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RESEARCH NEWS

27.11.24
A research team led by Patrick Huber of DESY and the Technical University of Hamburg has discovered a surprising phenomenon in a nanoscopic silicate glass with a “nanoscale sponge”.
14.11.24
The Zero C project aims to create necessary conditions in higher education to provide the shipping industry and governmental institutions in Albania and Montenegro.
15.08.24
Modeling Cyber-Physical Systems (CPS) requires knowledge from various domains, including computer science, electrical and mechanical engineering, and control theory. One conventional approach to model CPS is to describe the physical relationships as a classical system of formulas. This requires, a solid understanding of the application domain is required to ensure relevant and accurate models. The behavior of a CPS can be estimated by numerical simulations using e.g. Matlab, Simulink, or Modelica. However, these approaches require that the system’s internals are sufficiently and accurately known, which often is not the case CPS. Thus we employ data driven learning approaches to automatically generate CPS models. We develop Flowcean, which offers a toolbox for modeling CPS from various industrial domains [1]. The project’s consortium spans three distinct application domains, maritime systems, energy grids, and intralogistics, represented by industrial partners KALP GmbH, VIVAVIS AG, SICK AG and KION GROUP AG. The company KALP deploys self-sufficient automated twistlock handling platform based on a hydraulic pressure system. VIVAVIS provides smart IoT solutions especially for the efficient control of smart electricity grids [2]. Associated partners bring further expertise in sensor technology (SICK) and robotics (KION) for intralogistic scenarios [3]. All partners provide either software or hardware solutions to demonstrate how Flowcean can improve testing, operation, and monitoring of CPS. Flowcean applies data driven learning to understand and replicate the individual system behavior. The modeling process is structured into four steps: 1. Loading recorded data or starting a simulation 2. Transforming data to a suitable format 3. Learning models using data driven techniques 4. Evaluating the model’s performance via various metrics Flowcean encompasses both online and offline learning techniques [4],[5]. To be able to model CPS of various domains, the entire pipeline has a modular structure. Thus, each transforming or learning step is composable with others to create distinct pipelines. So far, the design of the framework’s architecture and the implementation of basic examples prove a functioning application. Our upcoming goals are • the analysis of more complex CPS from the domains of the project’s consortium, • finalizing the integration of online and offline learning strategies as well as • the development of tools to use learned models for testing [6], monitoring, or behavioral prediction. Partners: • Fraunhofer Center for Maritime Logistics and Services (CML) • Institute of Embedded Systems, Hamburg University of Technology • Institute of Technical Logistics, Hamburg University of Technology • OFFIS – Institut für Informatik • VIVAVIS AG • KALP GmbH • SICK AG • KION GROUP AG The project is funded by the Federal Ministry of Education and Research (BMBF). Contact: Hendrik Rose & Markus Knitt Institute for Technical Logistics hendrik.wilhelm.rose@tuhh.de, markus.knitt@tuhh.de Maximilian Schmidt & Swantje Plambeck & Görschwin Fey Institute of Embedded Systems maximilian.schmidt@tuhh.de, swantje.plambeck@tuhh.de, goerschwin.fey@tuhh.de Bibliography [1] M. Knitt et al., “Towards the Automatic Generation of Models for Prediction, Monitoring, and Testing of Cyber-Physical Systems”, in International Conference on Emerging Technologies and Factory Automation (ETFA), 2023. [2] L. Fischer, J.-M. Memmen, E. M. S. P. Veith, and M. Tröschel, “Adversarial Resilience Learning - Towards Systemic Vulnerability Analysis for Large and Complex Systems”, ArXiv, 2018. [3] M. Knitt, Y. Elgouhary, J. Schyga, H. Rose, P. Braun, and J. Kreutzfeldt, “Benchmarking for the Indoor Localization of Autonomous Mobile Robots in Intralogistics”, Logistics Journal : Proceedings, no. 1, 2023. [4] J. Schyga, S. Plambeck, J. Hinckeldeyn, G. Fey, and J. Kreutzfeldt, “Decision Trees for Analyzing Influences on the Accuracy of Indoor Localization Systems”, in International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2022. [5] E. Veith et al., “palaestrAI: A Training Ground for Autonomous Agents”, in European Simulation and Modelling Conference (ESM), 2023. [6] S. Plambeck and G. Fey, “Data-Driven Test Generation for Black-Box Systems From Learned Decision Tree Models”, in International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS), 2023.
25.07.24
System-on-Chip (SoC) technology is a driving force behind the growth and advancement of various digital technologies in our daily lives.  Focussing on cyber-physical systems (CPS), the past decade has seen massive growth in demand for different kinds of SoCs, encompassing increased computational power, energy efficiency, and cost-effectiveness. To ensure the reliable functionality of SoC devices, post-silicon validation plays a pivotal role. This is one of the most intricate and costly stages of the SoC design cycle, primarily because the post-silicon validation process generates a large amount of data (e.g. trace files, electrical test reports, oscilloscope images, etc., see Figure 1). While the complexity of SoCs is growing, the amount of test data is growing too and there is pressure to reduce the post-silicon validation time amidst fierce market competition. To overcome this issue, we propose AI (artificial intelligence) for smart post-silicon validation. This is a  collaborative venture between the massively parallel systems group, the smart sensors group, and NXP Hamburg. Our project introduces an AI-powered method to automatically detect anomalies in the test traces and oscilloscope images, which provides several benefits including a reduction in validation time, errors, and accelerated time-to-market. One of the standout features of our models lies in their training on real SoC project data, thanks to NXP Hamburg for the collaboration!  Training our models on 8,044 labeled oscilloscope images—deemed 'good'—we further evaluated their performance using the Reconstruction Error (RCE) metric. Although RCE is a prevalent metric, we introduce the use of Kernel Density Estimate (KDE) to refine anomaly detection accuracy. The decision whether a  given oscilloscipe image is anomalous or not is made by identifying a suitable threshold for the RCE (RCETh) and KDE (KDETh) metrics. Figure 2 shows the model’s performance to detect anomalies in oscilloscope images. Our goal is to minimize false negatives (predicted label 0, actual label 1) to ensure that critical anomalies are not overlooked and reliable SoCs are delivered to users, while simultaneously aiming to maintain false positives (predicted label 1, actual label 0) within an acceptable range to reduce human effort. While the combination of metrics greatly reduces the number of false negatives (68%) compared to using only the RCE metric, our quest remains to drive the false negatives to zero, ensuring airtight SoC reliability.  Our journey unveils the potential for AI to revolutionize the complex and crucial process of post-silicon validation, thus bringing fast and more reliable SoCs to market to meet the growing demands of digitalization of our world by CPS. Contact Info:  Kowshic Ahmed Akash (kowshicahmed.akash@nxp.com)  NXP Hamburg Prof. Dr.-Ing. Sohan Lal (Tel.: +49 40 42878 2037, sohan.lal@tuhh.de)  Massively Parallel Systems Group (E-EXK5) Prof. Dr.-Ing. Ulf Kulau (Tel.: +40 42878 2601, ulf.kulau@tuhh.de) Smart Sensors (E-EXK3) Hamburg University of Technology (TUHH)  Am Schwarzenberg-Campus 3, 21073 Hamburg
10.06.24
Correctly placing hydropower plants in a river is one of many examples where good knowledge of the bottom topography, also called bathymetry, is needed. While direct measurement of the bathymetry is possible, for example with a side scan sonar operated by a boat or an underwater remotely operated vehicle, this is very time consuming and expensive. Therefore, methods that can infer the bathymetry from the easier to measure surface height of the water are attractive. Mathematically speaking, this is an inverse problem where unknown parameters of a system are reconstructed from typically incomplete and noisy measurements of the system state. One approach to solve such inverse problems is so-called partial differential equation constrained optimisation, where system parameters are computed that reproduce the measurements but also satisfy physical constraints like mass or momentum conservation. Researchers from TUHH’s Institute of Mathematics (E-10) and Institute of Mechanics and Ocean Engineering (M-13) as well as from the the Department of Mathematics at the University of Hamburg (UHH) have published a joint paper that provides the first demonstration that this approach can reconstruct a real-world bathymetry. In their experiment, they placed a small hill, manufactured from skate board ramps, at the bottom of a 12 m long wave flume. The water at rest had a depth of 30cm and waves were being generated by a wave flap. Four sensors were installed that measure wave heights. This measured data was used to reconstruct the manufactured bathymetry by numerically solving a minimisation problem with the shallow water equations as constraints. The mathematical algorithm was implemented in Python using the Dedalus software. It could generate a qualitative reconstruction of the hill, even though the change in wave height caused by the bathymetry was only in the range of a few millimetres. Contact: Judith Angel judith.angel(a)tuhh.de Prof. Daniel Ruprecht ruprecht(a)tuhh.de Institute of Mathematics (E-10)
30.05.24
The CRC hosted the third international workshop on "Tailor-made Multiscale Materials Systems" at the TUHH from 15 to 17 May 2024

Research Projects

Kolloquium des Studiendekanats Elektrotechnik, Informatik und Mathematik (EIM)

 

Das Studiendekanat Elektrotechnik, Informatik und Mathematik der Technischen Universität Hamburg (TUHH) freut sich, im Rahmen seines Kolloquiums eine weitere Antrittsvorlesung und einen Forschungsvortrag aus dem Bereich der Betriebssysteme und System-Software mit der gesamten TUHH und mit der Öffentlichkeit zu teilen. Dieses Kolloquium des Dekanats EIM beginnt am

Donnerstag, den 7. April 2022 ab 14:00 Uhr

mit folgendem kurzen Programm:

  • 14:00 Uhr: Antrittsvorlesung „New Directions for Managing Memory“.
    Prof. Christian Dietrich, Operating System Group, Technische Universität Hamburg (TUHH)
  • 14:45 Uhr: A (System-) Software Perspective on Disruptive Hardware Technologies.
    Prof. Olaf Spinczyk, Arbeitsgruppe Eingebettete Softwaresysteme, Universität Osnabrück

Alle Vorträge werden mittels Zoom live für die Öffentlichkeit über das Internet übertragen, interessierte Personen können sich zum Erhalt der Zugangsdaten hier anmelden: https://lists.tuhh.de/sympa/subscribe/kolloq.eim


I3 Junior Project “Merging Computer- and Material Science using Artificial Intelligence”

 

The motivation for this research is to improve the performance of epoxy based lightweight structures in the renewable energy and transportation sector as one factor to meet global climate goals such as the Paris Agreement. Obviously, a reduction of weight results in fewer emissions. In addition, a better understanding and design of composite structures may become a key enablers for new concepts such as electric propulsion flight or structure integrated batteries with a tremendous reduced impact on emissions. In order to use the superior properties of modern fiber-reinforced polymer (FRP) materials, one has to cope as well with the drawback of the highly complex material. To encounter this, our approach is to study the material behavior by a joined material- and computer science study.

Therefore, several thermosetting matrix materials, like epoxy resins, are exposed to different mechanical loads while the material state is characterized using modern infrared spectroscopy devices. The challenge of highly scattered signals and many influencing factors is overcome by combining specific domain knowledge with relevant machine learning algorithms.

(14. März 2022)

Schwimmende Pilotanlage zur Herstellung von Mikroalgen im Harburger Binnenhafen

 

Die gesellschaftlich weitgehend akzeptierten Bestrebungen, den anthropogenen Klimawandel durch Minderung der Klimagasemissionen zu begrenzen und gleichzeitig die Energie- und Rohstoffversorgung nachhaltig und vor allem versorgungssicher auszubauen, stellen große Herausforderungen an Politik, Industrie, Gesellschaft und Wissenschaft. Dies gilt für die Energiewirtschaft und Chemieindustrie ebenso wie für Branchen, die bisher zu einem großen Anteil auf der Basis fossil biogener und fossil mineralischer Rohstoffe wirtschaften. Die Substitution konventioneller – und folglich im Wesentlichen fossiler – Ressourcen und entsprechender Prozesse durch neue biotechnologische Verfahren sowie die Nutzung von nachwachsenden Rohstoffen unterschiedlichster Zusammensetzung und Herkunft gewinnen entsprechend immer mehr an Bedeutung.

(31. Januar 2022)

Kick-Off der ahoi.digital Graduiertenschule sharing.city.college

 

Metropolen rund um den Globus stehen vor großen logistischen, gesellschaftlichen und ökologischen Herausforderungen. Die rasche Urbanisierung, der Klimawandel und der demografische Wandel, konfrontiert mit Ressourcenknappheit in städtischen Gebieten, haben zu verschiedenen Stressfaktoren wie Umweltverschmutzung und Verkehrsstaus geführt, die sich direkt auf die Lebensqualität auswirken.

Die Antwort der Informatik und Technologie auf diese Herausforderungen wird oft als „Smart City“ bezeichnet. Dieses Konzept bezeichnet ein System von Systemen, in dem eine große Menge heterogener Daten, die teilweise von Internet-of-Things (IoT)-Sensoren gesammelt werden, auf intelligente Weise verarbeitet werden, um knappe Ressourcen (wie Grünflächen, Mobilitätsdienste oder Energie) effizient zu verwalten und Dienstleistungen zu schaffen, die die Lebensqualität der Bürger erhöhen.

Eine wichtige Komponente einer Smart City sind die Bürger, d.h. die Nutzer, die nicht nur einen Großteil der Daten generieren und teilen, sondern auch eine zentrale Rolle bei der Gestaltung, Förderung und Versorgung von Smart-City-Systemen und -Diensten spielen. Die Beteiligung der Nutzer an der Gestaltung, Entwicklung und Nutzung von Smart-City-Diensten ist daher entscheidend für eine nachhaltige, datenzentrierte Smart City, die wir sharing.city nennen.

(20. Dezember 2021)

Kolloquium des Studiendekanats Elektrotechnik, Informatik und Mathematik (EIM)

Das Studiendekanat Elektrotechnik, Informatik und Mathematik der Technischen Universität Hamburg (TUHH) freut sich, im Rahmen seines Kolloquiums eine weitere Antrittsvorlesung und einen Forschungsvortrag aus dem Bereich der Security und Kryptographie mit der gesamten TUHH und mit der Öffentlichkeit zu teilen. Dieses Kolloquium des Dekanats EIM beginnt am

Freitag, den 7. Januar 2022 ab 10:30 Uhr

mit folgendem kurzen Programm:

 

  • 10:30 Uhr: Antrittsvorlesung „Security for Safety and Resilience“.
    Prof. Sibylle Fröschle, Institut für Sichere Cyber-Physische Systeme, Technische Universität Hamburg (TUHH)
  • 11:15 Uhr: Post-Quantum Crypto: The Embedded Challenge.
    Dr. Joppe Bos, Senior Principal Cryptographic Researcher, NXP Semiconductors

Alle Vorträge werden mittels Zoom live für die Öffentlichkeit über das Internet übertragen, interessierte Personen können sich zum Erhalt der Zugangsdaten hier anmelden: https://lists.tuhh.de/sympa/subscribe/kolloq.eim

(20. Dezermber 2021)

Kolloquium des Studiendekanats Elektrotechnik, Informatik und Mathematik (EIM)

Das Studiendekanat Elektrotechnik, Informatik und Mathematik der Technischen Universität Hamburg (TUHH) freut sich, im Rahmen seines Kolloquiums eine weitere Antrittsvorlesung und einen Forschungsvortrag aus dem Bereich der Avionik mit der gesamten TUHH und mit der Öffentlichkeit teilen. Dieses Kolloquium des Dekanats EIM beginnt am

Freitag, den 5. November 2021 ab 14:00 Uhr

mit folgendem kurzen Programm:

•   14:00 Uhr: Antrittsvorlesung „Software Security Challenges in the 2020s“.
Prof. Riccardo Scandariato, Institut für Software-Sicherheit, Technische Universität Hamburg (TUHH)

•   14:45 Uhr: Security Above the Clouds – Protecting Aircraft Information Systems.
Dr. Timo Warns, Technical Information Security Consultant, Airbus Hamburg

Alle Vorträge werden mittels Zoom live für die Öffentlichkeit über das Internet übertragen, interessierte Personen können sich zum Erhalt der Zugangsdaten hier anmelden: https://lists.tuhh.de/sympa/subscribe/kolloq.eim

(25. Oktober 2021)

DFG and Fraunhofer fund trilateral projects in the field of knowledge transfer

The German Research Foundation (DFG) and the Fraunhofer Gesellschaft are again funding trilateral projects for the transfer of knowledge from DFG-funded projects to industry. The Joint Committee of the DFG and the Fraunhofer board selected five projects from 16 submitted full proposal applications after an evaluation of the written proposals and an additional online appraisal from this year‘s call for proposals. The new projects, in which universities, Fraunhofer institutes and companies cooperate, are funded by the DFG and the Fraunhofer Gesellschaft with a total of around 4.5 million euros for three years. The three partners should further develop the results of DFG-funded basic research on the basis of a joint work program.

The rights and obligations of the three partners are regulated by a cooperation agreement. This gives companies the opportunity to participate in research innovations at an early stage. The Fraunhofer experts take the lead in the exploitation of the project results for the application partners or for other interested parties. In return, the universities receive a fixed percentage of the proceeds.

Two of the five funded trilateral projects are coordinated on the university side by professors from the TUHH.

(10. September 2021)

Multiagentenbasierte Sensor-/Aktor-Systeme für intelligente Fassaden

Das Bundesministerium für Bildung und Forschung (BMBF) fördert das Verbundprojekt „BioFass“, kurz für „Biologisch inspirierte Fassaden“, das gemeinsam von der Technischen Universität Hamburg und der Bauhaus-Universität Weimar bearbeitet wird. An der TUHH befasst sich das Institut für Digitales und Autonomes Bauen mit „multiagentenbasierten Sensor-/Aktor-Systeme für intelligente Fassaden“. Zusammen mit der Bauhaus-Universität Weimar und dem Industriepartner Fuchs GmbH wird ein intelligentes System zur Verbesserung der Luftqualität durch Effizienzsteigerung von photokatalytisch selbstreinigenden Fassaden entwickelt.

(20. August 2021)

Schwerpunktprogramm „Hundert plus – Verlängerung der Lebensdauer komplexer Baustrukturen durch intelligente Digitalisierung“ (SPP 2388)

 

 Die Deutsche Forschungsgemeinschaft (DFG) hat die Einrichtung des Schwerpunktprogramms „Hundert plus – Verlängerung der Lebensdauer komplexer Baustrukturen durch intelligente Digitalisierung“ beschlossen (SPP 2388). Das Schwerpunktprogramm wurde von Professor Marx (Koordinator, Technische Universität Dresden), Professor Smarsly (Technische Universität Hamburg), Professorin Klemt-Albert (Leibniz Universität Hannover), Professor Geißler (Technische Universität Berlin) und Professor Reiterer (Institut für Nachhaltige Technische Systeme, Albert-Ludwigs-Universität Freiburg) initiiert. Das Schwerpunktprogramm befasst sich mit der Verlängerung der Lebensdauer komplexer Baustrukturen durch intelligente Digitalisierung. Der Zustand eines Bauwerks ist – ähnlich dem von Menschen – mit fortschreitendem Lebensalter von einer immer schneller zunehmenden Degradation geprägt. Vorbeugende Maßnahmen gegen Alterung sind umso erfolgreicher, je eher sie ergriffen werden. 

(05. Juli 2021)

Kolloquium des Studiendekanats Elektrotechnik, Informatik und Mathematik (EIM)

Das Studiendekanat Elektrotechnik, Informatik und Mathematik der Technischen Universität Hamburg (TUHH) freut sich, im Rahmen seines Kolloquiums eine weitere Antrittsvorlesung und einen Forschungsvortrag aus dem Kontext der Hamburg-weiten Informatik-Plattform ahoi.digital mit der gesamten TUHH und mit der Öffentlichkeit teilen. Dieses Kolloquium des Dekanats EIM beginnt am

Freitag, den 16. Juli 2021 ab 10:00 Uhr 

mit folgendem kurzen Programm:

•   10:00 Uhr: Antrittsvorlesung „Zufällige Graphen und komplexe Netzwerke“.
Prof. Dr. Matthias Schulte, Lehrstuhl Stochastik, Institut für Mathematik, Technische Universität Hamburg (TUHH)

•   10:45 Uhr: Statistics and Machine Learning for Speech Enhancement.
Prof. Dr.-Ing. Timo Gerkmann, Arbeitsgruppe Signal Processing, Universität Hamburg (UHH) und ahoi.digital

Alle Vorträge werden mittels Zoom live für die Öffentlichkeit über das Internet übertragen, interessierte Personen können sich zum Erhalt der Zugangsdaten hier anmelden: https://lists.tuhh.de/sympa/subscribe/kolloq.eim

(28. Juni 2021)

Laser pulses make nanomaterials sound

 

Nanostructuring of materials leads to completely new, often surprising properties; this makes them highly interesting for new fields of application and technologies. However, whether these materials can be processed into robust components and thus find their way into applications depends very much on their mechanical properties. These are usually particularly difficult to determine without changing them through the measuring process or even destroying the materials. A German-French research group led by TUHH researchers has now developed a non-contact and non-destructive measurement method using laser ultrasound in such a way that the elastic properties of nanostructured materials can be characterised in detail. They report on their research results in the journal "Nature Communications".

(21. Juni 2021)

Dance of the molecules

Hamburg Scientists investigate nanoscale interfaces for tailor-made materials systems

A Hamburg research team is paving the way for new methods of producing tailor-made materials: for the first time, the scientists from the Hamburg University of Technology (TUHH) and DESY NanoLab have deciphered the collective arrangement of organic acid molecules on an iron oxide surface at the atomic level. The formic acid molecules they studied perform a kind of dance in groups of three on magnetite (Fe3O4), as the team led by Gregor Vonbun-Feldbauer from TUHH and Andreas Stierle from DESY is reporting in The Journal of Physical Chemistry Letters. The work is part of the TUHH’s Collaborative Research Centre 986 “Tailor-Made Multi-Scale Materials Systems (M3)”, which has just been prolonged for another three and a half years.

(31. Mai 2021)

Bridging the Modeling Gap: Huygens' Principle for Brain Implants

 

Human brain implants that can monitor or partially control neuronal activity have been designed and deployed for many years, such as clinic treatments using deep brain stimulation (DBS) and Vagus nerve stimulation for Parkinson's and depression. In the foreseeable future their usage quite likely will increase to a point where brain implants become ubiquitous: not only for changing patients’ life, but also for advancing normal human beings’ thinking and living. With time brain implants will become highly integrated and intelligent devices of ultra-small size, low-power consumption but full abilities of sensing, controlling, data processing, wireless data and power transmission. Because of its importance to human life and health, it is therefore foreseeable that both the electromagnetic (EM) emission from implants into the surrounding brain tissue and the electromagnetic interference with other implants will have to be tightly controlled.

(25. Mai 2021)

Kolloquium des Studiendekanats Elektrotechnik, Informatik und Mathematik (EIM)

Das Studiendekanat Elektrotechnik, Informatik und Mathematik der Technischen Universität Hamburg (TUHH) freut sich, im Rahmen seines Kolloquiums eine weitere Antrittsvorlesung und einen Forschungsvortrag aus dem Kontext der Hamburg-weiten Informatik-Plattform ahoi.digital mit der gesamten TUHH und mit der Öffentlichkeit teilen.

Dieses Kolloquium des Dekanats EIM beginnt am

Dienstag, den 1. Juni 2021 ab 14:00 Uhr

mit folgendem kurzen Programm:

•   14:00 Uhr: Antrittsvorlesung „Algorithmen und Komplexität im Zeitalter datengetriebener Forschung“.
Prof. Dr. Matthias Mnich, Institut für Algorithmen und Komplexität, Technische Universität Hamburg (TUHH)

•   14:45 Uhr: Cross-Modal Sensor Data Acquisition and Processing.
Prof. Dr. Simone Frintrop, Arbeitsgruppe Computer Vision, Universität Hamburg (UHH) und ahoi.digital

Alle Vorträge werden mittels Zoom live für die Öffentlichkeit über das Internet übertragen, interessierte Personen können sich zum Erhalt der Zugangsdaten hier anmelden: https://lists.tuhh.de/sympa/subscribe/kolloq.eim

(19. Mai 2021)

Microbial production of 1,3-propanediol: from laboratory study to industrial application

1, 3-propanediol (1,3-PDO) is an important chemical material used mainly in the production of polyester, e.g., polytrimethylene terephthalate (PTT), but also for the synthesis of pharmaceutical intermediates and as cosmetic ingredient. Realizing highly efficient microbial production of this versatile chemical from raw glycerol, e.g. generated as an abundant byproduct of industrial biodiesel production, is of economic and environmental significance and have drawn vast attentions.
To realize industrial scale microbial production of 1,3-PDO, based on our previous success in producing 1,3-PDO from raw glycerol by a Clostridium pasteurianum wild-type strain under unsterile conditions, adaptive laboratory evolution (ALE) of this strain was applied to obtain a highly efficient and raw glycerol tolerant 1,3-PDO producer strain. This was realized by using a continuous adaptive evolution system that automatically monitors cell growth in real time to determine the cycles of adaptation to the increase in raw glycerol concentration. 

(11. Mai 2021)