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Obnovit | RAW

Institute of Physics of the CAS, v.v.i.

List of available PhD theses

Hybrid nanosctructured lithium - ion batteries

Department: Department of Physics and Measurement, Faculty of Chemical Engineering
Theses supervisor: RNDr. Pavel Galář, Ph.D.

Annotation

Current rapid developments in wearable electronics, production of electric energy from renewable sources, electric vehicles and other applications emphasizes increasing demands on the energy storage. While the standard lithium-ion batteries (LIB) seem to reach their maximum, new structural solutions are needed. As one of the most promising anode material for LIB technology is considered to be silicon. Silicon based anode has potential to increase storage capacity of the batteries about ten times in contrast to commonly used graphite. Unfortunately the silicon expands its volume by more than 300% during lithium charging that cause significant structural fractures and thus limits application of bulk silicon in LIB technology. The goal of this work is to study the applicability of nanostructured silicon as a part of LIB anodes and advanced flexible organic materials as electrode scaffold materials that would be electrochemically stable, highly conductive and strong and elastic enough to withstand the nanocrystal expansion.

Integration of metabolomics data into metabolic pathways

Department: Department of Informatics and Chemistry, Faculty of Chemical Technology
Study programme: Bioinformatika
Theses supervisor: Mgr. Michal Kolář, Ph.D.

Annotation

Metabolomics provides information on metabolite concentrations and is functionally closest to the biological manifestations of the genome and proteome. Although the individual omics follow each other logically, each of these scientific fields is at a different level of knowledge.
The aim is to develop a specific approach by which metabolomic data (metabolite concentrations) will be processed into the format of metabolic pathways (Wikipathways, SMPDB, etc.), and their integration with proteomic and genomic data. Part of the work is understanding the concept of LC-MS metabolomics, annotation of metabolites according to databases, work with metabolite identifiers at various levels of identification (summary formula, exact structure, ...), scripts and applications in Python and R, visualization of pathways from databases and based on own designs.
Using the resulting methodology, omic projects based on clinical studies and animal models will be processed. The work will be carried out at the FGÚ AV ČR, where the metabolomics and proteomics service laboratory is located. The work is financially secured.
Prerequisite for success is knowledge of programming languages for data mining (Python, R), basics of biochemistry (metabolites, pathways, cell compartments) and basics in omic disciplines.


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