ERC FUNDED PROJECTS

Climate change and the decreasing availability of fossil fuels require society to move towards sustainable and renewable resources. 2DNanoCaps will focus on electrochemical energy storage, specifically supercapacitors. In terms of performance supercapacitors fill up the gap between batteries and the classical capacitors. Whereas batteries possess a high energy density but low power density, supercapacitors possess high power density but low energy density. Efforts are currently dedicated to move supercapacitors towards high energy density and high power density performance. Improvements have been achieved in the last few years due to the use of new electrode nanomaterials and the design of new hybrid faradic/capacitive systems. We recognize, however, that we are reaching a newer limit beyond which we will only see small incremental improvements. The main reason for this being the intrinsic difficulty in handling and processing materials at the nano-scale and the lack of communication across different scientific disciplines. I plan to use a multidisciplinary approach, where novel nanomaterials, existing knowledge on nano-scale processing and established expertise in device fabrication and testing will be brought together to focus on creating more efficient supercapacitor technologies. 2DNanoCaps will exploit liquid phase exfoliated two-dimensional nanomaterials such as transition metal oxides, layered metal chalcogenides and graphene as electrode materials. Electrodes will be ultra-thin (capacitance and thickness of the electrodes are inversely proportional), conductive, with high dielectric constants. Intercalation of ions between the assembled 2D flakes will be also achievable, providing pseudo-capacitance. The research here proposed will be initially based on fundamental laboratory studies, recognising that this holds the key to achieving step-change in supercapacitors, but also includes scaling-up and hybridisation as final objectives.

1 501 296 €

Start date: 2011-10-01, End date: 2016-09-30

"A low-cost sensor able to perceive 3D information would be a breakthrough for a number of applications. Automotive applications would benefit from a low-cost obstacle detector to increase road safety; agricultural vehicles would be able to sense the environment and perform precise (and even autonomous) maneuvers improving their effectiveness; efficient sensing would be a key also to future building automation: elevators doors would close just after boarding and keep open when detecting people's intention to enter, automatic doors would not open when individuals would move in their sensed area but without the intention to cross the door. Even the entertainment industry, which lately invested massively on innovative and interactive sensors, would benefit from precise 3D sensors working even outdoor or in combination with multiple identical sensors. This proposal is aimed at preparing an engineered version of the current stereo-based system developed for vehicles within the OFAV ERC-funded Advanced Grant and currently under test in many other application domains. It is based on two microcameras and a smart software reconstructing the 3D environment; the software will be ported on a low-cost FPGA+DSP integrated into the sensor box, providing a small and light passive sensor for a variety of applications that nowadays either use other technologies (laser based) or are not able to reach the performance provided by this sensor (e.g. IR-based elevators' door control which is not working in highly illuminated sites and covers only smaller areas). The algorithm which is now working on a PC-based platform is owned by the team working for the OFAV Project and delivers superb results in terms of accuracy. This proposal is intended to provide resources to implement this solution in hardware and produce a low-cost, small-sized, and high performance sensor to be used in a very wide range of applications."

148 061 €

Start date: 2012-06-01, End date: 2013-10-31

I intend to investigate what cognitive mechanisms give us combinatorial speech. Combinatorial speech is the ability to make new words using pre-existing speech sounds. Humans are the only apes that can do this, yet we do not know how our brains do it, nor how exactly we differ from other apes. Using new experimental techniques to study human behavior and new computational techniques to model human cognition, I will find out how we deal with combinatorial speech. The experimental part will study individual and cultural learning. Experimental cultural learning is a new technique that simulates cultural evolution in the laboratory. Two types of cultural learning will be used: iterated learning, which simulates language transfer across generations, and social coordination, which simulates emergence of norms in a language community. Using the two types of cultural learning together with individual learning experiments will help to zero in, from three angles, on how humans deal with combinatorial speech. In addition it will make a methodological contribution by comparing the strengths and weaknesses of the three methods. The computer modeling part will formalize hypotheses about how our brains deal with combinatorial speech. Two models will be built: a high-level model that will establish the basic algorithms with which combinatorial speech is learned and reproduced, and a neural model that will establish in more detail how the algorithms are implemented in the brain. In addition, the models, through increasing understanding of how humans deal with speech, will help bridge the performance gap between human and computer speech recognition. The project will advance science in four ways: it will provide insight into how our unique ability for using combinatorial speech works, it will tell us how this is implemented in the brain, it will extend the novel methodology of experimental cultural learning and it will create new computer models for dealing with human speech.

1 276 620 €

Start date: 2012-02-01, End date: 2017-01-31

1.2 billion people worldwide lack access to safe drinking water. Drinking water quality is threatened by newly emerging organic micro-pollutants (pesticides, pharmaceuticals, industrial chemicals) in source waters. Nanofiltration is a technology that is expected to play a key role in future water treatment processes due to its effectiveness in removal of micropollutants. However, the loss of membrane flux due to fouling is one of the main impediments in the development of membrane processes for use in drinking water treatment. Currently there is a wholly inadequate mechanistic understanding of the role of biofilm on the fouling of nanofiltration membranes. Applying techniques including confocal microscopy, force spectroscopy, and infrared spectroscopy using an experimental programme informed by a technique known as scale-down together with mathematical modelling, it is confidently expected that significant advances will be gained in the mechanistic understanding of nanofiltration biofouling. The specific objectives are 1. How is the rate of formation and extent of such biofilms influenced by the biological response to the local microenvironment? 2 Elucidate the effect of extracellular polysaccharide substances on physical properties, composition and structure of these biofilms. 3: Investigate mechanisms to enhance biofilm removal by a physical detachment process complemented by techniques that alter biofilm material properties. A more fundamental insight into the mechanisms of nanofiltration operation will help in further development of this treatment method in future water treatment processes.

1 468 987 €

Start date: 2011-10-01, End date: 2016-09-30