Climate and environmental problems caused by increasing CO2 concentration in the atmosphere make the direct air capture (DAC) technology having great prospects for development. As the widely used solvent in carbon capture based on chemical absorption processes, MEA still fails to address the issues of high energy consumption and high costs when used in DAC process. In this study, piperazine (PZ) was used as the new solvent for DAC process. The new configuration was simulated in Aspen Plus® V11 and the model was validated through experimental data and model comparison. It is followed by investigation of the potential for energy efficiency and cost reduction. The standard DAC-PZ configuration could reduce the reboiler duty from 10.7 GJ/tCO2 to 8.9 GJ/tCO2 for DAC-MEA process. Economic analysis will be carried out through Aspen Process Economic Analyzer®. Further analysis (e.g. sensitivity analysis for different parameters and optimisation) will be performed to further reduce the energy c... [more]

Engineering can be made simple and more impactful by observing and understanding how organisms in nature solve eminent problems. For example, scientists around the world have observed green plants thriving without organic food inputs using the complex photosynthesis process to kick-start a self-sustaining biochemical food chain. In this study, two biological analogues for advanced water treatment, i.e., visible-light photocatalysis using porphyrin-Bi12O17Cl2 and BiOIO3 compounds and interfacial solar desalination by a by Reduced Graphene Oxide-Black TiO2 (rGO-Black TiO2) were investigated. For the visible-light photocatalytic process for dye decolouration, a porphyrin@Bi12O17Cl2 system was applied to successfully degrade Rhodamine B dye in batch experiments, achieving up to 79% degradation within 240 minutes. These results show that more advances and more efficient engineered systems can be achieved by observing nature and how these systems have survived over billions of years. The rGO... [more]

Biomass conversion to chemical derivatives and essential intermediates is regarded as a long-term strategy for the chemical sector. Among the numerous valuable chemicals obtained from biomass, 5-hydroxymethylfurfural (HMF) is considered an industrially relevant compound due to its capacity to be converted into a variety of value-added chemicals. Compared to conventional catalytic synthesis, bio-catalysis has emerged as a potential greener substitute for HMF conversion to value-added compounds. HMF conversion through bio-catalysis, although more sustainable, seldom leads to the production of a single derivative. Thus, the development of efficient purification and separation processes of several products are crucial to scalability. The downstream process for the novel enzymatic conversion of HMF to high value-added chemicals (i.e., 1-phenylethylamine, 2,5-bis(hydroxymethyl)furan, 1-phenylethylalcohol, and 5-(aminomethyl)-2-furanmethanol) was designed by means of rigorous simulations in A... [more]

Plastic recycling is prevalently mechanical, which is inefficient at removing contaminants and produces low-grade materials. Solvent-based polymer dissolution and precipitation is emerging as a low-energy alternative to mechanical recycling when tackling highly contaminated plastic waste streams. We present a computer-aided molecular and process design (CAMPD) formulation for the selection of optimal solvents and process temperatures for polymer recycling via a dissolution and precipitation process. A mixed-integer nonlinear programming (MINLP) model is proposed to minimize the energy requirement for the dissolution of commercial low-density polyethylene, a ubiquitous polymer in industrial and municipal plastic waste, while minimizing the solvent viscosity and toxicity through multiobjective optimization. We integrate the SAFT-??Mie group-contribution equation of state in the optimization framework to predict key thermodynamic properties and to ensure that the desired phase behaviour i... [more]

Acrylonitrile is a critical commodity chemical used to produce a variety of industrial polymers, such as carbon fibers, plastics, etc. Currently 90% of the global acrylonitrile production is based on propylene ammoxidation. However, there is no literature reporting the whole process holistically in detail, and which also looks into the energy utilization of the whole process including the reaction heat as well as the energy demands of the downstream separation. This original study provides a rigorous process design of the full process from a holistic viewpoint, covering 7 sections of acrylonitrile production (reaction, acid quenching, absorption-desorption, hydrogen cyanide recovery, acrolein recovery, acrylonitrile-acetonitrile-water separation, acetonitrile recovery sections). In order to further improve the energy efficiency, three energy integration strategies are proposed (1) Energy integrated downstream processing; (2) Systematic heat integration utilizing the heat of reaction; (... [more]

Steel mill off gas fermentation presents a promising green alternative to petrochemical isopropyl alcohol (isopropanol, IPA) and acetone production while potentially reducing greenhouse gas emissions. A pilot-scale study stated negative global warming potential (GWP) at 85% gas conversion and 90% product selectivity. However, industrial-scale plant design including detailed techno-economic assessment (TEA) and life cycle assessment (LCA) remain undescribed. Therefore, this study modelled a heat-integrated 47.5 kton/ year gas fermentation process to IPA and acetone, based on pilot-scale data. The downstream processing was designed using vacuum distillation and heat-pump integrated (extractive) distillation to purify the 50 gproduct/ L broth with biomass and acetate as byproducts, to obtain 41.8 kton/ year of 99.6 wt. % IPA and 5.64 kton/ year of 99.0 wt. % acetone. Notably, no steam is consumed and 2.6 MWh of electricity is generated by utilising the energy from the steel mill off gas.... [more]

Oxidation of arabinose to arabinoic acid is an innovative way to valorize local biomass to a high add value product. Previously done experiments on oxidation of arabinose to arabinoic acid with molecular oxygen were used to determine the optimum reaction conditions, scale-up the process and analyse the techno-economic aspects. These results were utilized to analyse the environmental impact of the scaled-up process during its lifetime using the life cycle assessment (LCA) methodology. SimaPro software combined with the impact assessment method IMPACT 2002+ were applied. The results revealed that heating seems to be the largest contributor to the environmental impact even if the reaction is performed under rather mild conditions (70oC). This highlights the importance of reducing the energy consumption via efficient heat integration.

An intensified approach to ?-valerolactone (GVL) production is achieved using a reactive distillation column. Conventional methods require multiple units, leading to high energy consumption, costs, and limited scalability. The proposed technology integrates reaction and separation into a single unit, enhancing process efficiency for biomass-derived chemicals. A multiobjective optimization framework balances economic, environmental, and operational goals, reducing total annual cost (TAC) by 43% and environmental impact (EI99) by 45% compared to conventional processes. Additionally, energy consumption drops by 63%, while GVL production increases by 25%, highlighting the potential of reactive distillation for improved efficiency and sustainability.

Bipolar membrane electrodialysis are receiving the attention of the research community in the last years because they can help the electrification and the spread of direct air capture systems. In this work, a mathematical model of a bipolar membrane electrodialysis cell for carbon dioxide recovery is carried out in order to find the most significant parameters on efficiency through a global sensitivity analysis. The electrochemical cell can be integrated into an absorption column capturing carbon dioxide from the air. Results show that the most important parameter over all investigated figures of merit (specific energy consumption, costs, carbon dioxide desorption efficiency, potassium transport number, removal ratio of potassium cation and carbon) is the potassium cation concentration in the rich solution feeding the cell. A trade-off between energy efficiency, process speed and operational cost is suggested. Future research should be conducted in order to apply the global sensitivity... [more]

In this research, a novel process is developed that utilizes low density polyethylene from plastic waste to produce ethylene. In this process, waste polyethylene is reacted in a microwave reactor to produce ethylene. A conceptual flowsheet based on this reactor is developed in the ASPEN Plus environment. Heat integration tools are utilized to reduce the hot and cold utilities used in this process. This novel design is compared with the conventional process of making ethylene from ethane via cracking. A technoeconomic analysis is conducted to demonstrate the economic feasibility of this process.

In this research, a chemical looping scheme is combined with dry reforming of natural gas in a novel microwave reactor to produce industrial quantity of methanol. Simulation results show that the chemical looping scheme can produce all the hydrogen required by the methanol reactor as well as a significant portion of the carbon dioxide required for the syngas reactor. A heat exchanger network is developed to substantially reduce the hot and cold utility usage. A technoeconomic analysis indicates a significant positive net present value along with a substantial reduction in carbon dioxide emissions as well as a reduction in energy consumption.

This study focuses on enhancing heat and shaft power integration within existing nitric acid production processes to optimize waste heat recovery and identify opportunities to improve process efficiency. A digital twin of the operational plant is utilized, which features a dual-stage pressure nitric acid production process with a capacity of 50 tons/h of HNO3 (100% equivalent). The authors conducted a simultaneous analysis of the thermal energy potential and the expansion capacity of tail gases to effectively fulfil the primary process's heating, cooling, and power requirements while increasing steam generation through waste heat recovery, all without compromising plant throughput. The proposed process modifications lead to a 23.8% reduction in cooling water usage and a 35.6% decrease in CO2 equivalent emissions while achieving a 13.1% increase in steam generation. These utility savings culminate in a 10.2% enhancement in plant throughput.

Process Systems Engineering (PSE) provides the advanced conceptual framework and software tools to formulate and optimise well-considered integrated solutions that could accelerate the sustainability transition within the industrial sector. The landscape of advanced PSE is poised to undertake a considerable transformation with the rise in popularity of open-source and script-based software platforms with predictive modelling capabilities based on modern mathematical optimization techniques. This paper highlights three leading equation-based platforms—IDAES, Modelica, and GEKKO-that are increasingly utilised for the modelling, simulation, and optimisation of complex systems within the advanced PSE domain, alongside the strengths and limitations of each approach. Following this, we present a framework through which emerging techniques within the domain of Software Engineering could be leveraged to address these limitations, with a vision of improving the accessibility and flexibility of... [more]

The deployment of CO2 capture technologies at a large scale will largely benefit from the knowledge acquired during pilot testing. A mobile CO2 capture pilot unit is currently being designed at the University of Liège. Here, the pilot plant is introduced, and the column sizing results are presented. The sizing was performed with a process model built in Aspen Plus. Overall, the pilot installation is expected to serve for process model validation, data collection and technology de-risking while assisting Belgian industries in their transition towards carbon neutrality.

As demand for long and accurate molecular simulations increases so too does the computation demand. Beyond using new, enterprise scale processor developments - such as the ARM neoverse chips – or performing simulations leveraging Graphics Processing Unit compute, there exists a potentially faster and more power efficient option in the form of custom hardware. Using hardware description languages it is possible to transform existing algorithms into custom, high performance hardware layouts. This can lead to faster and more efficient simulations but compromises on the required development time and flexibility. In order to take the greatest advantage of the potential performance gains, the focus should be on transforming the most computationally expensive parts of the algorithms. When performing molecular dynamics simulations in a polar solvent like water, non-bonded electrostatic calculations dominate each simulation step, as the interactions between the solvent and the molecular structu... [more]

Integrated Carbon Capture and Conversion (ICCC) technologies offer an efficient alternative to conventional Carbon Capture, Utilization, and Storage (CCUS) methods by simultaneously capturing and converting CO2 into value-added chemicals. Dual-function materials (DFMs) are particularly promising due to their capability to integrate adsorption and catalysis in a single step, thereby reducing both energy consumption and associated costs. This study models the dynamic behavior of CO2 adsorption within a laboratory-scale packed-bed reactor employing DFMs. The mathematical model incorporates momentum, mass, and heat transfer equations, implemented using COMSOL Multiphysics v5.6, and evaluates various axial dispersion models (ADMs) and mass transfer coefficients (MTCs). The results indicate that the Rastegar-Gu ADM, combined with an MTC of 8.3 × 10-2 s-1, provides the most accurate representation of breakthrough and saturation times, as well as the total quantity adsorbed. Furthermore, relat... [more]

Predicting the critical micelle concentration (CMC) of surfactants is essential for optimizing their applications in various industries, including pharmaceuticals, detergents, and emulsions. In this study, we investigate the performance of graph-based machine learning models, specifically Graph Convolutional Networks (GCN), Graph Attention Networks (GAT), and a graph-transformer model, PharmHGT, for predicting CMC values. We aim to determine the most effective model for capturing the structural and physicochemical properties of surfactants. Our results provide insights into the relative strengths of each approach, highlighting the potential advantages of transformer-based architectures like PharmHGT in handling molecular graph representations compared to traditional graph neural networks. This comparative study serves as a step towards enhancing the accuracy of CMC predictions, contributing to the efficient design of surfactants for targeted applications.

In the present paper, we come up with application of machine learning using data for flow visualization as a method for predicting unsteady flow patterns in oscillatory baffled reactors (OBRs). Application of the proper orthogonal decomposition (POD) is investigated for dynamic analysis of spatio-temporal data acquired by particle image velocimetry (PIV) to determine inputs and outputs for neural network model. It has demonstrated that three sets of modes and time-varying mode coefficients extracted by the POD could be useful for dynamic analysis and prediction of time-variant flow patterns in OBR. Also it is shown that decomposition of the time-series data for the mode coefficients by Fourier series expansion was effective for deriving reduced order model.

Accurately predicting biogas production for real-time applications remains a challenge in anaerobic digestion (AD) due to the process's complexity and dynamic nature. While mechanistic models are essential for understanding and modelling AD processes, however they are highly non-linear and depend on detailed feedstock characterisation and parameter calibration. In contrast, data-driven models do not rely on predefined equations and rather use process data to capture the system's underlying dynamics. This study compares mechanistic and data-driven models for biogas prediction using lab-scale data. A state estimation framework with a rolling window was used for the mechanistic model, based on biomass and substrate concentrations with Haldane kinetics, achieved an accuracy of (R² = 0.91). A Long Short-Term Memory (LSTM) model with Bayesian Optimisation for hyperparameter optimisation, trained on the same data showed superior performance (R² = 0.93–0.98) and captured temporal dependencies... [more]

This paper evaluates the thermodynamic efficiency of a newly synthesized large-scale pre-combustion CO2 capture process using a novel ionic liquid (IL) 1-octyl-2,3-methylimidazolium thiocyanate [OMMIM][SCN] for blue H2 production. In addition, the potential eco-toxicity of the selected IL was assessed using the ADMETlab 2.0 web tool. The results of these analyses were compared to those of an established IL 1-butyl-2,3-dimethylimidazolium bis(trifluoromethyl sulfonyl)imide [BMMIM][TF2N]. The eco-toxicity assessment confirmed that [OMMIM][SCN] is less environmentally toxic than [BMMIM][TF2N]. Thermodynamic analysis of the novel system shows the COOLER unit accounts for the highest energy demand; however, the [OMMIM][SCN] system demonstrates a 7.45% reduction in energy consumption in the COOLER unit compared to [BMMIM][TF2N]. The system experienced the highest exergy losses (irreversibilities) in the COOLER unit for [BMMIM][TF2N] (12982 kW) and in the flash separator unit for [OMMIM][SCN]... [more]

This work presents a comprehensive multiscale model for Solid Oxide Fuel Cells (SOFCs), integrating microscale and macroscale simulations to analyze internal reforming and its impact on overall cell performance. The microscale model [1], [2] captures the intricate mass and charge transport phenomena at the pore scale of porous electrodes, resolving electrochemical reactions at the triple-phase boundaries and modeling chemical reactions at pore spaces. Simultaneously, the macroscale model provides a broader view of the entire cell's behavior by solving the same transport equations on a coarser computational mesh. The multiscale approach is particularly useful for addressing the challenges posed by simultaneous chemical and electrochemical reactions at the anode, which complicate the modeling of internal reforming. To overcome these challenges, a novel approach is introduced [3], spatially separating the regions of chemical and electrochemical activity in the pore scale domain by taking... [more]

The co-gasification of biomass and plastic waste offers a promising pathway for sustainable syngas production, necessitating precise prediction of its composition to optimize efficiency. This study compares the performance of Aspen Plus models, including the thermodynamic equilibrium model (TEM) and restricted thermodynamic equilibrium model (RTM), with machine learning (ML) techniques, focusing on the support vector regression (SVR) for syngas prediction during steam and air co-gasification. Aspen Plus simulations provided valuable mechanistic insights, while the ML model demonstrated superior predictive accuracy. The SVR, enhanced by principal component analysis (PCA), significantly improved performance, achieved R² values of 0.879 for H2, 0.856 for CO, 0.859 for CO2, and 0.744 for CH4 on the testing dataset. It also outperformed other models in terms of RMSE, achieving exceptional precision for CH4 (0.0087), CO (0.0193), and H2 (0.0194). In contrast, RTM exhibited moderate accuracy... [more]

Process simulation is essential for optimizing chemical processes, offering a cost-effective alternative to the experimental approach. This study presents a co-current hollow fibre membrane model for CO2 separation, integrated into Aspen HYSYS® using the CAPE-OPEN standard. A one-dimensional boundary value problem (BVP) is solved through the shooting method, ensuring accuracy for complex gas separation processes. The unit is implemented in C++, facilitating interoperability, error handling, and optimization of key performance indicators like energy consumption and separation efficiency. Appropriate output variables are employed in the Aspen HYSYS® environment to enable direct sensitivity analysis and optimization within the process simulator. Results Sensitivity analysis results demonstrate that the co-current hollow fiber membrane unit improves methane recovery compared to a pressure swing water absorption (PSWA) column for biogas upgrading to biomethane. While membrane technology sho... [more]

Cell culture processes play a central role in the production of various therapeutic compounds. These processes are multiscale and highly complex, making them challenging to describe comprehensively using fully mechanistic models. In this study, we employ an integrated hybrid machine learning and first principles model to predict the viable cell density, product titer, and metabolite concentration profiles. We employ the concept of degree of hybridization, where we create a family of hybrid models each with increasing degree of process knowledge. Predictions from the feasible hybrid architecture were integrated with a genome scale metabolic model to evaluate the flux distribution of reactions related to the central carbon metabolism of the cell throughout the process duration. We demonstrate that the current approach not only reasonably predicts the bioprocess profile but also provides biologically relevant information that can uncover dynamics of intracellular metabolism which can open... [more]

Proton Exchange Membrane (PEM) fuel cells are gaining traction in automotive applications due to their efficiency and environmental benefits, but they face challenges such as high costs, degradation rates, and limited hydrogen availability. To address these issues, novel operational methods have been developed, focusing on customized designs rather than traditional uniform configurations. These advancements include the variable temperature flow field, which maintains high relative humidity without external humidification by leveraging internally generated water and heat, and graded catalyst loading, which enhances current density distribution. Additionally, complex flow fields have been designed using 3D metal printing to mitigate liquid water accumulation. These innovations have shown significant performance improvements, particularly when combined, demonstrating a 260% increase in current density at 0.6 V. These advancements hold promise for overcoming the limitations of conventional... [more]