Posts by Collection
projects
publications
Optimization of an artificial neural network structure for modelling carbon capture in spray columns
Computer Aided Chemical Engineering, 2022In this paper we apply bayesian optimization to identify the most efficient neural network structure to predict mass-transfer coefficients CO2 capture spray columns
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A comparative study of swarm intelligence and artificial neural networks applications in modeling complex reaction processes
Computer Aided Chemical Engineering, 2022In this paper we compare the performance of artificial neural networks and polynomial models optimized with warm intelligence in predicting process behaviours under different data scenario
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A new look to the old solvent: Mass transfer performance and mechanism of CO2 absorption into pure monoethanolamine in a spray column
Chemical Engineering and Processing - Process Intensification, 2023In this paper we investigate the effect of MEA concentration on the overall mass transfer coefficient in spray column on CO2 capture
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Predicting overall mass transfer coefficients of CO2 capture into monoethanolamine in spray columns with hybrid machine learning
Journal of CO2 Utilization, 2023In this paper we apply hybrid modeling to predict mass-transfer coefficients in spray columns for CO2 capture
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Reinforcement learning-based approach for optimizing solvent-switch processes
Computers & Chemical Engineering, 2023In this paper we apply reinforcement learning techniques to improve the efficiency of solvent switch process.
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Hybrid modelling of a batch separation process
Computers & Chemical Engineering, 2023In this paper we investigate the application of hybrid modelling technique to predict the solvent switch process behaviour.
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CO2 water-lean capture: Mathematical modelling and analysis of the industrial process
Computer Aided Chemical Engineering, 2023In this paper we investigate the effect of MEA concentration on the overall CO2 capture process efficiency
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Real-time optimization of a chemical plant with continuous flow reactors via reinforcement learning
Computer Aided Chemical Engineering, 2023In this paper we investigate the application of reinforcement learning techniques to improve the efficiency of continous reaction processes
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SI-M/O: Swarm Intelligence-based Modeling and Optimization of complex synthesis reaction processes
Computers & Chemical Engineering, 2023In this paper we investigate the application of hybrid modelling to predict poorly specified reaction system. After the modelling effot, we propose a method to optimize the reaction system.
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HybridGamma: A thermodynamically consistent framework for hybrid modelling of activity coefficients
Chemical Engineering Journal, 2023In this paper we investigate the application of hybrid modelling to predict activity coefficients
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An artificial intelligence course for chemical engineers
Education for Chemical Engineers, 2023In this paper we propose the structure teaching machine learning application for Chemical Engineering Master’s students
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Simulation and quantitative analysis of Raman spectra in chemical processes with autoencoders
Chemometrics and Intelligent Laboratory Systems, 2024In this paper we present an autoencoder-based methodology that simulates Raman spectra from process variables and predicts the concentrations of different chemicals.
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Correlating the partitioning of organic molecules between water and [MeoeMPyrr]+ [FAP]- through machine learning
Computer Aided Chemical Engineering, 2024This study proposes a hybrid model correlating the partitioning of organic molecules in octanol/water with the partitioning in ionic-liquid/water systems.
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Physics-informed machine learning predicting CO₂ capture performances of organic mixtures
Chemical Engineering and Processing - Process Intensification, 2025In this paper we develop an hybrid model for CO₂ solubility prediction differentiating physical and chemical absorption
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Hybrid Models Identification and Training through Evolutionary Algorithms
Systems & Control Transactions, 2025In this paper we apply evolutionary algorithm for the automatic generation of hybrid models for chemical processes starting from mechanistic model description
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Structural Optimization of Translucent Monolith Reactors through Multi-objective Bayesian Optimization
Systems & Control Transactions, 2025In this paper we apply bayesian optimisation algorithm to analyse the effect of shapes and dimensions of monolith channels in photochemical reactor and including multiobjective optimisation to improve its design
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Predicting Surface Tension of Organic Molecules using COSMO-RS Theory and Machine Learning
Systems & Control Transactions, 2025In this paper we apply machine learning technique to improve the accuracy of COSMO-RS model in predicting surface tension of liquids employing molecular descriptors
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AI-aided process intensification of structures
Chemical Engineering and Processing - Process Intensification, 2025In this paper we review the capabilities of AI in generating novel reactor designs employing CFD simulations
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Hybrid modelling approaches in process intensification: A thorough review
Chemical Engineering and Processing - Process Intensification, 2025In this paper we review the capabilities of hybrid modelling in process intensification domain
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SINDybrid: automatic generation of hybrid models for dynamic systems
Chemical Engineering Science, 2025In this paper we propose a MILP formulation for the automatic identification and training of hybrid models starting from mechanistic information and data
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talks
Application of Swarm Intelligence to Parameter Estimation in Multi-Reaction Processes Modeling
Published:
AI aided multiparameter identification for a chemical engineering problem – the solvent switch case
Published:
Optimization of an artificial neural network structure for modeling carbon capture in spray columns
Published:
hybridGamma: a thermodynamically consistent framework for hybrid modelling of activity coefficients
Published:
SI-M/O: Swarm Intelligence-based Modelling and Optimisation of complex reaction processes
Published:
Real-time optimization of a chemical plant with continuous flow reactors via reinforcement learning
Published:
Automated Approach for Reactor Design
Published:
Predicting Surface Tension of Organic Molecules Using COSMO-RS Theory and Machine Learning
Published:
Physics-informed machine learning predicting CO₂ capture performances of organic mixtures
Published:
teaching
ICT tools for Chemical Engineers
Bachelor's course, KU Leuven, Faculty of Engineering Technology, 2020
New strategy for process control
Master's course, KU Leuven, Faculty of Engineering Technology, 2023
Hybrid modeling of cyclopentenol Production on a CSTR
Workshop, 5th Hybrid Modeling Summer School, 2023
Process Simulation in the Chemical Industry
Master's course, KU Leuven, Faculty of Engineering Science, 2025