Invited Speaker



Bionanomachine Evolution and Nanoecology
A story on real-time modular evolution in the bacterial flagellar motor and the nanoscopic anatomy of a bacteriophage attack

Life as we know it relies on complexes of interacting proteins that perform vital functions in the cell. Although comparative analysis shows that the origin and innovation of protein complexes involved modular integration of foreign subunits, experimental evidence of the capacity of evolution to achieve is lacking. I will present results from an evolution experiment that captured the integration of incompatible protein subunits into an existing complex. We replaced genes that encode an essential part of the bacterial flagellar motor—a nanoscopic rotary motor that powers bacterial swimming—with related genes that encode similar subunits in different species. The data reveal a remarkable combinatorial potential and show that evolution is able to overcome interaction conflicts at and beyond the compatibility horizon along parallel, step-wise mutational trajectories. Remarkably, bacteria that evolved compatibility with a foreign part often remain backward compatible with the original component. I will also discuss results from an ongoing project that is revealing the nanoscopic behavioral ecology of bacterial viruses as they select and kill their targets.


Day Chair


University of Groningen

The group of Prof. Tamalika Banerjee studies emergent phenomena in Spintronics at different material interfaces such as correlated oxides, topological insulators, graphene and transition metal oxides using different transport schemes. Novel phenomena such as electric field modulation of spin states in complex oxide semiconductors and graphene, tunnelling anisotropic magnetoresistance coexisting with colossal electroresistance at memristive interfaces, topological Hall effect in ruthenates, spin hall magnetoresistance in antiferromagnetic oxides are a few recent highlights. Their work is relevant for applications in reconfigurable spintronics architecture as well as for bioinspired computing.


Kim van Adrichem

Machine Learning for Inorganic-Organic Hybrid Materials

Inorganic-organic hybrid Materials have received a lot of attention recently due to the rapid increase in solar cell efficiency of methylammonium lead halide based perovskite materials. The combination of inorganic and organic ions provide a very broad playing field for generating materials with new properties and the origin of these properties is often challenging to unravel. I focussed on the infrared absorption of such materials and how it is related to organic ion orientation and halide content in the perovskites.

In this project, a machine learning algorithm has been developed to predict infrared absorption spectra of perovskites by utilizing information from electronic structure calculations and molecular dynamics simulations. In particular, the effect of changing the species of halide on the vibrational frequency of the organic methylammonium cation has been investigated.

Alberto Carta

Alberto Carta

Simulation of Excitonic Transport in Self-assembled Nanofibers

Modelling and understanding exciton transport in nanowires is a great challenge. Here, the spectroscopic signatures and the transport properties of vibrationally dressed Frenkel excitons in heterotriangulene self-assembled H-aggregates is investigated. The analysis is carried out by simulating the absorption spectra of both the monomer and the aggregate. Furthermore, the structurally sensitive circular dichroism spectra are reproduced.

Using the parameters determined from the spectroscopic modelling the exciton transport is studied. At early times diffusive behavior is observed, which is analyzed via the Haken-Strobl-Reineker (HSR) model. The aggregate then transitions to a subdiffusive regime which is theoretically investigated through the introduction of trap states implemented via a Semi-Markovian approach to the propagation of the dynamics. The findings connect well with recent single aggregate experiments.


Panagiotis Koutsogiannis

Structural Investigation of Metal Nanoparticle thin films Prepared by Spark Ablation Deposition Technique

Thin nanocomposite films have many important technological applications such as electronic, optical and magnetic applications. In the present work, we deposited airborne Nanoparticles (NPs) of different size in a simple, safe and efficient way, generated by spark ablation technique and we investigated thin films composed of Sn NPs and PEDOT:PSS/Sn polymers/ metal composites. Structural parameters such as NPs size, shape, size polydispersity and aggregation behaviour were revealed using surface sensitive grazing-incidence small-angle X-ray scattering (GISAXS) along with complementary characterisation techniques, such as SEM, EDS and XRD. These results illustrate the advantages and disadvantages of the spark ablation deposition technique and how the grazing-incidence X-ray scattering techniques can assist the characterisation of thin metal and metal/polymers nanocomposite films.


Sameer Rodrigues

Complex Coacervation Based on Polyglutamic Acid and Protamine Sulfate

It is understood that some marine creatures, such as the sandcastle worm, synthesize protein based bio-adhesives using a process known as complex coacervation. These bio-adhesives are now being investigated as a potential alternative to surgical sutures and staples, due to their ability to adhere to wet surfaces. Complex coacervation involves a phase separation when two oppositely charged molecules are mixed in solution. This phase separation results in a dense coacervate phase (polymer-rich) and a dilute aqueous phase (polymer-deficient). The degree of complexation is heavily dependent on external parameters such as the polymer chemistry, salt concentration, pH and mixing ratios. In this study, polyglutamic acid and protamine sulfate were investigated to find the ideal conditions for complex coacervate formation. 


Cristhian Sumba

Theoretical Study on the Locked Movement in a Molecular Motor

Molecule switches, that can persist in two or more distinct states, have a high potential in applications such as information processing and data storage. Over-crowded alkenes (OCA) function as rotary motors by undergoing discrete switching-steps in which bulky aromatic groups move between local energy minima when driven by light and heat. The proposed project centered on employing theoretical and computational tools on a specific OCA, that undergoes a four-step rotary motion (tidally locked), to obtain atomic-level mechanistic insights into light- and mechanically-induced processes and physical properties that we will translate into useful molecular-electronic device functionality. A special emphasis will be laid on accurate description of the electronic structure of the molecular switches during switching process, calibration and benchmarking of different electronic structure approaches for both ground and excited states.


Jack Mayo

Developing Machine Learning Algorithms for Predicting Molecular Structure-function Relationship in Molecular Tunneling Junctions

The field of molecular electronics relies heavily on chemical intuition to make progress, coming in large part from previously studied molecular systems in complement to predictive studies based on DFT/Green’s functions. However, predictive analysis by DFT fails in the case of highly disordered systems with larger numbers of degrees of freedom. Machine learning offers a way to circumvent complications from ab-initio calculation by anchoring predictive capabilities in empirical measurements. Availability of large open-source datasets from laboratories around the world lends feasibility this application, allowing structural information to be directly linked to functional properties. In this work, a supervised encoder-decoder system is trained by projecting molecular structures onto an intermediate latent space. The encoder is trained a second time in tandem with an approximator, giving rise to additional structure in the latent space correlating with molecular properties. As a proof of concept, we compare results from a restricted open-source dataset with one constructed by hand from the molecular electronics literature.


Evgenios Stylianidis

Thiol-based Ligands for Water Soluble PbS Quantum Dots Inks and Their Electronic Properties in Thin Films

Semiconducting colloidal quantum dots (QDs) have attracted considerable interest for applications in opto-electronics, for example in photovoltaic or light emitting devices. The dependence of QD electronic properties on their capping agent offers the intriguing opportunity for the design of new solution-processable materials. In this project, we investigate the functionalization of the surface of PbS QDs with a thiol-containing amino acid – L-cysteine. By using a solution-phase ligand exchange process, we replace native oleic acid ligands from the surface of PbS nanocrystals and prepare water-based inks allowing an easier devices fabrication. At the same time, we avoid the harmful highly polar solvents that are usually used in QDs inks. In addition, the electronic transport properties of the new material are studied in field-effect transistors via direct single-step deposition of the prepared inks.


Miina Leiviskä

Simulations on charge transport in doped Organic Semiconductors 


Yahia Mostafa

Deuteration of Polycyclic Aromatic Hydrocarbons: A journey across space

Molecular hydrogen formation in space eludes many scientists. Molecular hydrogen is the most abundant hydrogen in the universe, however, its synthesis in interstellar media is not well understood. previous studies have speculated the formation of molecular hydrogen through hydrogen attachment to Polycyclic Aromatic Hydrocarbons (PAHs). The hydrogenation of many PAHs is done in solution which does not accurately present the attachment probabilities and interaction mechanisms between PAHs and hydrogen. In our lab, hydrogen and Deuterium are attached to PAHs in flight using a tandem mass spectrometer along a hydrogen, or deuterium, source. This allows for the accurate measurement of interactions of PAHs in an attempt to solve the mystery of molecular hydrogen in the universe. 


Vincent Goossens

Anti-icing Coating on the Basis of Graphene

Ice-formation on outdoor infrastructures operating under icing conditions is an important challenge, which hampers wind turbines, aircrafts, windshields, optical sensors, shipping and offshore operation. Fluorine-terminated graphene has recently been identified as an outstanding anti-icing coating. This project will concentrate on the application of fluorine-terminated graphene to optical sensors where the surface to be protected is sapphire. In particular, we aim to develop a upscalable way to produce such a coating. The graphene is grown using chemical vapour deposition and then transferred using molecular caging and PVA lamination, after which the transferred graphene undergoes a fluorination step.

Amara Zahid

Amara Zahid

Modelling Evolutionary Dynamics of Seed Evolvable Systems of Peptide- Nucleotide Self Assembling Molecular Self Replicators 

It is becoming increasingly evident that the answer to the age-old question ‘what is life’, and the description of the earliest processes that lead to abiogenesis – the emergence of life from non-life, lies not with biology, but chemistry.

In this project, we mathematically model evolution in seeded self-assembling competing systems of self replicators constituted of fibers of cyclic trimers formed from 2 peptides and a nucleotide. The systems show cross catalysis between peptides and nucleotide bases which enables complexity, selection and evolution in the replicators. Differential equation based rate laws define the system’s components, the intramolecular, intermolecular and supramolecular interactions, capture all occurring reactions, and describe the changing concentration of each species in the system.

When the simulations confirm experimentally determined results, that is indicative that this model is a good description of the system. By developing an intuition for the system’s non-evident interactions through modelling and exploring different initial conditions for the various building blocks and species, we aim to narrow down the initial conditions required for the emergence of specialist competing systems.