Publications

HybridML: Open source platform for hybrid modeling
A tool for hybrid modeling.
HybridML: Open source platform for hybrid modeling
Multi-objective Bayesian optimisation of a two-step synthesis of p-cymene from crude sulphate turpentine
Multi-objective Bayesian optimisation of a two-step synthesis of p-cymene from crude sulphate turpentine
Pushing nanomaterials up to the kilogram scale – An accelerated approach for synthesizing antimicrobial ZnO with high shear reactors, machine learning and high-throughput analysis
Pushing nanomaterials up to the kilogram scale – An accelerated approach for synthesizing antimicrobial ZnO with high shear reactors, machine learning and high-throughput analysis
Efficient hybrid multiobjective optimization of pressure swing adsorption
Efficient hybrid multiobjective optimization of pressure swing adsorption
Machine learning in chemical engineering: A perspective
Discussion of perspecitves for future interdisciplinary research and transformation of chemical engineering by identifying challenges and formulation problems for machine learning.
Machine learning in chemical engineering: A perspective
Insight to gene expression from promoter libraries with the machine learning workflow Exp2Ipynb
Insight to gene expression from promoter libraries with the machine learning workflow Exp2Ipynb
Chemical data intelligence for sustainable chemistry
Chemical data intelligence for sustainable chemistry
Designing production-optimal alternative fuels for conventional, flexible-fuel, and ultra-high efficiency engines
Designing production-optimal alternative fuels for conventional, flexible-fuel, and ultra-high efficiency engines
Deterministic global optimization with Gaussian processes embedded
Deterministic global optimization with Gaussian processes embedded
Obey validity limits of data-driven models through topological data analysis and one-class classification
Obey validity limits of data-driven models through topological data analysis and one-class classification
Globally optimal working fluid mixture composition for geothermal power cycles
Globally optimal working fluid mixture composition for geothermal power cycles
The potential of hybrid mechanistic/data‐driven approaches for reduced dynamic modeling: application to distillation columns
The potential of hybrid mechanistic/data‐driven approaches for reduced dynamic modeling: application to distillation columns
Deterministic global superstructure-based optimization of an organic Rankine cycle
Deterministic global superstructure-based optimization of an organic Rankine cycle
Hybrid mechanistic data-driven modeling for the deterministic global optimization of a transcritical organic Rankine cycle
Hybrid mechanistic data-driven modeling for the deterministic global optimization of a transcritical organic Rankine cycle
Modelling circular structures in reaction networks: Petri nets and reaction network flux analysis
Modelling circular structures in reaction networks: Petri nets and reaction network flux analysis
Graph neural networks for prediction of fuel ignition quality
Graph neural networks for prediction of fuel ignition quality
Multi-scale membrane process optimization with high-fidelity ion transport models through machine learning
Multi-scale membrane process optimization with high-fidelity ion transport models through machine learning
Nonlinear scheduling with time‐variable electricity prices using sensitivity‐based truncations of wavelet transforms
Nonlinear scheduling with time‐variable electricity prices using sensitivity‐based truncations of wavelet transforms
Deterministic global nonlinear model predictive control with neural networks embedded
Deterministic global nonlinear model predictive control with neural networks embedded
Working fluid selection for organic rankine cycles via deterministic global optimization of design and operation
Working fluid selection for organic rankine cycles via deterministic global optimization of design and operation
Simultaneous rational design of ion separation membranes and processes
Simultaneous rational design of ion separation membranes and processes
Automated self-optimisation of multi-step reaction and separation processes using machine learning
Automated self-optimisation of multi-step reaction and separation processes using machine learning
Wavelet-based grid-adaptation for nonlinear scheduling subject to time-variable electricity prices
Wavelet-based grid-adaptation for nonlinear scheduling subject to time-variable electricity prices
Impact of accurate working fluid properties on the globally optimal design of an organic Rankine cycle
Impact of accurate working fluid properties on the globally optimal design of an organic Rankine cycle
Deterministic global process optimization: Flash calculations via artificial neural networks
Deterministic global process optimization: Flash calculations via artificial neural networks
Machine learning and molecular descriptors enable rational solvent selection in asymmetric catalysis
Machine learning and molecular descriptors enable rational solvent selection in asymmetric catalysis
Deterministic global optimization with artificial neural networks embedded
Deterministic global optimization with artificial neural networks embedded
Deterministic global process optimization: Accurate (single-species) properties via artificial neural networks
Deterministic global process optimization: Accurate (single-species) properties via artificial neural networks
Model-based bidding strategies on the primary balancing market for energy-intense processes
Model-based bidding strategies on the primary balancing market for energy-intense processes
Rational design of ion separation membranes
Rational design of ion separation membranes
Machine learning meets continuous flow chemistry: Automated optimization towards the Pareto front of multiple objectives
Machine learning meets continuous flow chemistry: Automated optimization towards the Pareto front of multiple objectives
Dynamic modeling and optimization of sustainable algal production with uncertainty using multivariate Gaussian processes
Dynamic modeling and optimization of sustainable algal production with uncertainty using multivariate Gaussian processes
Correction to: Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm
Correction to: Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm
Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm
Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm
The concept of selectivity control by simultaneous distribution of the oxygen feed and wall temperature in a microstructured reactor
The concept of selectivity control by simultaneous distribution of the oxygen feed and wall temperature in a microstructured reactor
A multiobjective optimization including results of life cycle assessment in developing biorenewables-based processes
A multiobjective optimization including results of life cycle assessment in developing biorenewables-based processes
Techno-economic optimization of a green-field post-combustion CO2 capture process using superstructure and rate-based models
Techno-economic optimization of a green-field post-combustion CO2 capture process using superstructure and rate-based models