Kinetics of CO2 capture by novel amine-functionalized magnesium oxide adsorbents

A sustainable and economical solution for CO2 capture with biobased carbon materials derived from palm kernel shells

This study investigates the synthesize of activated carbon for carbon dioxide adsorption using palm kernel shell (PKS), a by-product of oil palm industry. The adsorbent synthesis involved a simple two-step carbonization method. Firstly, PKS was activated with potassium oxide (KOH), followed by functionalization with magnesium oxide (MgO). Surface analysis revealed that KOH activated PKS has resulted in a high specific surface area of 1086 m2/g compared to untreated PKS (435 m2/g). However, impregnation of MgO resulted in the reduction of surface area due to blockage of pores by MgO. Thermogravimetric analysis (TGA) demonstrated that PKS-based adsorbents exhibited minimal weight loss of less than 30% up to 500 °C, indicating their suitability for high-temperature applications. CO2 adsorption experiments revealed that PKS-AC-MgO has achieved a higher adsorption capacity of 155.35 mg/g compared to PKS-AC (149.63 mg/g) at 25 °C and 5 bars. The adsorption behaviour of PKS-AC-MgO was well fitted by both the Sips and Langmuir isotherms, suggesting a combination of both heterogeneous and homogeneous adsorption and indicating a chemical reaction between MgO and CO2. Thermodynamic analysis indicated a spontaneous and thermodynamically favourable process for CO2 capture by PKS-AC-MgO, with negative change in enthalpy (- 0.21 kJ/mol), positive change in entropy (2.44 kJ/mol), and negative change in Gibbs free energy (- 729.61 J/mol, - 790.79 J/mol, and - 851.98 J/mol) across tested temperature. Economic assessment revealed that the cost of PKS-AC-MgO is 21% lower than the current market price of commercial activated carbon, indicating its potential for industrial application. Environmental assessment shows a significant reduction in greenhouse gas emissions (381.9 tCO2) through the utilization of PKS-AC-MgO, underscoring its environmental benefits. In summary, the use of activated carbon produced from PKS and functionalised with MgO shows great potential for absorbing CO2. This aligns with the ideas of a circular economy and sustainable development.

Ensemble meta machine learning for predicting the adsorption of anionic and cationic dyes from aqueous solutions using Polymer/graphene/clay/MgFeAl-LTH nanocomposite

Adsorption is one of the most promising wastewater treatment methods due to its simplicity and efficacy at ambient temperature and pressure. However, the technical and economic feasibility of this process largely depends on the performance of the utilized adsorbents. In this study, a promising adsorbent made of polyethyleneimine, graphene oxide (GO), bentonite, and MgFeAl-layered triple hydroxide (MgFeAl-LTH) has been synthesized and characterized. The results revealed that the synthesized nanocomposite (abbreviated as PGB-LTH) possesses good porosity and crystallinity. The adsorption performance of the PGB-LTH nanocomposite towards two harmful water pollutants (i.e., methyl orange (MO) and crystal violet (CV)) was investigated, and the results revealed that the nanocomposite outperforms its parental materials (i.e., GO, bentonite, and MgFeAl-LTH). The maximum adsorption capacity (qmax) of MO and CV onto the nanocomposite could reach 1666.7 and 1250.0 mg/g, respectively, as predicted using the Langmuir adsorption isotherm. Additionally, the PGB-LTH nanocomposite is highly reusable with an insignificant decline in performance upon repetitive use. In terms of thermodynamics, MO adsorption onto the nanocomposite is exothermic while CV adsorption is endothermic despite that both dyes adsorb spontaneously as revealed by the negative values of the Gibbs free energy change at all the examined temperatures. The generated adsorption data were utilized for constructing and assessing ensemble meta-machine learning techniques aimed at cost-effective simulation and prediction of the proposed adsorption method. Bagging and boosting methods were developed and evaluated intensively using the obtained adsorption data. The Extra Trees model achieved promising results as evidenced by the high correlation coefficient of 99% as well as low computed RMSE and MAE errors of 11.42 and 5.11, respectively, during the testing phase. These results demonstrate the model strong capability to effectively simulate and predict the adsorption process in question.

Mg-O-F Nanocomposite Catalysts Defend against Global Warming via the Efficient, Dynamic, and Rapid Capture of CO2 at Different Temperatures under Ambient Pressure

The utilization of Mg-O-F prepared from Mg(OH)₂ mixed with different wt % of F in the form of (NH₄F·HF), calcined at 400 and 500 °C, for efficient capture of CO₂ is studied herein in a dynamic mode. Two different temperatures were applied using a slow rate of 20 mL·min^-1 (100%) of CO₂ passing through each sample for only 1 h. Using the thermogravimetry (TG)-temperature-programed desorption (TPD) technique, the captured amounts of CO₂ at 5 °C were determined to be in the range of (39.6-103.9) and (28.9-82.1) mg_CO2 ·g^-1 for samples of Mg(OH)₂ mixed with 20-50% F and calcined at 400 and 500 °C, respectively, whereas, at 30 °C, the capacity of CO₂ captured is slightly decreased to be in the range of (32.2-89.4) and (20.9-55.5) mg_CO2 ·g^-1, respectively. The thermal decomposition of all prepared mixtures herein was examined by TG analysis. The obtained samples calcined at 400 and 500 °C were characterized by X-ray diffraction and surface area and porosity measurements. The total number of surface basic sites and their distribution over all samples was demonstrated using TG- and differential scanning calorimetry-TPD techniques using pyrrole as a probe molecule. Values of (ΔH) enthalpy changes corresponding to the desorption steps of CO₂ were calculated for the most active adsorbent in this study, that is, Mg(OH)₂ + 20% F, at 400 and 500 °C. This study's findings will inspire the simple preparation and economical design of nanocomposite CO₂ sorbents for climate change mitigation under ambient conditions.