Project acronym C8
Project Consistent computation of the chemistry-cloud continuum and climate change in Cyprus
Researcher (PI) Johannes Lelieveld
Host Institution (HI) THE CYPRUS RESEARCH AND EDUCATIONAL FOUNDATION
Country Cyprus
Call Details Advanced Grant (AdG), PE10, ERC-2008-AdG
Summary We have developed a new numerical method to consistently compute atmospheric trace gas and aerosol chemistry and cloud processes. The method is computationally efficient so that it can be used in climate models. For the first time cloud droplet formation on multi-component particles can be represented based on first principles rather than parameterisations. This allows for a direct coupling in models between aerosol chemical composition and the continuum between hazes and clouds as a function of ambient relative humidity. We will apply the method in a new nested global-limited area model system to study atmospheric chemistry climate interactions and anthropogenic influences. We will focus on the Mediterranean region because it is a hot spot in climate change exposed to drying and air pollution. The limited area model will also be applied as cloud-resolving model to study aerosol influences on precipitation and storm development. By simulating realistic meteorological conditions at high spatial resolution our method can be straightforwardly tested against observations. Central questions are: - How does the simulated haze-cloud continuum compare with remote sensing measurements and what is the consequence of abandoning the traditional and artificial distinction between aerosols and clouds? - How are cloud and precipitation formation influenced by atmospheric chemical composition changes? - To what extent do haze and cloud formation in polluted air exert forcings of synoptic meteorological conditions and climate? - Can aerosol pollution in the Mediterranean region exacerbate the predicted and observed drying in a changing climate? The model system is user-friendly and will facilitate air quality and climate studies by regional scientists. The project will be part of the Energy, Environment and Water Centre of the newly founded Cyprus Institute, provide input to climate impact assessments and contribute to a regional outreach programme.
Summary
We have developed a new numerical method to consistently compute atmospheric trace gas and aerosol chemistry and cloud processes. The method is computationally efficient so that it can be used in climate models. For the first time cloud droplet formation on multi-component particles can be represented based on first principles rather than parameterisations. This allows for a direct coupling in models between aerosol chemical composition and the continuum between hazes and clouds as a function of ambient relative humidity. We will apply the method in a new nested global-limited area model system to study atmospheric chemistry climate interactions and anthropogenic influences. We will focus on the Mediterranean region because it is a hot spot in climate change exposed to drying and air pollution. The limited area model will also be applied as cloud-resolving model to study aerosol influences on precipitation and storm development. By simulating realistic meteorological conditions at high spatial resolution our method can be straightforwardly tested against observations. Central questions are: - How does the simulated haze-cloud continuum compare with remote sensing measurements and what is the consequence of abandoning the traditional and artificial distinction between aerosols and clouds? - How are cloud and precipitation formation influenced by atmospheric chemical composition changes? - To what extent do haze and cloud formation in polluted air exert forcings of synoptic meteorological conditions and climate? - Can aerosol pollution in the Mediterranean region exacerbate the predicted and observed drying in a changing climate? The model system is user-friendly and will facilitate air quality and climate studies by regional scientists. The project will be part of the Energy, Environment and Water Centre of the newly founded Cyprus Institute, provide input to climate impact assessments and contribute to a regional outreach programme.
Max ERC Funding
2 196 000 €
Duration
Start date: 2009-01-01, End date: 2014-12-31
Project acronym FAULT-ADAPTIVE
Project Fault-Adaptive Monitoring and Control of Complex Distributed Dynamical Systems
Researcher (PI) Marios Polycarpou
Host Institution (HI) UNIVERSITY OF CYPRUS
Country Cyprus
Call Details Advanced Grant (AdG), PE7, ERC-2011-ADG_20110209
Summary "The emergence of networked embedded systems and sensor/actuator networks has facilitated the development of advanced monitoring and control applications, where a large amount of sensor data is collected and processed in real-time in order to activate the appropriate actuators and achieve the desired control objectives. However, in situations where a fault arises in some of the components (e.g., sensors, actuators, communication links), or an unexpected event occurs in the environment, this may lead to a serious degradation in performance or, even worse, to an overall system failure. There is a need to develop a systematic framework to enhance the reliability, fault-tolerance and sustainability of complex distributed dynamical systems through the use of fault-adaptive monitoring and control methods. The work proposed here will contribute to the development of such a framework with emphasis on applications related to critical infrastructure systems (e.g., power, water, telecommunications and transportation systems). It will provide an innovative approach based on the use of networked intelligent agent systems, where the state of the infrastructure is monitored and controlled by a network of sensors and actuators with cooperating agents for fault diagnosis and fault tolerant control. A hierarchical fault diagnosis architecture will be developed, with neighbouring fault diagnosis agents cooperating at a local level, while transmitting their information, as needed, to a regional monitoring agent, responsible for integrating in real-time local information into a large-scale “picture” of the health of the infrastructure. A key motivation is to exploit spatial and temporal correlations between measured variables using learning methods, and to develop the tools and design methodologies that will prevent relatively “small” faults or unexpected events from causing significant disruption or complete system failures in complex distributed dynamical systems."
Summary
"The emergence of networked embedded systems and sensor/actuator networks has facilitated the development of advanced monitoring and control applications, where a large amount of sensor data is collected and processed in real-time in order to activate the appropriate actuators and achieve the desired control objectives. However, in situations where a fault arises in some of the components (e.g., sensors, actuators, communication links), or an unexpected event occurs in the environment, this may lead to a serious degradation in performance or, even worse, to an overall system failure. There is a need to develop a systematic framework to enhance the reliability, fault-tolerance and sustainability of complex distributed dynamical systems through the use of fault-adaptive monitoring and control methods. The work proposed here will contribute to the development of such a framework with emphasis on applications related to critical infrastructure systems (e.g., power, water, telecommunications and transportation systems). It will provide an innovative approach based on the use of networked intelligent agent systems, where the state of the infrastructure is monitored and controlled by a network of sensors and actuators with cooperating agents for fault diagnosis and fault tolerant control. A hierarchical fault diagnosis architecture will be developed, with neighbouring fault diagnosis agents cooperating at a local level, while transmitting their information, as needed, to a regional monitoring agent, responsible for integrating in real-time local information into a large-scale “picture” of the health of the infrastructure. A key motivation is to exploit spatial and temporal correlations between measured variables using learning methods, and to develop the tools and design methodologies that will prevent relatively “small” faults or unexpected events from causing significant disruption or complete system failures in complex distributed dynamical systems."
Max ERC Funding
2 035 200 €
Duration
Start date: 2012-04-01, End date: 2018-03-31
Project acronym LOGOS
Project Light-operated logic circuits from photonic soft-matter
Researcher (PI) Igor MUSEVIC
Host Institution (HI) INSTITUT JOZEF STEFAN
Country Slovenia
Call Details Advanced Grant (AdG), PE7, ERC-2019-ADG
Summary I propose a revolutionary photonic technology based on self-assembled soft matter that is likely to evolve into currently unforeseen, futuristic technologies. The liquid nature and responsiveness of soft matter delivers the spontaneous self-assembly of tuneable liquid micro-lasers, liquid micro-fibres, liquid light switches, and tuneable optical micro-resonators with extremely smooth interfaces, low optical losses, elastic deformability and self-healing, all of which are difficult to obtain with hard matter. These photonic micro-devices operate exclusively on light and can be easily integrated into 3D photonic chips by micro-injection into a polymer scaffold or elastic binding via topological defect loops and points.
LOGOS will create integrated and self-organized photonic chips with the focus on four specific challenges: (i) an all optically switchable spherical 3D Bragg-onion optical transistor made of chiral liquid crystals (LCs), (ii) logic micro-gates made of LCs that operate entirely on light, (iii) optically switchable Whispering-Gallery-Mode LC micro-resonators that redirect light, and (iv) soft-matter photonic integrated circuits in 3D assembled using topology. The validity of the approach will be demonstrated by AND and NAND logic gates, and an add-drop Whispering-Gallery-Mode filter, which will be assembled from soft matter and will use only light to perform the logic operation and optical signal gating and redirecting beyond the GHz range.
This very high-risk, high-gain proposal challenges the mainstream photonic roadmaps by offering a disruptive technology that reduces production times, waste and energy, and enables light processing by light, all currently difficult to obtain in the solid state. LOGOS’s results will not only have a major impact on future data centres and optical networks, but could also revolutionize implantable, biocompatible and wearable photonics.
Summary
I propose a revolutionary photonic technology based on self-assembled soft matter that is likely to evolve into currently unforeseen, futuristic technologies. The liquid nature and responsiveness of soft matter delivers the spontaneous self-assembly of tuneable liquid micro-lasers, liquid micro-fibres, liquid light switches, and tuneable optical micro-resonators with extremely smooth interfaces, low optical losses, elastic deformability and self-healing, all of which are difficult to obtain with hard matter. These photonic micro-devices operate exclusively on light and can be easily integrated into 3D photonic chips by micro-injection into a polymer scaffold or elastic binding via topological defect loops and points.
LOGOS will create integrated and self-organized photonic chips with the focus on four specific challenges: (i) an all optically switchable spherical 3D Bragg-onion optical transistor made of chiral liquid crystals (LCs), (ii) logic micro-gates made of LCs that operate entirely on light, (iii) optically switchable Whispering-Gallery-Mode LC micro-resonators that redirect light, and (iv) soft-matter photonic integrated circuits in 3D assembled using topology. The validity of the approach will be demonstrated by AND and NAND logic gates, and an add-drop Whispering-Gallery-Mode filter, which will be assembled from soft matter and will use only light to perform the logic operation and optical signal gating and redirecting beyond the GHz range.
This very high-risk, high-gain proposal challenges the mainstream photonic roadmaps by offering a disruptive technology that reduces production times, waste and energy, and enables light processing by light, all currently difficult to obtain in the solid state. LOGOS’s results will not only have a major impact on future data centres and optical networks, but could also revolutionize implantable, biocompatible and wearable photonics.
Max ERC Funding
2 474 268 €
Duration
Start date: 2021-01-01, End date: 2025-12-31
Project acronym MULTraSonicA
Project Multiscale modeling and simulation approaches for biomedical ultrasonic applications
Researcher (PI) Matej Praprotnik
Host Institution (HI) KEMIJSKI INSTITUT
Country Slovenia
Call Details Advanced Grant (AdG), PE8, ERC-2019-ADG
Summary Ultrasound-guided drug and gene delivery (USDG) enables controlled and spatially precise delivery of drugs and macromolecules, encapsulated in microbubbles (MBs) and submicron gas vesicles (GVs), to target areas such as cancer tumors. It is a non-invasive, high precision, low toxicity process with drastically reduced drug dosage. These advantages open doors to numerous biomedical applications, from sonothrombolysis to blood–brain barrier opening. However, the progress and deployment of this technology is subject to extensive experimentation and heuristics. The proposal aims to develop a virtual environment to quantify and optimize USDG and in particular the MBs and GVs utilized as drug carriers and contrast agents. Their type and concentration, and interface with ultrasound (US) are critical to the success and efficiency of USDG. State-of-the-art USDG systems operate in a narrow range of empirically-tuned US parameters. This empiricism entails severe risks and limitations for clinical applications and delays the adoption of this potent technology. I propose a computational framework that would allow for controlled testing, data-driven quantification of uncertainties, and a rational optimization of experimental US parameters. The framework will rely on submicron resolution modeling and simulation of cavitating MBs and GVs interacting with US. Limitations of existing models based on continuum theory preclude an accurate description of cavitation, drastically degrading the prediction of drug delivery outcomes. I will develop new, data-informed mesoscopic models of US contrast agents, capturing their rheological and acoustic behavior. Specific interactions of US and agents at a submicron level will be included by harnessing novel multiscale methods that enable seamless propagation of US from the macro to microscopic level. The proposed framework will be integrated with experimental efforts to advance USDG across biomedical applications.
Summary
Ultrasound-guided drug and gene delivery (USDG) enables controlled and spatially precise delivery of drugs and macromolecules, encapsulated in microbubbles (MBs) and submicron gas vesicles (GVs), to target areas such as cancer tumors. It is a non-invasive, high precision, low toxicity process with drastically reduced drug dosage. These advantages open doors to numerous biomedical applications, from sonothrombolysis to blood–brain barrier opening. However, the progress and deployment of this technology is subject to extensive experimentation and heuristics. The proposal aims to develop a virtual environment to quantify and optimize USDG and in particular the MBs and GVs utilized as drug carriers and contrast agents. Their type and concentration, and interface with ultrasound (US) are critical to the success and efficiency of USDG. State-of-the-art USDG systems operate in a narrow range of empirically-tuned US parameters. This empiricism entails severe risks and limitations for clinical applications and delays the adoption of this potent technology. I propose a computational framework that would allow for controlled testing, data-driven quantification of uncertainties, and a rational optimization of experimental US parameters. The framework will rely on submicron resolution modeling and simulation of cavitating MBs and GVs interacting with US. Limitations of existing models based on continuum theory preclude an accurate description of cavitation, drastically degrading the prediction of drug delivery outcomes. I will develop new, data-informed mesoscopic models of US contrast agents, capturing their rheological and acoustic behavior. Specific interactions of US and agents at a submicron level will be included by harnessing novel multiscale methods that enable seamless propagation of US from the macro to microscopic level. The proposed framework will be integrated with experimental efforts to advance USDG across biomedical applications.
Max ERC Funding
2 490 750 €
Duration
Start date: 2021-03-01, End date: 2026-02-28
