Search Results (82)

Carbon capture and storage (CCS) is essential for achieving net-zero emissions, yet amine-based capture systems face significant challenges including high energy penalties (20–30% of power plant output) and operational costs ($50–120/tonne CO${}_2$). This study develops and validates a novel multi-scale Digital Twin (DT) framework integrating Physics-Informed Neural Networks (PINNs) to address these challenges through real-time optimization. The framework combines molecular dynamics, process simulation, computational fluid dynamics, and deep learning to enable real-time predictive control. A key innovation is the sequential training algorithm with domain decomposition, specifically designed to handle the nonlinear transport equations governing CO${}_2$ absorption with enhanced convergence properties.The algorithm achieves prediction errors below 1% for key process variables (R${}^2$> 0.98) when validated against CFD simulations across 500 test cases. Experimental validation against pilot-scale absorber data (12 m packing, 30 wt% MEA) confirms good agreement with measured profiles, including temperature (RMSE = 1.2 K), CO${}_2$ loading (RMSE = 0.015 mol/mol), and capture efficiency (RMSE = 0.6%). The trained surrogate enables computational speedups of up to four orders of magnitude, supporting real-time inference with response times below 100 ms suitable for closed-loop control. Under the conditions studied, the framework demonstrates reboiler duty reductions of 18.5% and operational cost reductions of approximately 31%. Sensitivity analysis identifies liquid-to-gas ratio and MEA concentration as the most influential parameters, with mechanistic explanations linking these to mass transfer enhancement and reaction kinetics. Techno-economic assessment indicates favorable investment metrics, though results depend on site-specific factors. The framework architecture is designed for extensibility to alternative solvent systems, with future work planned for industrial-scale validation and uncertainty quantification through Bayesian approaches. Full article

Carbon capture is an essential technology for reducing industrial CO₂ emissions, particularly in the power and cement sectors. Among the various capture methods, solvent-based absorption systems are widely used due to their efficiency and scalability, making the selection of the right solvent critical for near-term applications. This study analyzes several solvents for use in an absorption-based CO₂ capture system, emphasizing identifying the most suitable solvent for 2025–2030. The research methodology involves process modeling in Aspen Plus, sensitivity analysis, and evaluation of the regeneration duty for each solvent. The objective is to achieve at least 90% CO₂ capture and 95% CO₂ purity. The flue gas composition considered in this analysis is 19.8% CO₂, 9.3% O₂, 63% N₂, 7.5% H₂O, and other trace gases. Various solvents are evaluated to determine their effectiveness in capturing CO₂ while minimizing the energy consumption during solvent regeneration. A sensitivity analysis was conducted to optimize the system’s performance based on the solvent type, operating conditions, and regeneration duty. The results showed that amine blends demonstrated a CO₂ capture rate of 92% and a CO₂ purity of 96%, with regeneration energy requirements of around 3.2 GJ/ton of CO₂, significantly lower than those of traditional MEA systems, which typically require around 4.0 GJ/ton. In contrast, ionic liquids showed a CO₂ capture rate of 89% and a purity of 95%, with a regeneration energy of 2.8 GJ/ton, though their current cost is higher, limiting their immediate large-scale application. Annual capital expenditure (CAPEX) calculation revealed that amine blends could potentially reduce the CAPEX by 15–20% compared to MEA, while amino acid salts showed similar CAPEX reductions with a capture efficiency of 90%. Overall, the results indicate that hybrid amine solvents are the most cost-effective and practical solution for 2025–2030, with ionic liquids and amino acid salts emerging as promising alternatives as their costs decrease. Full article

The increasing atmospheric concentration of carbon dioxide (CO₂) poses a critical threat to global climate stability, highlighting the need for efficient carbon capture technologies. While amine-based solvents such as monoethanolamine (MEA) are widely used for industrial CO₂ capture, they are subject to limitations such as high energy requirements for regeneration, solvent degradation, and environmental concerns. This study investigates potassium carbonate/bicarbonate system as an alternative solution for CO₂ absorption. The absorption mechanism and reaction kinetics of potassium carbonate in the presence of bicarbonates were reviewed. A rate-based model was developed in Aspen Plus, using literature kinetics, to simulate CO₂ absorption using 20 wt% potassium carbonate (K₂CO₃) solution with 10% carbonate-to-bicarbonate conversion under different industrial conditions. Three flue gas compositions were evaluated: cement industry, biomass combustion, and anaerobic digestion, each at 3000 m³/h flow rate. The simulation was conducted to determine minimum column height and solvent loading requirements with a target output of 90% CO₂ removal from the gas streams. Results demonstrated that potassium carbonate systems successfully achieved the target removal efficiency across all scenarios. Column heights ranged from 18 to 25 m, with molar K₂CO₃/CO₂ ratios between 1.41 and 4.00. The biomass combustion scenario proved most favorable due to lower CO₂ concentration and effective heat integration. While requiring higher column heights (18–25 m) compared to MEA systems (6–12 m) and greater solvent mass flow rates, potassium carbonate demonstrated technical feasibility for CO₂ capture. The findings of this study provide a foundation for technoeconomic evaluation of potassium carbonate systems versus amine-based technologies for industrial carbon capture applications. Full article

Carbon capture is pivotal for achieving carbon neutrality; however, its high energy consumption severely limits the operational flexibility of power plants and remains a key challenge. This study, targeting a full flue gas carbon capture scenario for a 1000 MW coal-fired power plant, identified the dual-element (“steam” and “power generation”) coupling convergence mechanism. Based on this mechanism, a comprehensive set of mathematical model equations for the “carbon–electricity–heat” coupling process is established. This model quantifies the dynamic relationship between key operational parameters (such as unit load, capture rate, and thermal consumption level) and system performance metrics (such as power output and specific power penalty). To address the challenge of flexible operation, this paper further proposes two innovative coupled modes: steam thermal storage and chemical solvent storage. Model-based quantitative analysis indicated the following: (1) The power generation impact rate under full THA conditions (25.7%) is lower than that under 30% THA conditions (27.7%), with the specific power penalty for carbon capture decreasing from 420.7 kW·h/tCO₂ to 366.7 kW·h/tCO₂. (2) Thermal consumption levels of the capture system are a critical influencing factor; each 0.1 GJ/tCO₂ increase in thermal consumption leads to an approximate 2.83% rise in unit electricity consumption. (3) Steam thermal storage mode effectively reduces peak-period capture energy consumption, while the chemical solvent storage mode almost fully eliminates the impact on peak power generation and provides optimal deep peak-shaving capability and operational safety. Furthermore, these modeling results provide a basis for decision-making in plant operations. Full article

The European Union’s enhanced greenhouse gas (GHG) reduction targets for 2030 make the large-scale deployment of carbon capture and storage (CCS) technologies essential to achieve deep decarbonization goals. Within this context, this study aims to advance CCS research by developing and testing a pilot-scale system that integrates gasification for syngas and power production with CO₂ absorption and solvent regeneration. The work focuses on improving and validating the operability of a pilot plant section designed for CO₂ capture, capable of processing up to 40 kg CO₂ per day through a 6 m absorber and stripper column. Experimental campaigns were carried out using different amine-based absorbents under varied operating conditions and liquid-to-gas (L/G) ratios to evaluate capture efficiency, stability, and regeneration performance. The physical properties of regenerated and CO₂-saturated solvents (density, viscosity, pH, and CO₂ loading) were analyzed as potential indicators for monitoring solvent absorption capacity. In parallel, a process simulation and optimization study was developed in Aspen Plus, implementing a split-flow configuration to enhance energy efficiency. The combined experimental and modeling results provide insights into the optimization of solvent-based CO₂ capture processes at pilot scale, supporting the development of next-generation capture systems for low-carbon energy applications. Full article

Carbon Capture, Utilization and Storage (CCUS) is a critical area of research due to its potential to significantly reduce CO₂ emissions from industrial processes and fossil fuel-based power generation. Aqueous amine solutions are commonly used as chemical solvents for CO₂ capture. However, their application is disfavoured by the high energy requirements and related operational costs, toxicity, and corrosion issues. To address these limitations, research is in general focused on developing novel solvents that can overcome the drawbacks of traditional amines. This development needs the study of phase equilibria in systems for which detailed physicochemical data are often scarce in the literature. In particular, understanding the solubility of gases (CO₂) in possible solvent mixtures is essential for evaluating their suitability for chemical or physical absorption processes. In this work, a dedicated setup was installed to generate the experimental data for these novel systems. This unit was designed to measure the solubility and diffusivity of gases in low-volatility liquids that could be alternative CO₂ solvents. A detailed experimental procedure was established, and the unit was initially validated by measuring CO₂ solubility in a 30 wt% monoethanolamine (MEA) solution, one of the most widely used industrial solvents. The experiments were conducted under conditions representing both the absorption and the regeneration sections of a CO₂ removal plant. The resulting equilibrium data were analyzed by employing several thermodynamic models, and the model providing the best representation was selected. Full article

Background: In Siberian folk medicine, Sagan-Dalya (Rhododendron adamsii Rehder) of the Ericaceae family is used as a tonic and restorative in the form of infusions and decoctions. Pharmacological studies have shown that alcoholic extracts of this plant enhance performance and have anti-inflammatory and immunomodulatory effects. Rhododendron adamsii shoots accumulate essential oil (up to 1.6%), flavonoids (1.8–3.0%), tannins (up to 6.9%), phenolic carbolic acids, β-sitosterin, oleanolic and ursolic acids, simple phenolic compounds, and coumarins. Methods: Supercritical carbon dioxide extraction (SC-CO₂) is the most preferred environmentally friendly and selective method for extracting these natural compounds from the plant matrix of Rh. adamsii due to their high thermolability. Tandem mass spectrometry was applied to detect chemical compounds. Mass-spectrometry (MS) analysis was performed on an ion trap equipped with an ESI source in negative and positive ion modes. The capture rate was one spectrum/s for MS and two spectrum/s for MS/MS. All experiments were repeated three times. A four-stage ion separation mode (MS/MS mode) was implemented. Results: The operative parameters and working conditions have been optimized by different pressure (100–400 bars) and temperature (31–70 °C) regimes, and CO₂ flow rate (10–25 mL/min) with 1 C₂H₅OH as a co-solvent. The extraction time varied from 60 to 90 min. The maximum global yield of biologically active substances (BAS) from R. adamsii leaves and stems was observed under the following extraction conditions: Pressure: 350 bar, extraction temperature: 65 °C, extraction time: 1 h; the global yield of BAS was 8.5 mg/g of plant sample; the share of the co-solvent (C₂H₅OH) was 2%. In total, forty-nine different BAS were identified in the Rh. adamsii SC-CO₂ extracts. Conclusions: The obtained results may shed new light on the scientific basis for the traditional medicinal use of Rh. adamsii leaf and stem extracts. The pharmacological contribution of the identified phytocannabinoids requires further detailed study. It is hypothesized that the excellent transdermal permeability of supercritical extracts may open new therapeutic approaches using transdermal formulations based on SC-CO₂ extracts of Rh. adamsii. Full article

Amine-based CO₂ absorption is a leading technology for post-combustion carbon capture, but solvent degradation remains a critical barrier to its long-term sustainability. Degradation reduces capture efficiency, increases solvent make-up costs, and generates environmentally harmful by-products, undermining the viability of carbon capture as a sustainable climate mitigation strategy. This study applies advanced machine learning techniques—Artificial Neural Networks (ANN), Random Forest (RF), XGBoost, and Adaptive Neuro-Fuzzy Inference Systems (ANFIS)—to predict thermal and oxidative degradation of amine solvents under varying operating conditions. Experimental datasets for piperazine-based mixtures and tertiary amines were used to train and validate predictive models with high statistical accuracy. The results demonstrate that machine learning can reliably forecast degradation behaviour, reducing dependence on resource-intensive experimental campaigns and enabling more sustainable CO₂ capture systems. By improving solvent stability assessment and process monitoring, this work contributes to the development of more resilient, cost-effective, and environmentally responsible carbon capture technologies, directly supporting global sustainability and climate change mitigation goals. Full article

CO₂ emissions from various anthropogenic activities have led to serious global concerns (climate change and global warming), and, therefore, CO₂ capture by sustainable methods is a priority research topic. One of the most widely used and cost-effective technologies for post-combustion CO₂ capture (PCC) is the chemical absorption method, where potassium carbonate solution is proposed as a solvent (with or without the addition of promoters, such as amines). An ecological alternative, presented in this study, is the use of amino acids instead of amines as promoters—alanine (Ala), glycine (Gly) and sarcosine (Sar)—in concentrations of 25% by weight of K₂CO₃ + 5 or 10% by weight of amino acid salt, thus resulting in the so-called green solvents, which do not show high toxicity and inertness to biodegradability. The studies had as a first objective the characterization of the proposed green solvents, in terms of density and viscosity, and then the comparative testing of their efficiency for CO₂ retention from gaseous fluxes containing high CO₂ concentrations. The experiments were performed at temperatures of 298 K, 313 K, and 333 K at atmospheric pressure. The best performance was observed with K₂CO₃ + 5% Sar salt at 313 K, reaching an absorption capacity of 2.58 mol CO₂/L solvent, which is a promising improvement over the reference solution based on K₂CO₃. Increasing the amino acid concentration to 10% generally led to a reduced performance, especially for sarcosine, probably due to an increase in solution viscosity or a possible kinetic inhibition. This study provides valuable experimental data supporting the ecological potential of amino acid-promoted potassium carbonate systems, paving the way for further development of chemisorption processes and their implementation on an industrial scale. Full article

Despite growing interest in carbon capture and utilization (CCU), the transformation of captured CO₂ into dry ice remains poorly studied, particularly from a systems integration and energy optimization perspective. While previous works have examined individual components such as CO₂ absorption, liquefaction, or refrigerant evaluation, no existing study has modeled the full dry ice production chain from capture to solidification within a unified simulation framework. This study presents the first complete simulation and optimization of a dry ice production process, incorporating CO₂ absorption, solvent regeneration, dehydration, multistage compression, ammonia-based external liquefaction, and expansion-based solidification using Aspen HYSYS. The process features ammonia as a working refrigerant due to its favorable thermodynamic performance and zero global warming potential. Optimization of heat integration reduced total energy consumption by 66.67%, replacing conventional utilities with water-based heat exchangers. Furthermore, solvent recovery achieved rates of 75.65% for MDEA and 66.4% for piperazine, lowering operational costs and environmental burden. The process produced dry ice with 97.83% purity and 94.85% yield. A comparative analysis of refrigerants confirmed ammonia’s superiority over R-134a and propane. These results provide the first system-level roadmap for producing dry ice from captured CO₂ in an energy-efficient, scalable, and environmentally responsible manner. Full article

This study presents a comprehensive performance assessment of combustion-based options for Bioenergy with Carbon Capture and Storage (BECCS), widely regarded as key enablers of future climate neutrality. From 972 publications (2000–2025), 16 sources are identified as providing complete data. Seven technologies are considered: Calcium Looping (CaL), Chemical Looping Combustion (CLC), Hot Potassium Carbonate (HPC), low-temperature solvents (mainly amine-based), molten sorbents, Molten Carbonate Fuel Cells (MCFCs), and oxyfuel. First- and second-law efficiencies are reported for 53 bioenergy configurations (19 reference plants without carbon capture and 34 BECCS systems). Performance is primarily evaluated via the reduction in second-law (exergy) efficiency and the Specific Primary Energy Consumption per CO₂ Avoided (SPECCA), both relative to each configuration’s reference plant. MCFC-based systems perform best, followed by CLC; molten sorbents and oxyfuel also show very good performance, although each is documented by a single source. Low-temperature solvents span a wide performance range—from poor to competitive—highlighting the heterogeneity of this category; HPC performs in line with the average of low-temperature solvents. CaL exhibits modest efficiency penalties alongside appreciable energy costs of CO₂ capture, a counterintuitive outcome driven by the high performance of the benchmark plants considered in the definition of SPECCA. To account for BECCS-specific features (multiple outputs and peculiar fuels), a dedicated evaluation framework with a revised SPECCA formulation is introduced. Full article

Environmental contamination is a critical global concern, primarily due to detrimental greenhouse gas (GHG) emissions, especially carbon dioxide (CO₂), which significantly contribute to climate change. Moreover, the presence of harmful heavy metals like Ni, Cd, Cu, Hg, and Pb in soil and water ecosystems has led to poor water quality. Noble metal nanoparticles (MNPs), for instance, Pd, Ag, Pt, and Au, have emerged as promising solutions for addressing environmental pollution. However, the practical utilization of MNPs faces challenges as they tend to aggregate and lose stability. To overcome this issue, the reverse double-solvent method (RDSM) was utilized to synthesis melamine-based porous polyaminals (POPs) as a supportive material for the in situ growing of silver nanoparticles (Ag NPs). The porous structure of melamine-based porous polyaminals, featuring aminal-linked (-HN-C-NH-) and triazine groups, provides excellent binding sites for capturing Ag⁺ ions, thereby improving the dispersion and stability of the nanoparticles. The resulting material exhibited ultrafine particle sizes for Ag NPs, and the incorporation of Ag NPs within the porous polyaminals demonstrated a high surface area (~279 m²/g) and total pore volume (1.21 cm³/g), encompassing micropores and mesopores. Additionally, the Ag NPs@POPs showcased significant capacity for CO₂ capture (2.99 mmol/g at 273 K and 1 bar) and effectively removed Cu (II), with a remarkable removal efficiency of 99.04%. The nitrogen-rich porous polyaminals offer promising prospects for immobilizing and encapsulating Ag nanoparticles, making them outstanding adsorbents for selectively capturing carbon dioxide and removing metal ions. Pursuing this approach holds immense potential for various environmental applications. Full article

Dry ice, the solid form of carbon dioxide (CO₂), is widely used in cold chain logistics, industrial cleaning, and biomedical preservation. Its production, however, is closely linked to carbon capture, energy-intensive liquefaction, and solidification processes. This review critically evaluates and compares the existing methods of CO₂ capture, including chemical absorption, physical absorption, adsorption, and membrane-based separation as they pertain to dry ice production. This study further assesses liquefaction cycles using refrigerants such as ammonia and R744, highlighting thermodynamic and environmental trade-offs. Solidification techniques are examined in the context of energy consumption, process integration, and product quality. The comparative analysis is supported by extensive tabulated data on operating conditions, CO₂ purity, and sustainability metrics. This review identifies key technical and environmental challenges, such as solvent regeneration, CO₂ leakage, and energy recovery. Thus, it also explores emerging innovations, including hybrid cycles and renewable energy integration, to advance the sustainability of dry ice production. This, in turn, offers strategic insight for optimizing dry ice manufacturing in alignment with low-carbon industrial goals. Full article

Green hydrogen derived from renewable resources is increasingly recognized as a basis for future low-carbon energy systems. This study presents a comprehensive techno-environmental comparison of two thermochemical conversion pathways utilizing biomethane: steam methane reforming (SMR) and chemical looping reforming (CLR). Through integrated process simulations, compositional analyses, energy modeling, and cost evaluation, we examine the comparative advantages of each route in terms of hydrogen yield, carbon separation efficiency, process energy intensity, and economic performance. The results demonstrate that CLR achieves a significantly higher hydrogen concentration in the raw syngas stream (62.44%) than SMR (43.14%), with reduced levels of residual methane and carbon monoxide. The energy requirements for hydrogen production are lower in the CLR system, averaging 1.2 MJ/kg, compared to 3.2 MJ/kg for SMR. Furthermore, CLR offers a lower hydrogen production cost (USD 4.3/kg) compared to SMR (USD 6.4/kg), primarily due to improved thermal integration and the absence of solvent-based CO₂ capture. These insights highlight the potential of CLR as a next-generation reforming strategy for producing green hydrogen. To advance its technology readiness, it is proposed to develop a pilot-scale CLR facility to validate system performance under operational conditions and support the pathway to commercial implementation. Full article

The rising concentration of atmospheric carbon dioxide (CO₂), driven largely by fossil fuel combustion, is a major contributor to global climate change and ocean acidification. As conventional CO₂ capture technologies, primarily amine-based solvents, face challenges such as high energy requirements, volatility, and degradation, there is an urgent need for alternative materials that are both efficient and sustainable. Ionic liquids (ILs) and poly (ionic liquids) (PILs) have emerged as promising candidates due to their unique physicochemical properties, including negligible vapor pressure, high thermal and chemical stability, structural tunability, and strong CO₂ affinity. This review provides a comprehensive overview of recent advancements in the design, synthesis, and application of ILs and PILs for CO₂ capture. We examine the mechanisms of CO₂ absorption in IL and PIL systems, analyze the structure-property relationships influencing capture performance, and compare their advantages and limitations relative to conventional solvents. Special attention is given to the role of functional groups, anion/cation selection, and polymeric architectures in enhancing CO₂ uptake and reducing regeneration energy. Finally, the review highlights current challenges and future research directions for scaling up IL and PIL-based technologies in industrial carbon capture and sequestration systems. Full article