This study investigates and validates a thermodynamic model for aqueous ammonia (NH3) in postcombustion CO2 capture, focusing on both vapor-liquid equilibrium (VLE) and NH4HCO3 precipitation. Experimental VLE data at 4-8 wt % NH3 (40-80 °C) and existing literature data sets were used to refine an electrolyte nonrandom two-liquid (e-NRTL) model. The results highlight that lower NH3 concentrations (under 7 wt %) eliminate solid precipitation (solidification) risk but may raise regeneration energy, while higher concentrations provide reduced circulation flow rates yet risk solid formation at high CO2 loadings. By applying a simplified regeneration energy analysis, we illustrate how stripper temperature, stripper pressure, and NH3 concentration influence the components of regeneration energy: reaction heat, sensible heat, and latent heat. For a 10 wt % NH3 solution, an optimal stripper temperature of about 130.0 °C and total pressure of 800 kPa are identified to minimize the total reboiler duty (2.90 GJ/tCO2). However, a further pressure increase reduces reaction and latent heat but simultaneously boosts lean loading, raising the sensible heat requirement. Overall, the thermodynamic model and parametric study provide operational strategies to reduce CO2 capture costs, highlighting temperature control and NH3 concentration as dominant factors.

This study compares conventional Fe-based high-pressure (Fe-HB@HP) and Ru-based low-pressure (Ru-HB@LP) Haber-Bosch processes for gray, blue, and green NH3 synthesis, focusing on energy, economic, and environmental (3 E) aspects. Specific energy consumption (SEC), levelized cost of ammonia (LCOA), and global warming potential (GWP) were evaluated at pressures ranging from 50 to 300 bar. Results indicate that at 50 bar, the Rubased process achieves the lowest total SEC (4.53 GJ/tonne NH3). However, if residual energy is fully utilized, a moderate pressure (150 bar) with an Fe-based catalyst yields a net SEC of 3.67 GJ/tonne NH3. Economically, RuHB@LP (50 bar) can be up to 10 % cheaper to operate than Fe-HB@HP (150 bar), despite the higher cost of Rubased catalysts. However, the green NH3 reaches a comparable LCOA to gray NH3 only if additional policy support compensates for green NH3's higher production expenses. From an environmental aspect, switching from gray to blue NH3 cuts CO2 emissions by about 80 %, while green NH3 reduces them by up to 90 %. Overall, the results highlight the trade-offs between energy, cost, and CO2 emissions: lower pressures minimize costs, while higher pressures lead to reduced GWP. Balancing these factors is critical to advancing sustainable NH3 production, especially as catalyst and renewable energy technologies continue to evolve.

The contribution of solvent regeneration energy to amine-based CO2 capture processes is a major hurdle to their large-scale economic viability. It is important to develop solvents that reduce CO2 capture cost without compromising the process performance or operations. To reduce regeneration energy, this study focuses on the development of aqueous blends of piperazine (PZ) and 3-dimethylamino-1-propanol (3DMA1P) as an energy-efficient absorbent for CO2 capture. The study relies on rigorous modeling, supported by experimental data. The experimental data from this study and the literature includes CO2 solubility, NMR speciation, heat of absorption, and physical properties. To determine the potential application of PZ-3DMA1P blend for CO2 capture, their equilibrium CO2 solubility, cyclic capacity, heat of absorption, and, more importantly, solvent regeneration energy was investigated. Regeneration energy is calculated and evaluated under the influence of various operating parameters such as absorber temperature (313.15–343.15 K), stripper temperature (373.15–403.15 K), CO2 partial pressure (1–30 kPa), stripper total pressure (200–400 kPa), CO2 recovery (80–95 %), amine blending ratio (PZ:3DMA1P, 0–10:40–30 wt.%) and water concentration (60–90 wt.%). The results were compared with those obtained under the same operating conditions using monoethanolamine (MEA) 30 and 40 wt.%, and CESAR-1, the benchmark solvents. Results of the current study for blends of PZ and 3DMA1P are promising, and the solvent system exhibits higher CO2 absorption capacity and lower regeneration energy compared to MEA and CESAR-1. A comprehensive parametric analysis of regeneration energy enhances the applicability of the results across a diverse range of industries.

Chemical absorption using amine-based aqueous solutions is a promising approach for limiting CO2 emissions. This study evaluated the performance of commercial amines, including monoethanolamine (MEA), diethanolamine (DEA), diisopropanolamine (DIPA), N-methyldiethanolamine (MDEA), triethanolamine (TEA), and 2-amino-2-methyl-1-propanol (AMP), along with their binary mixtures, with a focus on their synergistic effect in reducing the regeneration energy. The thermodynamic behavior of these aqueous amine systems for CO2 capture was analyzed using the electrolyte nonrandom two-liquid model; the shortcut method was used to estimate the regeneration energy. The CO2 loading ratio, concentrations of the molecules and ions in the liquid phase, heat of absorption, pH, and regeneration energy were included in the analysis. Amine blending was found to synergistically lower the regeneration energy in the following two cases. First, blending carbamate-forming and non-carbamate-forming amines enhanced carbamate formation, thereby increasing the CO2 cyclic capacity and reducing the regeneration energy in the DIPA-MDEA and DEA-AMP systems. Second, the MEA-MDEA system revealed an optimal blending ratio for balancing different heat components (sensible, reaction, and latent heat). These findings offer a guide for selecting and blending amines to optimize the CO2 capture performance.

Data driven thermodynamic models has a great potential to add value to the accuracy of simulation processes. In this study experimental data driven e-NRTL activity coefficient model is used to evaluate the behavior of MEA/ AMP and MDEA/AMP aqueous systems for biogas upgrading. The vapor liquid equilibrium (VLE) experimental data is used for regression of the electrolyte pair parameters of e-NRTL activity coefficient model, which were then used to design the process for biogas upgrading by using Aspen Plus in combination with MATLAB. Experiments have been carried out for CO2 solubility as a function of CO2 partial pressure (PCO2 ) at different amine blending ratios such as 9/21/70, 15/15/70, and 21/9/70 (w/w/w percent) for each MEA/AMP/H2O and MDEA/ AMP/H2O systems at a wide temperature range of 323.15-383.15 K. The importance of regressed parameters was confirmed through global sensitivity analysis (GSA) using Monte Carlo simulation. The local sensitivity analysis (LSA) and GSA for biogas upgrading process based on data driven thermodynamic modeling have been carried out in terms of the biomethane purity, reboiler heat duty, and methane slip. Finally, the optimal process parameters were found through multi-objective optimization (MOO) for developed biogas upgrading process.

Catalytic conversion of carbon dioxide (CO2) into value-added products is a promising approach to address the sustainable energy crisis and control the CO2 emissions. Cycloaddition of CO2, photocatalytic, and electrocatalytic reduction of CO2 into fuels and chemicals have attracted extensive attention among various conversion methods. However, challenges such as low CO2 uptake, desired chemical kinetics and selectivity, thermodynamic stability, lower CO2 conversion, light absorption efficiency, understanding of reaction mechanisms, high overpotential, Faradaic efficiency, scalability and practicality still exist. Thus, the fabrication of efficient catalysts and electrodes for CO2 conversion is an essential avenue to explore. Among the most promising catalysts, carbon nitrides (CNs) are extensively investigated for CO2 conversion due to their abundance, low price, morphology, suitable bandgap, large specific surface area and catalytic activity, high resistance, and eco-friendliness. Due to the poor performance of pure CNs in CO2 conversion, developing engineered materials in different forms and compositions with high-performance is essential.This study offers a comprehensive overview of the current research progress, synthesis, characterization, catalytic applications of CN based catalysts and electrodes for CO2 conversion. Critical parameters related to synthesis, catalysis and performance of CN based catalysts for CO2 conversion are discussed in detail. The study also comprehensively analyses challenges and prospects for developing carbon nitride-based catalysts for CO2 conversion.

Ethylene oxide (EO) is a pivotal intermediate in the chemical industry owing to its versatility and high demand. Currently, direct oxidation is the most important technical process to produce EO. This conventional process, in which ethylene is partially oxidized with air or oxygen, has limited selectivity for EO of 65-90%, leading to significant CO2 emissions. This study explores an alternative method involving the electrochemical selective oxidation of ethylene powered by renewable electricity. The electrochemical oxidation technology is expected to reduce CO2 emitted during EO production. Process models were developed based on existing literature data. A techno-economic evaluation and sensitivity analysis focusing on the electrochemical cell variables were conducted. In this assessment, the investment and production costs of the electro-oxidation process for EO production were compared with those of the conventional process. This assessment also compared processes producing of mono-ethylene glycol and ethylene carbonate from EO. These analyses reveal that the separation energy has a significant impact on the carbon footprint. While current economic and environmental benefits are not favorable, this study identifies key descriptors of the technology for further reducing the carbon footprint. Based on the evaluation results, this study demonstrates the potential to cut CO2 emissions in half compared to conventional plants by utilizing the electro-oxidation of ethylene via a direct route.

Hydrogen is one of the potential candidates to replace fossil fuels to meet net zero emissions target. This study reports a detailed techno-economic and environmental assessment of hydrogen production through ammonia decomposition. The case study is based on a multiple catalytic packed bed reactor with intermediate heating system. Aspen plus (R) and MATLAB (R) were linked to evaluate economic and environmental impact of the process. The process parameter like furnace temperature, flue gas recirculation, ammonia decomposition temperature, market ammonia supply pressure, ammonia decomposition pressure, hydrogen purification unit's pressure and equivalence ratio, and economic parameters of capital expenditure (CAPEX) and operating expenditure (OPEX) were considered. The overall thermal efficiency of the developed process is found to be 79%. The levelized cost of hydrogen (LCOH) is estimated and found to be 6.05 USD/kg of H2 based on CAPEX and OPEX. A major contribution of up to 62.2% to LCOH comes from the price of feed Ammonia. Based on 25 -year plant life with 10% discounted rate the plant is economically viable, with a return on investment of 23.7%, in a payback period of 3.58 years. Global warming potential of the process is also carried out.

As the supply of photovoltaic industry products increases rapidly, measures to solve the upcoming related waste problem are urgently required. In particular, the fabrication process of Si wafers leads to significant Si scrap residue, and approximately 40% of crystalline Si ingots are wasted as Si scrap. Here, a feasibility study was conducted to investigate the recycling of Si scrap waste collected during the solar panel manufacturing process using the transferred arc thermal plasma. Si-NP with a particle size of 100 nm or less applicable as an anode material for lithium-ion batteries (LIBs) was successfully upcycled by the transferable arc thermal plasma method, and the developed LIB showed excellent electrochemical performance. Si-NPs electrodes show a discharge capacity of 2920 mAh g-1 at 0.1 A g-1, and 2167 mAh g-1 at 0.4 A g-1. In addition, silicon-graphite (Si-G) composites were also prepared to improve the electrochemical properties of LIBs. Furthermore, the possible pros and cons of the method proposed in this study were discussed including economic evaluation. These results show that the transferred arc thermal plasma is a simple, eco-friendly, and cost-effective method of upcycling Si-NPs anode material from Si scrap waste for high-performance LIBs.

The partial liquefaction of natural gas (NG) is commonly conducted in the liquefied natural gas (LNG) industry toward facilitating the use of non-liquefied gas for power generation and utility systems, while simultaneously achieving the desired heating value of LNG. This study investigated the impact of the partial liquefaction of NG and the recovery of cold energy from non-liquefied gas on the efficiency of the liquefaction process, in terms of specific work. The optimal liquefaction ratio (LR) with no recovery was 64.2% (778.7 kJ/kg LNG), which is 21.7% reduction of specific work in relation to that achieved through full liquefaction (995.0 kJ/kg LNG). The result showed a trade-off relationship between a higher LR to compensate energy consumption for cooling NG to its dew-point temperature with no liquid production and produce flash gas at a cryogenic temperature and lower LR to avoid the liquefaction of light components, which are difficult to condense. However, this trade-off resolved upon cold energy recovery, because there was no energy consumption until an LR of 8.1% could be achieved through an expansion of high-pressure NG feed by the recovery. For practical reason, a case study was conducted with lower bounds of the LR at 85%, 90%, and 95%. The findings of this study can guide the decision-making of future LNG projects for an optimal LR.

This study reports the experimental data on CO2 solubility in aqueous aminoethylethanolamine (AEEA) and diethanolamine (DEA) under different amine blending ratios (9:21, 15:15 and 21:9 wt% AEEA: DEA, respectively and remaining 70 wt% being the water), CO2 partial pressure up to 477.4 kPa and temperatures up to 393.15 K. The complex nature of AEEA diamine and DEA was thermodynamically modeled to evaluate the behavior of aqueous blend of AEEA and DEA for CO2 capture. The electrolyte nonrandom two liquid (electrolyte NRTL) activity coefficient model is used to incorporate the nonideality of the system. The system of blended aqueous AEEA and DEA contained twelve equilibrium equations, three mass balance equations, one charge balance equation and one hydronium ion-based polynomial. These equations were simultaneously solved by using an inhouse built MATLAB code to determine the CO2 loading, CO2 cyclic capacity, pH, heat of absorption, activity coefficients and concentration of seventeen species in the system. Model results have been compared with literature and inhouse experimental data, which are in a good agreement. Furthermore, study reports activity coefficients, mole fractions of seventeen species, dependence of CO2 loading on temperature, pressure and concentration of individual amine. The Absolute average deviation percent in the model and experimental data for AEEA, DEA and their blend are 9.90%, 7.61% and 8.55%, respectively for CO2 loading.

A blue ammonia process was designed by incorporating the carbon capture and storage process into the gray ammonia process. A natural-gas-based ammonia synthesis process involved steam methane reforming, water gas shift reaction, acid gas removal, methanation, and ammonia synthesis. Energy analysis (specific energy consumption, SEC), economic analysis (levelized cost of ammonia, LCOA), and environmental analysis (global warming potential, GWP), denoted as 3E analysis, were executed for the gray and blue ammonia processes. Key process variables exhibiting a trade-off relationship for the 3E features were extracted via the local sensitivity analysis (LSA) and the global sensitivity analysis (GSA). Then, both processes were optimized by genetic algorithm (GA) based multi-objective optimization (MOO) technique for the 3E features, SEC, LCOA, and GWP. Three scenarios were selected on the Pareto front obtained through MOO, and the optimized results of the 3E analysis were compared. Through the MOO for 3E in the blue ammonia process, the minimum SEC, LCOA, and GWP were 31.03 GJ/tNH3, $415.15/tNH3, and 0.3172 tCO2eq/tNH3, respectively, compared to the gray ammonia process, +8.01%, +23.7%, and −81.47% increased or decreased.

In this study an internal carbon loop strategy for producing methanol from natural gas (NG) by introducing CO2 to enhance methanol productivity and minimize greenhouse gas (GHG) emissions. The overall process consists of a steam methane reforming (SMR) process (hydrogen production), methanol synthesis process (carbon utilization), crude methanol separation process, chemical absorption process (carbon capture), and CO2 compression and storage processes (carbon storage). Methanol was produced using hydrogen, carbon monoxide, and carbon dioxide as the products and by-products of the steam methane reforming process. In particular, the pressure of the compressed CO2 for storage was utilized to enhance profitability. A strategy for injecting the pressurized CO2 into the reforming reactor, methanol reactor, or splitting it between the two reactors was examined. The process variables used were the steam/natural gas ratio (1.5, 2.0, 2.5), CO2/natural gas ratio (0-0.5), natural gas flow rate (3000 kmol/h), reforming reaction pressure (5 barg), and methanol reaction pressure (80 barg). Methanol production was 2800-3000 tonMeOH/day under according to operating conditions. Carbon pricing was considered to assess the feasibility of installing and operating a carbon capture and storage (CCS) unit. The effect of the process economic and environment variables was investigated on total energy duty, levelized cost of methanol (LCOM) from a techno-economic analysis (TEA) perspective, and global warming potential (GWP) from a life cycle assessment (LCA) standpoint using local sensitivity analysis (LSA). Subsequently, multi-objective optimization (MOO) for levelized cost of methanol and global warming potential was performed to find optimal operating variables and establish various relevant scenarios. Scenario analysis reveals that implementing an internal carbon loop strategy through relatively simple retrofits can increase levelized cost of methanol by 12.8% while reducing global warming potential by 41.5%.

Ammonia is an important commodity for both direct and indirect applications. It can be used directly as a carbon-free fuel source as well as for the purpose of renewable hydrogen storage and transport. In this study, hydrogen production from ammonia decomposition in a multi catalytic packed bed reactor with an intermediate heating system is reported using Aspen Plus V.12. The process simulation model results have been validated through experimental data for commercially available Ru/Al2O3 catalyst and Temkin-Phyzev reaction kinetics. The results exhibit that ammonia decomposition is a highly endothermic reaction, therefore requires significant heat energy. The decomposition parameters such as temperature and pressure are optimized for large-scale ammonia decomposition. For the ammonia combustion, thermal efficiency, fuel-saving, and product yield are analyzed and optimum values are found to be 59%, 22% and 77% for each parameter, respectively. During the pure ammonia combustion, NOX emissions are a major issue. To monitor the NOX emissions, parameters such as equivalence ratio, temperature and pressure are analyzed to witness the optimum operating conditions. To improve the flame quality such as laminar velocity, minimum ignition temperature, and adiabatic flame tem-perature of the ammonia combustion, waste hydrogen stream from the pressure swing adsorption (PSA) unit is blended with the fuel ammonia. The blending of hydrogen with fuel ammonia resulted in higher NOX emissions, which can be reduced by recirculation of 30% of the flue gas with air-fuel stream.

Biofuels have been widely recognized as potential solutions to addressing the climate crisis and strengthening energy security and sustainability. However, techno-economic and environmental challenges for the production of biofuels remain and complicated conversion processes and factors, such as materials and process design, need to be taken into consideration for solving the challenges, which is not easy. Machine Learning (ML) has been combined with the theories of thermochemical biofuel conversion processes to achieve accurate and efficient biofuel process modelling. In this review, existing ML applications to predict biofuel yield and composition are critically reviewed. The details of the input and output variables of the developed models for thermochemical biofuel conversion processes were summarized, and their development procedures were compared. Techno-economic analysis results incorporating ML applications in biofuels were also reviewed. Although developed models in literature showed good performance for their targets, respectively, they can hardly be applied to other feedstocks or operating conditions. To overcome the challenge and develop universal model, perspective ap-proaches were suggested in this study. It was suggested that it is essential to develop systematic datasets to support more comprehensive machine learning-based modelling towards practical applications. Potential pro-spective research and development directions on machine learning-based thermochemical biofuel conversion process modeling were recommended, so that it can assist in the commercialization and optimization of various biofuel conversions leading to a sustainable and circular society.

The absorption mechanism of CO2 in an aqueous solution containing three alkanolamines was analyzed experimentally and theoretically. The vapor-liquid equilibrium of a CO2-monoethanolamine (MEA)-diisopropanolamine (DIPA)-2-amino-2-methyl-propanol (AMP)-H2O system was evaluated experimentally over a wide temperature range (323.15-393.15 K) at several MEA:DIPA:AMP:H2O blending ratios (15:10:5:70, 10:10:10:70, 7.5:7.5:15:70, and 5:15:10:70 wt%). The successive substitution method was used to calculate the concentrations of five molecules (CO2, MEA, DIPA, AMP, and H2O) and nine electrolytes (four cations and five anions) in the liquid phase by solving eight equilibrium equations, four mass balance equations, and one charge balance equation. The Deshmukh-Mather model, which is based on an activity coefficient approach, and the fugacity coefficient model were used to evaluate the nonideality of the liquid and vapor phases, respectively. Thereafter, the effect of the MEA:DIPA:AMP blending ratio was evaluated using the triangular diagrams of the carbamate, bicarbonate and carbonate molar fractions in liquid phase, CO2 loading ratio, CO2 cyclic capacity, and heat of CO2 absorption.

Ammonia is an important commodity for both direct and indirect applications. It can be used directly as a carbon-free fuel source as well as for the purpose of renewable hydrogen storage and transport. In this study, green hydrogen production from ammonia decomposition in a multi catalytic packed bed reactor with an intermediate heating system is reported using Aspen Plus V.12. The process simulation model results have been validated through experimental data for commercially available Ru/Al2O3 catalyst and Temkin-Phyzev reaction kinetics. The results exhibit that ammonia decomposition is a highly endothermic reaction, therefore requires significant heat energy. The decomposition parameters such as temperature and pressure are optimized for large-scale ammonia decomposition. For the ammonia combustion, thermal efficiency, fuel-saving, and product yield are analyzed and optimum values are found to be 59%, 22% and 77% for each parameter, respectively. During the pure ammonia combustion, NOX emissions are a major issue. To monitor the NOX emissions, parameters such as equivalence ratio, temperature and pressure are analyzed to witness the optimum operating conditions. To improve the flame quality such as laminar velocity, minimum ignition temperature, and adiabatic flame temperature of the ammonia combustion, waste hydrogen stream from the pressure swing adsorption (PSA) unit is blended with the fuel ammonia. The blending of hydrogen with fuel ammonia resulted in higher NOX emissions, which can be reduced by recirculation of 30% of the flue gas with air-fuel stream.

Experimental data on CO2 solubility in diisopropanolamine (DIPA) and methyldiethanolamine (MDEA) blended aqueous solutions were measured at different amine blending ratios and working temperatures. The successive (iterative) substitution method was implemented to calculate the molar fractions of all chemical species, including molecules and electrolytes, from equilibrium along with four material balances and one electroneutrality equation. The electrolyte universal quasi-chemical (electrolyte UNIQUAC) model was used to consider the nonideality in the liquid phase. The partial pressures of CO2 in the gas phase and molar fractions of all components in the liquid phase were recalculated using thermodynamic models. In addition, the effect of the blending ratio of DIPA, MDEA, and H2O was investigated and expressed using the newly applied triangular diagrams of pH, heat of absorption, and cyclic capacity of CO2 according to the absorption and stripping conditions.