Fourteen promising young Delft researchers receive Veni grant

Photo-active hydrogen bonded pairs for efficient artificial leaves
Dr. Tessel Bouwens, Applied Sciences (AS)

Using sunlight to generate the building blocks for medicines? Yes, we can, if we manage to solve the
efficiency problem in artificial photosynthetic devices. This research proposes to address the efficiency
problem by developing a molecular shuttlebus for delivering charged species at the desired location at
the right time to circumvent that these reactive charged species will undergo destructive side reactions.
Using the concept of the molecular shuttlebus, I want to develop a new method to generate the building
blocks for medicines employing solar energy, without using the polluting fossil fuels.

Combinatorial applications in parameterized algorithms
Dr. Carla Groenland, Electrical Engineering, Mathematics & Computer Science (EEMCS)

Network algorithms are ubiquitous: you use them for example when finding the shortest route home. In
this project, insights from combinatorics are used to find better algorithms, bringing fundamental
mathematics a step in the direction of real-life applications. The project includes reconstructing
properties from as few questions as possible (``query reconstruction'') and recognizing redundant steps
in sorting algorithms (``slow sorting''). The latter has implications for routing algorithms.
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Characterization of organic matter through spectro-polarimetry
Dr. Sandra Potin, Aerospace Engineering (AE)

The light holds information on the surface it has been reflected on. This is currently used as a technique
to detect signs of organic molecules, the building blocks of life in the Solar System. But this can be
limited by the detection capacity of the space scientific instrument. This project proposes to use an
intrinsic property of the light, polarization, to isolate and better identify the carbon-based molecules.
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Ultrafast detection of short-lived intermediates during the electrocatalytic CO2 reduction reaction
Dr. Yan Vogel, Applied Sciences (AS)

The petrochemical industry provides us with the products required to sustain our current living
standards, but also releases ~40 Gt a year of carbon dioxide driving climate change. The use of
renewable electricity to convert carbon dioxide into valuable chemicals can solve this problem.
However, we are currently unable to obtain the desired products because of the lack of understanding
of the carbon dioxide reactions. This project aims to unlock the mechanism behind these reactions by
using advanced spectroscopic tools, leading to a new method of chemical visualization for the
production of clean chemicals.
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RECLIMATE: Resource-efficient climate-resilient buildings by multi-hazard risk modelling and
resilience-oriented decision-making
Dr. Simona Bianchi, Architecture and the Built Environment

Climate change poses higher risks to our vulnerable homes. Urgent adaptation solutions are needed to
create resilient urban communities. Yet, current design and assessment methods do not consider multi-
hazard resilience quantifications and extreme heat consequences, which results in ineffective solutions.
This project pioneers a comprehensive assessment framework to measure the heat vulnerability of
buildings and quantify their overall resilience in the face of climate uncertainties. It introduces novel
multi-disciplinary design methods, frameworks and digital tools for resource-efficient resilient designs
and retrofits in the era of climate-induced extremes.
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Energy-Efficient Real-Time Edge Intelligence for Wearable Healthcare Devices
Dr. Chang Gao, Electrical Engineering, Mathematics & Computer Science (EEMCS)

In this innovative project, researchers are developing new software and hardware technology to make
healthcare wearables, like eye movement trackers, hearing aids, and heart rate monitors, smarter and
more efficient. By processing personal data and artificial intelligence algorithms for healthcare directly
on these devices powered by specialised AI hardware accelerators, the project aims to enable instant
wearable healthcare and enhance privacy. This approach also reduces energy use, promising longer
battery life and more sustainable devices. The technology could transform how we monitor health
conditions, making it quicker, more secure, and accessible to a wider audience.
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Revealing Hidden Networks of Coastal Sediment Pathways via Laboratory & Numerical Experiments
Dr. ir. Stuart Pearson, Civil Engineering and Geosciences (CEG)

Sediment is essential for creating a safe and sustainable coast. In this project, I will track the pathways
that sand takes on an experimental laboratory beach and extend those findings with computer models.
By revealing the interconnected network of sediment pathways shaping our coast, we can better
understand how to manage the sediment that builds ecosystems and protects us against flooding.
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Signal Processing and Learning from Higher-Order Network Dynamics
Dr. Elvin Isufi, Electrical Engineering, Mathematics & Computer Science (EEMCS)
Networks, such as those that distribute water to our homes or our brain, generate streams of data according to their topology but conventional processing techniques do not fully capture their complex dependencies. The research will investigate novel techniques to better leverage the network structure for processing these data so as to detect more accurately brain anomalies, forecast future water demands, and make them deployable to a large-scale setting.