Karlsruhe Institute of Technology

About: Karlsruhe Institute of Technology is a education organization based out in Karlsruhe, Germany. It is known for research contribution in the topics: Computer science & Catalysis. The organization has 37946 authors who have published 82138 publications receiving 2197068 citations. The organization is also known as: KIT & University of Karlsruhe.

Polymer-Coated Nanoparticles Interacting with Proteins and Cells: Focusing on the Sign of the Net Charge

Abstract: To study charge-dependent interactions of nanoparticles (NPs) with biological media and NP uptake by cells, colloidal gold nanoparticles were modified with amphiphilic polymers to obtain NPs with identical physical properties except for the sign of the charge (negative/positive). This strategy enabled us to solely assess the influence of charge on the interactions of the NPs with proteins and cells, without interference by other effects such as different size and colloidal stability. Our study shows that the number of adsorbed human serum albumin molecules per NP was not influenced by their surface charge. Positively charged NPs were incorporated by cells to a larger extent than negatively charged ones, both in serum-free and serum-containing media. Consequently, with and without protein corona (i.e., in serum-free medium) present, NP internalization depends on the sign of charge. The uptake rate of NPs by cells was higher for positively than for negatively charged NPs. Furthermore, cytotoxicity assays re...

Modeling Elementary Heterogeneous Chemistry and Electrochemistry in Solid-Oxide Fuel Cells

Abstract: This paper presents a new computational framework for modeling chemically reacting flow in anode-supported solid-oxide fuel cells (SOFC). Depending on materials and operating conditions, SOFC anodes afford a possibility for internal reforming or catalytic partial oxidation of hydrocarbon fuels. An important new element of the model is the capability to represent elementary heterogeneous chemical kinetics in the form of multistep reaction mechanisms. Porous-media transport in the electrodes is represented with a dusty-gas model. Charge-transfer chemistry is represented in a modified Butler-Volmer setting that is derived from elementary reactions, but assuming a single rate-limiting step. The model is discussed in terms of systems with defined flow channels and planar membrane-electrode assemblies. However, the underlying theory is independent of the particular geometry. Examples are given to illustrate the model.

Evaluation and Modeling of the Cell Resistance in Anode-Supported Solid Oxide Fuel Cells

Abstract: The impedance of anode-supported single cells [Ni/8 yttria-stabilized zirconia (YSZ) anode; La 0.58 Sr 0.4 Co 0.2 Fe 0.8 O 3-δ cathode; 8YSZ electrolyte; area 1 cm 2 ] was characterized in a broad measuring range of temperature and air/fuel gas composition. The data has been analyzed by calculating the distribution function of relaxation times (DRTs). DRT computations enabled us to separate five different loss mechanisms occurring inside the cathode and anode without the need of an equivalent circuit. Two processes exhibit a systematic dependency on changes in the oxygen partial pressure of the cathode gas and thus can be attributed to diffusional and electrochemical losses on the cathode side. The remaining three processes are very sensitive to changes in the fuel gas but are not affected by variations of the cathode gas. These resistances are classified as a gas diffusion polarization within the anode-substrate and as an electro-oxidation reaction at the triple-phase boundary, respectively.

Deconvolution of electrochemical impedance spectra for the identification of electrode reaction mechanisms in solid oxide fuel cells

Abstract: The polarization processes occurring at the electrode–electrolyte interfaces of solid oxide fuel cells (SOFC) were investigated by electrochemical impedance spectra measured at single cells under realistic operating conditions. The approach presented is based on distributions of relaxation times which are the basic quantity of interest in electrochemical impedance data analysis. A deconvolution method was developed and implemented that yields these characteristic distribution patterns directly from the impedance spectra. In contrast to nonlinear least squares curve fit of equivalent circuit models, no a priori circuit choice has to be made. Even more importantly, the excellent resolving capacity allows the untangling of the impedance contributions of up to three physically distinct processes within one frequency decade. With the method, processes with the highest polarization losses can be identified and targeted to improve cell performance. Based on the distributions, a general strategy for the identification of the reaction mechanisms is given. The evaluation of the distributions in terms of peak parameters is illustrated by a physical model for oxygen reduction at the SOFC cathode–electrolyte interface. The method is expected to find many applications in electrochemistry beyond the field of solid oxide fuel cell development.