A systematic framework is proposed for the design of electrodialysis (ED) systems with photovoltaics (PV) and batteries (BAT), focusing on nitrate ions removal. The framework combines multi-objective optimization (MOO) with non-linear sensitivity analysis for evaluation of the system operation under variability. Optimum designs are initially derived considering variables such as the ED stack voltage and membrane area, and the PV and BAT capacities. Multiparametric disturbances are imposed on selected designs that exhibit optimum steady-state trade-offs, to evaluate their robustness based on performance indicators such as the final outlet concentration of nitrates, the annualized system cost and the non-renewable electricity consumption. Designs obtained from single-objective optimization become both suboptimal and prone to violations of the nitrate concentration limit for potable water under the influence of multiple, simultaneous and large in magnitude disturbances. Designs identified through MOO are economically superior and guarantee the feasibility of the water quality specifications.

Solvent-based CO2 capture is very important for the mitigation of greenhouse gases. The presence of SO2 and NO2 is observed in several types of CO2-containing industrial flue gases and even small concentrations can cause significant changes in the performance of the solvent. Their effects on the CO2 solubility have received very little attention. To simulate the effect of dissolution and accumulation of SO2 and NO2 acid gases on the CO2 loading of aqueous ethanolamine (MEA) solutions, H2SO4 and HNO3 were added, as sources of NO 3 and SO 2 4 anions, respectively. The CO2 solubility in 30 % wt. aqueous MEA solutions containing 2.9 % wt. H2SO4 with and without 1.8 % wt. HNO3 was experimentally measured using a pressure decay method at 313, 333 and 353 K and approximately 5-500 kPa. In both cases, it is revealed that the addition of H2SO4 and HNO3 substantially decreases the CO2 solubility. In addition, the modified Kent-Eisenberg model was used to predict the CO2 solubility in all systems and at all the studied conditions. The model predictions are in satisfactory agreement with the experimental data presenting Average Absolute Deviations between 4.8 and 6.8 % in all cases.

Organic Rankine cycle (ORC) systems are a class of distributed power-generation systems that are suitable for the efficient conversion of low-to-medium temperature thermal energy to useful power. These versatile systems have significant potential to contribute in diverse ways to future clean and sustainable energy systems through, e.g., deployment for waste-heat recovery in industrial facilities, but also the utilisation of renewable-heat sources, thereby improving energy access and living standards, while reducing primary energy consumption and the associated emissions. The energetic and economic performance, but also environmental sustainability of ORC systems, all depend strongly on the working fluid employed, and therefore a significant effort has been made in recent years to select, but also to design novel working fluids for ORC systems. In this context, computer-aided molecular design (CAMD) techniques have emerged as highly promising approaches with which to explore the key role of working fluids, and present an opportunity, by focusing on the design of new eco-friendly fluids with low environmental footprints, to identify alternatives to traditional refrigerants with improved characteristics. In this review article, an overview of working-fluid and system optimisation methodologies that can be used for the design and operation of next-generation ORC systems is provided. With reference to wide-ranging applications from waste-heat recovery in industrial and automotive applications, to biomass, geothermal and solar-energy conversion and/or storage, this review represents a comprehensive, forward-looking exposition of the application of CAMD to the design of ORC technology.

We investigate the presence and effects of impurities in the carbon capture, transportation and sequestration (CCS) technology chain. We start from the composition of flue gases and investigate the subsequent treatment methods, the technical and operating characteristics of solvent-based CO2 capture pilot plants, the compositions of the absorber and desorber outlet streams and the CO2 stream specifications for downstream compression, transportation and storage processes. We present public data from 40 campaigns in large capture pilot plants and 20 sets of specifications for CO2 transportation and underground storage from national agencies, companies and projects worldwide. We identify and categorize the impurities depending on the flue gas source and the solvent type. The most commonly identified emissions in the treated gas are ammonia (NH3) and the solvent used in each plant. Monoethanolamine (MEA) emissions are higher compared to those of the other amine solvents. Sulfur and nitrogen oxides (SOx, NOx) are the most investigated impurities, whereas oxalate and formate are the most reported degradation products. Regardless of the solvent used, NOx, NH3 and aldehydes are reported in the CO2 gas product stream of most campaigns. The specifications for transportation and sequestration have similarities, with those of Northern Lights being stricter.

Solvent-based electrochemical CO2 reduction (CO2R) enables the production of chemicals or fuels using CO2 from a preceding absorption process. Employing previously tested CO2 capture solvents does not ensure their suitability for either CO2R or integrated CO2 absorption-reduction. We propose solvent selection criteria that include the CO2 solubility, kinetic constant, ionic conductivity, concentration of the bicarbonate, carbamate, and solvent cation in the CO2-loaded solution, and sustainability indicators. They are implemented for solvent selection (a) from novel, aqueous mixtures of N-methylcyclohexylamine (MCA) with piperazine (PZ), 2-amino-2-methyl-1-propanol (AMP), potassium hydroxide (KOH), and potassium chloride (KCl) and (b) from aqueous monoethanolamine (MEA), AMP, KOH, MCA, and PZ solutions. Versions of a modified Kent-Eisenberg model for strong bases, carbamate, and non-carbamate-forming amine solutions are developed and parameterized through experimental equilibrium measurements. CO2R experimental results are presented for solutions of KOH and MCA + KOH, as these indicate desired trade-offs for CO2 absorption and reduction.

Reactive absorption in aqueous solutions is a widely applied CO2 capture technology, but its efficiency can be significantly enhanced through process intensification. Rotating Packed Bed (RPB) technology offers a promising solution by intensifying mass transfer and enabling substantial equipment size reduction compared to packed columns. Incorporating biocatalysts, such as the enzyme carbonic anhydrase (CA), further boosts the efficiency of the CO2 absorption process. This study employs a data-driven approach to model enzyme-enhanced CO2 absorption in an RPB system using LightGBM, a gradient boosting framework that builds decision trees in a sequential manner, utilizing histogram-based learning and leaf-wise tree growth for enhanced accuracy and efficiency. The model is trained and validated based on experimental data collected from CO2 absorption experiments with a 30 wt% N-methyldiethanolamine (MDEA) solution, with and without CA across various gas and liquid flow rates. The LightGBM model achieved a high mean cross-validation R2 score (0.98) and low root mean squared error value (0.3) in predicting absorption efficiency, indicating high predictive accuracy. Shapely Additive Explanations (SHAP) are employed to analyze feature importance and understand the key parameters influencing absorption efficiency. The validated model is then used for operational analysis, offering insights into system performance optimization. Results reveal that enzyme-enhanced absorption can improve CO2 absorption efficiency by up to 245.87% compared to the solvent without the enzyme, underscoring the potential of combining high-gravity technology with biocatalysts and machine learning techniques for next generation carbon capture systems.

Rotating Packed Beds (RPBs) are emerging as a promising alternative for CO2 capture, due to the intense centrifugal force that is generated as they spin, which significantly enhances the mass transfer and greatly facilitates CO2 absorption. RPBs are expected to enable over 10-15 times lower volume compared to conventional packed beds of the same capture efficiency, allowing a reduction in capture costs. To date very few 1.0 tCO2/d demonstrations of RPB units and plants have been reported. Project HiRECORD is developing a 10.0 t CO2/d capture pilot plant that is based on advanced RPB technologies for absorption and desorption. This will be demonstrated in three industrial sites that emit flue gases of different specifications. This work highlights the features of the pilot plant and of the industrial sites. It also provides an overview of various complementary research activities pertaining to solvent testing, development of thermodynamic and process models and sustainability assessment.

Rotating Packed Beds (RPBs) are poised to replace conventional Packed Bed (PB) towers, advancing solvent-based CO₂ capture through intensified mass transfer processes. Effective modeling is crucial for understanding these intensified phenomena and complex liquid flow patterns during CO₂ absorption in RPB reactors. While the cavity section—located between the packing and the casing—plays a significant role in overall capture efficiency, it is often overlooked in existing models that primarily focus on the packing section. In the cavity section, the liquid flows as droplets and forms a film along the casing wall. This work addresses this gap by integrating two distinct mass transfer methodologies, each adapted to the liquid flow variations in both the packing and cavity sections. The proposed integrated absorption model captures all critical phenomena along the radial dimension, offering a comprehensive simulation of RPB performance. The methodology builds on an existing rate-based, steady-state framework from our previous work, while incorporate a semi-empirical approach to predict mass transfer in the cavity section. A custom model for the packing section uses the shooting method to solve material and energy balance equations, focusing on a monoethanolamine (MEA) solution. The model was validated using up-to-date experimental data for a 30 wt.% MEA solution in a RPB absorber across twenty different tests, considering various conditions such as rotational speed, liquid-to-gas ratio, and lean loading. The predicted outlet gas CO₂ mole fraction aligned closely with experimental results, showing a mean absolute deviation of 4%. Additionally, the simulation enabled detailed analysis of key gas and liquid phenomena along the radial dimension, such as variations in gas phase CO₂ molar flow rate and liquid temperature. Notably, the cavity section enhanced capture efficiency, particularly near the inner casing wall where droplets accumulate to form a film.

This work is devoted to evaluating the corrosion behaviors of SS 304L and SS 316L in monoethanolamine solutions (MEA) containing SOX and NOX pollutants, examining both lean and CO2-loaded conditions at 25 °C and 40 °C. Electrochemical techniques (potentiodynamic and cyclic polarization) were used along with Scanning Electron Microscopy, Confocal Microscopy and weight loss measurements. The results reveal that the introduction of SOX and NOX pollutants increased the corrosion rate, whereas CO2 loading primarily reduced the corrosion resistance in the lean MEA solution, while its impact on solutions with SOX and NOX was less pronounced. This suggests that SOX and NOX play primary roles in the metal’s dissolution. Also, SS 316L demonstrated superior corrosion resistance compared to 304L in nearly all of the cases examined. Elevated temperatures were also found to intensify the corrosion rate, indicating a correlation between the corrosion rate and temperature. A microscopic observation and EDX analysis revealed that corrosion products are characterized by high concentrations of iron (Fe) and oxygen (O) as well as carbon (C). There is also an indication of the possible formation of amine complexes, suggesting a potential for amine degradation. No pitting corrosion was observed in SS 304L and SS 316L across any tested solution. Finally, the immersion results expose a tendency for passivity in all amine solutions and at both temperatures after several days of exposure. Moreover, they confirm the very low corrosion rate calculated from potentiodynamic curves due to minimal weight loss after 24 days of immersion.

Post-combustion CO2 2 capture plants include high costs that are associated with intense energy consumption. Heat pumps can recover heat from the flue gas and other sources in the CO2 2 emitting plant and upgrade it to reduce the use of fossil-based steam. The few studies regarding heat pumps in CO2 2 capture systems include arbitrary selection among limited working fluids, without optimizing the underlying cycle. This work implements a multi-criteria investigation of the performance of 20 working fluids for vapor compression heat pumps (VCHP) and 21 refrigerant/absorber pairs for absorption heat transformers (AHT), considering the operating optimization of each cycle for each fluid. A cascade cycle combining the two configurations (AHT-VCHP) is proposed, using the optimum fluids cyclopentane and water/potassium nitrate identified for the VCHP and the AHT. The annual operating costs are higher than the annualized capital expenditures. The proposed fluids outperform the conventional options. The VCHP with cyclopentane covers 58 % (2.68 GJ/t CO2) 2 ) of the reboiler duty with recovered heat and exhibits the lowest cost of $33.8/tCO2. 2 . This is $18.7/tCO2 2 lower than the cost of the conventional direct contact cooling unit that is used in capture plants. The VCHP remains competitive for up to 57 % increase in the electricity price.

Biphasic solvents are receiving increased attention in post-combustion CO2 capture systems as they reduce the regeneration energy requirements compared to conventional, single-phase solvents. The appearance of a second liquid phase in biphasic solvents results in a complex dynamic behavior of the capture process that has never been investigated. We develop for the first time a dynamic model for the novel biphasic solvent S1N/DMCA (N-Cyclohexyl-1,3-Propanediamine/ N,N -Dimethylcyclohexylamine) to investigate its behavior compared to the conventional MEA (monoethanolamine). The model accounts for both the mass and energy holdup in the liquid phase, whereas a control scheme with two proportional-integral (PI) controllers is used to compare the dynamic performance of the two solvents. For 10% increase in the total flue gas flow, the biphasic solvent is more robust, due to 2.5% and 3% lower change in the reboiler energy demand and solvent replenishing requirement than MEA. The required steam cost is also reduced by 3% compared to MEA.

Carbon capture, utilisation and storage (CCUS) is a key area of research for CO2 abatement. To that end, CO2 capture, transport and storage has accrued several decades of development. However, for successful implementation of CCUS, utilisation or conversion of CO2 to valuable products is important. Electrochemical conversion of the captured CO2 to desired products provides one such route. This technique requires a cathode "electrocatalyst" that could favour the desired product selectivity. Copper (Cu) is unique, the only metal "electrocatalyst" demonstrated to produce C-2 products including ethylene. In order to achieve high-purity Cu deposits, electrodeposition is widely acknowledged as a straightforward, scalable and relatively inexpensive method. In this review, we discuss in detail the progress in the developments of electrodeposited copper, oxide/halide-derived copper, copper-alloy catalysts for conversion of CO2 to valuable products along with the future challenges.

Electrodialysis is receiving increased attention for the separation of important ions from industrial effluents. Insights on the simultaneous removal of lead and sulfate ions remain largely elusive in published work, while the works that address only lead removal consider concentrations higher than 100 mg/L. Effluents that contain lead and sulfate ions at industrially relevant concentrations (5 mg/L and 500-2000 mg/L, respectively, based on battery manufacturing characteristics) are investigated in this work. A pilot-scale electrodialysis setup is used that comprises 66 cell pairs of cation- and anion-exchange membranes of 5 m2 effective membrane area/stack, operated in batch mode. The setup is initially optimized according to key process parameters (applied voltage, product-to-concentrate ratio, and initial feed concentration) for sulfate ion removal, with the optimized conditions applied for simultaneous removal of lead and sulfate ions. Tests showed the negative effect of the high concentration ratio of sulfate-to-lead ions on the removal of lead. In order to improve the combined removal of lead ions, the operating conditions were changed and the optimal values corresponding to superficial velocity of 2 cm/s and applied voltage of 0.6 V/cell pair, resulted in 91% and 75% removal of sulfate and lead ions after 4 h of electrolysis, with energy consumption of 7 kWh/m3.

District cooling (DC) is an emerging approach to deal with heavy cooling demands since it offers substantial energy savings, up to 40

Electrochemical CO2 reduction is a promising utilization process. The use of amine solvents to deliver the captured CO2 into the cell is receiving experimental attention, but models are also needed to investigate the performance of such systems. This work aims to model and assess the performance of the electrochemical reduction of CO2 into CO in an amine capture solvent. The developed process model is validated using a conventional electrolyte (KHCO3), exhibiting good match and low deviation from experimental data. The process is evaluated for monoethanolamine (MEA), and compared to KHCO3 within a range of 2-20 cm3/min of total inlet cell flow. MEA enables lower undesirable H2 formation (less than 5% of the total current density) and faster reaction, as implied by the higher CO current density (from 45%, up to 98.7% within the considered flow range). KHCO3 exhibits higher conversion rates than MEA, but MEA’s higher CO production rate within the entire inlet flow range reaches a value of 30.8% at the lower flow end.

A significant effort is under way to identify improved solvents for carbon dioxide (CO2) capture by chemisorp-tion. We develop a predictive framework that is applicable to aqueous solvent + CO2 mixtures containing cyclic amines, alkyl polyamines, and alkanolamines. A number of the mixtures studied exhibit liquid-liquid phase separation, a behaviour that has shown promise in reducing the energetic cost of CO2 capture. The proposed framework is based on the SAFT-y Mie group-contribution (GC) approach, in which chemical reactions are described via physical association models that allow a simpler, implicit, treatment of the chemical speciation characteristic of these mixtures. We use previously optimized group interaction parameters between some amine groups and water (Perdomo et al., 2021), and develop new group interactions for the cNH, cN, NH2, NH, N, cCHNH, and cCHN groups with CO2; a set of second-order group parameters are also developed to account for proximity effects in some alkanolamines. A combination of literature data and new experimental measurements for the absorption of CO2 in aqueous cyclohexylamine systems obtained in our current work, are used to develop and test the proposed models. The SAFT-y Mie GC approach is used to predict the thermodynamics of selected mixtures, including ternary phase diagrams and mixing properties relevant in the context of CO2 capture. The current work constitutes a substantial extension of the range of aqueous amine-based solvents that can be modelled and thus offers the most comprehensive thermodynamically consistent platform to date to screen novel candidate solvents for CO2 capture.

Effective modelling of the Rotating Packed Bed (RPB) process is crucial for accurately simulating CO2 absorption in aqueous amine solutions. Existing models often incorporate simplifying assumptions and rarely capture the simultaneous variations of critical phenomena inside the RPB apparatus, such as gas phase CO2 mass flow rate, liquid and gas temperatures, and pressure drop. This work addresses these challenges by developing a rate-based, steady-state model designed for CO2 capture, using monoethanolamine (MEA) as the solvent. Unlike previous works, this model effectively captures all these critical phenomena simultaneously. The model employs a first principles approach and solves material and energy balance equations using the shooting method. Two-film theory is used to represent mass transfer in conjunction with up-to-date correlations. The predicted results exhibit excellent agreement with the experimental data for a 30 wt. % MEA solution when comparing rich loading, with a maximum deviation of 1.1 %. The analysis of previously overlooked phenomena in RPB-based CO2 absorption provides valuable insights regarding the variations of key parameters along the radius, such as the influence of pressure drop and temperature. The observed decrease in gas pressure and sharp drop near the inner radius demonstrate the significant impact of frictional losses. In contrast, the temperature profiles of the gas and liquid phase reveal the interplay between exothermic reactions and counter-current flow.

This work presents the use of an optimization algorithm with approximate computing capabilities in the simultaneous CO2 capture (CC) and utilization (CU) process design and controllability assessment. The CC design problem includes 6 solvent and process flowsheet combinations, followed by the use of a Rotating Packed Bed (RPB) process for the production of precipitated calcium carbonate (PCC) minerals as the CU option. The algorithm employs memoization and task dropping to accelerate execution in a high-performance cluster. The results indicate up to 141.7 h of saved CPU time due to the use of the approximate computing techniques. When the CC and CU processes are considered simultaneously, the generated Pareto front changes compared to the one of the CC process. The 2-Aminoethanol 30 wt. % solvent with intercooling and side feeds in the desorber results in almost equally profitable PCC production to the 3-Amino-1-Propanol 35 wt. % solvent in simpler flowsheets.