Swing Adsorption Process Research Articles

Surrogate modeling and optimization of Pressure/Vacuum Swing Adsorption (P/VSA) processes for carbon capture from post-combustion CO2 point sources

In the present work, a surrogate-based modeling framework has been developed to simulate and optimize Pressure/Vacuum Swing Adsorption (P/VSA) processes, for the efficient separation of CO2 from post-combustion carbon point sources. A single-stage 4-step P/VSA process is considered, using zeolite 13X as adsorbent, aiming to minimize the energy requirements with minimum CO2 purity and recovery targets of 95% and 90%, respectively. The developed P/VSA surrogate model consists of simple non-linear algebraic expressions developed by the ALAMO algorithm, which describe the key process performance indicators as functions of several process variables. In all cases examined, the optimization results from the P/VSA surrogate model are in excellent agreement with the ones obtained from the respective mechanistic model, with a relative deviation of less than 1% between the optimal solutions of the mechanistic and the surrogate model. On the other hand, the computational time for the optimization of the surrogate model is 3-4 orders of magnitude lower compared to that required for the optimization of the mechanistic model, which renders surrogate models particularly suitable for online applications that involve rapid and continuous responses to various input fluctuations.

Dual-stage vacuum pressure swing adsorption for green hydrogen recovery from natural gas grids

Purification of green hydrogen (GH) from natural gas grids (NGG) can be expensive and challenging through a single-step Pressure Swing Adsorption (PSA) process due to the low H2 concentration in the grid (<20 % v/v). Herein, we report for the first time the design of a dual-stage vacuum pressure swing adsorption process (DS-VPSA) to purify H2 blended in NGG with a synergy action of two types of adsorbents: a Carbon Molecular Sieve 3K (CMS) in stage 1 and zeolite 13X in stage 2. In Stage 1, the CMS kinetically separates H2 from CH4, pre-concentrating H2 from 20 % to over 50–60 % (v/v), followed by Stage 2, where a thermodynamic separation with zeolite 13X achieves a final product with a high H2 purity content (>99 % v/v). A mathematical model is developed in Aspen adsorption, where numerical simulations are performed to establish the best operating conditions of the global DS-VPSA. A parametric study is also conducted to optimize performance parameters such as recovery, purity, productivity, and specific energy. The results indicate that it is possible to achieve a final H2 product with a purity of 99.97 % (fuel cell grade), a recovery of 67 %, and productivity of 1.60x10-2 kgH2/kgads/hr, and a total specific energy consumption of 10.06 MJ/kgH2, which is a significant achievement reported so far.

Exploring Geometric Properties and Cycle Design in Packed Bed and Monolith Contactors Using Temperature-Vacuum Swing Adsorption Modeling for Direct Air Capture.

This study presents a comprehensive comparison between the packed bed and monolith contactor configurations for direct air capture (DAC) via process modeling of a temperature-vacuum swing adsorption (TVSA) process. We investigate various design parameters to optimize performance across different contactor geometries, including pellet size, monolith wall thickness, active sorbent content in monoliths, and packed bed structure configurations, considering both a traditional long column (PB40) and multiple shorter columns configured in parallel (PB5). Our parametric analysis assesses specific exergy consumption, sorbent, and volume requirements across different operating conditions of a five-step TVSA cycle. For minimizing sorbent requirements, PB5 and monoliths with over 80% sorbent loading were the best-performing contactor designs with overlapping performance in the low-exergy region. Beyond this region, PB5 faced limitations in reducing sorbent requirements further and was constrained by a maximum velocity at which it is sensible to operate without substantially increasing the exergy demand. In contrast, monoliths decreased sorbent requirements with minimal exergy increase due to reduced mass transfer resistances and lower pressure drop associated with their thin walls. The analysis of volume requirement-specific exergy Pareto fronts revealed that PB5 was less competitive with this metric due to the requirements for additional void space in the contactor configuration. The study also revealed that optimal sorbent loading for reducing volume requirements in monoliths differed from those minimizing sorbent usage, with the most effective loading being below 100%. Thus, the optimal contactor design varies depending on the goals of minimizing sorbent and volume requirements, and the choice and design of the contactor will depend on the relative costs of these factors. Lastly, our findings challenge the assumption that higher velocities are always preferable for direct air capture, suggesting instead that the operating velocity depends on the contactor configuration.

A multi-scale method for the study of deep drying of ethylene with 3A zeolite

Coal-based ethanol to ethylene (ETE) is an emerging production pathway with the advantages of a short construction period, high product purity, and few by-products. N2 is commonly used in industry to regenerate zeolites during the ETE process, with the problems of excessive material consumption, energy consumption and environmental pollution. To solve this problem, this paper proposed a method of using the ethylene product as regeneration gas to regenerate the zeolite and recover the desorbed gas. In this work, we adopted a multi-scale simulation method combining microscale apparent diffusivity and macroscale mass transfer models. Reactive force field and molecular dynamics (ReaxFF-MD) were used to obtain an equation for the diffusion coefficient versus temperature. The start-up of the twin-tower temperature and pressure swing adsorption (TPSA) process was simulated using Computational Fluid Dynamics (CFD). The TPSA process achieved an outlet water content below 5 ppm, fulfilling the process specifications.

Using ligand regulation, metal replacement, and ligand doping strategies on Zr-FUM to improve methane separation from coalbed gas

Developing adsorbents suitable for industrial applications that can effectively enhance the separation of methane (CH4) from nitrogen (N2) in coalbed gas is crucial to improve energy recovery and mitigate greenhouse gas emissions. In this study, three modification strategies were implemented on Zr-FUM, including ligand regulation, metal replacement, and ligand doping, to synthesize Zr-FDCA, Al-FUM, and Zr-FUM-FA, with the aim of improving the performance of CH4/N2 separation under humid conditions. The results demonstrated that the promotion of robust orbital overlap and strengthened electrovalent bonding on adsorbents can selectively enhance CH4 adsorption. As a result, Zr-FUM-FA achieved a saturated CH4 adsorption capacity of 1.37 mmol/g, a CH4 working window of 307 s, and a CH4/N2 sorbent selection parameter (Ssp) of 47.31, exceeding the performance of most reported adsorbents. Analyses of the pore structure, surface morphology, and functional groups revealed that the presence of an ultramicropore proximity to CH4, reduced static resistance, and enhanced electrovalent bond were key factors for CH4 separation. Grand Canonical Monte Carlo and Density Functional Theory studies indicated that the introduction of -C-H- in FA played a crucial role in enhancing CH4 adsorption. Optimization of adsorption parameters using the Aspen adsorption package showed that in a dual-adsorbent bed system, the recovery and purity of CH4 in Zr-FUM-FA reach 99.5% and 97.3%, respectively, providing important theoretical support for the improvement of CH4 recovery in the pressure swing adsorption process from coalbed gas.

A PLC-Embedded Implementation of a Modified Takagi–Sugeno–Kang-Based MPC to Control a Pressure Swing Adsorption Process

The paper presents a case study that applies a model predictive control (MPC) approach in a Micro850 programmable logic controller (PLC) to a laboratory pressure swing adsorption (PSA) process used for separating gas mixtures of CO2 and CH4. PLC is an industrial hardware characterized by its robustness to hazardous environments and limited computational capacities, which poses computational challenges for MPC implementation. This paper’s main contribution is the application of the modified Takagi–Sugeno–Kang-based MPC (MTSK-MPC) algorithm to this PSA unit, which provides features to investigate and implement feasible MPC designs in PLCs. The investigation consists of a sensitivity analysis of how some design parameters influence the PLC memory and the MPC implementation and a comparative evaluation of the computational processing from different MPC algorithms and simulations. The comparison comprises software-in-the-loop simulations with three algorithms in the PC: an implicit MPC, an explicit MPC, and the MTSK-MPC. Additionally, it includes a hardware-in-the-loop simulation with the implemented MTSK-MPC in Micro850. The results show that the MPC algorithms achieve close performance, tracking setpoint changes and rejecting output disturbances, with the MTSK-MPC presenting the lower processing time among the MPCs in the PC. The study concludes that the implementation of MTSK-MPC in the Micro850 is feasible.

The impact of design and operational parameters on the optimal performance of direct air capture units using solid sorbents

Direct capture of CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_2$$\\end{document} from ambient air is technically feasible today, with commercial units already in operation. A demonstrated technology for achieving direct air capture (DAC) is chemical separation of CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_2$$\\end{document} in a steam-assisted temperature-vacuum swing adsorption (S-TVSA) process. However, the potential to develop scalable solutions remains high, requiring a detailed understanding of the impact of both process design and operation on the performance of the DAC unit. Here, we address this knowledge gap by presenting a state-of-the-art process simulation tool for the purification of CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_2$$\\end{document} from ambient air by a 5-step S-TVSA process. By considering the benchmark adsorbent APDES-NFC, we conduct multi-objective productivity/energy usage optimization of the DAC unit, subject to the requirement of producing a high purity CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_2$$\\end{document} product (≥95\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ge 95$$\\end{document}%). For the base case scenario, we find a maximum productivity of Prmax=6.20\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{\\max } = 6.20$$\\end{document} kg/m3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^3$$\\end{document}/day and a minimum specific equivalent work of WEQ,min=1.66\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{\ ext {EQ},\\min } = 1.66$$\\end{document} MJ/kg. While in reasonable agreement with published data, our results indicate that the description of both competitive adsorption and adsorption kinetics are key factors in introducing uncertainty in process model predictions. We also demonstrate that the application of formal optimization techniques, rather than design heuristics, is central to reliably assess the process performance limits. We identity that system designs employing moderate CO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_2$$\\end{document} sorption kinetics and contactors with low length-to-radius ratios yield the best performance in terms of system productivity. Finally, we find that moderate-high ambient relative humidities (50–75%) offer significantly favourable performance, and that a wide range of feed temperatures (5–30 ∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\circ$$\\end{document}C) can be accommodated via process optimization without a significant impact on performance.

Multi-objective optimization of ANN-based vacuum pressure swing adsorption process for ethane and ethylene separation

A bilevel optimization methodology was developed for separating ethane and ethylene using vacuum pressure swing adsorption. Data generated through Latin hypercube sampling and normalization were employed to construct a neural network at a lower level, serving as a surrogate model for the comprehensive first-principle adsorption process. Following sensitivity analysis based on Monte Carlo simulation, optimization, data resampling, and reconciliation were performed at an upper level. Two cases were performed to optimize the ethane and ethylene separation process. In the first scenario, ethylene recovery was optimized under a purity constraint, resulting in an enhancement from 65.28 % to 87.19 %. In the second scenario, both ethylene recovery and energy consumption were simultaneously optimized with the purity constraint, leading to the generation of a Pareto front. From this Pareto front, two operating conditions were determined: one using TOPSIS and the other aimed at reducing energy consumption from a conventional distillation column to 0.733 MJ/kg-ethylene. Compared to conventional distillation, the vacuum pressure swing adsorption (VPSA) process showed 82.8 % recovery with 0.747 MJ/kg-ethylene and 72.21 % recovery with 0.683 MJ/kg-ethylene. A dynamic analysis and an economic analysis of scaling up VPSA process were performed to compare with C2 splitter.

Pressure swing adsorption process modeling using physics-informed machine learning with transfer learning and labeled data

Pressure swing adsorption (PSA) modeling remains a challenging task since it exhibits strong dynamic and cyclic behavior. This study presents a systematic physics-informed machine learning method that integrates transfer learning and labeled data to construct a spatiotemporal model of the PSA process. To approximate the latent solutions of partial differential equations (PDEs) in the specific steps of pressurization, adsorption, heavy reflux, counter-current depressurization, and light reflux, the system's network representation is decomposed into five lightweight sub-networks. On this basis, we propose a parameter-based transfer learning (TL) combined with domain decomposition to address the long-term integration of periodic PDEs and expedite the network training process. Moreover, to tackle challenges related to sharp adsorption fronts, our method allows for the inclusion of a specified amount of labeled data at the boundaries and/or within the system in the loss function. The results show that the proposed method closely matches the outcomes achieved through the conventional numerical method, effectively simulating all steps and cyclic behavior within the PSA processes.

Modeling and design of a combined electrified steam methane reforming-pressure swing adsorption process

Steam methane reforming (SMR) is the most widely used hydrogen (H2) production method, converting natural gas and steam into H2 and carbon dioxide (CO2). SMR is a mature industrial technology that burns fossil fuels to provide heat to the endothermic reforming reaction and to generate steam, which contributes to the production of greenhouse gas emissions. In order to reduce heating-based emissions, an electrically-heated steam methane reforming process has been proposed. Conventional SMR uses a packed bed catalyst and receives heat through radiation from hot flames in the surrounding furnace; on the other hand, an electrified SMR employs a washcoated catalyst, and is resistively-heated through the wall of the reactor coil. To gain further insight into the scalability of hydrogen production processes using electrically-heated reformers, this paper takes experimental data from an electrified reformer built at UCLA, extracts kinetic parameters, and uses these parameters to model and scale up a hydrogen production plant with a hydrogen production capacity of 231 kg/h (2607 Nm3/h). The simulated plant includes a reformer, two water gas shift reactors, pressure swing adsorption (PSA) for separation, and a heat exchange network to make steam for the reformer. A two-column-PSA process is dynamically modeled to output 99% H2 purity, and the pressures necessary for separation and H2 recovery are calculated using steady-state simulation data. A sensitivity analysis is conducted for the most energy-efficient H2 production conditions (e.g., operating pressure, heat flux), and CO2 production amounts are compared to a conventional SMR process, demonstrating that electrified SMR can potentially be a significantly cleaner alternative. The optimization of electrified reformers must target high mass and heat transfer along the full length of the reformer to achieve near full methane conversion that will minimize off-gas generation from the PSA unit.

Adsorption capability and regenerability of carbon slit micropores for CO2 capture

To date, the exceptional performance of microporous carbon in CO2 capture has been widely acknowledged as a crucial step towards achieving global zero carbon emissions. In this molecular simulation study, we employ grand canonical Monte Carlo simulation (GCMC) to shed light on the significant influence of micropores on CO2 adsorption capability and regenerability, emphasizing the need for a rigorous selection of the swing adsorption process based on pore size. Our findings corroborate numerous experimental and numerical studies that the ultramicropore (pore size < 7 Å) is the appropriate range for CO2 capture, as it facilitates the formation of a horizontal monolayer of CO2 molecules. Furthermore, we highlight the importance of designing porous carbon materials with a large pore volume at the optimal ultramicropore sizes (approximately 5.8-6.4 Å depending on adsorption and desorption conditions) for obtaining high CO2 capture capacity and effective adsorbent regeneration. For the first time, taking into account the operational parameters of practical swing adsorption processes, our simulation study provides valuable guidance for selecting the most appropriate technology tailored to each specific range of micropore size in porous carbon. For porous carbon materials with an abundant volume of ultramicropores, pressure swing adsorption (PSA) and pressure-temperature swing adsorption (PTSA), as conventional and hybrid swing adsorption processes respectively, are the most effective practices, achieving high CO2 working capacity and regenerability exceeding 80%.

Troubleshooting of an Industrial Ethane Treatment Unit: Ultradilute CO2 Adsorption from Ethane Stream by a Temperature Swing Adsorption Process

Troubleshooting of an Industrial Ethane Treatment Unit: Ultradilute CO₂ Adsorption from Ethane Stream by a Temperature Swing Adsorption Process

Multiscale screening of metal‐organic frameworks for one‐step ethylene purification in pressure‐swing adsorption processes

AbstractPurification of polymer‐grade (99.9%) C2H4 from C2 hydrocarbon mixture is industrially important but challenging. Cryogenic distillation is energy intensive. Recently, pressure/vacuum swing adsorption (P/VSA) processes using metal‐organic frameworks (MOFs) as adsorbents have been attracting increasing attention as an alternative technology. A multiscale hierarchical framework is proposed to select promising MOFs and design suitable P/VSA processes by combining property‐based material screening and model‐based process optimization. Using this framework, we successfully identified seven promising one‐step C2H4 purification MOFs that outperformed the benchmark TJT‐100 in both C2H4 purity and recovery for the 5/90/5 C2H2/C2H4/C2H6 feed mixture. Among them, OFUCAV exhibited the highest C2H4 productivity of 0.158 mol/m3/s while JAVTAC demonstrated the lowest energy consumption of 42.76 kWh/tonne. The latter can potentially save 80% of the energy consumption compared to cryogenic distillation. Moreover, these two P/VSA processes show very high robustness in response to composition fluctuations in the feed stream.

Operability-economics trade-offs in adsorption-based CO2 capture processes

Dispatchable low-carbon power underpins the transition to a sustainable energy system, providing balancing load for the integration of intermittent renewable power. In such load-following operation, the post-combustion carbon capture process must be capable of highly transient operation. Here we have developed a computational framework that integrates process design, operability and techno-economic assessment of a pressure-vacuum swing adsorption process for CO2 capture. We demonstrate that the cost-optimal design has limited process flexibility, challenging reactiveness to disturbances in the flue gas conditions. Flexibility can be introduced by relaxing the CO2 recovery constraint on the operation, albeit at the expense of the capture efficiency of the process. We discover that adsorption-based processes can be designed to enhance flexibility, while improving performance with respect to the operational constraints on CO2 recovery and purity. The results herein demonstrate a trade-off between process economics and process operability, which must be rationalised to integrate CO2 capture units in low-carbon energy systems.

Wood-structured carbon with reassembled pores showing high propylene adsorption rate for efficient separation of propylene/propane

Efficient separation of propylene/propane requires enhancing adsorption rates on adsorbents, while maintaining high adsorption capacity and selectivity, heavily relying on engineering pore structures within the adsorbents. Herein, we have prepared wood-structured carbon with reassembled pores by using wood frameworks incorporated with CuCl2 and a polymer coating. Upon carbonization, the wood framework transforms into microporous carbon, while the polymer coating converts into molecular sieving carbon. Notably, the evaporation of CuCl produced from the in-situ reduction of CuCl2 creates additional micropores in the molecular sieving carbon layer. This wood-structured carbon adsorbent exhibits a propylene diffusion constant of 0.011 min−1 at 0.5 bar, which is 4.1-fold higher than the sample without CuCl2. Additionally, this adsorbent shows a high propylene uptake of 2.38 mmol g−1 and a propylene/propane dynamic selectivity of up to 161 at 298 K and 1 bar. Aspen simulation suggests that a propylene purity of 99.9 % can be achieved with a 70 % recovery using a vacuum swing adsorption process. The enhanced performance is primarily attributed to the unique pore structures of the wood-structured carbon adsorbent.

Optimizing medical oxygen concentrators: Efficiency, flexibility, and patient-centric solutions

Medical oxygen concentrators (MOCs) play a vital role in providing oxygen therapy to patients with respiratory diseases. This paper offers a comprehensive evaluation of different adsorbents, including 13X, LiLSX, 5A, CaX, Ag-ETS-10, and AgLiLSX, utilized in MOCs. Process modeling and multi-objective optimization are conducted to assess the effectiveness of these adsorbents using the Skarstrøm cycle, employing pressure swing adsorption (PSA), vacuum swing adsorption (VSA), and pressure vacuum swing adsorption (PVSA) processes. The optimization result indicates that LiLSX is the top choice, providing medical-grade oxygen at a total product flow rate exceeding 15 SLPM. Additionally, 13X and CaX are identified as economical alternatives, particularly suitable for employment in the PSA and VSA processes, respectively. This study highlights the significance of establishing a connection between the Medical and Chemical Engineering communities through the direct incorporation of medical performance indicators, such as the fraction of inspired oxygen (FIO2), into the optimization process. The findings serve as a guide for selecting an appropriate design based on the patient’s requirements and demonstrate LiLSX’s capability to meet a diverse range of treatments, achieving FIO2 values up to 0.75. Furthermore, we explore the flexibility of MOC designs in meeting the demands of multiple patients simultaneously and propose energy-efficient design options based on patient needs. Overall, this study provides valuable insights into optimizing MOCs, ensuring effective and reliable oxygen therapy for patients, while also addressing challenges like the COVID-19 pandemic and potential global lithium scarcity.

Research on Oil and Gas Adsorption Optimization Based on CFD Modeling and Process Simulation.

In the process of oil extraction and refining, some of the liquid light hydrocarbon components will inevitably evaporate into the atmosphere, causing serious air pollution and safety hazards. This paper is focused on oil and gas adsorption systems to comprehensively optimize key parameters by combining computational fluid dynamics (CFD) modeling with process simulation, enabling the efficient treatment of hazardous materials. First, a CFD model of the hydrocarbon adsorption process is established to the porous media model by a user-defined function (UDF). Subsequently, the mass transfer process of oil and gas in porous media is successfully simulated to obtain the gas distribution in an industrial fixed bed adsorption tower. The adsorption tank is intensified, and the gas distribution in the tank is improved by optimizing the height-to-diameter ratio of the equipment and the design of the intake distributor. Third, the cyclic two-tank adsorption model of the pressure swing adsorption (PSA) process is established for key parameters optimization. Finally, the operating parameters and conditions of the PSA process are suspected by considering five factors affecting the adsorption efficiency: adsorption time, adsorption pressure, adsorption temperature, feed flow rate, and purge ratio of the washing step.

Solar-driven high-performance biomass porous carbon for efficient CO2 capture

Temperature swing adsorption (TSA) based on solid adsorbents is an efficient CO2 capture technology, but the temperature swing process is energy-intensive. Utilizing solar energy to regenerate adsorbents during the CO2 swing adsorption process can decrease energy consumption. This work reports a novel high-performance biomass porous carbon for efficient CO2 capture and separation in the solar-driven TSA process. Inspired by the distinctive internal expansion structure of succulents, the adsorbent is synthesized using succulents as precursors with a large specific surface area (1715 m2/g) and high solar absorbance (90.38 %), resulting in high CO2 adsorption capacity and solar thermal conversion capacity. It achieves a remarkable working capacity of 30.94 mg/g at a low desorption temperature (60 °C) in the solar-driven TSA process with a light intensity of 600 W/m2, 80.7 % higher than commercial activation carbon. The proposed biomass porous carbon derived from succulent plants has substantial potential for application in the solar-driven TSA process.

Efficient hybrid strategy for simultaneous design of refinery hydrogen networks and pressure swing adsorption unit

Refineries face increasing hydrogen demand due to the consumption of heavy and sour crude oil. This study presents a novel hybrid method to optimize hydrogen network configurations with a rigorous pressure swing adsorption (PSA) process model. This method utilizes Bayesian optimization to address the upper-level unknown constraints black-box optimization problem while employing deterministic algorithms to manage the lower-level nonlinear programming problem. Furthermore, infeasible regions are transformed into feasible ones by introducing a dummy stream, and the costs incurred during the transformation process are accurately calculated. The proposed method is validated using two literature cases. In Case 1, Bayesian optimization outperformed the Kriging model, resulting in a 7.84% reduction in total annual cost (TAC). In Case 2, a comparison of four search strategies revealed the developed two-phase strategy as the most effective one. This method offers a powerful and practical tool for optimizing real-world hydrogen networks with PSA processes.

Synthesis of biomass combustion fly ash derived zeolites for CO2 adsorption: Optimisation of hydrothermal synthetic pathway

Industrial biomass combustion fly ash has been investigated as a precursor for zeolites with a view to evaluate the potential for adsorption of CO2. The synthesis methodology has been optimised via Design of Experiment by employing a Taguchi L9 array. Three variables were identified as statistically significant, the crystallisation temperature, crystallisation time and the liquid to solid ratio. Analysis of the main effects revealed an optimum set of conditions which produced a sample with the highest adsorption capacity of those prepared, 1.84 mmol g−1 at 50 °C. This was a result of the conversion of the as-received fly ash into type A (LTA) and type X (FAU) zeolites after alkaline fusion with NaOH and hydrothermal treatment. The enthalpy of adsorption was estimated at -40.2kJmol−1 and was shown to be dependent on surface coverage; the isosteric enthalpy of adsorption at zero coverage was -86 kJ mol−1. The working capacity of the adsorbent was maintained at 85 % of the first adsorption uptake after a total of 40 cycles in a simulated temperature swing adsorption process (50 °C/150 °C adsorption/desorption). The equilibrium and kinetic CO2 adsorption isotherms are presented and modelled through non-linear regression to reveal the adsorption mechanisms demonstrated by the fly ash-derived zeolites. Significant heterogeneity exists within the multi-phase zeolite which presents both micro and mesoporosity. The developed adsorbent presents a feasible route to valorisation of biomass combustion fly ash with good potential for application in the separation of CO2.