a48	>POO	66.2032	53.0061	52.0701	51.9813
a19	[GaCl₄]^-	151.8823	133.3315	121.8828	127.5031	a49	[BBPhB]^-	449.3889	410.0913	343.7077	358.4873
a20	[AlCl₄]^-	150.1398	140.3866	120.2852	119.1695	a50	[ClO₄]^-	75.6789	64.7725	57.7302	59.8847
a21	—CH₃	22.5282	20.2353	17.1410	18.4048	a51	isoquin	153.6530	149.9763	125.8740	134.9791
a22	—CH₂—	23.7306	20.3829	21.2030	21.1868	a52	morph	102.4235	97.5111	74.6057	86.0866
a23	>CH—或[—CH—]^-	24.1542	20.2246	18.0718	19.6552	a53	[BSB]^-	302.9004	280.0698	245.5971	248.8058
a24	>C<或 [>C]^-	23.0386	18.4646	9.7866	12.9116	a54	—SO₃	70.8050	59.4857	56.4512	55.8970
a25	. $̿$ CH₂	17.4088	17.8537	12.0279	15.5348	a55	—SO₄	82.1872	70.4684	67.1649	66.5858
a26	. $̿$ CH-	19.7661	18.1608	17.4641	18.0304	a56	[Imidphf]^-	130.9107	123.9470	112.3453	122.4850
a27	$̿$ C<	20.3524	17.8412	20.6311	19.6341	a57	[salicylate]^-	155.9603	140.0384	122.5853	123.0451
a28	—H (ring)	0.3479	0.5889	0	0	a58	[B(CN)₄]^-	144.2575	136.6109	126.7380	128.0408
a29	—O—或[—O]^-	11.8365	11.3277	12.1500	11.8530	a59	I^-	61.4400	37.3200	43.4100	36.1700
a30	—OH	9.7960	9.8020	7.0168	8.3065	b₀	拟合常数	11.3393	8.8960	44.4916	36.1650

图2 比较ILs分子与基团片段计算得到的表面积和体积

表3 基团片段加和与ILs分子体积与表面积之间的相对偏差

AARD	体积	比表面积
COSMO	0.0041	0.0119
van der Waals	0.0062	0.0090

表4 UNIFAC模型的体积参数Rk 和表面积参数Qk

序号	基团	计算方法
		COSMO		van der Waals
		Q_k	R_k	Q_k	R_k
1	Im⁺	1.8023	3.1302	1.6154	3.0401
2	Pyr⁺	1.9078	3.5177	1.6568	3.6960
3	N⁺	0.4023	0.9842	0.1720	0.7428
4	P⁺	0.8642	1.6060	0.4847	1.4714
5	[BF₄]^-	1.3410	2.4731	1.1357	2.4306
6	[PF₆]^-	1.9820	3.5431	1.6318	3.4594
7	[Cl]^-	0.3980	1.0744	0.5493	1.6072
8	[Br]^-	0.5471	1.3332	0.7059	1.9129
9	[NO₃]^-	0.9781	1.8371	0.9707	2.2079
10	—CN	0.6322	1.1069	0.6223	1.1264
11	—SO₂—	0.9931	1.7565	0.9307	1.9240
12	—CH₃	0.4433	0.8036	0.4129	0.8945
13	—CH₂—	0.5105	0.8092	0.5108	0.9422
14	—O—	0.2855	0.4498	0.2927	0.4701
15	—OH	0.2002	0.3891	0.1691	0.3891
16	—H (non-ring)	0	0	0	0
17	—S	0.5917	1.2912	0.6264	1.6465
18	>N—	0.4040	0.6333	0.4317	0.8000
19	C $̿$ O	0.6170	0.9886	0.6023	1.0077
20	—CF₃	1.0056	1.7664	0.7960	1.6096
21	—COO	0.8943	1.6473	0.9536	2.0225
22	>POO	1.2523	2.1047	1.2545	2.6284
23	—SO₃	1.3467	2.3620	1.3600	2.8114
24	—SO₄	1.6043	2.7979	1.6180	3.2632
25	[B(CN)₄]^-	3.0847	5.4239	3.0534	5.7276

表4 UNIFAC模型的体积参数Rk 和表面积参数Qk

序号	基团	计算方法
		COSMO		van der Waals
		Q_k	R_k	Q_k	R_k
1	Im⁺	1.8023	3.1302	1.6154	3.0401
2	Pyr⁺	1.9078	3.5177	1.6568	3.6960
3	N⁺	0.4023	0.9842	0.1720	0.7428
4	P⁺	0.8642	1.6060	0.4847	1.4714
5	[BF₄]^-	1.3410	2.4731	1.1357	2.4306
6	[PF₆]^-	1.9820	3.5431	1.6318	3.4594
7	[Cl]^-	0.3980	1.0744	0.5493	1.6072
8	[Br]^-	0.5471	1.3332	0.7059	1.9129
9	[NO₃]^-	0.9781	1.8371	0.9707	2.2079
10	—CN	0.6322	1.1069	0.6223	1.1264
11	—SO₂—	0.9931	1.7565	0.9307	1.9240
12	—CH₃	0.4433	0.8036	0.4129	0.8945
13	—CH₂—	0.5105	0.8092	0.5108	0.9422
14	—O—	0.2855	0.4498	0.2927	0.4701
15	—OH	0.2002	0.3891	0.1691	0.3891
16	—H (non-ring)	0	0	0	0
17	—S	0.5917	1.2912	0.6264	1.6465
18	>N—	0.4040	0.6333	0.4317	0.8000
19	C $̿$ O	0.6170	0.9886	0.6023	1.0077
20	—CF₃	1.0056	1.7664	0.7960	1.6096
21	—COO	0.8943	1.6473	0.9536	2.0225
22	>POO	1.2523	2.1047	1.2545	2.6284
23	—SO₃	1.3467	2.3620	1.3600	2.8114
24	—SO₄	1.6043	2.7979	1.6180	3.2632
25	[B(CN)₄]^-	3.0847	5.4239	3.0534	5.7276

表5 UNIFAC模型的计算值与实验值的AARD

序号	体系	样本数量	AARD/%
序号	体系	样本数量	COSMO	van der Walls
总计		1524	7.86	12.57
1	[BMIM][BF₄]-CO₂ [HMIM][BF₄]-CO₂ [EMIM][BF₄]-CO₂ [OMIM][BF₄]-CO₂	229	8.30	15.08
2	[BMIM][PF₆]-CO₂ [HMIM][PF₆]-CO₂ [EMIM][PF₆]-CO₂ [NMIM][PF₆]-CO₂	224	9.70	9.02
3	[BMIM] [Tf₂N]-CO₂ [EMIM] [Tf₂N]-CO₂ [HMIM] [Tf₂N]-CO₂ [OMIM] [Tf₂N]-CO₂ [C₅MIM] [Tf2N]-CO₂	248	10.70	11.11
4	[BMIM][MSEGSO₄] -CO₂ [EMIM][MSEGSO₄] -CO₂	55	13.24	16.51
5	[BMIM][TfO]-CO₂ [HMIM][TfO] -CO₂ [EMIM][TfO] -CO₂ [OMIM] [TfO]-CO₂	107	7.56	4.60
6	[BMIM][SCN]-CO₂	47	10.06	18.76
7	[BMIM][NO₃]-CO₂	80	3.51	13.98
8	[BMIM][Cl]-CO₂	21	7.44	13.98
9	[HMIM][Br]-CO₂	7	10.18	11.91
10	[BMIM][MeSO₃]-CO₂ [EMIM][MeSO₃]-CO₂	79	9.82	10.26
11	[HEMIM][OH]-CO₂	44	7.48	9.38
12	[BMIM][DBPO₄]-CO₂ [EMIM][DEPO₄]-CO₂	40	3.68	3.35
13	[HMIM][TCB]-CO₂	32	10.01	11.11
14	[BMPYR][Tf₂N]-CO₂ [HMPYR][Tf₂N]-CO₂ [NMPYR][Tf₂N]-CO₂ [OMPYR][Tf₂N]-CO₂ [C₃MPYR][Tf₂N]-CO₂ [C₅MPYR][Tf₂N]-CO₂ [C₇MPYR][Tf₂N]-CO₂	144	1.03	21.99
15	[BMPYR][TfO]-CO₂	49	0.05	13.86
16	[BMPYR][LEV]-CO₂	10	0.78	2.51
17	[m-2-HEA][FOR]-CO₂	65	7.27	14.21
18	[P_6,6,6,14][Br]-CO₂	43	12.31	15.08

图3 UNIFAC官能团活度系数模型的计算值与IL-CO2体系的实验值比较

图4 不同ILs-CO2二元体系的UNIFAC模型预测的ARD分布

图5 UNIFAC模型拟合的基团相互作用参数（anm,amn ）分布

参考文献 32

[1]	LI Yi, SHANG Jiahui, ZHANG Chi, et al. The role of freshwater eutrophication in greenhouse gas emissions: A review[J]. Science of The Total Environment, 2021, 768: 144582.
[2]	KROON M C, ZUBEIR L F. Deep eutectic solvents for sustainable CO₂ capture[C]//Abu Dhabi International Petroleum Exhibition & Conference. Abu Dhabi, UAE: Society of Petroleum Engineers, 2016.
[3]	YANG Sheng, QIAN Yu, YANG Siyu. Development of a full CO₂ capture process based on the rectisol wash technology[J]. Industrial & Engineering Chemistry Research, 2016, 55(21): 6186-6193.
[4]	KOSTYANAYA Margarita I, NOVITSKII Eduard G, BAZHENOV Stepan D. CO₂ absorption/desorption on gas-liquid membrane contactors using monoethanolamine solvent: Comparison of porous and composite hollow fibers[J]. Key Engineering Materials, 2020, 869: 321-335.
[5]	AHMAD Naveed, LIN Xingyu, WANG Xiaoxiao, et al. Understanding the CO₂ capture performance by MDEA-based deep eutectics solvents with excellent cyclic capacity[J]. Fuel, 2021, 293: 120466.
[6]	SHANG Dawei, LIU Xinyan, BAI Lu, et al. Ionic liquids in gas separation processing[J]. Current Opinion in Green and Sustainable Chemistry, 2017, 5: 74-81.
[7]	SCHOLES Colin A, ANDERSON Clare J, STEVENS Geoff W, et al. Membrane gas separation-physical solvent absorption combined plant simulations for pre-combustion capture[J]. Energy Procedia, 2013, 37: 1039-1049.
[8]	SHARMA Pooja, SHARMA Shubham, KUMAR Harsh. Introduction to ionic liquids, applications and micellization behaviour in presence of different additives[J]. Journal of Molecular Liquids, 2024, 393: 123447.
[9]	EBRAHIMI Mohammad, FATYEYEVA Kateryna, KUJAWSKI Wojciech. Different approaches for the preparation of composite ionic liquid-based membranes for proton exchange membrane fuel cell applications-recent advancements[J]. Membranes, 2023, 13(6): 593.
[10]	FRIESS Karel, Pavel IZÁK, Magda KÁRÁSZOVÁ, et al. A review on ionic liquid gas separation membranes[J]. Membranes, 2021, 11(2): 97.
[11]	WATKINS Tylan, KUMAR Ashok, BUTTRY Daniel A. Designer ionic liquids for reversible electrochemical deposition/dissolution of magnesium[J]. Journal of the American Chemical Society, 2016, 138(2): 641-650.
[12]	TAHERI Mohsen, ZHU Ruisong, YU Gangqiang, et al. Ionic liquid screening for CO₂ capture and H₂S removal from gases: The syngas purification case[J]. Chemical Engineering Science, 2021, 230: 116199.
[13]	RASHID Taslim Ur. Ionic liquids: Innovative fluids for sustainable gas separation from industrial waste stream[J]. Journal of Molecular Liquids, 2021, 321: 114916.
[14]	GREER Adam J, JACQUEMIN Johan, HARDACRE Christopher. Industrial applications of ionic liquids[J]. Molecules, 2020, 25(21): 5207.
[15]	CHEN Yuqiu, LIU Xinyan, WOODLEY John M, et al. Gas solubility in ionic liquids: UNIFAC-IL model extension[J]. Industrial & Engineering Chemistry Research, 2020, 59(38): 16805-16821.
[16]	KLAMT Andreas, ECKERT Frank. COSMO-RS: A novel and efficient method for the a priori prediction of thermophysical data of liquids[J]. Fluid Phase Equilibria, 2000, 172(1): 43-72.
[17]	FANG Jing, ZHAO Rui, SU Weiyi, et al. A molecular design method based on the COSMO-SAC model for solvent selection in ionic liquid extractive distillation[J]. AIChE Journal, 2016, 62(8): 2853-2869.
[18]	COTO Baudilio, Inmaculada SUÁREZ, TENORIO Maria José, et al. Oil acidity reduction by extraction with imidazolium ionic liquids: Experimental, COSMO description and reutilization study[J]. Separation and Purification Technology, 2021, 254: 117529.
[19]	Urszula DOMAŃSKA, Michał WLAZŁO, Kamil PADUSZYŃSKI. Extraction of butan-1-ol from aqueous solution using ionic liquids: An effect of cation revealed by experiments and thermodynamic models[J]. Separation and Purification Technology, 2018, 196: 71-81.
[20]	BERALDO Cleiton S, LIANG Xiaodong, FOLLEGATTI-ROMERO Luis A. Predicting the solubility of gases in imidazolium-based ionic liquids with SAFT-VR Mie EoS by a novel approach based on COSMO[J]. Chemical Engineering Science, 2024, 285: 119610.
[21]	HAN Jingli, DAI Chengna, LEI Zhigang, et al. Gas drying with ionic liquids[J]. AIChE Journal, 2018, 64(2): 606-619.
[22]	DAI Chengna, LEI Zhigang, CHEN Biaohua. Gas solubility in long-chain imidazolium-based ionic liquids[J]. AIChE Journal, 2017, 63(6): 1792-1798.
[23]	LIU Xinyan, ZHOU Teng, ZHANG Xiangping, et al. Application of COSMO-RS and UNIFAC for ionic liquids based gas separation[J]. Chemical Engineering Science, 2018, 192: 816-828.
[24]	VENKATRAMAN Vishwesh, ALSBERG Bjørn Kåre. Predicting CO₂ capture of ionic liquids using machine learning[J]. Journal of CO₂Utilization, 2017, 21: 162-168.
[25]	SONG Zhen, SHI Huaiwei, ZHANG Xiang, et al. Prediction of CO₂ solubility in ionic liquids using machine learning methods[J]. Chemical Engineering Science, 2020, 223: 115752.
[33]	LU Tian, CHEN Feiwu. Multiwfn: A multifunctional wavefunction analyzer[J]. Journal of Computational Chemistry, 2012, 33(5): 580-592.
[26]	LEI Zhigang, DAI Chengna, LIU Xing, et al. Extension of the UNIFAC model for ionic liquids[J]. Industrial and Engineering Chemistry Research, 2012, 51(37): 12135-12144.
[27]	LEI Zhigang, DAI Chengna, YANG Qian, et al. UNIFAC model for ionic liquid-CO(H₂) systems: An experimental and modeling study on gas solubility[J]. AIChE Journal, 2014, 60(12): 4222-4231.
[28]	DONG Yichun, GUO Yanyan, ZHU Ruisong, et al. UNIFAC model for ionic liquids. 2. Revision and extension[J]. Industrial & Engineering Chemistry Research, 2020, 59(21): 10172-10184.
[29]	CHEN Guzhong, SONG Zhen, QI Zhiwen, et al. Neural recommender system for the activity coefficient prediction and UNIFAC model extension of ionic liquid-solute systems[J]. AIChE Journal, 2021, 67(4): e17171.
[30]	ZHU Peng, KANG Xuejing, LATIF Ullah, et al. A reliable database for ionic volume and surface: Its application to predict molar volume and density of ionic liquid[J]. Industrial & Engineering Chemistry Research, 2019, 58(23): 10073-10083.
[31]	HUANG Ying, DONG Haifeng, ZHANG Xiangping, et al. A new fragment contribution-corresponding states method for physicochemical properties prediction of ionic liquids[J]. AIChE Journal, 2013, 59(4): 1348-1359.
[32]	DITCHFIELD R, HEHRE W J, POPLE J A. Self‐consistent molecular‐orbital methods. IX. An extended Gaussian‐type basis for molecular‐orbital studies of organic molecules[J]. The Journal of Chemical Physics, 1971, 54(2): 724-728.