Physik (Goedecker)Head of Research Unit Prof. Dr.Stefan GoedeckerOverviewMembersPublicationsProjects & CollaborationsProjects & Collaborations OverviewMembersPublicationsProjects & Collaborations Projects & Collaborations 19 foundShow per page10 10 20 50 Towards Quantifying the Synthesizability of Materials Research Project | 3 Project MembersThe discovery of new materials is an essential ingredient for technological progress. It is generally agreed upon that simulation methods can make important contributions to this field and extensive research activities are under way worldwide. In this context unbiased structure prediction methods have revealed a large number of possible structures for numerous materials. However only a relatively small fraction of these structures can be found in nature or can be synthesized in the laboratory. This observation poses fundamental and technological challenges. One would like to understand whether the unobserved structures can for some hitherto unknown fundamental reason not exist or whether simply the correct synthesis recipe has not yet been found. If they can not exist, synthesis should not be tried for these materials. If they may exist, simulation could give guidance to synthesis efforts. Since a time resolved atomistic simulation of the actual nucleation and growth processes occurring during synthesis is not feasible in connection with a high-accuracy description of the potential energy surface, we will use concepts from thermodynamics to predict the final structure without following the relevant processes in time. In this context, it will be necessary to develop much more efficient methods to calculate free energies. To understand the behavior of the free energy at formation conditions requires developing improved methods to calculate this quantity at high temperatures, where the harmonic approximation breaks down. To obtain the correct energetic ordering at room temperature, it is frequently necessary to include nuclear quantum effects into the free energy calculations. Applying some of the latest mathematical tools, we will develop novel algorithms that are considerably more powerful than the existing ones. Finally we will also search for new quantities that can be obtained from the potential energy surface at affordable numerical cost and that contain relevant information about the synthesizability of a material. All these new methods should then finally allow to directly assess the synthesizability of a material. The new methods will be used for several materials that have potential applications in energy production and storage. Preferentially materials will be used that have already been studied in the group and for which fast machine learning force fields will be available when the project starts. Development of a Neural Network Potential with Accurate Electrostatic Interactions Research Project | 2 Project MembersIn recent years, a new generation of interatomic potentials based on machine learning techniques has been introduced. These potentials, which provide a direct functional relation between the atomic positions and the potential-energy, combine the accuracy of electronic structure methods with the efficiency of simple empirical potentials. Because of the absence of system-specific terms they allow to perform extended simulations of a large variety of systems. Most of these potentials rely on atomic properties like energies and charges depending only on the local chemical environments of the atoms. Such local charges are, however, unable to capture long-range charge transfer. This prevents the accurate description of systems in which distant structural features have global effects on the charge distribution in the system. Examples for such systems are semiconductors including defects, polar surfaces of oxides and metal-organic molecules with different possible metal oxidation states. In order to overcome these intrinsic limitations of current machine learning potentials, we propose to combine high-dimensional neural networks with the charge equilibration neural network technique. The resulting new method will be generally applicable to all types of systems, which we will demonstrate by analyzing the potential-energy surfaces of different model systems covering all types of bonding using the minima hopping method. NCCR MARVEL - Computational Design and Discovery of Novel Materials Research Project | 1 Project Memberssee: http://nccr-marvel.ch/project Structure and dynamics of materials based on advanced electronic structure calculations Research Project | 4 Project MembersIn atomistic simulations the positions of all the involved atoms are individually known. In this way the structure as well as the dynamics of molecular systems can be studied and understood in depth. A prerequisite for such atomistic simulations is the availability of a high quality potential energy surface and methods to explore it efficiently. Potential energy surfaces calculated on the density functional level are usually considered to be state of the art, even though their accuracy is not sufficient in numerous cases. In this project several key aspects of atomistic simulations will be addressed. Based on our recently developed methods to navigate in the configurational space, the efficiency of our structure prediction schemes will be further improved and its applicability enlarged. In addition we will deduce from our exploration of the potential energy surface not only structural but also dynamic properties. Improved density functional methods will be implemented to give higher accuracy potential energy surfaces and consequently improved predictability for atomistic simulations. We will work both on the validation of methods within mainstream density functional schemes as well as on some non-standard approaches inspired by quantum chemistry methods. For some specific systems, machine learning based force fields will be constructed that are not only highly accurate but also orders of magnitude faster to evaluate than potential energy surfaces resulting from density functional calculations. All these developments will allow to find new materials with useful properties faster and to predict their properties with higher reliability. In particular we will apply these methods to study molecular crystals and cluster assembled materials. A highly efficient implementation of direct GPU to GPU communication in a library for direct exchange calculations Research Project | 2 Project MembersA higjhly efficient GPU based excat exhange library will be developped Atolys - Atomic-Scale Analysis of SiC-Oxide Interface for Improved High-Power MOSFETs Research Project | 2 Project MembersIn the Atolys Argovia project, teams of scientists led by Professor Stefan Goedecker from the Department of Physics at the University of Basel are investigating specific components of transistors that are designed for high currents. In the project, researchers from the University of Basel, the Paul Scherrer Institute and ABB in Baden-Dättwil combine theoretical and experimental methods to examine interfaces between silicon carbide and silicon dioxide in semiconductors. The studies, which aim to provide the most precise data about the structure of the semiconductors, will help to further improve devices designed for high currents. ABB researches high-performance semiconductors The global trend for increased use of sustainable energies means that innovative and efficient systems must be developed for generating and distributing power. The ABB Corporate Research Center (CRC) in the Canton of Aargau conducts research in this area and develops power electronics that can also intelligently handle large currents at high voltages. A large part of these efforts is devoted to developing and researching materials for high-performance semiconductors. These are used, for example, to convert direct current into alternating current. This is necessary, among other things, to feed power generated through photovoltaics into the grid or to transport power across large distances. Silicon carbide - the material of the future The semiconductors of the future may not be made from silicon, but from silicon carbide. Its properties allow smaller devices to be built that are easier to cool and have less resistance. In special semiconductor elements (MOSFETs), the boundary layer between silicon carbide and the insulating material silicon dioxide plays an important role. There is empirical evidence that the number of defects can be reduced with nitrogen and other elements. The microscopic mechanisms that lead to this passivation - the formation of a protective layer - are as yet unknown. To investigate these mechanisms and thus to clarify related questions, the scientific team - including Professor Goedecker, Professor Thomas Jung (PSI), and Dr. Jörg Lehmann and Dr. Holger Bartolf (both ABB) - will combine theoretical simulations with experimental studies and analyze the atomic structure of the boundary layers. SINERGIA Impact of composition and nanometer scale DISorder in transparent Conductive Oxides: a new route to design materials with enhanced transport properties (DisCO) Research Project | 1 Project MembersIn the past 10 years we have experienced a revolution in optoelectronic devices, which are becoming more efficient, lighter, in some cases wearable or even fully transparent. This includes ubiquitous flat-panels displays, solar cells, x-ray detectors. This trend demands a rapid development of new Transparent Conductive Oxide (TCOs) materials (which are used as transparent electrode in most optoelectronic devices) with not only the basic requirements of transparency and conductivity, but also properties like homogeneity (e.g to avoid grain boundaries when used in transistors) and mechanical robustness or flexibility when used in bendable devices. The extensive application of TCOs also requires the use of earth-abundant materials for their production, and therefore the replacement of, for example the rather rare metal indium (In). With the ultimate goal of designing and discovering new TCO materials, this collaborative project aims at bridging the gap between material processing, material simulation and material characterization, to understand the factors affecting the charge transport in disordered or "amorphous" TCOs. This will make possible the design and synthesize of new earth-abundant TCO materials with superior electrical, optical and mechanical properties. Disordered TCO materials are of great interest because of their ease of fabrication, and because of the variety of composition and atomic structure achieved ranging from quasi-polycrystalline to fully amorphous. However, disordered TCO materials are complex systems and, their electronic properties cannot be fully understood from sole experimental methods or material simulations, slowing down the development of new materials. To address this problem, we combine three strongly complementary fields in material science research, one theoretical (structural and electronic properties modeling) and two experimental ones (thin-film growth and nano-scale microscopy). The goal is to unravel the missing link between measured and simulated microstructural and electronic properties, to understand the factors affecting electron transport in disordered TCOs. This will be done by local nano-scale characterization of microstructure using unique ex and in situ advanced electron microscopy techniques; material structure and electronic properties prediction using high-end modeling algorythms; and material synthesis using superior thin-film TCO fabrication facilities. The gathered knowledge will be exploited to propose novel TCO coating processes allowing the design of new earth-abundant TCO materials with optimized electrical and optical properties. Due to the complex structure of disordered materials, both experimental and numerical studies will be highly challenging, but the complementary nature of the techniques constitutes the originality and strength of this project. NCCR MARVEL - Materials' Revolution: Computational Design and Discovery of Novel Materials (MARVEL) Research Project | 1 Project MembersHorizontal Project 4, Advanced Sampling Methods , aims to push the frontiers for structure-prediction, phase space and composition sampling. Earlier work of these groups laid the foundations for future ambitious achievements, from the development of metadynamics and well-tempered metadynamics, basin-hopping methods, and sketch maps. Predicting cluster assembled materials Research Project | 4 Project MembersThe number of possible materials which can be assembled out of cluster based superatoms is much larger than the number of materials whose building blocks are ordinary atoms. It is most likely that such new materials will be highly useful for numerous technological application such as hydrogen storage. The relatively small number of cluster assembled materials known at present has in most cases been found by human intuition together with trial and error based experiments. Given the recent progress in theoretical structure prediction methods it should now be possible to search for such materials in a systematic way by computer simulations. By an extensive screening of a very large number of structural ground states of neutral and ionized clusters of various compositions we will in a first step identify superatoms. i.e. suitable structural building blocks for cluster assembled materials. In a second step we will then explore what kind of materials can be constructed out of these building blocks. To obtain highly reliable predictions, all this work will be done using highly accurate density functional theory. ENVIRON: A Library for Complex Electrostatic Environments in Electronic-structure Simulations Research Project | 2 Project MembersA libray for wet environments in DFT calculations 12 12 OverviewMembersPublicationsProjects & Collaborations
Projects & Collaborations 19 foundShow per page10 10 20 50 Towards Quantifying the Synthesizability of Materials Research Project | 3 Project MembersThe discovery of new materials is an essential ingredient for technological progress. It is generally agreed upon that simulation methods can make important contributions to this field and extensive research activities are under way worldwide. In this context unbiased structure prediction methods have revealed a large number of possible structures for numerous materials. However only a relatively small fraction of these structures can be found in nature or can be synthesized in the laboratory. This observation poses fundamental and technological challenges. One would like to understand whether the unobserved structures can for some hitherto unknown fundamental reason not exist or whether simply the correct synthesis recipe has not yet been found. If they can not exist, synthesis should not be tried for these materials. If they may exist, simulation could give guidance to synthesis efforts. Since a time resolved atomistic simulation of the actual nucleation and growth processes occurring during synthesis is not feasible in connection with a high-accuracy description of the potential energy surface, we will use concepts from thermodynamics to predict the final structure without following the relevant processes in time. In this context, it will be necessary to develop much more efficient methods to calculate free energies. To understand the behavior of the free energy at formation conditions requires developing improved methods to calculate this quantity at high temperatures, where the harmonic approximation breaks down. To obtain the correct energetic ordering at room temperature, it is frequently necessary to include nuclear quantum effects into the free energy calculations. Applying some of the latest mathematical tools, we will develop novel algorithms that are considerably more powerful than the existing ones. Finally we will also search for new quantities that can be obtained from the potential energy surface at affordable numerical cost and that contain relevant information about the synthesizability of a material. All these new methods should then finally allow to directly assess the synthesizability of a material. The new methods will be used for several materials that have potential applications in energy production and storage. Preferentially materials will be used that have already been studied in the group and for which fast machine learning force fields will be available when the project starts. Development of a Neural Network Potential with Accurate Electrostatic Interactions Research Project | 2 Project MembersIn recent years, a new generation of interatomic potentials based on machine learning techniques has been introduced. These potentials, which provide a direct functional relation between the atomic positions and the potential-energy, combine the accuracy of electronic structure methods with the efficiency of simple empirical potentials. Because of the absence of system-specific terms they allow to perform extended simulations of a large variety of systems. Most of these potentials rely on atomic properties like energies and charges depending only on the local chemical environments of the atoms. Such local charges are, however, unable to capture long-range charge transfer. This prevents the accurate description of systems in which distant structural features have global effects on the charge distribution in the system. Examples for such systems are semiconductors including defects, polar surfaces of oxides and metal-organic molecules with different possible metal oxidation states. In order to overcome these intrinsic limitations of current machine learning potentials, we propose to combine high-dimensional neural networks with the charge equilibration neural network technique. The resulting new method will be generally applicable to all types of systems, which we will demonstrate by analyzing the potential-energy surfaces of different model systems covering all types of bonding using the minima hopping method. NCCR MARVEL - Computational Design and Discovery of Novel Materials Research Project | 1 Project Memberssee: http://nccr-marvel.ch/project Structure and dynamics of materials based on advanced electronic structure calculations Research Project | 4 Project MembersIn atomistic simulations the positions of all the involved atoms are individually known. In this way the structure as well as the dynamics of molecular systems can be studied and understood in depth. A prerequisite for such atomistic simulations is the availability of a high quality potential energy surface and methods to explore it efficiently. Potential energy surfaces calculated on the density functional level are usually considered to be state of the art, even though their accuracy is not sufficient in numerous cases. In this project several key aspects of atomistic simulations will be addressed. Based on our recently developed methods to navigate in the configurational space, the efficiency of our structure prediction schemes will be further improved and its applicability enlarged. In addition we will deduce from our exploration of the potential energy surface not only structural but also dynamic properties. Improved density functional methods will be implemented to give higher accuracy potential energy surfaces and consequently improved predictability for atomistic simulations. We will work both on the validation of methods within mainstream density functional schemes as well as on some non-standard approaches inspired by quantum chemistry methods. For some specific systems, machine learning based force fields will be constructed that are not only highly accurate but also orders of magnitude faster to evaluate than potential energy surfaces resulting from density functional calculations. All these developments will allow to find new materials with useful properties faster and to predict their properties with higher reliability. In particular we will apply these methods to study molecular crystals and cluster assembled materials. A highly efficient implementation of direct GPU to GPU communication in a library for direct exchange calculations Research Project | 2 Project MembersA higjhly efficient GPU based excat exhange library will be developped Atolys - Atomic-Scale Analysis of SiC-Oxide Interface for Improved High-Power MOSFETs Research Project | 2 Project MembersIn the Atolys Argovia project, teams of scientists led by Professor Stefan Goedecker from the Department of Physics at the University of Basel are investigating specific components of transistors that are designed for high currents. In the project, researchers from the University of Basel, the Paul Scherrer Institute and ABB in Baden-Dättwil combine theoretical and experimental methods to examine interfaces between silicon carbide and silicon dioxide in semiconductors. The studies, which aim to provide the most precise data about the structure of the semiconductors, will help to further improve devices designed for high currents. ABB researches high-performance semiconductors The global trend for increased use of sustainable energies means that innovative and efficient systems must be developed for generating and distributing power. The ABB Corporate Research Center (CRC) in the Canton of Aargau conducts research in this area and develops power electronics that can also intelligently handle large currents at high voltages. A large part of these efforts is devoted to developing and researching materials for high-performance semiconductors. These are used, for example, to convert direct current into alternating current. This is necessary, among other things, to feed power generated through photovoltaics into the grid or to transport power across large distances. Silicon carbide - the material of the future The semiconductors of the future may not be made from silicon, but from silicon carbide. Its properties allow smaller devices to be built that are easier to cool and have less resistance. In special semiconductor elements (MOSFETs), the boundary layer between silicon carbide and the insulating material silicon dioxide plays an important role. There is empirical evidence that the number of defects can be reduced with nitrogen and other elements. The microscopic mechanisms that lead to this passivation - the formation of a protective layer - are as yet unknown. To investigate these mechanisms and thus to clarify related questions, the scientific team - including Professor Goedecker, Professor Thomas Jung (PSI), and Dr. Jörg Lehmann and Dr. Holger Bartolf (both ABB) - will combine theoretical simulations with experimental studies and analyze the atomic structure of the boundary layers. SINERGIA Impact of composition and nanometer scale DISorder in transparent Conductive Oxides: a new route to design materials with enhanced transport properties (DisCO) Research Project | 1 Project MembersIn the past 10 years we have experienced a revolution in optoelectronic devices, which are becoming more efficient, lighter, in some cases wearable or even fully transparent. This includes ubiquitous flat-panels displays, solar cells, x-ray detectors. This trend demands a rapid development of new Transparent Conductive Oxide (TCOs) materials (which are used as transparent electrode in most optoelectronic devices) with not only the basic requirements of transparency and conductivity, but also properties like homogeneity (e.g to avoid grain boundaries when used in transistors) and mechanical robustness or flexibility when used in bendable devices. The extensive application of TCOs also requires the use of earth-abundant materials for their production, and therefore the replacement of, for example the rather rare metal indium (In). With the ultimate goal of designing and discovering new TCO materials, this collaborative project aims at bridging the gap between material processing, material simulation and material characterization, to understand the factors affecting the charge transport in disordered or "amorphous" TCOs. This will make possible the design and synthesize of new earth-abundant TCO materials with superior electrical, optical and mechanical properties. Disordered TCO materials are of great interest because of their ease of fabrication, and because of the variety of composition and atomic structure achieved ranging from quasi-polycrystalline to fully amorphous. However, disordered TCO materials are complex systems and, their electronic properties cannot be fully understood from sole experimental methods or material simulations, slowing down the development of new materials. To address this problem, we combine three strongly complementary fields in material science research, one theoretical (structural and electronic properties modeling) and two experimental ones (thin-film growth and nano-scale microscopy). The goal is to unravel the missing link between measured and simulated microstructural and electronic properties, to understand the factors affecting electron transport in disordered TCOs. This will be done by local nano-scale characterization of microstructure using unique ex and in situ advanced electron microscopy techniques; material structure and electronic properties prediction using high-end modeling algorythms; and material synthesis using superior thin-film TCO fabrication facilities. The gathered knowledge will be exploited to propose novel TCO coating processes allowing the design of new earth-abundant TCO materials with optimized electrical and optical properties. Due to the complex structure of disordered materials, both experimental and numerical studies will be highly challenging, but the complementary nature of the techniques constitutes the originality and strength of this project. NCCR MARVEL - Materials' Revolution: Computational Design and Discovery of Novel Materials (MARVEL) Research Project | 1 Project MembersHorizontal Project 4, Advanced Sampling Methods , aims to push the frontiers for structure-prediction, phase space and composition sampling. Earlier work of these groups laid the foundations for future ambitious achievements, from the development of metadynamics and well-tempered metadynamics, basin-hopping methods, and sketch maps. Predicting cluster assembled materials Research Project | 4 Project MembersThe number of possible materials which can be assembled out of cluster based superatoms is much larger than the number of materials whose building blocks are ordinary atoms. It is most likely that such new materials will be highly useful for numerous technological application such as hydrogen storage. The relatively small number of cluster assembled materials known at present has in most cases been found by human intuition together with trial and error based experiments. Given the recent progress in theoretical structure prediction methods it should now be possible to search for such materials in a systematic way by computer simulations. By an extensive screening of a very large number of structural ground states of neutral and ionized clusters of various compositions we will in a first step identify superatoms. i.e. suitable structural building blocks for cluster assembled materials. In a second step we will then explore what kind of materials can be constructed out of these building blocks. To obtain highly reliable predictions, all this work will be done using highly accurate density functional theory. ENVIRON: A Library for Complex Electrostatic Environments in Electronic-structure Simulations Research Project | 2 Project MembersA libray for wet environments in DFT calculations 12 12
Towards Quantifying the Synthesizability of Materials Research Project | 3 Project MembersThe discovery of new materials is an essential ingredient for technological progress. It is generally agreed upon that simulation methods can make important contributions to this field and extensive research activities are under way worldwide. In this context unbiased structure prediction methods have revealed a large number of possible structures for numerous materials. However only a relatively small fraction of these structures can be found in nature or can be synthesized in the laboratory. This observation poses fundamental and technological challenges. One would like to understand whether the unobserved structures can for some hitherto unknown fundamental reason not exist or whether simply the correct synthesis recipe has not yet been found. If they can not exist, synthesis should not be tried for these materials. If they may exist, simulation could give guidance to synthesis efforts. Since a time resolved atomistic simulation of the actual nucleation and growth processes occurring during synthesis is not feasible in connection with a high-accuracy description of the potential energy surface, we will use concepts from thermodynamics to predict the final structure without following the relevant processes in time. In this context, it will be necessary to develop much more efficient methods to calculate free energies. To understand the behavior of the free energy at formation conditions requires developing improved methods to calculate this quantity at high temperatures, where the harmonic approximation breaks down. To obtain the correct energetic ordering at room temperature, it is frequently necessary to include nuclear quantum effects into the free energy calculations. Applying some of the latest mathematical tools, we will develop novel algorithms that are considerably more powerful than the existing ones. Finally we will also search for new quantities that can be obtained from the potential energy surface at affordable numerical cost and that contain relevant information about the synthesizability of a material. All these new methods should then finally allow to directly assess the synthesizability of a material. The new methods will be used for several materials that have potential applications in energy production and storage. Preferentially materials will be used that have already been studied in the group and for which fast machine learning force fields will be available when the project starts.
Development of a Neural Network Potential with Accurate Electrostatic Interactions Research Project | 2 Project MembersIn recent years, a new generation of interatomic potentials based on machine learning techniques has been introduced. These potentials, which provide a direct functional relation between the atomic positions and the potential-energy, combine the accuracy of electronic structure methods with the efficiency of simple empirical potentials. Because of the absence of system-specific terms they allow to perform extended simulations of a large variety of systems. Most of these potentials rely on atomic properties like energies and charges depending only on the local chemical environments of the atoms. Such local charges are, however, unable to capture long-range charge transfer. This prevents the accurate description of systems in which distant structural features have global effects on the charge distribution in the system. Examples for such systems are semiconductors including defects, polar surfaces of oxides and metal-organic molecules with different possible metal oxidation states. In order to overcome these intrinsic limitations of current machine learning potentials, we propose to combine high-dimensional neural networks with the charge equilibration neural network technique. The resulting new method will be generally applicable to all types of systems, which we will demonstrate by analyzing the potential-energy surfaces of different model systems covering all types of bonding using the minima hopping method.
NCCR MARVEL - Computational Design and Discovery of Novel Materials Research Project | 1 Project Memberssee: http://nccr-marvel.ch/project
Structure and dynamics of materials based on advanced electronic structure calculations Research Project | 4 Project MembersIn atomistic simulations the positions of all the involved atoms are individually known. In this way the structure as well as the dynamics of molecular systems can be studied and understood in depth. A prerequisite for such atomistic simulations is the availability of a high quality potential energy surface and methods to explore it efficiently. Potential energy surfaces calculated on the density functional level are usually considered to be state of the art, even though their accuracy is not sufficient in numerous cases. In this project several key aspects of atomistic simulations will be addressed. Based on our recently developed methods to navigate in the configurational space, the efficiency of our structure prediction schemes will be further improved and its applicability enlarged. In addition we will deduce from our exploration of the potential energy surface not only structural but also dynamic properties. Improved density functional methods will be implemented to give higher accuracy potential energy surfaces and consequently improved predictability for atomistic simulations. We will work both on the validation of methods within mainstream density functional schemes as well as on some non-standard approaches inspired by quantum chemistry methods. For some specific systems, machine learning based force fields will be constructed that are not only highly accurate but also orders of magnitude faster to evaluate than potential energy surfaces resulting from density functional calculations. All these developments will allow to find new materials with useful properties faster and to predict their properties with higher reliability. In particular we will apply these methods to study molecular crystals and cluster assembled materials.
A highly efficient implementation of direct GPU to GPU communication in a library for direct exchange calculations Research Project | 2 Project MembersA higjhly efficient GPU based excat exhange library will be developped
Atolys - Atomic-Scale Analysis of SiC-Oxide Interface for Improved High-Power MOSFETs Research Project | 2 Project MembersIn the Atolys Argovia project, teams of scientists led by Professor Stefan Goedecker from the Department of Physics at the University of Basel are investigating specific components of transistors that are designed for high currents. In the project, researchers from the University of Basel, the Paul Scherrer Institute and ABB in Baden-Dättwil combine theoretical and experimental methods to examine interfaces between silicon carbide and silicon dioxide in semiconductors. The studies, which aim to provide the most precise data about the structure of the semiconductors, will help to further improve devices designed for high currents. ABB researches high-performance semiconductors The global trend for increased use of sustainable energies means that innovative and efficient systems must be developed for generating and distributing power. The ABB Corporate Research Center (CRC) in the Canton of Aargau conducts research in this area and develops power electronics that can also intelligently handle large currents at high voltages. A large part of these efforts is devoted to developing and researching materials for high-performance semiconductors. These are used, for example, to convert direct current into alternating current. This is necessary, among other things, to feed power generated through photovoltaics into the grid or to transport power across large distances. Silicon carbide - the material of the future The semiconductors of the future may not be made from silicon, but from silicon carbide. Its properties allow smaller devices to be built that are easier to cool and have less resistance. In special semiconductor elements (MOSFETs), the boundary layer between silicon carbide and the insulating material silicon dioxide plays an important role. There is empirical evidence that the number of defects can be reduced with nitrogen and other elements. The microscopic mechanisms that lead to this passivation - the formation of a protective layer - are as yet unknown. To investigate these mechanisms and thus to clarify related questions, the scientific team - including Professor Goedecker, Professor Thomas Jung (PSI), and Dr. Jörg Lehmann and Dr. Holger Bartolf (both ABB) - will combine theoretical simulations with experimental studies and analyze the atomic structure of the boundary layers.
SINERGIA Impact of composition and nanometer scale DISorder in transparent Conductive Oxides: a new route to design materials with enhanced transport properties (DisCO) Research Project | 1 Project MembersIn the past 10 years we have experienced a revolution in optoelectronic devices, which are becoming more efficient, lighter, in some cases wearable or even fully transparent. This includes ubiquitous flat-panels displays, solar cells, x-ray detectors. This trend demands a rapid development of new Transparent Conductive Oxide (TCOs) materials (which are used as transparent electrode in most optoelectronic devices) with not only the basic requirements of transparency and conductivity, but also properties like homogeneity (e.g to avoid grain boundaries when used in transistors) and mechanical robustness or flexibility when used in bendable devices. The extensive application of TCOs also requires the use of earth-abundant materials for their production, and therefore the replacement of, for example the rather rare metal indium (In). With the ultimate goal of designing and discovering new TCO materials, this collaborative project aims at bridging the gap between material processing, material simulation and material characterization, to understand the factors affecting the charge transport in disordered or "amorphous" TCOs. This will make possible the design and synthesize of new earth-abundant TCO materials with superior electrical, optical and mechanical properties. Disordered TCO materials are of great interest because of their ease of fabrication, and because of the variety of composition and atomic structure achieved ranging from quasi-polycrystalline to fully amorphous. However, disordered TCO materials are complex systems and, their electronic properties cannot be fully understood from sole experimental methods or material simulations, slowing down the development of new materials. To address this problem, we combine three strongly complementary fields in material science research, one theoretical (structural and electronic properties modeling) and two experimental ones (thin-film growth and nano-scale microscopy). The goal is to unravel the missing link between measured and simulated microstructural and electronic properties, to understand the factors affecting electron transport in disordered TCOs. This will be done by local nano-scale characterization of microstructure using unique ex and in situ advanced electron microscopy techniques; material structure and electronic properties prediction using high-end modeling algorythms; and material synthesis using superior thin-film TCO fabrication facilities. The gathered knowledge will be exploited to propose novel TCO coating processes allowing the design of new earth-abundant TCO materials with optimized electrical and optical properties. Due to the complex structure of disordered materials, both experimental and numerical studies will be highly challenging, but the complementary nature of the techniques constitutes the originality and strength of this project.
NCCR MARVEL - Materials' Revolution: Computational Design and Discovery of Novel Materials (MARVEL) Research Project | 1 Project MembersHorizontal Project 4, Advanced Sampling Methods , aims to push the frontiers for structure-prediction, phase space and composition sampling. Earlier work of these groups laid the foundations for future ambitious achievements, from the development of metadynamics and well-tempered metadynamics, basin-hopping methods, and sketch maps.
Predicting cluster assembled materials Research Project | 4 Project MembersThe number of possible materials which can be assembled out of cluster based superatoms is much larger than the number of materials whose building blocks are ordinary atoms. It is most likely that such new materials will be highly useful for numerous technological application such as hydrogen storage. The relatively small number of cluster assembled materials known at present has in most cases been found by human intuition together with trial and error based experiments. Given the recent progress in theoretical structure prediction methods it should now be possible to search for such materials in a systematic way by computer simulations. By an extensive screening of a very large number of structural ground states of neutral and ionized clusters of various compositions we will in a first step identify superatoms. i.e. suitable structural building blocks for cluster assembled materials. In a second step we will then explore what kind of materials can be constructed out of these building blocks. To obtain highly reliable predictions, all this work will be done using highly accurate density functional theory.
ENVIRON: A Library for Complex Electrostatic Environments in Electronic-structure Simulations Research Project | 2 Project MembersA libray for wet environments in DFT calculations
