Capture Process Research Articles

A novel fast hybrid capture sequencing method for high-efficiency common human coronavirus whole-genome acquisition.

Rapid and accurate sequencing of the entire viral genome, coupled with continuous monitoring of genetic changes, is crucial for understanding the epidemiology of coronaviruses. We designed a novel method called micro target hybrid capture system (MT-Capture) to enable whole-genome sequencing in a timely manner. The novel design of probes used in target binding exhibits a unique and synergistic "hand-in-hand" conjugation effect. The entire hybrid capture process is within 2.5 hours, overcoming the time-consuming and complex operation characteristics of the traditional liquid-phase hybrid capture (T-Capture) system. By designing specific probes for these coronaviruses, MT-Capture effectively enriched isolated strains and 112 clinical samples of coronaviruses with cycle threshold values below 37. Compared to multiplex PCR sequencing, it does not require frequent primer updates and has higher compatibility. MT-Capture is highly sensitive and capable of tracking variants.IMPORTANCEMT-Capture is meticulously designed to enable the efficient acquisition of the target genome of the common human coronavirus. Coronavirus is a kind of virus that people are generally susceptible to and is epidemic and infectious, and it is the virus with the longest genome among known RNA viruses. Therefore, common human coronavirus samples are selected to evaluate the accuracy and sensitivity of MT-Capture. This method utilizes innovative probe designs optimized through probe conjugation techniques, greatly shortening the time and simplifying the handwork compared with traditional hybridization capture processes. Our results demonstrate that MT-Capture surpasses multiplex PCR in terms of sensitivity, exhibiting a thousandfold increase. Moreover, MT-Capture excels in the identification of mutation sites. This method not only is used to target the coronaviruses but also may be used to diagnose other diseases, including various infectious diseases, genetic diseases, or tumors.

Plasma–ionic liquid-assisted CO2 capture and conversion: A novel technology

The present study focused on CO2 capture, storage, and conversion through the innovative integration of plasma–ionic liquid (IL) technology. For the first time, we employed plasma-IL technology to confront climate change challenges. We utilized 1-Butyl-3-methylimidazolium chloride IL to capture and store CO2 under atmospheric pressure, and subsequently employed plasma to induce the transformation of IL-captured CO2 into CO. Furthermore, we performed computer simulations to enhance our understanding of the CO2 and CO capture processes of water and IL solutions. This comprehensive approach provides valuable insights into the potential of plasma–IL technology as a viable solution for climate change.

The intermediate neutron capture process

Context. The intermediate neutron capture process (i-process) can develop during proton ingestion events (PIE), potentially during the early stages of low-mass low-metallicity asymptotic giant branch (AGB) stars. Aims. We examine the impact of overshoot mixing on the triggering and development of i-process nucleosynthesis in AGB stars of various initial masses and metallicities. Methods. We computed AGB stellar models, with initial masses of 1, 2, 3, and 4 M⊙ and metallicities in the −2.5 ≤ [Fe/H] ≤ 0 range, using the stellar evolution code STAREVOL with a network of 1160 nuclei coupled to the transport equations. We considered different overshooting profiles below and above the thermal pulses, and below the convective envelope. Results. The occurrence of PIEs is found to be primarily governed by the amount of overshooting at the top of pulse (ftop) and to increase with rising ftop. For ftop = 0, 0.02, 0.04, and 0.1, we find that 0%, 6%, 24%, and 86% of our 21 AGB models with −2 < [Fe/H] < 0 experience a PIE, respectively. Variations of the overshooting parameters during a PIE leads to a scatter on abundances of 0.5 − 1 dex on elements, with 36 < Z < 56; however, this barely impacts the production of elements with 56 < Z < 80, which therefore appear to be a reliable prediction of our models. Actinides are only produced if the overshooting at the top of pulse is small enough. We also find that PIEs leave a 13C-pocket at the bottom of the pulse that can give rise to an additional radiative s-process nucleosynthesis. In the case of the 2 M⊙ models with [Fe/H] = −1 and −0.5, it produces a noticeable mixed i + s chemical signature at the surface. Finally, the chemical abundance patterns of 22 observed r/s-stars candidates (18 dwarfs or giants and 4 post-AGB) with −2 < [Fe/H] < −1 are found to be in reasonable agreement with our AGB model predictions. The binary status of the dwarfs/giants being unclear, we suggest that these stars have acquired their chemical pattern either from the mass transfer of a now-extinct AGB companion or from an early generation AGB star that polluted the natal cloud. Conclusions. The occurrence of PIEs and the development of i-process nucleosynthesis in AGB stars remains sensitive to the overshooting parametrization. A high (yet realistic) ftop value triggers PIEs at (almost) all metallicities. The existence of r/s-stars at [Fe/H] ≃ −1 is in favour of an i-process operating in AGB stars up to this metallicity. Stricter constraints from multi-dimensional hydrodynamical models on overshoot coefficients could deliver new insights into the contribution of AGB stars to heavy elements in the Universe.

Development of a portable electronic nose for the classification of tea quality based on tea dregs aroma

Abstract The current assessment of tea quality is considered subjective. This study aims to develop a portable electronic nose to assess the aroma of tea dregs objectively by relying on the aromatic capture process through sensors and using multilayer perceptron (MLP). A MLP with some hyperparameter variations is used and compared with five machine-learning classifiers. The classification using MLP model with ReLU activation function and 3 hidden layers with 100 hidden nodes resulted in the highest accuracy of 0.8750 ± 0.0241. The MLP model using ReLU activation function is better than Sigmoid while increasing the number of hidden layers and hidden nodes does not necessarily enhance its performance. In the future, this research can be improved by adding sensors to the portable electronic nose, increasing the number of datasets used, and using ensemble learning or deep learning models.

CO2 capture using silica-immobilized dicationic ionic liquids with magnetic and non-magnetic properties

The need to find alternative materials to replace aqueous amine solutions for the capture of CO2 in post-combustion technologies is pressing. This study assesses the CO2 sorption capacity and CO2/N2 selectivity of three dicationic ionic liquids with distinct anions immobilized in commercial mesoporous silica support (SBA- 15). The samples were characterized by UART-FTIR, NMR, Raman, FESEM, TEM, TGA, Magnetometry (VSM), BET and BJH. The highest CO2 sorption capacity and CO2/N2 selectivity were obtained for sample SBA@DIL_2FeCl4 [at 1 bar and 25 °C; 57.31 (±0.02) mg CO2/g; 12.27 (±0.72) mg CO2/g]. The results were compared to pristine SBA-15 and revealed a similar sorption capacity, indicating that the IL has no impact on the CO2 sorption capacity of silica. On the other hand, selectivity was improved by approximately 3.8 times, demonstrating the affinity of the ionic liquid for the CO2 molecule. The material underwent multiple sorption/desorption cycles and proved to be stable and a promising option for use in industrial CO2 capture processes.

Preface

The 6th International Conference on Chemical Engineering, Food and Biotechnology (ICCFB2023) The 6th ICCFB - International Conference on Chemical Engineering, Food and Biotechnology was successfully held in Ho Chi Minh City, Vietnam during September 29th-30th, 2023. The scientific conference was organized by the Faculty of Chemical Engineering, Ho Chi Minh City University of Technology (HCMUT), VNU-HCM, and co-organized by PetroVietnam University.During the 6th ICCFB, the emerging technologies and scientific advancements in the fields of Chemical Engineering, Food and Biotechnology were disseminated. It served as a platform for strengthening partnership between academia and industry. The scientific papers submitted to the conference were categorized into three sections (Sustainability, Green Technology and Process Safety Engineering; Material Sciences, Environmental Engineering; Agriculture, Biotechnology and Food Technology) and carefully reviewed with a double-blind process. All the accepted papers were presented in the conference.The plenary speeches were given to make the conference more productive and precious.• Prof. Nobuyuki Kijima, Institute of Food Research, National Agriculture and Food Research Organization, Japan - What is the major impact of antibiotic-application to agricultural field? • Prof. Won-Chun Oh, Hanseo University, Korea - Recent advances in CO2 reduction applications: progress, challenges and perspectives.• Prof. Suresh Sagadevan, University of Malaya, Malaysia - Nanocomposite photocatalysts for wastewater treatment.• Prof. Sanggono Adisasmito, Institut Teknologi Bandung, Indonesia - Energy Transition and Carbon Capture Process for Coal-Fired Power Plants in Indonesia.We thank all distinguished guests, authors, participants for their contributions to make a successful conference and look forward to the 7th ICCFB in 2025.List of Steering Committee and Editors are available in this pdf.

Thermodynamic Feasibility Evaluation of Alkaline Thermal Treatment Process for Hydrogen Production and Carbon Capture from Biomass by Process Modeling

Hydrogen is attracting attention as a low-carbon fuel. In particular, economical hydrogen production technologies without carbon emissions are gaining increasing attention. Recently, alkaline thermal treatment (ATT) has been proposed to reduce carbon emissions by capturing carbon in its solid phase during hydrogen production. By adding an alkali catalyst to the conventional thermochemical hydrogen production reaction, ATT enables carbon capture through the reaction of an alkali catalyst and carbon. In this study, a thermodynamic feasibility evaluation was carried out, and the effects of the process conditions for ATT with wheat straw grass (WSG) as biomass were investigated using Aspen Plus software V12.1. First, an ATT process model was developed, and basic thermodynamic equilibrium compositions were obtained in various conditions. Then, the effects of the process parameters of the reactor temperature and the mass ratio of NaOH/WSG (alkali/biomass, A/B value) were analyzed. Finally, the product gas compositions, process efficiency, and amount of carbon capture were evaluated. The results showed that the ATT process could be an efficient hydrogen production process with carbon capture, and the optimal process conditions were a reactor temperature of 800 °C, an A/B value of three, and a flow rate of steam of 6.9 × 10−5 L/min. Under these conditions, the maximum efficiency and the amount of carbon dioxide captured were 56.9% and 28.41 mmol/g WSG, respectively.

ASSESSMENT OF HEAT BALANCE IN THE FSRU REGASIFICATION CYCLE ALIGNS WITH IMO’S DECARBONISATION STRATEGY

In 2023, the International Maritime Organization revised its greenhouse gas strategy, striving to reduce annual emissions from international shipping by at least 70% by 2040. The Mediterranean Sea will become an emission control area for sulphur oxides and particulate matter from May 2025, and the EU will include shipping in its Emission Trading System from 2024. Liquid natural gas is expected to become a cleaner marine fuel, but it alone cannot meet emission reduction goals. The cryogenic carbon capture process can separate CO2 from exhaust gases, compress it, and store it in a liquid state with high density. This study aims to integrate an energy balance equation model to analyse the energy exchange in the regasification process and identify potential areas for improvement and targeted solutions to enhance performance and comply with IMO emission regulations. Based on a mathematical model, the energy balances are calculated and yield the following results: steam heater (26,999 kW), R-290 preheater (5,837 kW), trim heater (3,290 kW), R-290 evaporator (13,322 kW), and LNG vaporiser (23,118 kW). A report also determined that within a temperature range between -56.6℃ and 31℃ and a pressure range of greater than 5.2 bar (absolute) and less than 74 bar (absolute), the CO2 is in a liquid phase. Due to CO2 density which fluctuates in liquid at 1032 kg/m3 and in solid phase at 1562 kg/m3 the physical condition is compatible with the storage stage of capture emission.

Monoethanolamine assisted CO2 hydrogenation to methanol – A computational study

Carbon dioxide emission to the atmosphere has to be reduced which can be done by utilizing CO2 in the synthesis of added value products. At the same time this will lead to a process which can help to store renewable energy. The use of hydrogen produced from the electrolysis of water in carbon dioxide reduction to methanol could be an efficient way to store energy and to convert CO2 into an added value product. The synthesis of methanol from CO2 is usually performed catalytically in gas phase. Many scientists nowadays expressed interest in testing the feasibility of the reaction also in aqueous phase. In this direction, monoethanolamine (MEA) can be used as a solvent for capturing and trapping carbon dioxide in an aqueous phase. In this work, the hydrogenation of (2-hydroxyethyl) carbamic acid (HO-(CH2)2-NH-COOH) which is one of the produced species during the capture process has been investigated by using computational tools. The uncatalyzed and catalyzed-like hydrogenation mechanisms leading to methanol (and MEA+water) as a product has been studied by using high level ab initio calculations in aqueous phase. The mechanisms have been described at the molecular level to provide a deeper understanding of the processes. The calculations indicate that the highest barrier height in the catalyzed-like process is only 114.67 kJ/mol, which is 227.71 kJ/mol lower than the corresponding step in the uncatalyzed mechanism. Furthermore, the energy storage efficiency of the catalyzed-like process is 96.68 %, which is 7.5 times more efficient than the uncatalyzed mechanism.

Indoor CO2 capture-driven passive cooling for photovoltaics with ventilation energy reduction utilizing amine-functionalized adsorbents

In carbon capture, utilization, and storage processes, CO2 capture consumes 80 % of total energy consumption, reaching 3–8 MJ/kg which poses a formidable challenge. Conversely, buildings are responsible for approximately 40 % of final energy consumption and contribute over 30 % of CO2 emissions, highlighting the urgent need to reduce the building energy. In this work, a sustainable indoor CO2 capture-driven passive cooling system is developed for building-integrated photovoltaics with ventilation energy reduction by coating amine-impregnated mesoporous silica (PEI/MCM-41) to the rear of PV cells using supersonic cold spraying method. During nighttime, it effectively mitigates indoor CO2 concentration increase due to human respiration by capturing 1.64 mmol/g of CO2, enabling a reduction of 180 MJ/kg-thermal in winter and 30.4 MJ/kg-electric in summer within the building. In daylight hours, PV cells generate electricity, and the supplied radiant solar heat is consumed for CO2 desorption (latent cooling), lowering the average temperature of the PV cells and improving the power efficiency. PEI/MCM-41 achieves a remarkable cooling energy density of 242 J/g and average cooling power of 357 W/m2. It has been demonstrated that the present system can simultaneously reduce the building energy consumption and CO2 emission.

Technical and economic performance assessment of blue hydrogen production using new configuration through modelling and simulation

Steam methane reforming (SMR) is the dominant process for hydrogen production, which produce large amount of carbon dioxide (CO2) as a by-product. To address concerns about carbon emissions, there is an increasing focus on blue hydrogen to mitigate carbon emissions during hydrogen production. However, the commercialization of blue hydrogen production (BHP) is hindered by the challenges of high cost and energy consumption. This study proposes a new configuration to address these challenges, which is characterized by: (a) the use of piperazine (PZ) as a solvent, which has a high CO2 absorption efficiency; (b) a more efficient heat exchange configuration which recovers the waste exergy from flue gas; (c) the advanced flash stripper (AFS) was adopted to reduce the capital cost due to its simpler stripper configuration. In addition, the technical and economic performance of the proposed energy and cost-saving blue hydrogen production (ECSB) process is investigated and compared with the standard SMR process. The detailed models of the SMR process and the post-combustion carbon capture (PCC) process were developed and integrated in Aspen plus® V11. The results of the technical analysis showed that the ECSB process with 30 wt.% PZ achieves a 36.3 % reduction in energy penalty when compared to the standard process with 30 wt.% Monoethanolamine (MEA). The results of the economic analysis showed that the lowest levelized cost of blue hydrogen (LCBH) was achieved by the ECSB process with 30 wt.% PZ. Compared to the BHP process with 30 wt.% MEA, the LCBH was reduced by 19.7 %.

The intermediate neutron capture process

Context. The observed surface abundance distributions of carbon-enhanced metal-poor (CEMP) r/s stars suggest that these stars could have been polluted by an intermediate neutron capture process (the so-called i-process) occurring at intermediate neutron densities between the r- and s-processes. Triggered by the ingestion of protons inside a convective He-burning zone, the i-process could be hosted in several sites, a promising one being the early AGB phase of low-mass, low-metallicity stars. The i-process remains affected however by many uncertainties, including those of nuclear origin, since it involves hundreds of nuclei for which reaction rates have not yet been determined experimentally. Aims. We investigate both the systematic and statistical uncertainties associated with theoretical nuclear reaction rates of relevance during the i-process and explore their impact on the i-process elemental production, and subsequently on the surface enrichment, of a low-mass, low-metallicity star during the early AGB phase. Methods. We used the TALYS reaction code to estimate both the model and parameter uncertainties affecting the photon strength function and the nuclear level densities, and hence the radiative neutron capture rates. The impact of correlated systematic uncertainties was estimated by considering different nuclear models, as was detailed in Paper II. In contrast, the uncorrelated uncertainties associated with local variation in model parameters were estimated using a variant of the backward-forward Monte Carlo method to constrain the parameter changes to experimentally known cross sections before propagating them consistently to the neutron capture rates. The STAREVOL code (Siess 2006, A&A, 448, 717) was used to determine the impact of nuclear uncertainties on the i-process nucleosynthesis in a 1 M⊙ [Fe/H] = –2.5 model star during the proton ingestion event in the early AGB phase. A large nuclear network of 1160 species coherently coupled to the transport processes was solved to follow the i-process nucleosynthesis. Results. We find that the uncorrelated parameter uncertainties lead the surface abundance uncertainties of elements with Z ≥ 40 to range between 0.5 and 1.0 dex, with odd-Z elements displaying higher uncertainties. The correlated model uncertainties are of the same order of magnitude, and both model and parameter uncertainties have an important impact on potential observable tracers such as Eu and La. We find around 125 important (n, γ) reactions impacting the surface abundances, including 28 reactions that have a medium to high impact on the surface abundance of elements that are taken as observable tracers of i-process nucleosynthesis in CEMP stars. Conclusions. Both the correlated model and uncorrelated parameter uncertainties need to be estimated coherently before being propagated to astrophysical observables through multi-zone stellar evolution models. Many reactions are found to affect the i-process predictions and will require improved nuclear models guided by experimental constraints. Priority should be given to the reactions influencing the observable tracers.

Theoretical Advances in Beta and Double-Beta Decay

Weak interaction processes continue to be hot topics in fundamental physics research. In this paper, we briefly review some recent advances in the theoretical study of beta and double-beta decays that include both the nuclear and atomic part of these processes. On the nuclear side, we present a statistical approach for the computation of the nuclear matrix elements (NME) for neutrinoless double-beta (0νββ). A range of NME values, the most probable value for NME, and the associated theoretical uncertainty are given. Correlations with other related observables are shown as well. On the atomic side, we first briefly review the methods used to obtain the electrons’ wave functions. Further, we use them for the computation of some relevant kinematic quantities such as Fermi functions, electron spectra, and angular correlation between the emitted electrons. Then, we present applications of these calculations to the experimental data analysis related to the search of the Lorentz invariance violation in two-neutrino double-beta (2νββ) decay and description of the decay rates and decay rate ratios for allowed and unique forbidden electron capture (EC) processes.

A Scalable Robust Microporous Al-MOF for Post-Combustion Carbon Capture.

Herein, a robust microporous aluminum tetracarboxylate framework, MIL-120(Al)-AP, (MIL, AP: Institute Lavoisier and Ambient Pressure synthesis, respectively) is reported, which exhibits high CO2 uptake (1.9mmol g-1 at 0.1bar, 298 K). In situ Synchrotron X-ray diffraction measurements together with Monte Carlo simulations reveal that this structure offers a favorable CO2 capture configuration with the pores being decorated with a high density of µ2-OH groups and accessible aromatic rings. Meanwhile, based on calculations and experimental evidence, moderate host-guest interactions Qst (CO2) value of MIL-120(Al)-AP (-40kJ mol-1) is deduced, suggesting a relatively low energy penalty for full regeneration. Moreover, an environmentally friendly ambient pressure green route, relying on inexpensive raw materials, is developed to prepare MIL-120(Al)-AP at the kilogram scale with a high yield while the Metal- Organic Framework (MOF)is further shaped with inorganic binders as millimeter-sized mechanically stable beads. First evidences of its efficient CO2/N2 separation ability are validated by breakthrough experiments while operando IR experiments indicate a kinetically favorable CO2 adsorption over water. Finally, a techno-economic analysis gives an estimated production cost of ≈ 13 $ kg-1, significantly lower than for other benchmark MOFs. These advancements make MIL-120(Al)-AP an excellent candidate as an adsorbent for industrial-scale CO2 capture processes.

From chaotic construction to coevolution: Tbilisi’s 2019 master plan and the right to the city

ABSTRACT A cautious revival for planning is emerging in some post-socialist cities including Tbilisi, Georgia – a response to diminished quality of life after decades of “investor urbanism” policies. Tbilisi’s 2019 Master Plan takes a pragmatic approach to the right to the city – emphasizing human rights to urban mobility and green space but in cooperation with market processes and detached from ideological narrative. The adoption and implementation of Tbilisi’s plan has the potential to yield a coevolution of local governance institutions, now oriented for the first time since independence to administer long-term urban policy. While full implementation of the plan vision will likely be limited by existent processes of state capture, the plan offers a promising new framework for urban governance and the social function of urban space. Although Georgia exhibits troubling signs of democratic backsliding, Tbilisi’s plan asserts alignment with international best practices including European Union accession criteria – thus serving as a potent geopolitical tool.

Rapid detection of capture and emission processes in surface and buffer traps: Understanding dynamic degradation in GaN power devices

This study utilized a rapid detection technique, Isothermal Capture Transient Spectroscopy (ICTS), to identify and evaluate defects related to GaN device surface and buffer traps, and investigated the mechanisms by which they affect the dynamic performance of GaN based devices. Interface states and dielectric bulk traps were analyzed, unveiling distinctive device behavior under positive gate pulse-biased ICTS. The observed S-shaped threshold voltage (VTH) instability and dynamic gate-drain capacitance (CGD) issues were directly associated with these interface states and bulk traps. Negative gate pulse-biased ICTS revealed the presence of logarithmic electron trapping originating from extended electron traps, and spatial wide distributed hole traps within the GaN buffer layer, significantly impacting the dynamic on-resistance (RON) during off-state stress of the devices. The rapid assessment capabilities of this method provide a valuable tool for optimizing GaN epitaxy and manufacturing processes.

ENHANCING CARBON CAPTURE AND STORAGE EFFICIENCY IN THE OIL AND GAS SECTOR: AN INTEGRATED DATA SCIENCE AND GEOLOGICAL APPROACH

This paper proposes a novel framework that integrates data science techniques with geological insights to optimize carbon capture and storage (CCS) processes in the oil and gas industry. By leveraging machine learning algorithms, geospatial data analysis, and predictive modeling, the study aims to identify optimal geological formations for carbon storage, predict carbon sequestration capacities, and minimize environmental impacts. The research will address the challenges of data heterogeneity, scalability, and the complexity of geological variables, aiming to provide a comprehensive solution for sustainable carbon management in the fossil fuel sector.
 Keywords: Carbon, Storage, Efficiency, Capture, Oil & Gas, Predictive, Modeling.

Cathode tailoring of micro-tubular protonic ceramic electrochemical reactors for CO2 hydrogenation

Protonic ceramic electrochemical reactors (PCER), having the advantages of high efficiency, adjustability, and scalability, exhibit great potential in energy storage such as conversion of CO2 into high-value chemicals. Designing critical components like the electrolyte and electrodes of electrochemical reactors is essential to widen commercial applications. The present work constructed a three-layer microtubular PCER (MT-PCER) for CO2 hydrogenation. BaCe0.5Zr0.3Y0.2O3-δ (BCZY) was used as the electrolyte material to prepare BCZY/Ni-BCZY/Ni triple-layer hollow fibers (TLHFs) by a phase-inversion based co-spinning/co-sintering process. Porous Ni-BCZY was the catalytic functional (cathode) layer, and the metallic Ni composed the current collector layer. Results indicated that CO2 conversion and CH4 selectivity were significantly enhanced when the NiO content in the cathode layer increased from 40 % to 60 %, while there was no significant change for the content continuously increasing to 80 %. Compared with the reactor employing dual-layer hollow fibers, the Ni collector layer in TLHFs presented a remarkable intensification of the methanation performance. As a result, the MT-PCER with 60 % NiO content in the cathode layer and utilizing the Ni current collector was the recommended reactor structure, which possessed the CO2 conversion of 29.8 %, CH4 selectivity of 50.9 %, CH4 yield of 15.2 %, and faradaic efficiency of 43.6 % at 700 °C and 2 V applied voltage. The adjusted design of the TLHF facilitated the advancement of the performance and efficacy of the MT-PCER, promoting carbon capture, utilization, and storage processes.

Numerical investigation of carbon dioxide capture using nanofluids via machine learning

Using nanofluids to capture CO2 is a promising method of reducing emissions. The goal of this study was to develop models that could forecast how well water-based nanofluids would absorb CO2. Several machine learning models, such as Decision Tree, Random Forest, eXtreme Gradient Boosting, and K-Nearest Neighbors, underwent training using a total of 1306 experimental datasets. These datasets contained information on the CO2 solubility in aqueous solutions for different types of nanoparticles. In terms of Average Absolute Relative Deviation (AARD%), Mean Absolute Error (MAE), Relative Absolute Error, Mean Squared Error, and Correlation Coefficient, the predictive performance on separate test data was assessed. The XGBoost model demonstrates a higher degree of accuracy in simulating the absorption capacity of aqueous nanofluid compared to other models. This is evident through the AARD value of 2.8%, MSE of 0.00084, MAE of 0.012 and an R value of 0.992. The research provides insight into the utilization of different machine learning algorithms for simulating the absorption of CO2 by nanofluids. By employing accurate data-driven models, the efficiency of nanofluid-based CO2 capture processes can be enhanced through improvements in their design and operating conditions.

Combining neural networks and phenomenological equations to model carbon dioxide adsorption on Zeolitic imidazolate framework (ZIF-8)

This study proposes the combined use of a phenomenological model and neural networks trained by experimental data to predict Carbon dioxide adsorption on Zeolitic imidazolate framework – 8 (ZIF-8) considering different temperature and surface area conditions. The Sips model presented the best fit among the models studied and the perceptron networks presented the best performance to represent the phenomenon. The use of genetic algorithms assisted in the optimization of the neural network architecture, in a shorter computational time. The model indicates that at high pressures the area presents a strong positive correlation for carbon capture, however at lower pressures (of the order of 1 bar) the influence was negative, but with less significance. The study contributes to the development of more efficient carbon capture processes, helping to direct future research in the area of greenhouse gas mitigation, particularly in the field of developing products for carbon capture, among other applications involving carbon dioxide adsorption.