DFT Studies on Thermal and Oxidative Degradation of Monoethanolamine

Thermal oxidation mechanism of palmitic aicd

The oxidation and degradation of fats lead to a decrease in the nutritional value of food and pose safety concerns. Saturated fatty acids also hold a significant position in the field of lipid oxidation. In this study, the oxidation products of methyl palmitate were investigated by using gas chromatography mass spectrometry (GC-MS). Seven monohydroperoxides and 72 secondary oxidation products were detected. Combined with density functional theory (DFT) calculations, the formation mechanisms of oxidation products can be summarized into four stages. The initial stage involved the formation of monohydroperoxides and alkanes, followed by the subsequent stage involving methyl x-oxo(hydroxy)hexadecanoates. The third stage involved the formation of methyl ketones, carboxylic acids, and aldehydes, while the final stage involved lactones. Meanwhile, methyl ketones were the most abundant oxidation product, approximately 25 times more abundant than aldehydes; the calculated results agreed well with the experimental results. The establishment of a comprehensive thermal oxidation mechanism for palmitic acid provided a new foundation for future lipid oxidation analyses.

Hybrid Smart Strategies to Predict Amine Thermal Degradation in Industrial CO2 Capture Processes

CO2 emission reduction is an essential step to achieve the climate change targets. Solvent-based post-combustion CO2 capture (PCC) processes are efficient to be retrofitted to the existing industrial operations/installations. Solvent degradation (and/or loss) is one of the main concerns in the PCC processes. In this study, the thermal degradation of monoethanolamine (MEA) is investigated through the utilization of hybrid connectionist strategies, including an artificial neural network-particle swarm optimization (ANN-PSO), a coupled simulated annealing-least squares support vector machine (CSA-LSSVM), and an adaptive neuro-fuzzy inference system (ANFIS). Moreover, gene expression programming (GEP) is employed to generate a correlation that relates the solvent concentration to the operating variables involved in the adverse phenomenon of solvent thermal degradation. The input variables are the MEA initial concentration, CO2 loading, temperature, and time, and the output variable is the remaining/final MEA concentration after the degradation phenomenon. According to the training and testing phases, the most accurate model is ANFIS, and the reliability/performance of its optimal network is assessed by the coefficient of determination (R2), mean squared error, and average absolute relative error percentage, which are 0.992, 0.066, and 2.745, respectively. This study reveals that the solvent initial concentration has the most significant impact, and temperature plays the second most influential effect on solvent degradation. The developed models can be used to predict the thermal degradation of any solvent in a solvent-based PCC process regardless of the complicated reactions involved in the degradation phenomenon. The models introduced in this study can be employed for the development of more accurate hybrid models to optimize the proposed systems in terms of cost, energy, and environmental prospects.

Mechanism of the initial oxidation of monounsaturated fatty acids

The development of detection technology prompts the need to elaborate on the theory behind the oxidation of unsaturated fatty acids. This study integrates the detection of monounsaturated fatty acid oxidation at 60 °C with computational simulations to provide an advanced theoretical basis for the formation of hydroperoxides and allyl. The results indicate that oxidation reaction led to increases of 3.4 mg/g for 8-hydroperoxy-trans-9-octadecenoate (trans8) and 2.7 mg/g for 9-hydroperoxy-trans-10-octadecenoate (trans9) and 10-hydroperoxy-trans-8-octadecenoate (trans10) despite low temperatures. The energy of peroxyl radical production was 0.36 kcal/mol and that of allylic isomerization was 78.52 kcal/mol, indicating the existence of two pathways for hydroperoxides formation: β-fragmentation and the allylic isomerization. Structural equation modeling (SEM) verified the multistep competitive side reactions that occurred during oxidation. This finding provides a new basis for future analysis of lipid oxidation.

Why does 2-(2-aminoethylamino)ethanol have superior CO2 separation performance to monoethanolamine? A computational study

Our computational reaction analysis shows that 2-(2-aminoethylamino)ethanol (AEEA) has superior performance to monoethanolamine for CO₂ separation, in terms of its ability to sorb CO₂ by its primary amine and desorb CO₂ by its secondary amine.