Multi-Objective Optimization of TETA Blended Amines for Microwave-Regenerated CO2 Capture via RSM and Entropy-Weighted TOPSIS

To improve regeneration performance and shorten desorption time in amine-based CO2 capture, this study proposes an integrated “blended-amine solvent and microwave regeneration” process. Triethylenetetramine (TETA) was used as the primary absorbent and blended with diethanolamine (DEA) and 2-amino-2-methyl-1-propanol (AMP). Response Surface Methodology (RSM, Box–Behnken design) was employed to establish formulation–performance relationships, and an entropy-weighted TOPSIS method was further applied for multi-objective evaluation and optimization. The optimal formulation consisted of TETA, DEA, and AMP at a mass ratio of 6:1:2. Under the optimized conditions (20 wt% aqueous solvent, 30 °C absorption, 95 °C microwave regeneration), the solvent achieved an absorption capacity of 1.0 mol CO2·mol−1 amine with a CO2 recovery of 93.56%. Compared with conventional heating, microwave regeneration markedly accelerated CO2 desorption, reducing regeneration time from 30 min to 4 min. The estimated total regeneration energy was approximately 2.4 GJ·t−1 CO2 under microwave heating for the optimized blend. In addition, among the water/n-butanol formulations tested, the fully aqueous system showed the best overall absorption–regeneration performance. Overall, the data-driven solvent design coupled with microwave regeneration offers a practical route toward more efficient CO2 capture processes.

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Publication Details

Journal
Separations
Published
2026-08-26
DOI
https://doi.org/10.3390/separations13090242
Primary Topic
Carbon Dioxide Capture Technologies
Type
article
Field-Weighted Citation Impact
0.00

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article

Multi-Objective Optimization of TETA Blended Amines for Microwave-Regenerated CO2 Capture via RSM and Entropy-Weighted TOPSIS

Rezeye Rehemituli, Qiaoyu Liu, Xinyue Wang, Yansheng Liu et al.
Separations
Carbon Dioxide Capture Technologies
article

Multi-Objective Optimization of TETA Blended Amines for Microwave-Regenerated CO2 Capture via RSM and Entropy-Weighted TOPSIS

Rezeye Rehemituli, Qiaoyu Liu, Xinyue Wang, Yansheng Liu, Junwei Hou, Jingmao Wang, Ziheng Zhang
article en

Abstract

To improve regeneration performance and shorten desorption time in amine-based CO2 capture, this study proposes an integrated “blended-amine solvent and microwave regeneration” process. Triethylenetetramine (TETA) was used as the primary absorbent and blended with diethanolamine (DEA) and 2-amino-2-methyl-1-propanol (AMP). Response Surface Methodology (RSM, Box–Behnken design) was employed to establish formulation–performance relationships, and an entropy-weighted TOPSIS method was further applied for multi-objective evaluation and optimization. The optimal formulation consisted of TETA, DEA, and AMP at a mass ratio of 6:1:2. Under the optimized conditions (20 wt% aqueous solvent, 30 °C absorption, 95 °C microwave regeneration), the solvent achieved an absorption capacity of 1.0 mol CO2·mol−1 amine with a CO2 recovery of 93.56%. Compared with conventional heating, microwave regeneration markedly accelerated CO2 desorption, reducing regeneration time from 30 min to 4 min. The estimated total regeneration energy was approximately 2.4 GJ·t−1 CO2 under microwave heating for the optimized blend. In addition, among the water/n-butanol formulations tested, the fully aqueous system showed the best overall absorption–regeneration performance. Overall, the data-driven solvent design coupled with microwave regeneration offers a practical route toward more efficient CO2 capture processes.

SeparationsVol. 13(9)
China University of Petroleum, Beijing (CN)
Government of Xinjiang Uygur Autonomous Region of China, National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 19%
Carbon Dioxide Capture Technologies
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Multi-Objective Optimization of TETA Blended Amines for Microwave-Regenerated CO2 Capture via RSM and Entropy-Weighted TOPSIS — Rezeye Rehemituli, Qiaoyu Liu, et al. · Separations (2026) | TGRS Research Map | TGRS