Accurately predicting CO2 equilibrium solubility is essential for optimizing amine-based sorbents in carbon capture processes. However, traditional experimental approaches require extensive testing, making data collection time-consuming and often incomplete. In this study, we address this challenge by developing six machine learning models to predict CO2 solubility in three dual-amine blends (MEA + MDEA

In the context of micromixers, it is imperative to ensure a high mixing performance while maintaining a low-pressure drop. In this study, an innovative baffle based on trigonometric functions was proposed and combined with a convergent-divergent channel to improve the mixing performance of the micromixer. A comprehensive approach combining experimental visualization and numerical simulation was adopted

The one-step conversion of crude oil into light olefins through catalytic pyrolysis is a revolutionary technology in the petrochemical industry. However, crude oil contains a huge variety of molecules with different reaction reactivities, posing challenges for the design and optimization of pyrolysis catalysts, reactors, and processes. The molecular-level kinetic model is an essential tool for accelerating

The coarse-grained computational fluid dynamics–discrete element method (CG CFD-DEM) and particle replacement model (PRM) were combined to investigate the motion and breakage behaviors of biomass particles in a binary fluidized bed. Two key parameters, i.e., the cross-sectional aspect ratio of the fluidized bed (RA) and sand parcel number (Np), were examined. Simulation results reveal that, as RA increases

In this work, a dynamic optimization model is developed for the evacuation of a networked system of multiple process vessels and interconnecting piping. This is motivated by the requirements of large-scale, adsorption-based DAC (direct air capture) CO2 -capture processes. Pressure and gas hold-up in the vessels and piping are modelled using the isothermal partial-differential Euler equations which

The construction industry generates 38% of Europe’s total waste, highlighting the need for improved sustainability. This study proposes a mathematical model, implemented in COMSOL Multiphysics 6.2,which incorporates the three primary phenomena occurring during the carbonation of hydrated lime: chemical reaction, diffusion, and water evaporation. Water plays a crucial role in this process, and this

A CO2/CH4 separation process using protic and aprotic ionic liquids (ILs) was developed and compared to DEPG, a widely used benchmark solvent in gas separation processes. The study focused on six ILs: three protic ILs (1-butylimidazolium bis(trifluoromethanesulfonyl)amide, 1-butylimidazolium tetrafluoroborate, and N-butyldimethylammonium bis(trifluoromethanesulfonyl)amide) and three aprotic ILs (1

The emissions of CO2 and other greenhouse gases from fossil fuel combustion have been increasing yearly, exacerbating environmental issues such as global warming. In order to reduce CO2 emissions during coal-fired power generation, this study establishes a CO2 capture model of post-combustion process using [emim][NTf2] as an absorbent. Single-parameter optimization achieves CO2 capture rate of 93.43 %

Residence time distribution (RTD) is of significance for reflecting materials or intermediate products dispersion and actual reaction time inside continuous hydrothermal reactors of supercritical water gasification technology. Generally, RTD is strictly related to flow field, which can be affected by wall heating schemes. In order to propose methods to regulating RTD, effects of different heating schemes

In this paper, a Euler-Euler CFD model based on the two-fluid model is developed for the industrial-scale biological methanation process. The model resolves the hydrodynamics of the bubbly flow, along with the effects of the multispecies mass transfer (H2, CO2 and CH4) and bioreaction kinetics. Three-dimensional simulations were performed with the commercial CFD code ANSYS Fluent® version 2021 R1 and

This study investigates the use of Symbolic Regression, a machine learning technique, to develop a model for mixing time in large petroleum storage tanks stirred by side-entry impellers. Studies involving the mixing time for side-entry mixers are relatively scarce when compared to research on mixing time models for top-mounted impellers. This limited availability of predictive models for side-entry

Multi-step prediction models can forecast variables ahead of time, which is valuable for process variable monitoring. Although deep learning (DL) is promising in multi-step prediction, its compatibility, interpretability and practicality, which are crucial for chemical applications, have received little attention. Thus, a DL architecture—Light Attention-Mixed Base Target Autoregression Unit (LAMB-TAU)

This study investigates the size-induced axial segregation of binary mixtures in rotating drums, particularly focusing on the effect of drum length. The results indicate that long drums require more time to achieve stable segregation and form more segregation bands. The core region under the free bed surface remains predominantly filled with small particles, indicating that radial segregation occurs

Precise control of ion transport of fluids in nanochannels is a key challenge. In this study, two control methods, field effect transistor (FET) and solution pH, were used to regulate the ion transport of power-law fluids in a nanochannel. The velocity field, potential distribution, and ion distribution were calculated by numerical simulation, and the effects of power-law index (n) and bulk pH (pHb)

The flow of fluids between minerals involves complex physicochemical coupling effects, and using real rock cores as reactors for characterization presents significant challenges. This is due to the lack of fluid visualization capabilities in rock cores, as well as their highly heterogeneous structure. This study introduces a biomimetic microfluidic chip fabrication method that enables the direct observation

The considerable influence of inflow variations within hydrocyclones on separation efficiency and the time required to achieve steady-state flow made the examination of the transient behavior of two-phase flow crucial. This study investigated the overall progression of two-phase flow, starting from the injection of oil droplets until reaching a steady state in a de-oiling hydrocyclone simulated using

In this study, the prediction of CO2 solubility in blended amine is investigated using machine learning (ML) techniques. A novel feature engineering method of blended amine structure encoding (BSE) was developed and combined with four models: eXtreme Gradient Boosting (XGBoost), Random Forest (RF), Convolutional Neural Network (CNN), and Deep Neural Network (DNN). The newly developed BSE method demonstrated

Calculation of the rate of evaporation of volatile chemicals exposed to air is needed in many situations to determine environmental impact and need for mitigating actions such as providing ventilation. Such situations include emission sources in industrial manufacturing operations such as open surface tanks, container filling, indoor spills, spills occurring in transportation and from bulk storage

Particle-wall collisions play a critical role in various natural and industrial processes. When submicron particle layers are present on surfaces, predicting particle adhesion and kinetic energy dissipation becomes increasingly complex. This study investigates how layer material composition and thickness influence impact energy dissipation of incident microparticles. Using a layer-by-layer self-assembly

In traditional extraction columns, it is prior to guarantee the droplet dispersion so that it is hard to develop the ideal flow pattern with alternate droplet coalescence and breakage regions. In this study, the novel internals with composite wettability, namely hydrophilia and hydrophobicity, were proposed for the process intensification of pulsed columns. In addition to the successful construction

The impact of combining micro-baffles, vortex generators, and elastic walls on the thermal performance of microchannels commonly utilized in many sectors has not been investigated in the literature. Using the Arbitrary Lagrangian-Eulerian method, this study extensively examines the effects of integrating elastic walls, vortex generators, and the distribution of micro-baffles insidemicrochannels on

Natural gas liquids (NGL) are among the products of gas processing systems which have several applications and their production has been increasing in recent years. Previous publications did not provide an integrated framework capable of effectively assessing the various environmental and economic impacts linked to the NGL recovery process, and indentifying their most important contributors. This research

Alkaline water electrolysis (AWE) plays a leading role in green hydrogen production due to its scalability and cost-effectiveness, but suffers from low current density and gas-crossover issues. This study demonstrates substantial progress in AWE performances through synergistic membrane-electrode optimization. Zirconia-polysulfone (Z-PSU) and zirconia-polyethersulfone (Z-PESf) membranes were prepared

Direct air capture (DAC) technology of CO2 is one of the most important ways to achieve the “dual carbon” goal, which can promote the green transformation of society, and alleviate global warming. In view of the current situation of few types of CO2 air capture materials and poor stability, the phase conversion method was adopted to prepare macroporous ionic polymer membrane materials. Through the

The use of layer of protection analysis (LOPA) – a semi-quantitative risk assessment method – for the accurate quantification and assessment of the performance of safety barriers in complex chemical processes with multi-temporal and spatial scales, multi-risk elements, and multi-hazardous episodes, is challenging. Its use has resulted in chemical risk scenarios that lead to severe accidents due to

A reaction kinetics model for pitch polymerization is established by integrating the changes in components with the growth of mesophase under multi-component and non-homogeneous conditions. The fitting results present that at polymerization temperatures of 430, 450 and 465 °C, the rate constants of the first-step component consecutive reactions are 0.04, 0.07 and 0.11 h−1, the rate constants of the

This study investigates bubble dynamics in the freeboard region of a fluidized bed flotation column, focusing on the effects of liquid (Uw) and gas (Ug) superficial velocities on gas holdup, bubble size distribution (BSD), and surface area flux (Sb). Three distinct flow regimes (fixed bed (Regime I), agitated bed (Regime II), and complete fluidization bed (Regime III)) and two transition water velocities

This study investigated the non-catalytic hydrolysis of polyamide-6 (PA6) in subcritical water (Sub-CW) and developed reaction kinetic model based on random chain scission. Molecular dynamics simulations and product characterization reveal that PA6 hydrolysis in Sub-CW occurs not only at the interface but also within the molten PA6. The temporal evolution of the degree of polymerization (DP) distribution

This study extends the investigation of artificial neural network (ANN) models for single droplet evaporation by incorporating Stefan flow and convective effects for more realistic scenarios. The objectives are to assess how these complexities affect ANN accuracy and to see if previous modeling approaches remain effective. Four architectures were compared: conventional no-physics, non-dimensional,

A falling film evaporation model is developed, incorporating the growth of crystal scaling and phase change heat transfer. The influence of spray density, liquid film temperature, salinity, and tube diameter on the dynamic growth of calcium carbonate crystals is studied by solving the physical equations of momentum, energy, and concentration diffusion with the finite element method. The dynamical growth