Research project Descriptions


Project D.1: Cell Design and Production


Project Description
Development of universal methods for prediction of producibility is used to accelerate the transformation from a laboratory scale to robust mass production. Correlations between material and process parameters will be revealed. Parameters, which are decisive for producibility, are identified by a two-stage screening process. First, manufacturing processes are screened in order to determine whether an energy storage device “beyond lithium” can be produced on an industrial scale or not. In a second step, necessary handling operations and quality assurance measures are derived. The overall result is a selection of suitable manufacturing processes in agreement with associated handling and quality assurance processes. The model will be capable to evaluate the producibility of a promising new cell design with proposed materials and components.

Expected scientific background:
Development of universal methods for prediction of producibility is used to accelerate the transformation from a laboratory scale to robust mass production. Correlations between material and process parameters will be revealed. Parameters, which are decisive for producibility, are identified by a two-stage screening process. First, manufacturing processes are screened in order to determine whether an energy storage device “beyond lithium” can be produced on an industrial scale or not. In a second step, necessary handling operations and quality assurance measures are derived. The overall result is a selection of suitable manufacturing processes in agreement with associated handling and quality assurance processes. The model will be capable to evaluate the producibility of a promising new cell design with proposed materials and components.

Supervisor: Prof. Dr. Jürgen Fleischer (Karlsruhe Institute of Technology)

Employer: Karlsruhe Institute of Technology

Location: Karlsruhe Institute of Technology

Link for Application: www.kit.edu


Project A.1/B.1/C.3: Systematic Coupling of Atomistic and Continuum Scale Theories


Project Description
A predictive theoretical description of batteries requires a seamless coupling of processes on each spatial scale from the atomistic over the molecular and meso-scale up to the macroscopic cell scale. Motivated by the urge of a theoretical framework that allows describing electrochemical interfaces or even full battery cells, this project aims for developing a Free Energy based reaction-transport theory for Post-Lithium-Batteries which would allow a stronger coupling to DFT and Reactive Force field approaches. By introducing a stronger coupling of continuum theories and DFT via the concept of free energy also the results of DFT for reaction paths and surface morphologies become more accurate and in addition the parameters for continuum modeling can be determined, consistent with lower scale theories.

Expected scientific background:
PhD (or equivalent) in physics, chemistry or applied mathematics. Experience in one or more of the following subjects are beneficial: Mathematical Modeling, Density Functional Theory, Non-Equilibrium Thermodynamics.

Supervisor: Prof. Dr. Arnulf Latz (Helmholtz-Institute Ulm)

Employer: Ulm University

Location: Helmholtz-Institute Ulm

Link for Application: www.uni-ulm.de


Project C.3: Model studies on the nature and formation of interphase


Project Description
The project aims at a detailed understanding of interactions between electrodes and electrolytes in next generation batteries, to gain information on the structure, formation and stability of the interphases formed between electrodes and the electrolyte. Specifically, this involves the preparation and structural / chemical characterization of structurally and chemically well-defined planar model systems, which are less complex than realistic electrodes, under ultrahigh vacuum (UHV) conditions. In a next step, the interaction with typical solvents and electrolytes shall be studied, using different microscopic and spectroscopic techniques such as UHV-STM and -AFM or XPS, UPS, IR, TDS, and finally electrochemical methods.

Expected scientific background:
PhD (or equivalent) in chemistry or physics with a background in Surface Science. Practical experience in one or more of the following subjects are required: Handling of UHV equipment, Scanning probe microscopy, surface spectroscopies such as XPS, UPS etc.

Supervisor: Prof. Dr. R. Jürgen Behm (Institute of Surface Chemistry and Catalysis, Ulm University)

Employer: Ulm University

Location: Ulm University

Link for Application: www.uni-ulm.de


Project A.1.1: Automatic SEI insight generation formation from combinatorial electrolyte formulation


Project Description
This project aims to automatically extract fundamental knowledge about early SEI/SCI formation, composition and structure by utilizing machine learning on large datasets from combinatorial electrolyte formulation, electrochemical characterization & testing, XPS, UPS, and low resolution SEM. The PhD student will work with the hardware developement team of the group to synthesize materials libraries spanning a controlled variation of up to seven electrolyte components and perform an in depth characterization of the SEI/SCI using high-throughput methods. Milimeter scale batteries will be formed using a scanning droplet cell that allows direct investigation of the SEI/SCI. Automated extraction of fundamental knowledge will be done through explainable AI.

Expected scientific background:
M.Sc. in either Chemistry, Physics or Mechanical Engineering with a focus on either physical Chemistry or Spectroscopic Methods. Good programming skills, excellent english, basic knowldege of organic chemistry or electrochemistry. Preferrably a background in hardware developement or machine learning.

Supervisor: Prof. Dr. Helge S. Stein (Helmholtz-Institute Ulm)

Employer: Karlsruhe Institute of Technology

Location: Helmholtz-Institute Ulm

Starting Date:: 01.01.2020
The position is for 36 months.


Project A.1.1: Combinatorial assembly of coin cell batteries for AI accelerated formulation optimization


Project Description
This PhD Project aims to build a fully automatic coin cell battery assembly line for post-Li Ion batteries that is capable of freely formulating the electrolyte using a variety of electrodes. The robot will pick and place nessesary parts, formulate a liquid electrolyte, assemble the battery and place it into a testing rack. In the rack batteries will be tested until failiure. In close collaoration with colleagues of the group the robot interface and data management will allow for targeted electrolyte formulations chosen by a machine learning algorithm. The aim will be to aquire the to-date largest coin cell battery library of >1000 controlled electrolyte variations and use it to extract new fundamental knowledge i.e. why and how certian formulations produce long lived batteries.

Expected scientific background:
M.Sc. in Mechanical Engineering or Computer Science Background in Hardware Developent, Computer Aided Design (CAD), Automation Good programming skills, interest in data science and database design

Supervisor: Prof. Dr. Helge S. Stein (Helmholtz-Institute Ulm)

Employer: Karlsruhe Institute of Technology

Location: Helmholtz-Institute Ulm

Starting Date:: 01.01.2020
The position is for 36 months.


Project A.1.1: Exploration and visualization of high-entropy oxide battery electrode materials


Project Description
High-entropy oxides (HEO) are a promising class of materials for structural and energy related applications. This PhD project will explore different HEO by means of combinatorial reactive magnetron sputtering, high-throughput Raman spectroscopy and high-throughput electrochemistry. The goal is to identify taylored HEO electrode materials for different post-Li ion battery chemistries and investigate off-stoichiometric effects on long term stability. Identified top-materials will be in-depth characterized using in-situ XRD and finally scaled up into devices using the in-house build assembly line.

Expected scientific background:
M.Sc. in Chemistry, Physics, Materials Science or Mechanical engineering Good programming skills, interest in data science and database design Good knowledge of materials science

Supervisor: Prof. Dr. Helge S. Stein (Helmholtz-Institute Ulm)

Employer: Karlsruhe Institute of Technology

Location: Helmholtz-Institute Ulm

Starting Date:: 01.05.2020
The position is for 36 months.


Project A.1.1: Functional phase mapping for batteries - translating domain brideing ex-situ spectroscopy


Project Description
Combinatorial synthesis offers controlled variation of processing, formulation, composition and morphology that this PhD project will characterize in-depth using high-throughput electrochemistry, FTIR, Raman, XPS, UPS and SEM to build functional phase diagrams. The topic is split between 1) an experimental part dealing with deploying high-throughput FTIR and UPS mapping capabilities 2) a computational part that is aimed at developing an automatic data analysis and management framework. The goal is to extract formulation-composition-structure-property correlation maps for novel battery chemistries in reduced time.

Expected scientific background:
M.Sc. in Chemistry, Physics, Materials Science or Mechanical engineering Good programming skills, interest in data science and database design Good knowledge of materials science

Supervisor: Prof. Dr. Helge S. Stein (Helmholtz-Institute Ulm)

Employer: Karlsruhe Institute of Technology

Location: Helmholtz-Institute Ulm

Starting Date:: 01.01.2020
The position is for 36 months.


Project B.2.1. Inorganic and Polymer Solid Electrolytes as Single-Cation Conductor


Project Description
Our goal is the improvement of solid electrolytes with regard to stability and performance. The work ranges from synthesis and preparation of polymer films until the assembly and characterization of experimental cells. The focus lies on the polymer based material, which shall be investigated with electrochemical and mechanical methods in order to derive structure-property relationships. Furthermore, the interactions between electrolyte and various electrodes shall be analyzed by isothermal microcalorimetry.

Expected scientific background:
Master’s degree in chemistry, engineering, e.g. chemical process engineering or similar. Practical experiences in one or more of the following subjects are beneficial: Electrochemistry, Polymer Science, Material Science, Thermodynamics

Supervisor: Prof. Dr. Jens Tübke (Helmholtz-Institute Ulm)

Employer: Karlsruhe Institute of Technology

Location: Helmholtz-Institute Ulm

Starting Date:: 01.01.2020
The position is for 36 months.

Link for Application: www.kit.edu

Top News


4.04.2020


BATTERY2030+: Roadmap for battery research in Europe

In order to develop future batteries, partners from science and industry from all over Europe have launched the BATTERY 2030+ research initiative. A roadmap specifies the milestones: a platform for material development using artificial intelligence (AI), networked sensors and self-healing technology for batteries as well as sustainable manufacturing and recycling processes. Via the research platform CELEST, the Karlsruhe Institute of Technology (KIT), the University of Ulm and the Zentrum für Sonnenenergie- und Wasserstoff-Forschung Baden-Württemberg (ZSW) are involved in the consortium.


9.10.2019


Freshly chosen Nobel Prize winner at ABAA12 in Ulm

M. Stanley Whittingham, John B. Goodenough, and Akira Yoshino receive the Nobel Prize in Chemistry for their invention of the lithium-ion battery. M. Stanley Whittingham was at the ABAA 12 (Advanced Lithium Batteries for Automobile Applications) conference in Ulm when the news of the award went around the world.

Read more in the NEWS section.