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Tong S, Zhu J, Wang Z, Yan J. Highly Selective SO 2 Capture by Triazine-Functionalized Triphenylamine-Based Nanoporous Organic Polymers. ACS APPLIED MATERIALS & INTERFACES 2024; 16:42717-42725. [PMID: 39086140 DOI: 10.1021/acsami.4c08905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/02/2024]
Abstract
The emissions of sulfur dioxide (SO2) from combustion exhaust gases pose significant risks to public health and the environment due to their harmful effects. Therefore, the development of highly efficient adsorbent polymers capable of capturing SO2 with high capacity and selectivity has emerged as a critical challenge in recent years. However, existing polymers often exhibit poor SO2/CO2 and SO2/N2 selectivity. Herein, we report two triazine-functionalized triphenylamine-based nanoporous organic polymers (ANOP-6 and ANOP-7) that demonstrate both good SO2 uptake and high SO2/CO2 and SO2/N2 selectivity. These polymers were synthesized through cost-effective Friedel-Crafts reactions using cyanuric chloride, 3,6-diphenylaminecarbazole, and 2,2',7,7'-tetrakis(diphenylamino)-9,9'-spirobifluorene. The resultant ANOPs are composed of triazine and triphenylamine units and feature an ultramicroporous structure. Remarkably, ANOPs exhibit impressive adsorption capacities for SO2, with uptakes of approximately 3.31-3.72 mmol·g-1 at 0.1 bar, increasing to 9.52-9.94 mmol·g-1 at 1 bar. The static adsorption isotherms effectively illustrate the ability of ANOPs to separate SO2 from SO2/CO2 and SO2/N2 mixtures. At 298 K and 1 bar, ANOP-6 shows outstanding selectivity toward SO2/CO2 (248) and SO2/N2 (13146), surpassing all previously reported triazine-based nanoporous organic polymers. Additionally, dynamic breakthrough tests demonstrate the superior separation properties of ANOPs for SO2 from an SO2/CO2/N2 mixture. ANOPs exhibit a breakthrough time of 73.1 min·g-1 and a saturated SO2 capacity of 0.53 mmol·g-1. These results highlight the exceptional adsorption properties of ANOPs for SO2, indicating their promising potential for the highly efficient capture of SO2 from flue gas.
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Affiliation(s)
- Sihan Tong
- International Scientific and Technological Cooperation Base of Industrial Solid Waste Cyclic Utilization and Advanced Materials, School of Materials Science and Engineering, North Minzu University, Yinchuan 750021, China
| | - Jiangli Zhu
- International Scientific and Technological Cooperation Base of Industrial Solid Waste Cyclic Utilization and Advanced Materials, School of Materials Science and Engineering, North Minzu University, Yinchuan 750021, China
| | - Zefeng Wang
- College of Ecology, Lishui University, Lishui 323000, China
- R&D Center of Green Manufacturing New Materials and Technology of Synthetic Leather, Sichuan University-Lishui University, Lishui 323000, China
| | - Jun Yan
- International Scientific and Technological Cooperation Base of Industrial Solid Waste Cyclic Utilization and Advanced Materials, School of Materials Science and Engineering, North Minzu University, Yinchuan 750021, China
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Guan K, Xu F, Huang X, Li Y, Guo S, Situ Y, Chen Y, Hu J, Liu Z, Liang H, Zhu X, Wu Y, Qiao Z. Deep learning and big data mining for Metal-Organic frameworks with high performance for simultaneous desulfurization and carbon capture. J Colloid Interface Sci 2024; 662:941-952. [PMID: 38382377 DOI: 10.1016/j.jcis.2024.02.098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Revised: 01/23/2024] [Accepted: 02/12/2024] [Indexed: 02/23/2024]
Abstract
Carbon capture and desulfurization of flue gases are crucial for the achievement of carbon neutrality and sustainable development. In this work, the "one-step" adsorption technology with high-performance metal-organic frameworks (MOFs) was proposed to simultaneously capture the SO2 and CO2. Four machine learning algorithms were used to predict the performance indicators (NCO2+SO2, SCO2+SO2/N2, and TSN) of MOFs, with Multi-Layer Perceptron Regression (MLPR) showing better performance (R2 = 0.93). To address sparse data of MOF chemical descriptors, we introduced the Deep Factorization Machines (DeepFM) model, outperforming MLPR with a higher R2 of 0.95. Then, sensitivity analysis was employed to find that the adsorption heat and porosity were the key factors for SO2 and CO2 capture performance of MOF, while the influence of open alkali metal sites also stood out. Furthermore, we established a kinetic model to batch simulate the breakthrough curves of TOP 1000 MOFs to investigate their dynamic adsorption separation performance for SO2/CO2/N2. The TOP 20 MOFs screened by the dynamic performance highly overlap with those screened by the static performance, with 76 % containing open alkali metal sites. This integrated approach of computational screening, machine learning, and dynamic analysis significantly advances the development of efficient MOF adsorbents for flue gas treatment.
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Affiliation(s)
- Kexin Guan
- Guangzhou Key Laboratory for New Energy and Green Catalysis, School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, China
| | - Fangyi Xu
- Guangzhou Key Laboratory for New Energy and Green Catalysis, School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, China
| | - Xiaoshan Huang
- Guangzhou Key Laboratory for New Energy and Green Catalysis, School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, China
| | - Yu Li
- Guangzhou Key Laboratory for New Energy and Green Catalysis, School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, China
| | - Shuya Guo
- Guangzhou Key Laboratory for New Energy and Green Catalysis, School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, China
| | - Yizhen Situ
- Guangzhou Key Laboratory for New Energy and Green Catalysis, School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, China; State Key Laboratory of Organic-Inorganic Composites, Beijing University of Chemical Technology, Beijing 100029, China
| | - You Chen
- Guangzhou Key Laboratory for New Energy and Green Catalysis, School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, China
| | - Jianming Hu
- College of Economics and Statistics, Guangzhou University, Guangzhou 510006, China
| | - Zili Liu
- Guangzhou Key Laboratory for New Energy and Green Catalysis, School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, China
| | - Hong Liang
- Guangzhou Key Laboratory for New Energy and Green Catalysis, School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, China
| | - Xin Zhu
- Guangzhou Key Laboratory for New Energy and Green Catalysis, School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, China; College of Economics and Statistics, Guangzhou University, Guangzhou 510006, China.
| | - Yufang Wu
- Guangzhou Key Laboratory for New Energy and Green Catalysis, School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, China.
| | - Zhiwei Qiao
- Guangzhou Key Laboratory for New Energy and Green Catalysis, School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, China.
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Gang SQ, Liu ZY, Wu SX, Yang S, Wang R, Du JL. A stable Zr(IV)-MOF for efficient removal of trace SO 2 from flue gas in dry and humid conditions. JOURNAL OF HAZARDOUS MATERIALS 2024; 470:134180. [PMID: 38569342 DOI: 10.1016/j.jhazmat.2024.134180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2024] [Revised: 03/24/2024] [Accepted: 03/30/2024] [Indexed: 04/05/2024]
Abstract
Obtaining suitable adsorbents for selective separation of SO2 from flue gas still remains an important issue. A stable Zr(IV)-MOF (Zr-PTBA) can be conveniently synthesized through the self-assembly of a tetracarboxylic acid ligand (H4L = 4,4',4'',4'''-(1,4-phenylenebis(azanetriyl))tetrabenzoic acid) and ZrCl4 in the presence of trace water. It exhibits a three-dimensional porous structure. The BET surface area is 1112.72 m2/g and the average pore size distribution focus on 5.9, 8.0 and 9.3 Å. Interestingly, Zr-PTBA shows selective adsorption of SO2. The maximum uptake reaches 223.21 cm3/g at ambient condition. While it exhibits lower adsorption uptake of CO2 (30.50 cm3/g) and hardly adsorbs O2 (2.57 cm3/g) and N2 (1.31 cm3/g). Higher IAST selectivities of SO2/CO2 (21.9), SO2/N2 (912.7), SO2/O2 (2269.9) and SO2/CH4 (85.0) have been obtained, which reveal its' excellent gas separation performance. Breakthrough experiment further confirms its application for flue gas deep desulfurization both in dry and humid conditions. Furthermore, the gas adsorption results and mechanisms have also been studied by theoretical calculations.
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Affiliation(s)
- Shu-Qi Gang
- State Key Laboratory of New Pharmaceutical Preparations and Excipients, Key Laboratory of Medicinal Chemistry and Molecular Diagnosis of Ministry of Education, Key Laboratory of Chemical Biology of Hebei Province (No. 22567635H), College of Chemistry and Materials Science, Hebei University, Baoding 071002, China
| | - Zi-Yue Liu
- State Key Laboratory of New Pharmaceutical Preparations and Excipients, Key Laboratory of Medicinal Chemistry and Molecular Diagnosis of Ministry of Education, Key Laboratory of Chemical Biology of Hebei Province (No. 22567635H), College of Chemistry and Materials Science, Hebei University, Baoding 071002, China
| | - Su-Xia Wu
- Hebei Normal University of Science and Technology, Qinhuangdao 066600, China
| | - Shu Yang
- State Key Laboratory of New Pharmaceutical Preparations and Excipients, Key Laboratory of Medicinal Chemistry and Molecular Diagnosis of Ministry of Education, Key Laboratory of Chemical Biology of Hebei Province (No. 22567635H), College of Chemistry and Materials Science, Hebei University, Baoding 071002, China
| | - Ruihan Wang
- Hebei Normal University of Science and Technology, Qinhuangdao 066600, China.
| | - Jian-Long Du
- State Key Laboratory of New Pharmaceutical Preparations and Excipients, Key Laboratory of Medicinal Chemistry and Molecular Diagnosis of Ministry of Education, Key Laboratory of Chemical Biology of Hebei Province (No. 22567635H), College of Chemistry and Materials Science, Hebei University, Baoding 071002, China.
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