Picture of the month
Graphite Anode in the drying channel
It has become an integral part of many areas of our lives and is used primarily as a mobile energy storage device in smartphones, notebooks and electric cars: the lithium-ion battery is currently in the focus of science in order to economically and eco-efficiently implement topics such as the energy revolution and the change in propulsion technologies. Our picture of the month was taken in the drying channel of the continuous coating line at Battery LabFactory Braunschweig (BLB). These are the process steps “coating and drying”, two of 18 process steps in total that a lithium-ion battery passes through during production.
In the simplest case, a lithium-ion battery cell consists of two electrodes (anode and cathode), an electrolyte and the separator, which electrically separates the two electrodes from each other. The picture of the month shows a copper foil on which the active electrochemical and passive materials were applied in advance using a comma bar process, i.e. a coating process. This is a graphite anode that represents the negative electrode.
Of the various institutes that are active at BLB, the Institute for Particle Technology deals, among other things, with the process steps of coating and drying. An alternative process that is being investigated at BLB is slot die coating. Besides the advantage of the intermittent coating, a coating with interruptions, the independence of the coating thickness from the properties of the electrode paste is given here.
Drying is a cost-intensive step in all industrial processes. The main focus is on technologies such as infrared drying to increase drying speeds and reduce energy costs. Furthermore, coating errors and binder migration can be avoided through optimized drying, thus reducing material waste.
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Pictures of previous months
Picture of the month October 2019
Klimt, Hundertwasser or who created this psychedelic picture? As a matter of fact, the photo, in which BRICS building can be made out in the background, comes from the Institute for System Safety at the TU Braunschweig. It gives an exciting insight into the world of artificial intelligence. In the photo, the scientists have reinforced the patterns that an artificial neural network “sees” internally. To classify the image as a building, dog or street sign, for example, the network first extracts fine block structures that were reinforced throughout the photo. Later, these are processed internally into more complex patterns, easily recognizable by the dog’s snouts. This example visually shows how we can better understand artificial neural networks before they are implemented, for instance in autonomous driving vehicles. As part of their research at the Institute for System Security, the scientists are investigating the use of artificial intelligence in safety-critical applications. They research how intelligent systems can be trained on the basis of data and thus adapt themselves to new risks. In this way, researchers can, for example, develop new methods for detecting computer malware. However, today’s artificial intelligence methods are themselves vulnerable. Attackers can either manipulate the learning process itself or produce the desired output through targeted manipulation. It has been shown, for example, that by affixing stickers to road signs it is possible to specifically manipulate the recognition of autonomous vehicles. Because of this, the institute scientists are also also investigating the target of artificial
intelligence. A better understanding of the learned interrelationships themselves is a key issue here – similar to how an exam helps to understand what the students have learned from a lecture.
Picture of the month September 2019
Our picture of the month September comes from the new Research Center for Quantum and Nanometrology, “Laboratory for Emerging Nanometrology” (LENA). More precisely, it is a direct view into the sample chamber of one of the large nanoanalytical instruments, the X-ray photoelectron spectrometer (XPS). This is a surface-sensitive technique that allows qualitative and quantitative statements to be made about the chemical elements present on the surface as well as their chemical environment, bonds and oxidation state.
The XPS is used, for example, in biomedical engineering. Within the research group “FOR 2180 Graded Implants”, Sarah Oehmichen from the Institute of Technical Chemistry deals with the surface optimization of polymer-based implants. These are electro-spun fibre mats which have been modified both in a classical chemical way and by plasma treatment. The XPS methodology is used here to prove the success of the respective modification and to better understand and classify results from other investigations, for example from cell tests. This is done with regard to the development of an implant for the tendon-bone transition in the shoulder. Another field of application is battery research, where the analysis of material properties on surfaces and interfaces plays an important role.
The new measurement setup in the LENA is equipped in such a way that scientists can reduce the standard information depth of this technique from 10 nm (with monochromatized Al K-alpha at 1486eV) to the outermost 1-3 nm of the sample surface by angle-resolved measurements or increase it to up to 15-20 nm by using a different anode material. With the help of an Arn+ Gas Cluster ion source, depth profiles can be recorded, which then make it possible to look even deeper into the sample. In addition to XPS, other measurement modes such as UPS, ISS, AES, SEM and SAM are also possible.