ARENHA (2019-2023)

Project title:

ARENHA: Advanced materials and Reactors for Energy storage tHrough Ammonia

Project description:

ARENHA (Advanced materials and Reactors for Energy storage tHrough Ammonia) is a European project with global impact seeking to develop, integrate and demonstrate key material solutions enabling the use of ammonia for flexible, safe and profitable storage and utilization of energy. Ammonia is an excellent energy carrier due to its high energy density, carbon-free composition, industrial know-how and relative ease of storage. ARENHA demonstrates the feasibility of ammonia as a dispatchable form of large-scale energy storage, enabling the integration of renewable electricity in Europe and creating global green energy corridors for Europe energy import diversification. Innovative Materials are developed and integrated into ground-breaking systems in order to demonstrate a flexible and profitable power-to-ammonia value chain but also several key energy discharge processes.

Co-PI: Professor Tejs Vegge, DTU Energi

BIG-MAP (2020-2023)

Project title:

BIG-MAP: Battery Interface Genome – Materials Acceleration Platform

Project description:
The BIG-MAP vision is to develop a modular, closed-loop infrastructure and methodology to bridge physical insights and data-driven approaches to accelerate the discovery of sustainable battery chemistries and technologies. BIG-MAP’s strategy is to cohesively integrate machine learning, computer simulations and AI-orchestrated experiments and synthesis to accelerate battery materials discovery and optimization. The project will be a lever to create the infrastructural backbone of a versatile and chemistry-neutral European Materials Acceleration Platform, capable of reaching a 10-fold increase in the rate of discovery of novel battery materials and interfaces.

 

Funded by: H2020-LC-BAT-12

PI: Professor Tejs Vegge, DTU Energi

DELIGHT (2021-2024)

Project title:

DEep LearnIng Green cHemical caTalysis

Project description:

Biomimetic catalysis and artificial enzymes have been investigated intensely for decades, but a transformative breakthrough in the understanding of the intricate structure-property relationship has remained elusive. Nitrogenase can transform atmospheric nitrogen into ammonia at ambient conditions; at the same time one of the simplest and most challenging chemical reactions, which is responsible for feeding the world population and for >1% of the anthropogenic CO2 emission.

Thus far, the pursuit of artificial green ammonia catalysts has been futile, but we propose a pioneering data centric approach, where the complex electronic interplay between the enzyme and the cofactors is learned using machine learning generated datasets of Ionic Liquid (IL) frameworks and inorganic catalysts via a deep inverse generative AI. The ILs will act as a rigid solvent that can be designed to direct a specific pathway, similar to that of a protein scaffold, to enhance the yield of green ammonia.

Funded by: Independent Research Fund Denmark

PI: Professor Tejs Vegge, DTU Energy

SURE (2020-2022)

Project title:
Self-correcting Unsupervised Reaction Energies

Project description: The control of chemical reactions is of vital importance in many fields of science, technology, and medicine. It is usually hindered by the enormous complexity of competing reaction mechanisms, where many molecular species and elementary reaction steps coexist and compete with each other. The key to successful modelling and prediction of such complex systems is twofold. First, ensuring a reliable estimation of data uncertainty and how it propagates throughout the reaction network. Secondly, to have efficient tools for on-the-fly identification and correction of errors. SURE will pull together the powerful techniques of molecular simulations and artificial intelligence to map out and quantify the complexity of chemical reaction networks. Both challenges will be solved thanks to the synergy between data-driven and physics-based modelling approaches. The developed autonomous and self-correcting framework will be validated for the reaction networks of organic redox flow battery.

A Novo Nordisk Foundation: Exploratory Interdisciplinary Synergy Programme project

Key people: Tejs Vegge (PI), Ole Winther (co-PI, DTU Compute), Arghya Bhowmik, Piotr de Silva, Peter Bjørn Jørgensen, Mikkel Nørgaard Schmidt (DTU Compute), Jonas Busk, Surajit Nanji*

Electrolytes optimization for redox targeting-based flow batteries (2019-2022)

Project title:

Electrolytes optimization for redox targeting-based flow batteries

 

Project description:

The aim of this project is to develop new organometallic electrolytes to be used as molecular mediators in redox targeting-based flow batteries. The solid-state active materials in the battery will comprise the lithium or sodium insertion electrodes and the battery will operate at neutral pH. The molecular design of new mediators will be based on the experimental and computational approach with subsequent experimental validation at the full cell level


Funded by: ALISTORE – European research institute

Partners: Laboratoire de Réactivité et Chimie des Solides at Université de Picardie Jules Verne (France)

PI: Piotr de Silva

SONAR (2020-2024)

Project title: Modelling for the search for new active materials for redox flow batteries

Project description: In search of truly competitive solutions for storing energy from renewable resources, the SONAR-team sets out to develop a framework for the simulation-based screening of electroactive materials for organic redox flow batteries (RFBs) – in aqueous and non-aqueous solutions. This will help to reduce the cost and time-to-market and thus strengthen the competitiveness of the EU’s battery industry.
  • We follow a multiscale modelling paradigm, starting from the automated generation of candidate structures for the electroactive material and then iterate through molecular-, electrochemical interface-, porous electrodes-, cell-, stack-, system- and techno-economic-level models.
  • Finally, storage technologies are only comparable when using the levelized-cost-of-storage (LCOS) as a global metric, which accounts for all relevant effects across all the scales.
  • The simulation results go into a database for further processing – we will exploit advanced data integration, analysis and machine-learning techniques, drawing on the growing amount of data produced during the project in order to speed up the computations.
  • Selected models will be validated by measurements in RFB half-cells and lab-sized test cells to ensure our predictions' quality. We will work closely with industrial partners to ensure the commercial viability of the results.

Funded by: EU, Horizon2020

Partners: Fraunhofer Institute for Chemical Technology (Germany), Fraunhofer Institute for Algorithms and Scientific Computing (Germany),  Laboratoire de Réactivité et Chimie des Solides at Université de Picardie Jules Verne (France), Zurich University of Applied Sciences (Switzerland), Karlsruhe Institute of Technology (Germany), University of New South Wales (Australia)

PIs: Piotr de Silva and Tejs Vegge

COMBO (2020-2022)

Project title:
Combining machine learning and human understanding for accelerated discovery of molecular materials

Project description:
Machine learning has been widely used to accelerate materials design; however, despite intensive research, almost all materials are still being discovered using heuristic design rules based on theory and experimentation. This raises a question if fully autonomous materials design is possible at all or whether it is a process that requires intellectual involvement. Or maybe there is a middle ground where both approaches can meet and reinforce each other? This proposal puts forward an idea of using model Hamiltonians combined with machine learning and human understanding to formulate new design rules for functional materials. We propose to expedite the human learning process by using algorithms to find patterns which can be transformed into new design rules. If successful, this approach could be a paradigm shift in accelerated materials discovery. The development of methodology will be driven by a concrete example in organic optoelectronics.

Funded by: Villum Foundation – Villum Experiment Programme

PI: Piotr de Silva

SEIinterfaces (2019-2021)

Project title:
Computational Study of the Solid Electrolyte Interface (SEI) Formation

Project description:
In this project, we will study the formation of the SEI layer on Li-ion batteries used in the automotive industry, by combining realistic quantum mechanical simulations with high-fidelity experiments. We will develop a methodology to model the interface as an open system and to obtain key information, such as Li adsorption potential and Li phase diagram, which will help us in unlocking the complex chemistry involved in the reduction of electrolyte and impurities, which are responsible for the SEI formation.


Funded by: BMW Research Group

Partners: BMW Research Group (Germany), Copenhagen University (Denmark), Technical University of Munich (Germany), Argonne National Laboratory (USA), MIT (USA)

PI (ASM): Assistant Professor Ivano E. Castelli

E-MAGIC (2019 - 2022)

 

Project title:

European Magnesium Interactive Battery Community

 

Project description:

E-MAGIC gathers the key scientific researchers in Europe to develop foundational approaches on rechargeable magnesium battery (RMB), bringing an effective work on R&D by a rational design of novel cathodes and electrolytes to overcome the rate-limiting reactions, and deliver a safe RMB with energy density of 450 Wh kg-1 at 100 €/Kwh.

The main objective of E-MAGIC will be to elaborate and develop a disruptive scientific and technical approach of the new generation of viable high energy density and environmental friendly (RMB). This will constitute a breakthrough in the development of novel battery materials and will have a disruptive impact on the battery market, providing in the long term (+10 years) an emerging technology in the field of energy storage.

The role of DTU Energy ASC in E-MAGIC is to develop a rational design of high voltage/high capacity cathode materials on the basis of computational approaches at different length scale to gain a better understanding of the rate-limiting reaction and transport processes that govern and limit the reversibility of the insertion and conversion Mg-based battery technologies.

 

Funded by: EU, Horizon2020, FET Proactive, Research and Innovation Framework Programme

 

Partners: Fundación CIDETEC (Spain), Bar Ilan University (Israel), Atomic Energy and Alternative Energies Commission (France), Agencia Estatal Consejo Superior de Investigaciones Científicas (Spain), Karlsruhe Institute of Technology / Helmholtz Institute Ulm (Germany), Deutsches Zentrum für Luft- und Raumfahrt e.V. (Germany), Technion Israel (Israel), Abengoa Innovación (Spain), University of Cambridge (UK)

 

PIs (ASC): Professor Tejs Vegge and Associate Professor Juan Maria García Lastra

BIKE (2018-2022)

Project title:
BIKE: Bimetallic catalyst knowledge based development for energy applications

Project description:
BIKE (BImetallic catalysts Knowledge-based development for Energy applications) is a network for training of T-shaped young promising scientists (early stage researchers, ESRs), who will develop and apply, by an innovative “holistic” approach, the next generation of bimetallic catalysts for energy management, in particular for blue and green hydrogen production processes. BIKE next generation bimetallic catalysts will exhibit superior performance under realistic conditions thanks to the combination of state-of-the-art tools (predictive modelling, advanced characterization, knowledge based design and novel preparation of catalysts, and explorative testing) in a single methodology to fully exploit their added value in a synergistic way.

Co-PI: Professor Tejs Vegge, DTU Energi

AiMade (2018-2022)

Project title:

AiMade: Autonomous Materials Discovery

Project description:
The current scientific paradigm for discovery of clean energy materials is based on human intuition about how specific properties are connected to their design and composition. The goal of Autonomous Materials Discovery (AiMade), at the Department of Energy Conversion and Storage (DTU Energy) at the Technical University of Denmark (DTU), is to challenge this mindset. In this four year initiative, we will strive to establish an platform for autonomous materials discovery of clean energy materials through creation of a common data-infrastructure and holistic ontology for materials data, connecting data and information from simulations, characterization, synthesis and testing, spanning multiple time- and length-scales.

 

PI: Professor Tejs Vegge, DTU Energi

SALBAGE (2018 - 2020)

Project title:

Sulfur-Aluminium Battery with Advanced Polymeric gel Eletroclytes

Project description:

In SALBAGE Project, a new secondary Aluminium Sulfur Battery will be developed. The focus will be put in the synthesis of solid-like electrolytes based on polymerizable ionic liquids (IL) and Deep Eutectic Solvents (DES) in order to obtain polymer-gel electrolytes with an overall ionic conductivity in the range of 1-10 mS/cm at room temperature. At the same time, the aluminium negative electrode will be combined with a sulfur positive electrode including the unprecedented use of redox mediators, to facilitate sulfur reaction kinetics and boost performance.
The new battery is expected to have a high energy density (1000Wh/kg) and low price compared with the actual Li-ion technology (-60%). Moreover, we will take advantage of the special features of the resulting battery (flexibility, adaptability, shapeability) to design a new device with the focus put on strategic applications such as transport, aircraft industry or ITs, for which the SALBAGE battery will be specially designed and tested in relevant conditions. To achieve the objectives a strong consortium has been gathered, with reputed experts in all the relevant fields, such as development of ILs and DES (University of Leicester, and Scionix Ltd.), polymerization (ICTP- CSIC), synthesis and characterization of materials for aluminium anode (TU Graz) and sulfur-cathode (Univ. of Southampton) and computational modelling (DTU). This consortium is leaded by a European SME’s, Albufera Energy Storage, expert in the development and testing of batteries, with great interest in the future market exploitation.

Funded by: EU, Horizon2020, FET Open, Research and Innovation Framework Programme

Partners: University of Leicester, Scionix Ltd., University of Southhampton (UK), Albufera Energy Storage, ICTP-CSIC (Spain), Technical University of Graz (Austria)

PI (ASC): Associate Professor Juan Maria García Lastra 

ORBATS (2017 - 2020)


Project title:

Organic Redox Flow Battery Systems

Project description:

ORBATS will develop a new, safe, environmentally benign, and fully scalable aqueous redox flow battery technology relying on the use of tunable water-soluble organic molecules as the charge storage medium. We will establish a cost-competitive battery solution for energy storage on the critical time-scale of 1-12 hours, needed for demand shifting and stable day-to-day operation of micro-grids in residential applications and remote locations, with a cost tar-get of < $100/kWh, including materials, stack and balance-of-plant.

The project combines the know-how of leading academic groups in Denmark (DTU, AU) and the US (Harvard) in the area of flow batteries, membranes, synthetic chemistry, computational science and ad-vanced electrochemical characterization, with industrial partners with expertise in flow battery development (VisBlue), wind power (Vestas), and battery management systems (Lithium Balance) to move this promising technology to the prototype stage.

Funded by: Innovation Fund Denmark

Partners: Aarhus University, Harvard University, VisBlue, Lithium Balance A/S, Vestas Wind Systems.

PI (ASC): Professor Tejs Vegge

Simba (2017 - 2020)

Project title:

Commercial Multi-Scale SIMulation tool for BAttery Research and Development

Project description:

The objective is to develop a new market leading multi-scale simulation tool for battery systems – the SimBa tool. Materials parameters will be obtained from first principles modelling of key parts of the battery. These parameters will be integrated into a continuum model of the entire battery cell for predicting the performance of the battery. The software will be delivered as a commercial tool for multi-scale simulation of batteries including detailed manuals and a graphical user interface.

Funded by: EU, EurostarsPartners: Quantum Wise A/S - project leader, Helmholtz Institute Ulm (Germany), Envites (Germany), AQComputare (Germany)

PI (ASC): Associate Professor Juan Maria Garcia Lastra

V-Sustain (2016-2024)

Project title:

The VILLUM Center for the Science of Sustainable Fuels and Chemicals

Project description:

The present proposal seeks to provide important parts of the scientific basis for energy and chemical transformation technology allowing solar and wind energy to be used to synthesize fuels and base chemicals for industrial production. By enabling the utilization of sustainable energy, our proposed project will facilitate the phasing out of fossil fuels, protecting the environment on Earth, its biodiversity and climate. We are focusing on six research projects that, if successful, all have the potential to make a significant difference to our future. All projects are dealing with the fundamental science of catalyzing processes such that solar energy can be converted into and stored as chemicals. The six projects are: 1) Efficient electrolysis for water splitting into hydrogen; 2) Fuel cell processes for hydrogen utilization; 3) Direct harvesting of sunlight for hydrogen production; 4) Thermally driven processes for CO2 reduction to fuels and chemical building blocks; 5) Electrochemical COreduction to fuels and base chemicals; and 6) Electrochemical N2 reduction to ammonia.

Funded by: Villum Fonden

Partners: Stanford University (SUNCAT Center for Interface Science and Catalysis), University of Copenhagen, University of Southern Denmark

PI (ASC): Professor Tejs Vegge

Mat4Bat (2015-2021)

Project title:

In silico design of efficient materials for next generation batteries

Project description:

An ideal material for a battery electrode should exhibit high energy density, long-term stability and high electrical conductivity. In order to design materials with such properties efficiently, traditional trial-and-error experimental strategies are too slow and expensive. It is therefore necessary to gain a better comprehension of the basic processes taking place in the battery electrodes. Once the fundamental processes are understood, it is possible to search for the best materials candidates. An efficient way to do this is through computational screening of materials and dopants, an approach that has been shown to be very successful in other research areas such as heterogeneous catalysis and drug discovery.  This is exactly what we propose to do in this project: To develop new theoretical tools for elucidating the intimate nature of the electronic conduction in alkaline metal battery electrodes and to find the optimal materials for achieving next generation, high capacity batteries. This approach provides an inexpensive and fast way to improve lithium-ion battery performance, and more importantly, to transform alkaline metal-air (and alkaline-earth metal-air) batteries from a promising technology to a reality. The latter will give electric vehicles the opportunity to compete on equal ground with fossil fuel based cars.

Funded by: Villum Foundation – Young Investigator Programme

Partners: MIT, Binghamton University, Max Planck Institute for the Structure and Dynamics of Matter

PI: Associate Professor Juan Maria García Lastra