Boosting CO<sub>2</sub> Uptake Potential of Amine Functionalized UiO-66 Nanoparticles Using Sonochemical Synthesis: Experimental Observations, Isotherm, Response Surface Methodology, and Exploring Artificial Neural Network Modeling

The rising carbon dioxide (CO2) concentration in the atmosphere poses significant environmental problems, especially global warming and climate change. To mitigate this issue, one of the most effective ways to enhance CO2 uptake efficiency at low pressure is to impregnate amine into the porous network structure of a suitable metal–organic framework (MOF) adsorbent. In this context, the influence of functionalization of UiO-66 nanoparticles with aminoethylethanolamine (AEEA) over CO2 adsorption was investigated. UiO-66 is renowned for its outstanding thermal and chemical stability compared to other materials. We synthesized nanoporous UiO-66 and UiO-66-NH2 adsorbents by the novel sonochemical method in only 2 h. The amine-incorporated materials were characterized using HRXRD, Raman spectroscopy, FTIR, FESEM, EDX, HRTEM, TGA, XPS, BET, and CHNS analysis, revealing findings comparable to pristine UiO-66 nanoparticles. The CO2 uptake behavior of the samples was analyzed employing the iSorb HP2 high-pressure gas adsorption analyzer under conditions of pressure and temperature swings, ranging from 0 to 30 bar and 25 to 80 °C, respectively. Various mathematical isotherm models were developed to correlate and forecast experimental CO2 sorption capability. Response surface methodology based on the Box–Behnken design is a statistical model employed to optimize circumstances for CO2 adsorption performance. The multilayer perceptron artificial neural networks model was developed to predict CO2 sorption properties by employing a back-propagation training approach. Remarkably, the 30% AEEA modified UiO-66 adsorbent manifested a significant augmentation in CO2 uptake efficacy (3.983 mmol/g), which was 3.06 times greater than the pristine UiO-66 nanoparticles (1.301 mmol/g) at the temperature of 25 °C and a partial pressure of 1 bar.

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Publication Details

Journal
Energy & Fuels
Published
2025-06-17
DOI
https://doi.org/10.1021/acs.energyfuels.5c01777
Citations
3
Primary Topic
Carbon Dioxide Capture Technologies
Type
article
Field-Weighted Citation Impact
2.14
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article

Boosting CO2 Uptake Potential of Amine Functionalized UiO-66 Nanoparticles Using Sonochemical Synthesis: Experimental Observations, Isotherm, Response Surface Methodology, and Exploring Artificial Neural Network Modeling

Radhapada Manna, Guruprasad Bhattacharya, Sibsankar Rahut, Amar Nath Samanta et al.
3 citations
Energy & Fuels
Carbon Dioxide Capture Technologies
2.14
article

Boosting CO2 Uptake Potential of Amine Functionalized UiO-66 Nanoparticles Using Sonochemical Synthesis: Experimental Observations, Isotherm, Response Surface Methodology, and Exploring Artificial Neural Network Modeling

Radhapada Manna, Guruprasad Bhattacharya, Sibsankar Rahut, Amar Nath Samanta, Puspendu Sardar, Shubham Raj, D. Krishna Kumar
article en
3 citations

Abstract

The rising carbon dioxide (CO2) concentration in the atmosphere poses significant environmental problems, especially global warming and climate change. To mitigate this issue, one of the most effective ways to enhance CO2 uptake efficiency at low pressure is to impregnate amine into the porous network structure of a suitable metal–organic framework (MOF) adsorbent. In this context, the influence of functionalization of UiO-66 nanoparticles with aminoethylethanolamine (AEEA) over CO2 adsorption was investigated. UiO-66 is renowned for its outstanding thermal and chemical stability compared to other materials. We synthesized nanoporous UiO-66 and UiO-66-NH2 adsorbents by the novel sonochemical method in only 2 h. The amine-incorporated materials were characterized using HRXRD, Raman spectroscopy, FTIR, FESEM, EDX, HRTEM, TGA, XPS, BET, and CHNS analysis, revealing findings comparable to pristine UiO-66 nanoparticles. The CO2 uptake behavior of the samples was analyzed employing the iSorb HP2 high-pressure gas adsorption analyzer under conditions of pressure and temperature swings, ranging from 0 to 30 bar and 25 to 80 °C, respectively. Various mathematical isotherm models were developed to correlate and forecast experimental CO2 sorption capability. Response surface methodology based on the Box–Behnken design is a statistical model employed to optimize circumstances for CO2 adsorption performance. The multilayer perceptron artificial neural networks model was developed to predict CO2 sorption properties by employing a back-propagation training approach. Remarkably, the 30% AEEA modified UiO-66 adsorbent manifested a significant augmentation in CO2 uptake efficacy (3.983 mmol/g), which was 3.06 times greater than the pristine UiO-66 nanoparticles (1.301 mmol/g) at the temperature of 25 °C and a partial pressure of 1 bar.

Energy & FuelsVol. 39(25)
Indian Institute of Technology Kharagpur (IN), NIMS University (IN)
Openalex Percentile: Top 13%
Carbon Dioxide Capture Technologies
2.14
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