A

Alexei

14 records found

Authored

Designing a simple, yet representative reaction network for subsequent micro-kinetic analysis is important for limiting the cost of evaluation and ensuring model solvability. This is currently achieved by employing sensitivity analysis over a comprehensive reaction network (CR ...

ERnet

A tool for the semantic segmentation and quantitative analysis of endoplasmic reticulum topology

The ability to quantify structural changes of the endoplasmic reticulum (ER) is crucial for understanding the structure and function of this organelle. However, the rapid movement and complex topology of ER networks make this challenging. Here, we construct a state-of-the-art ...

Production of functional molecules from renewable bio-feedstocks and bio-waste has the potential to significantly reduce the greenhouse gas emissions. However, the development of such processes commonly requires invention and scale-up of highly selective and robust chemistry f ...

Novel materials are the backbone of major technological advances. However, the development and wide-scale introduction of new materials, such as nanomaterials, is limited by three main factors—the expense of experiments, inefficiency of synthesis methods and complexity of scal ...

This study highlights new opportunities for optimal reaction route selection from large chemical databases brought about by the rapid digitalisation of chemical data. The chemical industry requires a transformation towards more sustainable practices, eliminating its dependenci ...

Pressure swing adsorption (PSA) is an energy-efficient technology for gas separation, while the multiobjective optimization of PSA is a challenging task. To tackle this, we propose a hybrid optimization framework (TSEMO + DyOS), which integrates two steps. In the first step, a ...

New material innovation is limited by the time, expertise and cost of development. In the face of rapidly growing crises like pandemics, resource scarcity and climate change, we require new methods and methodologies to create and scale-up new technologies. In this work, we introd ...

Modelling Circular Structures in Reaction Networks

Petri Nets and Reaction Network Flux Analysis

Optimal reaction pathways for the conversion of renewable feedstocks are often examined by reaction network flux analysis. An alternative modelling approach for reaction networks is a Petri net. These explicitly take the reaction sequence into account. In the optimisation of a ...

Rational solvent selection remains a significant challenge in process development. Here we describe a hybrid mechanistic-machine learning approach, geared towards automated process development workflow. A library of 459 solvents was used, for which 12 conventional molecular de ...

This paper explores the feasibility of controlling the selectivity of a partial oxidation reaction by simultaneous modulation of local oxygen concentration and coolant temperature along the length of a reactor. The microstructured membrane reactor (MMR) concept consists of an ...

Many engineering problems require the optimization of expensive, black-box functions involving multiple conflicting criteria, such that commonly used methods like multiobjective genetic algorithms are inadequate. To tackle this problem several algorithms have been developed us ...

Machine learning meets continuous flow chemistry

Automated optimization towards the Pareto front of multiple objectives

Automated development of chemical processes requires access to sophisticated algorithms for multi-objective optimization, since single-objective optimization fails to identify the trade-offs between conflicting performance criteria. Herein we report the implementation of a new ...

A decision support tool has been developed that uses global multiobjective optimization based on 1) the environmental impacts, evaluated within the framework of full life cycle assessment; and 2) process costs, evaluated by using rigorous process models. This approach is parti ...