Project acronym 3D-FABRIC
Project 3D Flow Analysis in Bijels Reconfigured for Interfacial Catalysis
Researcher (PI) Martin F. HAASE
Host Institution (HI) UNIVERSITEIT UTRECHT
Call Details Starting Grant (StG), PE8, ERC-2018-STG
Summary The objective of this proposal is to determine the unknown criteria for convective cross-flow in bicontinuous interfacially jammed emulsion gels (bijels). Based on this, we will answer the question: Can continuously operated interfacial catalysis be realized in bijel cross-flow reactors? Demonstrating this potential will introduce a broadly applicable chemical technology, replacing wasteful chemical processes that require organic solvents. We will achieve our objective in three steps:
(a) Control over bijel structure and properties. Bijels will be formed with a selection of functional inorganic colloidal particles. Nanoparticle surface modifications will be developed and extensively characterized. General principles for the parameters determining bijel structures and properties will be established based on confocal and electron microscopy characterization. These principles will enable unprecedented control over bijel formation and will allow for designing desired properties.
(b) Convective flow in bijels. The mechanical strength of bijels will be tailored and measured. With mechanically robust bijels, the influence of size and organization of oil/water channels on convective mass transfer in bijels will be investigated. To this end, a bijel mass transfer apparatus fabricated by 3d-printing of bijel fibers and soft photolithography will be introduced. In conjunction with the following objective, the analysis of convective flows in bijels will facilitate a thorough description of their structure/function relationships.
(c) Biphasic chemical reactions in STrIPS bijel cross-flow reactors. First, continuous extraction in bijels will be realized. Next, conditions to carry out continuously-operated, phase transfer catalysis of well-known model reactions in bijels will be determined. Both processes will be characterized in-situ and in 3-dimensions by confocal microscopy of fluorescent phase transfer reactions in transparent bijels.
Summary
The objective of this proposal is to determine the unknown criteria for convective cross-flow in bicontinuous interfacially jammed emulsion gels (bijels). Based on this, we will answer the question: Can continuously operated interfacial catalysis be realized in bijel cross-flow reactors? Demonstrating this potential will introduce a broadly applicable chemical technology, replacing wasteful chemical processes that require organic solvents. We will achieve our objective in three steps:
(a) Control over bijel structure and properties. Bijels will be formed with a selection of functional inorganic colloidal particles. Nanoparticle surface modifications will be developed and extensively characterized. General principles for the parameters determining bijel structures and properties will be established based on confocal and electron microscopy characterization. These principles will enable unprecedented control over bijel formation and will allow for designing desired properties.
(b) Convective flow in bijels. The mechanical strength of bijels will be tailored and measured. With mechanically robust bijels, the influence of size and organization of oil/water channels on convective mass transfer in bijels will be investigated. To this end, a bijel mass transfer apparatus fabricated by 3d-printing of bijel fibers and soft photolithography will be introduced. In conjunction with the following objective, the analysis of convective flows in bijels will facilitate a thorough description of their structure/function relationships.
(c) Biphasic chemical reactions in STrIPS bijel cross-flow reactors. First, continuous extraction in bijels will be realized. Next, conditions to carry out continuously-operated, phase transfer catalysis of well-known model reactions in bijels will be determined. Both processes will be characterized in-situ and in 3-dimensions by confocal microscopy of fluorescent phase transfer reactions in transparent bijels.
Max ERC Funding
1 905 000 €
Duration
Start date: 2019-06-01, End date: 2024-05-31
Project acronym ADIPODIF
Project Adipocyte Differentiation and Metabolic Functions in Obesity and Type 2 Diabetes
Researcher (PI) Christian Wolfrum
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Starting Grant (StG), LS6, ERC-2007-StG
Summary Obesity associated disorders such as T2D, hypertension and CVD, commonly referred to as the “metabolic syndrome”, are prevalent diseases of industrialized societies. Deranged adipose tissue proliferation and differentiation contribute significantly to the development of these metabolic disorders. Comparatively little however is known, about how these processes influence the development of metabolic disorders. Using a multidisciplinary approach, I plan to elucidate molecular mechanisms underlying the altered adipocyte differentiation and maturation in different models of obesity associated metabolic disorders. Special emphasis will be given to the analysis of gene expression, postranslational modifications and lipid molecular species composition. To achieve this goal, I am establishing several novel methods to isolate pure primary preadipocytes including a new animal model that will allow me to monitor preadipocytes, in vivo and track their cellular fate in the context of a complete organism. These systems will allow, for the first time to study preadipocyte biology, in an in vivo setting. By monitoring preadipocyte differentiation in vivo, I will also be able to answer the key questions regarding the development of preadipocytes and examine signals that induce or inhibit their differentiation. Using transplantation techniques, I will elucidate the genetic and environmental contributions to the progression of obesity and its associated metabolic disorders. Furthermore, these studies will integrate a lipidomics approach to systematically analyze lipid molecular species composition in different models of metabolic disorders. My studies will provide new insights into the mechanisms and dynamics underlying adipocyte differentiation and maturation, and relate them to metabolic disorders. Detailed knowledge of these mechanisms will facilitate development of novel therapeutic approaches for the treatment of obesity and associated metabolic disorders.
Summary
Obesity associated disorders such as T2D, hypertension and CVD, commonly referred to as the “metabolic syndrome”, are prevalent diseases of industrialized societies. Deranged adipose tissue proliferation and differentiation contribute significantly to the development of these metabolic disorders. Comparatively little however is known, about how these processes influence the development of metabolic disorders. Using a multidisciplinary approach, I plan to elucidate molecular mechanisms underlying the altered adipocyte differentiation and maturation in different models of obesity associated metabolic disorders. Special emphasis will be given to the analysis of gene expression, postranslational modifications and lipid molecular species composition. To achieve this goal, I am establishing several novel methods to isolate pure primary preadipocytes including a new animal model that will allow me to monitor preadipocytes, in vivo and track their cellular fate in the context of a complete organism. These systems will allow, for the first time to study preadipocyte biology, in an in vivo setting. By monitoring preadipocyte differentiation in vivo, I will also be able to answer the key questions regarding the development of preadipocytes and examine signals that induce or inhibit their differentiation. Using transplantation techniques, I will elucidate the genetic and environmental contributions to the progression of obesity and its associated metabolic disorders. Furthermore, these studies will integrate a lipidomics approach to systematically analyze lipid molecular species composition in different models of metabolic disorders. My studies will provide new insights into the mechanisms and dynamics underlying adipocyte differentiation and maturation, and relate them to metabolic disorders. Detailed knowledge of these mechanisms will facilitate development of novel therapeutic approaches for the treatment of obesity and associated metabolic disorders.
Max ERC Funding
1 607 105 €
Duration
Start date: 2008-07-01, End date: 2013-06-30
Project acronym AGGLONANOCOAT
Project The interplay between agglomeration and coating of nanoparticles in the gas phase
Researcher (PI) Jan Rudolf Van Ommen
Host Institution (HI) TECHNISCHE UNIVERSITEIT DELFT
Call Details Starting Grant (StG), PE8, ERC-2011-StG_20101014
Summary This proposal aims to develop a generic synthesis approach for core-shell nanoparticles by unravelling the relevant mechanisms. Core-shell nanoparticles have high potential in heterogeneous catalysis, energy storage, and medical applications. However, on a fundamental level there is currently a poor understanding of how to produce such nanostructured particles in a controllable and scalable manner.
The main barriers to achieving this goal are understanding how nanoparticles agglomerate to loose dynamic clusters and controlling the agglomeration process in gas flows during coating, such that uniform coatings can be made. This is very challenging because of the two-way coupling between agglomeration and coating. During the coating we change the particle surfaces and thus the way the particles stick together. Correspondingly, the stickiness of particles determines how easy reactants can reach the surface.
Innovatively the project will be the first systematic study into this multi-scale phenomenon with investigations at all relevant length scales. Current synthesis approaches – mostly carried out in the liquid phase – are typically developed case by case. I will coat nanoparticles in the gas phase with atomic layer deposition (ALD): a technique from the semi-conductor industry that can deposit a wide range of materials. ALD applied to flat substrates offers excellent control over layer thickness. I will investigate the modification of single particle surfaces, particle-particle interaction, the structure of agglomerates, and the flow behaviour of large number of agglomerates. To this end, I will apply a multidisciplinary approach, combining disciplines as physical chemistry, fluid dynamics, and reaction engineering.
Summary
This proposal aims to develop a generic synthesis approach for core-shell nanoparticles by unravelling the relevant mechanisms. Core-shell nanoparticles have high potential in heterogeneous catalysis, energy storage, and medical applications. However, on a fundamental level there is currently a poor understanding of how to produce such nanostructured particles in a controllable and scalable manner.
The main barriers to achieving this goal are understanding how nanoparticles agglomerate to loose dynamic clusters and controlling the agglomeration process in gas flows during coating, such that uniform coatings can be made. This is very challenging because of the two-way coupling between agglomeration and coating. During the coating we change the particle surfaces and thus the way the particles stick together. Correspondingly, the stickiness of particles determines how easy reactants can reach the surface.
Innovatively the project will be the first systematic study into this multi-scale phenomenon with investigations at all relevant length scales. Current synthesis approaches – mostly carried out in the liquid phase – are typically developed case by case. I will coat nanoparticles in the gas phase with atomic layer deposition (ALD): a technique from the semi-conductor industry that can deposit a wide range of materials. ALD applied to flat substrates offers excellent control over layer thickness. I will investigate the modification of single particle surfaces, particle-particle interaction, the structure of agglomerates, and the flow behaviour of large number of agglomerates. To this end, I will apply a multidisciplinary approach, combining disciplines as physical chemistry, fluid dynamics, and reaction engineering.
Max ERC Funding
1 409 952 €
Duration
Start date: 2011-12-01, End date: 2016-11-30
Project acronym ALGILE
Project Foundations of Algebraic and Dynamic Data Management Systems
Researcher (PI) Christoph Koch
Host Institution (HI) ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE
Call Details Starting Grant (StG), PE6, ERC-2011-StG_20101014
Summary "Contemporary database query languages are ultimately founded on logic and feature an additive operation – usually a form of (multi)set union or disjunction – that is asymmetric in that additions or updates do not always have an inverse. This asymmetry puts a greater part of the machinery of abstract algebra for equation solving outside the reach of databases. However, such equation solving would be a key functionality that problems such as query equivalence testing and data integration could be reduced to: In the current scenario of the presence of an asymmetric additive operation they are undecidable. Moreover, query languages with a symmetric additive operation (i.e., which has an inverse and is thus based on ring theory) would open up databases for a large range of new scientific and mathematical applications.
The goal of the proposed project is to reinvent database management systems with a foundation in abstract algebra and specifically in ring theory. The presence of an additive inverse allows to cleanly define differences between queries. This gives rise to a database analog of differential calculus that leads to radically new incremental and adaptive query evaluation algorithms that substantially outperform the state of the art techniques. These algorithms enable a new class of systems which I call Dynamic Data Management Systems. Such systems can maintain continuously fresh query views at extremely high update rates and have important applications in interactive Large-scale Data Analysis. There is a natural connection between differences and updates, motivating the group theoretic study of updates that will lead to better ways of creating out-of-core data processing algorithms for new storage devices. Basing queries on ring theory leads to a new class of systems, Algebraic Data Management Systems, which herald a convergence of database systems and computer algebra systems."
Summary
"Contemporary database query languages are ultimately founded on logic and feature an additive operation – usually a form of (multi)set union or disjunction – that is asymmetric in that additions or updates do not always have an inverse. This asymmetry puts a greater part of the machinery of abstract algebra for equation solving outside the reach of databases. However, such equation solving would be a key functionality that problems such as query equivalence testing and data integration could be reduced to: In the current scenario of the presence of an asymmetric additive operation they are undecidable. Moreover, query languages with a symmetric additive operation (i.e., which has an inverse and is thus based on ring theory) would open up databases for a large range of new scientific and mathematical applications.
The goal of the proposed project is to reinvent database management systems with a foundation in abstract algebra and specifically in ring theory. The presence of an additive inverse allows to cleanly define differences between queries. This gives rise to a database analog of differential calculus that leads to radically new incremental and adaptive query evaluation algorithms that substantially outperform the state of the art techniques. These algorithms enable a new class of systems which I call Dynamic Data Management Systems. Such systems can maintain continuously fresh query views at extremely high update rates and have important applications in interactive Large-scale Data Analysis. There is a natural connection between differences and updates, motivating the group theoretic study of updates that will lead to better ways of creating out-of-core data processing algorithms for new storage devices. Basing queries on ring theory leads to a new class of systems, Algebraic Data Management Systems, which herald a convergence of database systems and computer algebra systems."
Max ERC Funding
1 480 548 €
Duration
Start date: 2012-01-01, End date: 2016-12-31
Project acronym BATMAN
Project Development of Quantitative Metrologies to Guide Lithium Ion Battery Manufacturing
Researcher (PI) Vanessa Wood
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Starting Grant (StG), PE8, ERC-2015-STG
Summary Lithium ion batteries offer tremendous potential as an enabling technology for sustainable transportation and development. However, their widespread usage as the energy storage solution for electric mobility and grid-level integration of renewables is impeded by the fact that current state-of-the-art lithium ion batteries have energy densities that are too small, charge- and discharge rates that are too low, and costs that are too high. Highly publicized instances of catastrophic failure of lithium ion batteries raise questions of safety. Understanding the limitations to battery performance and origins of the degradation and failure is highly complex due to the difficulties in studying interrelated processes that take place at different length and time scales in a corrosive environment. In the project, we will (1) develop and implement quantitative methods to study the complex interrelations between structure and electrochemistry occurring at the nano-, micron-, and milli-scales in lithium ion battery active materials and electrodes, (2) conduct systematic experimental studies with our new techniques to understand the origins of performance limitations and to develop design guidelines for achieving high performance and safe batteries, and (3) investigate economically viable engineering solutions based on these guidelines to achieve high performance and safe lithium ion batteries.
Summary
Lithium ion batteries offer tremendous potential as an enabling technology for sustainable transportation and development. However, their widespread usage as the energy storage solution for electric mobility and grid-level integration of renewables is impeded by the fact that current state-of-the-art lithium ion batteries have energy densities that are too small, charge- and discharge rates that are too low, and costs that are too high. Highly publicized instances of catastrophic failure of lithium ion batteries raise questions of safety. Understanding the limitations to battery performance and origins of the degradation and failure is highly complex due to the difficulties in studying interrelated processes that take place at different length and time scales in a corrosive environment. In the project, we will (1) develop and implement quantitative methods to study the complex interrelations between structure and electrochemistry occurring at the nano-, micron-, and milli-scales in lithium ion battery active materials and electrodes, (2) conduct systematic experimental studies with our new techniques to understand the origins of performance limitations and to develop design guidelines for achieving high performance and safe batteries, and (3) investigate economically viable engineering solutions based on these guidelines to achieve high performance and safe lithium ion batteries.
Max ERC Funding
1 500 000 €
Duration
Start date: 2016-05-01, End date: 2021-04-30
Project acronym BIGCODE
Project Learning from Big Code: Probabilistic Models, Analysis and Synthesis
Researcher (PI) Martin Vechev
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Starting Grant (StG), PE6, ERC-2015-STG
Summary The goal of this proposal is to fundamentally change the way we build and reason about software. We aim to develop new kinds of statistical programming systems that provide probabilistically likely solutions to tasks that are difficult or impossible to solve with traditional approaches.
These statistical programming systems will be based on probabilistic models of massive codebases (also known as ``Big Code'') built via a combination of advanced programming languages and powerful machine learning and natural language processing techniques. To solve a particular challenge, a statistical programming system will query a probabilistic model, compute the most likely predictions, and present those to the developer.
Based on probabilistic models of ``Big Code'', we propose to investigate new statistical techniques in the context of three fundamental research directions: i) statistical program synthesis where we develop techniques that automatically synthesize and predict new programs, ii) statistical prediction of program properties where we develop new techniques that can predict important facts (e.g., types) about programs, and iii) statistical translation of programs where we investigate new techniques for statistical translation of programs (e.g., from one programming language to another, or to a natural language).
We believe the research direction outlined in this interdisciplinary proposal opens a new and exciting area of computer science. This area will combine sophisticated statistical learning and advanced programming language techniques for building the next-generation statistical programming systems.
We expect the results of this proposal to have an immediate impact upon millions of developers worldwide, triggering a paradigm shift in the way tomorrow's software is built, as well as a long-lasting impact on scientific fields such as machine learning, natural language processing, programming languages and software engineering.
Summary
The goal of this proposal is to fundamentally change the way we build and reason about software. We aim to develop new kinds of statistical programming systems that provide probabilistically likely solutions to tasks that are difficult or impossible to solve with traditional approaches.
These statistical programming systems will be based on probabilistic models of massive codebases (also known as ``Big Code'') built via a combination of advanced programming languages and powerful machine learning and natural language processing techniques. To solve a particular challenge, a statistical programming system will query a probabilistic model, compute the most likely predictions, and present those to the developer.
Based on probabilistic models of ``Big Code'', we propose to investigate new statistical techniques in the context of three fundamental research directions: i) statistical program synthesis where we develop techniques that automatically synthesize and predict new programs, ii) statistical prediction of program properties where we develop new techniques that can predict important facts (e.g., types) about programs, and iii) statistical translation of programs where we investigate new techniques for statistical translation of programs (e.g., from one programming language to another, or to a natural language).
We believe the research direction outlined in this interdisciplinary proposal opens a new and exciting area of computer science. This area will combine sophisticated statistical learning and advanced programming language techniques for building the next-generation statistical programming systems.
We expect the results of this proposal to have an immediate impact upon millions of developers worldwide, triggering a paradigm shift in the way tomorrow's software is built, as well as a long-lasting impact on scientific fields such as machine learning, natural language processing, programming languages and software engineering.
Max ERC Funding
1 500 000 €
Duration
Start date: 2016-04-01, End date: 2021-03-31
Project acronym BINDING FIBRES
Project Soluble dietary fibre: unraveling how weak bonds have a strong impact on function
Researcher (PI) Laura Nyström
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Call Details Starting Grant (StG), LS9, ERC-2015-STG
Summary Dietary fibres are recognized for their health promoting properties; nevertheless, many of the physicochemical mechanisms behind these effects remain poorly understood. While it is understood that dietary fibres can associate with small molecules influencing, both positively or negatively their absorption, the molecular mechanism, by which these associations take place, have yet to be elucidated We propose a study of the binding in soluble dietary fibres at a molecular level to establish binding constants for various fibres and nutritionally relevant ligands. The interactions between fibres and target compounds may be quite weak, but still have a major impact on the bioavailability. To gain insight to the binding mechanisms at a level of detail that has not earlier been achieved, we will apply novel combinations of analytical techniques (MS, NMR, EPR) and both natural as well as synthetic probes to elucidate the associations in these complexes from macromolecular to atomic level. Glucans, xyloglucans and galactomannans will serve as model soluble fibres, representative of real food systems, allowing us to determine their binding constants with nutritionally relevant micronutrients, such as monosaccharides, bile acids, and metals. Furthermore, we will examine supramolecular interactions between fibre strands to evaluate possible contribution of several fibre strands to the micronutrient associations. At the atomic level, we will use complementary spectroscopies to identify the functional groups and atoms involved in the bonds between fibres and the ligands. The proposal describes a unique approach to quantify binding of small molecules by dietary fibres, which can be translated to polysaccharide interactions with ligands in a broad range of biological systems and disciplines. The findings from this study may further allow us to predictably utilize fibres in functional foods, which can have far-reaching consequences in human nutrition, and thereby also public health.
Summary
Dietary fibres are recognized for their health promoting properties; nevertheless, many of the physicochemical mechanisms behind these effects remain poorly understood. While it is understood that dietary fibres can associate with small molecules influencing, both positively or negatively their absorption, the molecular mechanism, by which these associations take place, have yet to be elucidated We propose a study of the binding in soluble dietary fibres at a molecular level to establish binding constants for various fibres and nutritionally relevant ligands. The interactions between fibres and target compounds may be quite weak, but still have a major impact on the bioavailability. To gain insight to the binding mechanisms at a level of detail that has not earlier been achieved, we will apply novel combinations of analytical techniques (MS, NMR, EPR) and both natural as well as synthetic probes to elucidate the associations in these complexes from macromolecular to atomic level. Glucans, xyloglucans and galactomannans will serve as model soluble fibres, representative of real food systems, allowing us to determine their binding constants with nutritionally relevant micronutrients, such as monosaccharides, bile acids, and metals. Furthermore, we will examine supramolecular interactions between fibre strands to evaluate possible contribution of several fibre strands to the micronutrient associations. At the atomic level, we will use complementary spectroscopies to identify the functional groups and atoms involved in the bonds between fibres and the ligands. The proposal describes a unique approach to quantify binding of small molecules by dietary fibres, which can be translated to polysaccharide interactions with ligands in a broad range of biological systems and disciplines. The findings from this study may further allow us to predictably utilize fibres in functional foods, which can have far-reaching consequences in human nutrition, and thereby also public health.
Max ERC Funding
1 500 000 €
Duration
Start date: 2016-04-01, End date: 2021-03-31
Project acronym BIO-ORIGAMI
Project Meta-biomaterials: 3D printing meets Origami
Researcher (PI) Amir Abbas Zadpoor
Host Institution (HI) TECHNISCHE UNIVERSITEIT DELFT
Call Details Starting Grant (StG), PE8, ERC-2015-STG
Summary Meta-materials, best known for their extraordinary properties (e.g. negative stiffness), are halfway from both materials and structures: their unusual properties are direct results of their complex 3D structures. This project introduces a new class of meta-materials called meta-biomaterials. Meta-biomaterials go beyond meta-materials by adding an extra dimension to the complex 3D structure, i.e. complex and precisely controlled surface nano-patterns. The 3D structure gives rise to unprecedented or rare combination of mechanical (e.g. stiffness), mass transport (e.g. permeability, diffusivity), and biological (e.g. tissue regeneration rate) properties. Those properties optimize the distribution of mechanical loads and the transport of nutrients and oxygen while providing geometrical shapes preferable for tissue regeneration (e.g. higher curvatures). Surface nano-patterns communicate with (stem) cells, control their differentiation behavior, and enhance tissue regeneration.
There is one important problem: meta-biomaterials cannot be manufactured with current technology. 3D printing can create complex shapes while nanolithography creates complex surface nano-patterns down to a few nanometers but only on flat surfaces. There is, however, no way of combining complex shapes with complex surface nano-patterns. The groundbreaking nature of this project is in solving that deadlock using the Origami concept (the ancient Japanese art of paper folding). In this approach, I first decorate flat 3D-printed sheets with nano-patterns. Then, I apply Origami techniques to fold the decorated flat sheet and create complex 3D shapes. The sheet knows how to self-fold to the desired structure when subjected to compression, owing to pre-designed joints, crease patterns, and thickness/material distributions that control its mechanical instability. I will demonstrate the added value of meta-biomaterials in improving bone tissue regeneration using in vitro cell culture assays and animal models
Summary
Meta-materials, best known for their extraordinary properties (e.g. negative stiffness), are halfway from both materials and structures: their unusual properties are direct results of their complex 3D structures. This project introduces a new class of meta-materials called meta-biomaterials. Meta-biomaterials go beyond meta-materials by adding an extra dimension to the complex 3D structure, i.e. complex and precisely controlled surface nano-patterns. The 3D structure gives rise to unprecedented or rare combination of mechanical (e.g. stiffness), mass transport (e.g. permeability, diffusivity), and biological (e.g. tissue regeneration rate) properties. Those properties optimize the distribution of mechanical loads and the transport of nutrients and oxygen while providing geometrical shapes preferable for tissue regeneration (e.g. higher curvatures). Surface nano-patterns communicate with (stem) cells, control their differentiation behavior, and enhance tissue regeneration.
There is one important problem: meta-biomaterials cannot be manufactured with current technology. 3D printing can create complex shapes while nanolithography creates complex surface nano-patterns down to a few nanometers but only on flat surfaces. There is, however, no way of combining complex shapes with complex surface nano-patterns. The groundbreaking nature of this project is in solving that deadlock using the Origami concept (the ancient Japanese art of paper folding). In this approach, I first decorate flat 3D-printed sheets with nano-patterns. Then, I apply Origami techniques to fold the decorated flat sheet and create complex 3D shapes. The sheet knows how to self-fold to the desired structure when subjected to compression, owing to pre-designed joints, crease patterns, and thickness/material distributions that control its mechanical instability. I will demonstrate the added value of meta-biomaterials in improving bone tissue regeneration using in vitro cell culture assays and animal models
Max ERC Funding
1 499 600 €
Duration
Start date: 2016-02-01, End date: 2021-01-31
Project acronym BIOMORPHIC
Project Brain-Inspired Organic Modular Lab-on-a-Chip for Cell Classification
Researcher (PI) Yoeri Bertin VAN DE BURGT
Host Institution (HI) TECHNISCHE UNIVERSITEIT EINDHOVEN
Call Details Starting Grant (StG), PE8, ERC-2018-STG
Summary Brain-inspired (neuromorphic) computing has recently demonstrated advancements in pattern and image recognition as well as classification of unstructured (big) data. However, the volatility and energy required for neuromorphic devices presented to date significantly complicate the path to achieve the interconnectivity and efficiency of the brain. In previous work, recently published in Nature Materials, the PI has demonstrated a low-cost solution to these drawbacks: an organic artificial synapse as a building-block for organic neuromorphics. The conductance of this single synapse can be accurately tuned by controlled ion injection in the conductive polymer, which could trigger unprecedented low-energy analogue computing.
Hence, the major challenge in the largely unexplored field of organic neuromorphics, is to create an interconnected network of these synapses to obtain a true neuromorphic array which will not only be exceptionally pioneering in materials research for neuromorphics and machine-learning, but can also be adopted in a multitude of vital medical research devices. BIOMORPHIC will develop a unique brain-inspired organic lab-on-a-chip in which microfluidics integrated with sensors, collecting characteristics of biological cells, will serve as input to the neuromorphic array. BIOMORPHIC will combine modular microfluidics and machine-learning to develop a novel platform for low-cost lab-on-a-chip devices capable of on-chip cell classification.
In particular, BIOMORPHIC will focus on the detection of circulating tumour cells (CTC). Current methods for the detection of cancer are generally invasive, whereas analysing CTCs in blood offers a highly desired alternative. However, accurately detecting and isolating these cells remains a challenge due to their low prevalence and large variability. The strength of neuromorphics precisely lies in finding patterns in such variable data, which will result in a ground-breaking CTC classification lab-on-a-chip.
Summary
Brain-inspired (neuromorphic) computing has recently demonstrated advancements in pattern and image recognition as well as classification of unstructured (big) data. However, the volatility and energy required for neuromorphic devices presented to date significantly complicate the path to achieve the interconnectivity and efficiency of the brain. In previous work, recently published in Nature Materials, the PI has demonstrated a low-cost solution to these drawbacks: an organic artificial synapse as a building-block for organic neuromorphics. The conductance of this single synapse can be accurately tuned by controlled ion injection in the conductive polymer, which could trigger unprecedented low-energy analogue computing.
Hence, the major challenge in the largely unexplored field of organic neuromorphics, is to create an interconnected network of these synapses to obtain a true neuromorphic array which will not only be exceptionally pioneering in materials research for neuromorphics and machine-learning, but can also be adopted in a multitude of vital medical research devices. BIOMORPHIC will develop a unique brain-inspired organic lab-on-a-chip in which microfluidics integrated with sensors, collecting characteristics of biological cells, will serve as input to the neuromorphic array. BIOMORPHIC will combine modular microfluidics and machine-learning to develop a novel platform for low-cost lab-on-a-chip devices capable of on-chip cell classification.
In particular, BIOMORPHIC will focus on the detection of circulating tumour cells (CTC). Current methods for the detection of cancer are generally invasive, whereas analysing CTCs in blood offers a highly desired alternative. However, accurately detecting and isolating these cells remains a challenge due to their low prevalence and large variability. The strength of neuromorphics precisely lies in finding patterns in such variable data, which will result in a ground-breaking CTC classification lab-on-a-chip.
Max ERC Funding
1 498 726 €
Duration
Start date: 2019-01-01, End date: 2023-12-31
Project acronym BioNanoPattern
Project Protein nano-patterning using DNA nanotechnology; control of surface-based immune system activation
Researcher (PI) Thomas Harry SHARP
Host Institution (HI) ACADEMISCH ZIEKENHUIS LEIDEN
Call Details Starting Grant (StG), LS9, ERC-2017-STG
Summary Protein nanopatterning concerns the geometric arrangement of individual proteins with nanometre accuracy. It is becoming apparent that protein nanopatterns are essential for cellular function, and have roles in cell signalling and protection, phagocytosis and stem cell differentiation. Recent research indicates that our immune system is activated by nanopatterned antibody platforms, which initiate the classical Complement pathway by binding to the first component of Complement, the C1 complex. DNA nanotechnology can be used to form self-assembled nanoscale structures, which are ideal for use as templates to pattern proteins with specific geometries and nanometre accuracy. I propose to use DNA to nanopattern antigens and agonistic aptamers with defined geometry to study and control Complement pathway activation by the C1 complex.
To develop and demonstrate the potential use of DNA to nanopattern proteins, the first aim of this proposal is to design DNA nanotemplates suitable for patterning antibody-binding sites. Antibodies and C1 will bind with specific geometry, and the relationship between antibody geometry and Complement activation will be assessed using novel liposome assays. Using DNA to mimic antigenic surfaces will enable high-resolution structure determination of DNA-antibody-C1 complexes, both in solution and on lipid bilayer surfaces, using phase plate cryo-electron microscopy to elucidate the structure-activation relationship of C1.
The second aim of this proposal is to evolve agonistic aptamers that directly bind to and activate C1, and incorporate these into DNA nanotemplates. These nanopatterned aptamers will enable further study of C1 activation, and allow direct targeting of Complement activation to specific cells within a population of cell types to demonstrate targeted cell killing. This may open up new and highly efficient ways to activate our immune system in vivo, with potential for targeted anti-tumour immunotherapies.
Summary
Protein nanopatterning concerns the geometric arrangement of individual proteins with nanometre accuracy. It is becoming apparent that protein nanopatterns are essential for cellular function, and have roles in cell signalling and protection, phagocytosis and stem cell differentiation. Recent research indicates that our immune system is activated by nanopatterned antibody platforms, which initiate the classical Complement pathway by binding to the first component of Complement, the C1 complex. DNA nanotechnology can be used to form self-assembled nanoscale structures, which are ideal for use as templates to pattern proteins with specific geometries and nanometre accuracy. I propose to use DNA to nanopattern antigens and agonistic aptamers with defined geometry to study and control Complement pathway activation by the C1 complex.
To develop and demonstrate the potential use of DNA to nanopattern proteins, the first aim of this proposal is to design DNA nanotemplates suitable for patterning antibody-binding sites. Antibodies and C1 will bind with specific geometry, and the relationship between antibody geometry and Complement activation will be assessed using novel liposome assays. Using DNA to mimic antigenic surfaces will enable high-resolution structure determination of DNA-antibody-C1 complexes, both in solution and on lipid bilayer surfaces, using phase plate cryo-electron microscopy to elucidate the structure-activation relationship of C1.
The second aim of this proposal is to evolve agonistic aptamers that directly bind to and activate C1, and incorporate these into DNA nanotemplates. These nanopatterned aptamers will enable further study of C1 activation, and allow direct targeting of Complement activation to specific cells within a population of cell types to demonstrate targeted cell killing. This may open up new and highly efficient ways to activate our immune system in vivo, with potential for targeted anti-tumour immunotherapies.
Max ERC Funding
1 499 850 €
Duration
Start date: 2018-01-01, End date: 2022-12-31