Projects
Additive manufacturing of self-healing soft robots with integrated sensing capabilities. Vrije Universiteit Brussel
3D Structural Platform for Chemical Excellence. Ghent University
Science communication Exploring to lay the chemical and biological space through the link between the three-dimensional structure of bio (molecules) and their physicochemical properties, chemical reactivity and function has been shown to be one of the revolutionary techniques on a methodological level in the (bio ) chemical sciences in the last century. This is structural information in the post-genomic era has become an integral part of the ...
Artificial proteases based on polyoxo/hydroxo zirconate clusters KU Leuven
Zirconia (ZrO2) is one of the most common metal oxides present in Earth’s crust. In its bulk form zirconia finds broad applications as cell electrolyte, gate dielectric or chromatographic support, while zirconia nanoparticles supported on Au, Ag and Cu are efficient catalyst for the water-gas shift reaction, methanol synthesis and CO oxidation.
The synthesis and the characterization of nanoscopic zirconium-oxo/-hydroxo clusters ...
Liquid chromatograph interfaced with an isotope ratio mass spectrometry detector (LC-IRMS) Ghent University
The Isotope Bioscience Laboratory (ISOFYS) of the promoter-spokesperson is a centre of excellence holding unique expertise and equipment for analyses and applications of stable isotopes of light elements (H,C,N,O,S) ISOFYS currently manages eight platforms for stable isotope analyses, which foster interdisciplinary collaboration with UGent and (inter)national research groups, as the importance of stable isotopes for (life) science has ...
Design of hafnium oxide nanocrystals as computed tomography contrast agent for damage detection in high-end composites. Ghent University
The demand for light-weight, sustainable and high-performance materials is increasing exponentially. Fiber reinforced polymers offer higher strength-to-weight and stiffness-to-weight ratios than traditional materials such as steel, which allows for energy savings and carbon emission reductions. However, their heterogeneous and anisotropic nature makes their behavior far more complex than these traditional materials. In order to analyze their ...
Application of novel organic reactions for the preparation of new heteroaromatic scaffolds KU Leuven
N-containing heterocycles can be found in several bioactive small molecules, and it is well known that these are very prominent scaffolds in drug discovery. Additionally, the availability of organic reactions for different functionalizations is the key factor that may be limiting the development of new drugs. It is widely accepted that investments in basic chemistry for the development of new synthetic methodologies towards heterocycles are ...
Double dynamic polymer network architectures for multi-stimuliresponsive materials. Vrije Universiteit Brussel
design criteria for structures ever more complex and material
requirements ever more demanding. In light of these scientific
challenges, smart materials are being developed. Stimuli-responsive
materials are such smart materials, exhibiting adaptability in
response of environmental stimuli. Self-healing materials are able to
repair damage ...
Electrocatalytic N-functionalisation of olefins towards aziridines and amines KU Leuven
Ever since the Industrial Revolution, mankind has been progressively manufacturing a wide array of goods that led to an unprecedented growth in prosperity and quality of life. In response to the mounting ecological and social challenges, the 20th century witnessed the emergence of environmental movements and a growing awareness of the need for sustainable practices. The shift towards sustainability gained momentum as the global community ...
Interacting Particle Networks: a new deep learning approach to molecular simulation of condensed phases. Ghent University
Force fields are computationally very efficient, yet coarse approximations to the potential energy surface felt by nuclei in molecules. In this project, recent breakthroughs in machine learning will be exploited to increase their reliability. The goal of this work, is to establish force fields with a novel deep learning concept, designed to “understand” many-body interactions: the Interacting Particle Network (IPN).