Dr. Clemens Guhlke

Projects as a project leader

• CH11

  Sensing with Nanopores

  Dr. Jürgen Fuhrmann / Dr. Clemens Guhlke

  Project heads: Dr. Jürgen Fuhrmann / Dr. Clemens Guhlke
  Project members: -
  Duration: 01.06.2017 - 31.12.2018
  Status: completed
  Located at: Weierstraß-Institut
  

  Description

  Sensing with nanopores is a promising new technology to analyze macromolecules like DNA strands by low cost/high speed measurements. The sensing device is constructed based on a nanopore embedded into a membrane which separates two electrodes. The system is filled with an electrolyte containing macromolecules to be analyzed. An electric potential is applied to the electrodes and induces an ionic current through the pore. Sensing is based on the observation that this ionic current is influenced by the geometrical configurations of the pore and of the macromolecules positioned within the pore. Under controlled movement of the macromolecule through the pore a characteristic time dependent current signal is generated, which is correlated to the structure of the pore and the macromolecule. Therefore nanopores can be used to count and even to characterize macromolecules in an electrolytic solution. n order to achieve a better understanding of the of phenomena that control the passing time of the analytes (macromolecules) through the nanopore, and to derive a relation between characteristic properties of the macromolecule and the generated current, the project will focus on three groups of tasks: Development of an appropriate nanopore model in the context of non-equilibrium thermodynamics, which accounts for the geometrical properties of pore and analyte, the charged boundary layers, ion diffusion and fluid flow. Combination and analysis of novel numerical discretization schemes, like pressure robust methods for fluid flow and novel finite volume discretization approaches for the PNP system in order to provide physically meaningful numerical models of the double layer structure and its impact on the fluid flow. Use of asymptotic analysis to derive reduced models, which include the relevant features of the complete thermodynamic model in different regimes.
  
  https://www.wias-berlin.de/projects/ECMath-CH11/

• SE17

  Stochastic methods for the analysis of lithium-ion batteries

  Prof.Dr. Jean-Dominique Deuschel / Prof. Dr. Peter Karl Friz / Dr. Clemens Guhlke / Dr. Manuel Landstorfer

  Project heads: Prof.Dr. Jean-Dominique Deuschel / Prof. Dr. Peter Karl Friz / Dr. Clemens Guhlke / Dr. Manuel Landstorfer
  Project members: Dr. Michelle Coghi
  Duration: 01.06.2017 - 31.12.2019
  Status: running
  Located at: Technische Universität Berlin / Weierstraß-Institut
  

  Description

  Currently lithium-ion batteries are the most promising storage devices to store and convert chemical energy into electrical energy. An important class of modern lithium batteries contain electrodes that consist of many nano-particles. During the charging process of a battery, lithium is reversibly stored in the ensemble of the nano-particles and the particles undergo a phase transition from a Li-rich to a Li-poor phase. For this type of batteries a successful mathematical model was developed in the previous ECMath project SE8, based on a stochastic mean field interacting particle system. The new project focuses on modeling, analysis and simulations of extreme conditions in battery operation like fast charging, mostly full/empty discharge states, mechanical stresses within the electrode. The aim of the project is to achieve deeper understanding of the behavior of lithium-ion batteries in extreme conditions.
  
  http://www.wias-berlin.de/projects/ECMath-SE17/