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Quantifying Absorption‐Hydrolysis‐Desorption Coupling in primary amines for COS removal within a molecular-descriptor framework

Journal 2026 · IF 7.2 · 14(2): 121547 · 发表于 2026 年 1 月 31 日
作者: Bin Zhao,Bo Zhou,Peidong Zuo,Liping Chang,Jiawei Zhong,Mengmeng Wu,Chao Yang,Zhifeng Qin
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摘要

Primary amines are widely employed for Carbonyl sulfide (COS) removal owing to their rapid reactivity, yet insufficient regeneration remains a critical bottleneck for cyclic utilization. This limitation essentially arises from the lack of quantitative understanding of the coupling among absorption, hydrolysis, and desorption. In this study, nine primary amines were systematically evaluated, and their behaviors in absorption, hydrolysis, and desorption were integrated with molecular descriptors to construct a quantitative framework. The results showed that DL-2-aminobutanol (DL-2-AP) and 1-aminopropanol (1-AP) achieved nearly complete COS removal with hydrolysis yields of 60 %, stable regeneration with only a 5 % decline over five cycles, and lower regeneration energy than ethanolamine (MEA, >4300 kJ/mol), thereby showing the most favorable overall performance. Further analysis suggested that molecular features including Minimum Electrostatic Potential (ESP min ) around −2 eV, Highest Occupied Molecular Orbital (HOMO) energy on the order of −31 kJ/mol, viscosity near 0.9 cP, Mean SHI within 70–90 kJ/mol, and pKa in a mildly alkaline range (approximately 9–10) together with balanced solubility-activity were statistically associated with more favorable coupling of absorption, hydrolysis, and desorption. Moreover, multiple linear regression models based on ESP min , mean steric hindrance index (Mean SHI), and pKa showed high accuracy (R 2 = 0.85–0.97), suggesting that absorption and desorption exhibited the strongest statistical association with ESP min , whereas hydrolysis was most strongly associated with pKa within this regression based framework. This study establishes a predictive framework bridging molecular design with industrial COS removal, offering descriptor based insight and practical guidance.