Project acronym COSMOS
Project Computational Simulations of MOFs for Gas Separations
Researcher (PI) Seda Keskin Avci
Host Institution (HI) KOC UNIVERSITY
Call Details Starting Grant (StG), PE8, ERC-2017-STG
Summary Metal organic frameworks (MOFs) are recently considered as new fascinating nanoporous materials. MOFs have very large surface areas, high porosities, various pore sizes/shapes, chemical functionalities and good thermal/chemical stabilities. These properties make MOFs highly promising for gas separation applications. Thousands of MOFs have been synthesized in the last decade. The large number of available MOFs creates excellent opportunities to develop energy-efficient gas separation technologies. On the other hand, it is very challenging to identify the best materials for each gas separation of interest. Considering the continuous rapid increase in the number of synthesized materials, it is practically not possible to test each MOF using purely experimental manners. Highly accurate computational methods are required to identify the most promising MOFs to direct experimental efforts, time and resources to those materials. In this project, I will build a complete MOF library and use molecular simulations to assess adsorption and diffusion properties of gas mixtures in MOFs. Results of simulations will be used to predict adsorbent and membrane properties of MOFs for scientifically and technologically important gas separation processes such as CO2/CH4 (natural gas purification), CO2/N2 (flue gas separation), CO2/H2, CH4/H2 and N2/H2 (hydrogen recovery). I will obtain the fundamental, atomic-level insights into the common features of the top-performing MOFs and establish structure-performance relations. These relations will be used as guidelines to computationally design new MOFs with outstanding separation performances for CO2 capture and H2 recovery. These new MOFs will be finally synthesized in the lab scale and tested as adsorbents and membranes under practical operating conditions for each gas separation of interest. Combining a multi-stage computational approach with experiments, this project will lead to novel, efficient gas separation technologies based on MOFs.
Summary
Metal organic frameworks (MOFs) are recently considered as new fascinating nanoporous materials. MOFs have very large surface areas, high porosities, various pore sizes/shapes, chemical functionalities and good thermal/chemical stabilities. These properties make MOFs highly promising for gas separation applications. Thousands of MOFs have been synthesized in the last decade. The large number of available MOFs creates excellent opportunities to develop energy-efficient gas separation technologies. On the other hand, it is very challenging to identify the best materials for each gas separation of interest. Considering the continuous rapid increase in the number of synthesized materials, it is practically not possible to test each MOF using purely experimental manners. Highly accurate computational methods are required to identify the most promising MOFs to direct experimental efforts, time and resources to those materials. In this project, I will build a complete MOF library and use molecular simulations to assess adsorption and diffusion properties of gas mixtures in MOFs. Results of simulations will be used to predict adsorbent and membrane properties of MOFs for scientifically and technologically important gas separation processes such as CO2/CH4 (natural gas purification), CO2/N2 (flue gas separation), CO2/H2, CH4/H2 and N2/H2 (hydrogen recovery). I will obtain the fundamental, atomic-level insights into the common features of the top-performing MOFs and establish structure-performance relations. These relations will be used as guidelines to computationally design new MOFs with outstanding separation performances for CO2 capture and H2 recovery. These new MOFs will be finally synthesized in the lab scale and tested as adsorbents and membranes under practical operating conditions for each gas separation of interest. Combining a multi-stage computational approach with experiments, this project will lead to novel, efficient gas separation technologies based on MOFs.
Max ERC Funding
1 500 000 €
Duration
Start date: 2017-10-01, End date: 2022-09-30
Project acronym ENABLE
Project Advancing cell based therapies by supporting implant survival
Researcher (PI) Jeroen Leijten
Host Institution (HI) UNIVERSITEIT TWENTE
Call Details Starting Grant (StG), LS7, ERC-2017-STG
Summary Tissue engineering aims at the creation of living implants to replace, repair, or regenerate damaged, diseased, or aged tissues, which holds tremendous possibilities to both extend our lives and improve our quality of life. During the last decades, our ability to create small tissues to heal small animals e.g. mice and rats has taken a breath taking leap. However, we have relentlessly struggled to create viable tissues of human-relevant sizes. Creating solid large tissues imposes lethal nutrient diffusion limitations, which causes the living implant to suffer from starvation, loss of function, and inevitable failure.
I hypothesize that this key challenge can be tackled by recruiting and developing advanced enabling nano- and micro-technologies. The ENABLE project begins with the design and development of a widely applicable platform that will enable large solid engineered tissues to survive and function by actively sustaining the implants metabolic needs. This platform is based on a unique two pronged strategy that rely on distinct technologies: oxygen releasing micromaterials, fabricated using a next-generation droplet generator, to enable short term survival of the implant, while embedded bioprinting will endow implants with a complex 3D vascular network to enable their long term survival. As proof of principle, the effects of ENABLE’s platform will be investigated using a critical bone defect in which I analyse the survival and function of the created living implants.
The anticipated outcomes of this proposal are three fold: first, I will develop a next-generation engineered tissue that will overcome the current size restrictions via the use of enabling technologies; second, I will reveal new knowledge on the role of the oxygen tension on vascularization and tissue formation by enabling control over the in vivo oxygen tension; and third, I will develop a novel strategy that enables the treatment of critical bone defects.
Summary
Tissue engineering aims at the creation of living implants to replace, repair, or regenerate damaged, diseased, or aged tissues, which holds tremendous possibilities to both extend our lives and improve our quality of life. During the last decades, our ability to create small tissues to heal small animals e.g. mice and rats has taken a breath taking leap. However, we have relentlessly struggled to create viable tissues of human-relevant sizes. Creating solid large tissues imposes lethal nutrient diffusion limitations, which causes the living implant to suffer from starvation, loss of function, and inevitable failure.
I hypothesize that this key challenge can be tackled by recruiting and developing advanced enabling nano- and micro-technologies. The ENABLE project begins with the design and development of a widely applicable platform that will enable large solid engineered tissues to survive and function by actively sustaining the implants metabolic needs. This platform is based on a unique two pronged strategy that rely on distinct technologies: oxygen releasing micromaterials, fabricated using a next-generation droplet generator, to enable short term survival of the implant, while embedded bioprinting will endow implants with a complex 3D vascular network to enable their long term survival. As proof of principle, the effects of ENABLE’s platform will be investigated using a critical bone defect in which I analyse the survival and function of the created living implants.
The anticipated outcomes of this proposal are three fold: first, I will develop a next-generation engineered tissue that will overcome the current size restrictions via the use of enabling technologies; second, I will reveal new knowledge on the role of the oxygen tension on vascularization and tissue formation by enabling control over the in vivo oxygen tension; and third, I will develop a novel strategy that enables the treatment of critical bone defects.
Max ERC Funding
1 500 000 €
Duration
Start date: 2018-01-01, End date: 2022-12-31
Project acronym FUN-NOTCH
Project Fundamentals of the Nonlinear Optical Channel
Researcher (PI) Alex ALVARADO
Host Institution (HI) TECHNISCHE UNIVERSITEIT EINDHOVEN
Call Details Starting Grant (StG), PE7, ERC-2017-STG
Summary "Fibre optics are critical infrastructure for society because they carry nearly all the global Internet traffic. For a long time, optical fibre systems were thought to have infinite information-carrying capabilities. With current traffic demands growing by a factor between 10 and 100 every decade, however, this is no longer the case. In fact, it is currently unknown if the installed optical infrastructure will manage to cope with these demands in the future, or if we will face the so-called ""capacity crunch"".
To satisfy traffic demands, transceivers are being operated near the nonlinear regime of the fibres. In this regime, a power-dependent nonlinear phenomenon known as the Kerr effect becomes the key impairment that limits the information-carrying capability of optical fibres. The intrinsic nonlinear nature of these fibres makes the analysis very difficult and has led to a series of unanswered fundamental questions about data transmission in nonlinear optical fibres, and nonlinear media in general. For example, the maximum amount of information that optical fibres can carry in the highly nonlinear regime is still unknown, and the design of transceivers well-suited for this regime is also completely unexplored.
In this project, the PI will answer these fundamental questions by studying the simplest nontrivial building blocks underlying optical fibres, and will give a definitive answer to the capacity crunch question. The PI will use a systematic methodology that aims at embracing nonlinear effects, consider the continuous-time channel as the correct starting point for analysis, and redesign optical transceivers from scratch, lifting all linear assumptions. The proposed methodology is in sharp contrast with current research trends, which aim at mitigating nonlinearities, and consider discrete-time models in the linear regime. Due to the central role of information transmission in modern society, the results in this project will have broad societal impact."
Summary
"Fibre optics are critical infrastructure for society because they carry nearly all the global Internet traffic. For a long time, optical fibre systems were thought to have infinite information-carrying capabilities. With current traffic demands growing by a factor between 10 and 100 every decade, however, this is no longer the case. In fact, it is currently unknown if the installed optical infrastructure will manage to cope with these demands in the future, or if we will face the so-called ""capacity crunch"".
To satisfy traffic demands, transceivers are being operated near the nonlinear regime of the fibres. In this regime, a power-dependent nonlinear phenomenon known as the Kerr effect becomes the key impairment that limits the information-carrying capability of optical fibres. The intrinsic nonlinear nature of these fibres makes the analysis very difficult and has led to a series of unanswered fundamental questions about data transmission in nonlinear optical fibres, and nonlinear media in general. For example, the maximum amount of information that optical fibres can carry in the highly nonlinear regime is still unknown, and the design of transceivers well-suited for this regime is also completely unexplored.
In this project, the PI will answer these fundamental questions by studying the simplest nontrivial building blocks underlying optical fibres, and will give a definitive answer to the capacity crunch question. The PI will use a systematic methodology that aims at embracing nonlinear effects, consider the continuous-time channel as the correct starting point for analysis, and redesign optical transceivers from scratch, lifting all linear assumptions. The proposed methodology is in sharp contrast with current research trends, which aim at mitigating nonlinearities, and consider discrete-time models in the linear regime. Due to the central role of information transmission in modern society, the results in this project will have broad societal impact."
Max ERC Funding
1 497 982 €
Duration
Start date: 2018-01-01, End date: 2022-12-31
Project acronym GlycoEdit
Project New Chemical Tools for Precision Glycotherapy
Researcher (PI) Thomas BOLTJE
Host Institution (HI) STICHTING KATHOLIEKE UNIVERSITEIT
Call Details Starting Grant (StG), PE5, ERC-2017-STG
Summary Glycosylation, the expression of carbohydrate structures on proteins and lipids, is found in all the domains of life. The collection of all glycans found on a cell is called the “glycome” which is information rich and a key player in a plethora of physiological and pathological processes. The information that the glycome holds can be written, read and erased by glycosyltransferases, lectins and glycosidases, respectively. The immense structural complexity and the fact that glycan biosynthesis is not under direct genetic control makes it very difficult to study the glycome.
The glycosylation pattern of cancer cells is very different from that of healthy cells. It is still unclear whether aberrant glycosylation of cancer cells is a cause or consequence of tumorigenesis but it is associated with aggressive and invasive forms of cancer and hence poor prognosis. Malignant glycans are directly involved in a number of mechanisms that suppress the immune response, increase migration and extravasation (metastasis), block apoptosis and increase resistance to chemotherapy.
The aim of this proposal is develop new glycomimetics that can be used to edit the glycome of cancer cells to target such evasive mechanisms. Using combinations of new glycan based inhibitors, a coordinated attack on the cancer glycome can be carried out which is expected to severely cripple the cancers ability to grow and metastasize. This will make the tumor more susceptible to immune mediated killing which may be further enhanced in combination with other anti-cancer strategies.
To minimize systemic side effects, new methods for the local delivery/activation of glycan inhibitors will be developed. The developed methods are expected to have a much broader than just cancer alone since the studied mechanisms are also associated with autoimmune and neurodegenerative disease.
Summary
Glycosylation, the expression of carbohydrate structures on proteins and lipids, is found in all the domains of life. The collection of all glycans found on a cell is called the “glycome” which is information rich and a key player in a plethora of physiological and pathological processes. The information that the glycome holds can be written, read and erased by glycosyltransferases, lectins and glycosidases, respectively. The immense structural complexity and the fact that glycan biosynthesis is not under direct genetic control makes it very difficult to study the glycome.
The glycosylation pattern of cancer cells is very different from that of healthy cells. It is still unclear whether aberrant glycosylation of cancer cells is a cause or consequence of tumorigenesis but it is associated with aggressive and invasive forms of cancer and hence poor prognosis. Malignant glycans are directly involved in a number of mechanisms that suppress the immune response, increase migration and extravasation (metastasis), block apoptosis and increase resistance to chemotherapy.
The aim of this proposal is develop new glycomimetics that can be used to edit the glycome of cancer cells to target such evasive mechanisms. Using combinations of new glycan based inhibitors, a coordinated attack on the cancer glycome can be carried out which is expected to severely cripple the cancers ability to grow and metastasize. This will make the tumor more susceptible to immune mediated killing which may be further enhanced in combination with other anti-cancer strategies.
To minimize systemic side effects, new methods for the local delivery/activation of glycan inhibitors will be developed. The developed methods are expected to have a much broader than just cancer alone since the studied mechanisms are also associated with autoimmune and neurodegenerative disease.
Max ERC Funding
1 500 000 €
Duration
Start date: 2017-11-01, End date: 2022-10-31
Project acronym INFLUENCE
Project Influence-based Decision-making in Uncertain Environments
Researcher (PI) Frans OLIEHOEK
Host Institution (HI) TECHNISCHE UNIVERSITEIT DELFT
Call Details Starting Grant (StG), PE6, ERC-2017-STG
Summary Decision-theoretic sequential decision making (SDM) is concerned with endowing an intelligent agent with the capability to choose actions that optimize task performance. SDM techniques have the potential to revolutionize many aspects of society and recent successes, e.g., agents that play Atari games and beat a world champion in the game of Go, have sparked renewed interest in this field.
However, despite these successes, fundamental problems of scalability prevents these methods from addressing other problems with hundreds or thousands of state variables. For instance, there is no principled way of computing an optimal or near-optimal traffic light control plan for an intersection that takes into account the current state of traffic in an entire city. I will develop one in this project.
To achieve this, I will develop a new class of influence-based SDM methods that overcome scalability issues for such problems by using novel ways of abstraction. Considered from a decentralized system perspective, the intersection’s local problem is manageable, but the influence that the rest of the network exerts on it is complex. The key idea is that by using (deep) machine learning methods, we can learn sufficiently accurate representations of such influence to facilitate near-optimal decisions.
This project will construct a theoretical framework for such approximate influence representations and SDM methods that use them. Scalability of these methods will be demonstrated by rigorous empirical evaluation on two simulated challenge domains: traffic lights control in an entire city, and robotic order picking in a large-scale autonomous warehouse.
If successful, INFLUENCE will produce a range of influence-based SDM algorithms that can, in a principled manner, deal with a broad range of very large complex problems consisting of hundreds or thousands of variables, thus making an important step towards realizing the promise of autonomous agent technology.
Summary
Decision-theoretic sequential decision making (SDM) is concerned with endowing an intelligent agent with the capability to choose actions that optimize task performance. SDM techniques have the potential to revolutionize many aspects of society and recent successes, e.g., agents that play Atari games and beat a world champion in the game of Go, have sparked renewed interest in this field.
However, despite these successes, fundamental problems of scalability prevents these methods from addressing other problems with hundreds or thousands of state variables. For instance, there is no principled way of computing an optimal or near-optimal traffic light control plan for an intersection that takes into account the current state of traffic in an entire city. I will develop one in this project.
To achieve this, I will develop a new class of influence-based SDM methods that overcome scalability issues for such problems by using novel ways of abstraction. Considered from a decentralized system perspective, the intersection’s local problem is manageable, but the influence that the rest of the network exerts on it is complex. The key idea is that by using (deep) machine learning methods, we can learn sufficiently accurate representations of such influence to facilitate near-optimal decisions.
This project will construct a theoretical framework for such approximate influence representations and SDM methods that use them. Scalability of these methods will be demonstrated by rigorous empirical evaluation on two simulated challenge domains: traffic lights control in an entire city, and robotic order picking in a large-scale autonomous warehouse.
If successful, INFLUENCE will produce a range of influence-based SDM algorithms that can, in a principled manner, deal with a broad range of very large complex problems consisting of hundreds or thousands of variables, thus making an important step towards realizing the promise of autonomous agent technology.
Max ERC Funding
1 475 560 €
Duration
Start date: 2018-02-01, End date: 2023-01-31
Project acronym MemoMOFEnergy
Project Constructing polar rotors in metal-organic frameworks for memories and energy harvesting
Researcher (PI) Monique VAN DER VEEN
Host Institution (HI) TECHNISCHE UNIVERSITEIT DELFT
Call Details Starting Grant (StG), PE8, ERC-2017-STG
Summary I seek to develop new ferroelectrics based on metal-organic frameworks with dipolar rotors. Ferroelectrics are targeted to be used as physically flexible memories and mechanical energy harvesters for biocompatible sensors and implantable monitoring devices.
As ferroelectrics can store and switch their polarity, they can be used as memories. Via the piezoelectric effect, they can harvest mechanical vibrations. The materials most compatible with flexible substrates, are soft matter materials. However, these so far don’t meet the requirements. Especially lacking is a combination of i) polarisation stability, ii) a sufficiently low energy barrier for polarisation switching and iii) fast switching. As energy harvesters, soft matter materials are hampered by low piezoelectric coefficients.
The main objective of this proposal is rational design of ferroelectrics by obtaining a fundamental understanding of the relation between structure and properties. I will achieve this by uniquely synthesizing polar rotors into 3D crystalline scaffolds that allow to alter the rotors’ nano-environement. I will achieve this via polar ligands in metal-organic frameworks (MOFs). The variability of MOFs allows to tune the nature of the hindrance towards rotation of the polar rotors. The tuneable flexibility allows to regulate the energy harvesting efficiency. Moreover, MOFs have already shown potential as biocompatible materials that can be integrated on physically flexible substrates.
The research consists of i) synthesis of polar rotor MOFs with targeted variations, ii) reliable characterisation and computational modelling of the electronic properties, iii) nanoscopic insight in the switching dynamics. The approach allows to understand how ferro- and piezoelectricity are related to the materials’ structure, and hence to develop materials with exceptional performance. My recent observation of the ferroelectric behaviour of a nitrofunctionalised MOF is the basis for this proposal.
Summary
I seek to develop new ferroelectrics based on metal-organic frameworks with dipolar rotors. Ferroelectrics are targeted to be used as physically flexible memories and mechanical energy harvesters for biocompatible sensors and implantable monitoring devices.
As ferroelectrics can store and switch their polarity, they can be used as memories. Via the piezoelectric effect, they can harvest mechanical vibrations. The materials most compatible with flexible substrates, are soft matter materials. However, these so far don’t meet the requirements. Especially lacking is a combination of i) polarisation stability, ii) a sufficiently low energy barrier for polarisation switching and iii) fast switching. As energy harvesters, soft matter materials are hampered by low piezoelectric coefficients.
The main objective of this proposal is rational design of ferroelectrics by obtaining a fundamental understanding of the relation between structure and properties. I will achieve this by uniquely synthesizing polar rotors into 3D crystalline scaffolds that allow to alter the rotors’ nano-environement. I will achieve this via polar ligands in metal-organic frameworks (MOFs). The variability of MOFs allows to tune the nature of the hindrance towards rotation of the polar rotors. The tuneable flexibility allows to regulate the energy harvesting efficiency. Moreover, MOFs have already shown potential as biocompatible materials that can be integrated on physically flexible substrates.
The research consists of i) synthesis of polar rotor MOFs with targeted variations, ii) reliable characterisation and computational modelling of the electronic properties, iii) nanoscopic insight in the switching dynamics. The approach allows to understand how ferro- and piezoelectricity are related to the materials’ structure, and hence to develop materials with exceptional performance. My recent observation of the ferroelectric behaviour of a nitrofunctionalised MOF is the basis for this proposal.
Max ERC Funding
1 500 000 €
Duration
Start date: 2018-01-01, End date: 2022-12-31
Project acronym MUSE
Project Multi-perspective Ultrasound Strain Imaging & Elastography
Researcher (PI) Richard LOPATA
Host Institution (HI) TECHNISCHE UNIVERSITEIT EINDHOVEN
Call Details Starting Grant (StG), PE7, ERC-2017-STG
Summary Ultrasound (US) is the modality of choice for imaging and functional measurements of the cardiovascular system due to its high spatial and temporal resolution. In recent years, the use of US has been on the rise owing to huge advancements in acquisition speed and resolution. Nevertheless, because of physical constraints, several issues —limited field-of-view, refraction, resolution and, contrast anisotropy— cannot be resolved using a single probe.
This proposal will aim at tackling these issues introducing Multi-perspective Ultrasound Strain Imaging & Elastography (MUSE). MUSE will push the frontiers of 3-D US imaging by introducing a novel, multi-perspective 3-D US system. The revolutionary system will consist of two synchronously controlled 3-D matrix arrays and advanced signal and image processing to improve geometric and functional measurements (strain, elasticity). Validation will be performed for two applications: cardiac strain imaging in patients with aortic valve stenosis (AoS) and elastography of abdominal aortic aneurysms (AAA).
Fusion of dual-probe data will be challenged and achieved by new algorithms, preserving important features and improving both contrast and field-of-view. Advanced 3-D processing of the raw US data will be developed for motion and strain imaging. A novel compounding technique, fusion strain imaging, will combine multi-perspective strain data to improve accuracy and precision. A comprehensive framework for system verification and validation will be built, comprising US simulations, ex vivo experiments, and in vivo pilot studies on healthy volunteers. The proposed technique will be validated in AoS and AAA patients.
Ultimately, MUSE will introduce a non-invasive, ground-breaking US platform for functional screening and follow-up, and a breakthrough in early diagnosis, clinical decision making, and risk assessment of cardiovascular disease. Moreover, MUSE has the potential to replace invasive or costly imaging modalities with US.
Summary
Ultrasound (US) is the modality of choice for imaging and functional measurements of the cardiovascular system due to its high spatial and temporal resolution. In recent years, the use of US has been on the rise owing to huge advancements in acquisition speed and resolution. Nevertheless, because of physical constraints, several issues —limited field-of-view, refraction, resolution and, contrast anisotropy— cannot be resolved using a single probe.
This proposal will aim at tackling these issues introducing Multi-perspective Ultrasound Strain Imaging & Elastography (MUSE). MUSE will push the frontiers of 3-D US imaging by introducing a novel, multi-perspective 3-D US system. The revolutionary system will consist of two synchronously controlled 3-D matrix arrays and advanced signal and image processing to improve geometric and functional measurements (strain, elasticity). Validation will be performed for two applications: cardiac strain imaging in patients with aortic valve stenosis (AoS) and elastography of abdominal aortic aneurysms (AAA).
Fusion of dual-probe data will be challenged and achieved by new algorithms, preserving important features and improving both contrast and field-of-view. Advanced 3-D processing of the raw US data will be developed for motion and strain imaging. A novel compounding technique, fusion strain imaging, will combine multi-perspective strain data to improve accuracy and precision. A comprehensive framework for system verification and validation will be built, comprising US simulations, ex vivo experiments, and in vivo pilot studies on healthy volunteers. The proposed technique will be validated in AoS and AAA patients.
Ultimately, MUSE will introduce a non-invasive, ground-breaking US platform for functional screening and follow-up, and a breakthrough in early diagnosis, clinical decision making, and risk assessment of cardiovascular disease. Moreover, MUSE has the potential to replace invasive or costly imaging modalities with US.
Max ERC Funding
1 998 505 €
Duration
Start date: 2018-02-01, End date: 2023-01-31
Project acronym NANOSTORM
Project Design of Nanomaterials for Targeted Therapies Guided by Super Resolution Imaging
Researcher (PI) Lorenzo ALBERTAZZI
Host Institution (HI) TECHNISCHE UNIVERSITEIT EINDHOVEN
Call Details Starting Grant (StG), PE5, ERC-2017-STG
Summary Nanomaterials revolutionized the field of targeted cancer therapies introducing innovative approaches towards the molecular recognition of diseased cells. However, despite the large investments in nanotechnology-based drug delivery the translation into clinical applications is still unsatisfactory and up to date there are no actively-targeted materials approved for clinical use. One of the main reasons is the lack of knowledge about the behaviour of nanostructures in the biological environment that makes the rational design of effective drug delivery carriers extremely challenging.
NANOSTORM proposes the use of an innovative optical imaging technique such as super resolution microscopy to visualize and understand the molecular interactions of nanomaterials with their cellular targets in unprecedented detail. We recently reported for the first time the ability of Stochastic Optical Reconstruction Microscopy (STORM) to image self-assembled synthetic materials in vitro with nanometric resolution. NANOSTORM aims to bring this to the next level, using STORM to unveil the structure-activity relations of therapeutic nanomaterials in the biological environment at the single molecule level. The knowledge arising from this investigation will provide novel design principles for the next generation of nanomaterials for targeted therapies. In particular, in the framework of NANOSTORM novel nanomaterials for the targeted treatment of prostate cancer will be synthesized and evaluated.
This interdisciplinary research program will advance our understanding of nanostructures for targeted drug delivery and guide the formulation of novel materials for cancer therapy.
Summary
Nanomaterials revolutionized the field of targeted cancer therapies introducing innovative approaches towards the molecular recognition of diseased cells. However, despite the large investments in nanotechnology-based drug delivery the translation into clinical applications is still unsatisfactory and up to date there are no actively-targeted materials approved for clinical use. One of the main reasons is the lack of knowledge about the behaviour of nanostructures in the biological environment that makes the rational design of effective drug delivery carriers extremely challenging.
NANOSTORM proposes the use of an innovative optical imaging technique such as super resolution microscopy to visualize and understand the molecular interactions of nanomaterials with their cellular targets in unprecedented detail. We recently reported for the first time the ability of Stochastic Optical Reconstruction Microscopy (STORM) to image self-assembled synthetic materials in vitro with nanometric resolution. NANOSTORM aims to bring this to the next level, using STORM to unveil the structure-activity relations of therapeutic nanomaterials in the biological environment at the single molecule level. The knowledge arising from this investigation will provide novel design principles for the next generation of nanomaterials for targeted therapies. In particular, in the framework of NANOSTORM novel nanomaterials for the targeted treatment of prostate cancer will be synthesized and evaluated.
This interdisciplinary research program will advance our understanding of nanostructures for targeted drug delivery and guide the formulation of novel materials for cancer therapy.
Max ERC Funding
1 497 588 €
Duration
Start date: 2018-02-01, End date: 2023-01-31
Project acronym RECONFMATTER
Project From colloidal joints to reconfigurable matter
Researcher (PI) Daniela Jutta KRAFT
Host Institution (HI) UNIVERSITEIT LEIDEN
Call Details Starting Grant (StG), PE3, ERC-2017-STG
Summary Self-assembly of colloidal particles has emerged as the most promising strategy to obtain fundamental insights into otherwise prohibitively complex systems as well as to create new functional materials from the bottom up. However, most self-assembled colloidal structures are static and thus limited in their functionality.
Building on our recent discovery of colloidal joints, which enable a hinging-like motion between linked particles, I propose to unravel how such flexible bonds can be leveraged to obtain reconfigurable materials with unprecedented properties. I will investigate the impact of bond flexibility on the self-assembly, (multi-) stable configurations and phase behaviour of reconfigurable colloidal structures, and use these insights to create next generation materials that adapt their shape and thus functionality to external cues.
To reach these goals, the project will consist of three work packages:
1) I will elucidate how bond flexibility can be exploited to create and understand reconfigurable structures.
2) I will unravel the phase behaviour and hierarchical assembly of flexible colloidal molecules.
3) I will introduce active and actuatable elements to control switching between different configurations and create shape-changing and self-propelled structures.
Taking the concept of reconfigurability to the colloidal length scale will not only allow us to investigate the principles and consequences of structural flexibility on thermally excited objects, but also to develop the next generation of smart materials: materials with an adaptable shape and thus properties. These reconfigurable and actuatable structures have great potential for materials science and in biomedicine as they may feature switchable optical and acoustic properties, and ultimately could be employed in sensors, actuators, advanced coatings, and more complex functional devices such as micro-robots.
Summary
Self-assembly of colloidal particles has emerged as the most promising strategy to obtain fundamental insights into otherwise prohibitively complex systems as well as to create new functional materials from the bottom up. However, most self-assembled colloidal structures are static and thus limited in their functionality.
Building on our recent discovery of colloidal joints, which enable a hinging-like motion between linked particles, I propose to unravel how such flexible bonds can be leveraged to obtain reconfigurable materials with unprecedented properties. I will investigate the impact of bond flexibility on the self-assembly, (multi-) stable configurations and phase behaviour of reconfigurable colloidal structures, and use these insights to create next generation materials that adapt their shape and thus functionality to external cues.
To reach these goals, the project will consist of three work packages:
1) I will elucidate how bond flexibility can be exploited to create and understand reconfigurable structures.
2) I will unravel the phase behaviour and hierarchical assembly of flexible colloidal molecules.
3) I will introduce active and actuatable elements to control switching between different configurations and create shape-changing and self-propelled structures.
Taking the concept of reconfigurability to the colloidal length scale will not only allow us to investigate the principles and consequences of structural flexibility on thermally excited objects, but also to develop the next generation of smart materials: materials with an adaptable shape and thus properties. These reconfigurable and actuatable structures have great potential for materials science and in biomedicine as they may feature switchable optical and acoustic properties, and ultimately could be employed in sensors, actuators, advanced coatings, and more complex functional devices such as micro-robots.
Max ERC Funding
1 499 956 €
Duration
Start date: 2017-10-01, End date: 2022-09-30
Project acronym REM
Project Resonant Electromagnetic Microscopy: Imaging Cells Electronically
Researcher (PI) Mehmet Selim HANAY
Host Institution (HI) BILKENT UNIVERSITESI VAKIF
Call Details Starting Grant (StG), PE7, ERC-2017-STG
Summary Microfluidics technology has been quite successful in fabricating small, low-cost devices with excellent analyte handling capabilities. However, the main detection paradigm in microfluidics has still been optical microscopy — which is a bulky and expensive technique. A chip-scale detection scheme that can provide multidimensional information is much needed for the widespread adoption of lab-on-a-chip technology. So far, successful capacitive and resonant electrical sensors have been deployed in the field; yet the focus of these sensors has been to obtain the electrical volume or location of a particle — which constitutes only a limited piece of information about the analytes. Here we propose to redesign and utilize resonant electrical sensors in a radically different way to obtain images of cells in a microfluidic channel. The technique proposed can also multiplex on-chip cytometry greatly, accomplish low-cost and high-throughput single-cell transit-time characterization, obtain not only the electrical but also the geometrical size of analytes, determine the dielectric permittivity of analytes, in addition to capturing 1D profile or 2D images of cells. At the basic science level, the project will enhance our understanding of the interaction of electromagnetic fields and living matter at the single cell level and may provide new insights on cell motility, growth and mechanics.
Summary
Microfluidics technology has been quite successful in fabricating small, low-cost devices with excellent analyte handling capabilities. However, the main detection paradigm in microfluidics has still been optical microscopy — which is a bulky and expensive technique. A chip-scale detection scheme that can provide multidimensional information is much needed for the widespread adoption of lab-on-a-chip technology. So far, successful capacitive and resonant electrical sensors have been deployed in the field; yet the focus of these sensors has been to obtain the electrical volume or location of a particle — which constitutes only a limited piece of information about the analytes. Here we propose to redesign and utilize resonant electrical sensors in a radically different way to obtain images of cells in a microfluidic channel. The technique proposed can also multiplex on-chip cytometry greatly, accomplish low-cost and high-throughput single-cell transit-time characterization, obtain not only the electrical but also the geometrical size of analytes, determine the dielectric permittivity of analytes, in addition to capturing 1D profile or 2D images of cells. At the basic science level, the project will enhance our understanding of the interaction of electromagnetic fields and living matter at the single cell level and may provide new insights on cell motility, growth and mechanics.
Max ERC Funding
1 500 000 €
Duration
Start date: 2018-02-01, End date: 2023-01-31
