Project acronym NanoThermo
Project Energy Conversion and Information Processing at Small Scales
Researcher (PI) Massimiliano Gennaro Esposito
Host Institution (HI) UNIVERSITE DU LUXEMBOURG
Country Luxembourg
Call Details Consolidator Grant (CoG), PE3, ERC-2015-CoG
Summary Thermodynamics provided mankind with the intellectual tools to master energy transfers and energy conversion in macroscopic systems operating close to equilibrium. It is now one of the most fundamental theories in physics. My goal is to establish a thermodynamic theory describing energy conversion and information processing in small synthetic or biological systems operating far from equilibrium. Significant progress has been achieved in this direction over the last decade. The new theory is called stochastic thermodynamics (ST). It allows us to describe and understand energy conversion in systems as diverse as quantum junctions and molecular motors, and also to predict the energetic cost of information processing operations such as erasing bits of information or feedback controlling a small device. It was validated in single molecule pulling experiments, electronic circuits, NMR and colloidal particles in optical tweezers. Nevertheless, ST still suffers from serious limitations which prevent its application in more complex systems. Therefore, I propose to expand the theoretical foundations of ST far beyond its current realm of validity and to broaden the scope of its applications in various new directions. I want to answer questions such as: Can one design devices made of many small energy converters (e.g. thermoelectric junctions) arranged in such a way as to generate collective behaviors (e.g. synchronization) prompting higher powers and efficiencies? Can one do the same by engineer quantum effects? How can one reduce the dissipation occurring when computing very quickly with small devices? Why are metabolic networks so efficient in converting energy, transmitting information, and preventing errors (e.g. toxic byproducts)? I will do so in close contact with leading experimental groups in the field. My conviction is that ST will become as important for nanotechnologies and molecular biology as thermodynamics has been for the industrial revolution.
Summary
Thermodynamics provided mankind with the intellectual tools to master energy transfers and energy conversion in macroscopic systems operating close to equilibrium. It is now one of the most fundamental theories in physics. My goal is to establish a thermodynamic theory describing energy conversion and information processing in small synthetic or biological systems operating far from equilibrium. Significant progress has been achieved in this direction over the last decade. The new theory is called stochastic thermodynamics (ST). It allows us to describe and understand energy conversion in systems as diverse as quantum junctions and molecular motors, and also to predict the energetic cost of information processing operations such as erasing bits of information or feedback controlling a small device. It was validated in single molecule pulling experiments, electronic circuits, NMR and colloidal particles in optical tweezers. Nevertheless, ST still suffers from serious limitations which prevent its application in more complex systems. Therefore, I propose to expand the theoretical foundations of ST far beyond its current realm of validity and to broaden the scope of its applications in various new directions. I want to answer questions such as: Can one design devices made of many small energy converters (e.g. thermoelectric junctions) arranged in such a way as to generate collective behaviors (e.g. synchronization) prompting higher powers and efficiencies? Can one do the same by engineer quantum effects? How can one reduce the dissipation occurring when computing very quickly with small devices? Why are metabolic networks so efficient in converting energy, transmitting information, and preventing errors (e.g. toxic byproducts)? I will do so in close contact with leading experimental groups in the field. My conviction is that ST will become as important for nanotechnologies and molecular biology as thermodynamics has been for the industrial revolution.
Max ERC Funding
1 669 029 €
Duration
Start date: 2016-07-01, End date: 2021-12-31
Project acronym TUNE
Project Testing the Untestable: Model Testing of Complex Software-Intensive Systems
Researcher (PI) Lionel, Claude, Laurent Briand
Host Institution (HI) UNIVERSITE DU LUXEMBOURG
Country Luxembourg
Call Details Advanced Grant (AdG), PE6, ERC-2015-AdG
Summary Software-intensive systems pervade modern society and industry. These systems often play critical roles from an economic, safety or security standpoint, thus making their dependability indispensible. Software Verification and Validation (V&V) is core to ensuring software dependability. The most prevalent V&V technique is testing, that is the automated, systematic, and controlled execution of a system to detect faults or to show compliance with requirements. Increasingly, we are faced with systems that are untestable, meaning that traditional testing methods are highly expensive, time-consuming or infeasible to apply due to factors such as the systems’ continuous interactions with the environment and the deep intertwining of software with hardware.
TUNE will enable testing of untestable systems by revolutionising how we think about test automation. Our key idea is to frame testing on models rather than operational systems. We refer to such testing as model testing. The models that underlie model testing are executable representations of the relevant aspects of a system and its environment, alongside the risks of system failures. Such models inevitably have uncertainties due to complex, dynamic environment behaviours and the unknowns about the system. This necessitates that model testing be uncertainty-aware.
We propose to develop scalable, practical and uncertainty-aware techniques for test automation, leveraging our expertise on model-driven engineering and automated testing. Our solutions will synergistically combine metaheuristic search with system and risk models to drive the search for critical faults that entail the most risk. TUNE is the first initiative with the specific goal of raising the level of abstraction of testing from operational systems to models. The project will bring early and cost-effective automation to the testing of many critical systems that defy existing automation techniques, thus significantly improving the dependability of such systems.
Summary
Software-intensive systems pervade modern society and industry. These systems often play critical roles from an economic, safety or security standpoint, thus making their dependability indispensible. Software Verification and Validation (V&V) is core to ensuring software dependability. The most prevalent V&V technique is testing, that is the automated, systematic, and controlled execution of a system to detect faults or to show compliance with requirements. Increasingly, we are faced with systems that are untestable, meaning that traditional testing methods are highly expensive, time-consuming or infeasible to apply due to factors such as the systems’ continuous interactions with the environment and the deep intertwining of software with hardware.
TUNE will enable testing of untestable systems by revolutionising how we think about test automation. Our key idea is to frame testing on models rather than operational systems. We refer to such testing as model testing. The models that underlie model testing are executable representations of the relevant aspects of a system and its environment, alongside the risks of system failures. Such models inevitably have uncertainties due to complex, dynamic environment behaviours and the unknowns about the system. This necessitates that model testing be uncertainty-aware.
We propose to develop scalable, practical and uncertainty-aware techniques for test automation, leveraging our expertise on model-driven engineering and automated testing. Our solutions will synergistically combine metaheuristic search with system and risk models to drive the search for critical faults that entail the most risk. TUNE is the first initiative with the specific goal of raising the level of abstraction of testing from operational systems to models. The project will bring early and cost-effective automation to the testing of many critical systems that defy existing automation techniques, thus significantly improving the dependability of such systems.
Max ERC Funding
2 307 932 €
Duration
Start date: 2016-09-01, End date: 2022-02-28
