Marcin Filipiak, Magdalena Flont and Piotr Wisniewski are the authors of proposals that were awarded funding in the SONATA 19 competition of the National Science Centre.

On 24 May 2024, the National Science Centre (Poland) presented ranking lists of projects qualified for funding under competitions announced by the NCN on 15 September 2023: OPUS26 and SONATA 19.

In this edition of the SONATA competition, as many as three projects submitted by scientists from CEZAMAT WUT were selected – Marcin Filipiak, PhD ( Department of Medical Diagnostics), Magdalena Flont, PhD (Department of Medical Biotechnology) and Piotr Wiśniewski, PhD (Department of Intelligent Semiconductor Systems).

Congratulations!

Source: https://www.ncn.gov.pl/konkursy/wyniki/2023-05-24-opus26-sonata19

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Marcin Szymon Filipiak, Overcoming the Debye screening limitation with hybrid graphene-carbon nanotube devices for multi-biomarker diagnostics of sepsis

Field-effect transistors are the basis of all nowadays electronics and have been around for more than 70 years now. It is comprised of three terminals – source and drain with a switchable semiconducting channel in between, and gate. The functioning of a field-effect transistor would be much easier to understand with the water tap analogy. The pipe that delivers the water is the source and the water outlet – drain. The valve can be considered the gate that we can turn and thus control (electric field effect) the water flow (in the FET – electrons and electron holes) from the tap. As the mass production of electronic microchips is well established, researchers are trying to make use of FETs in (bio)chemistry for determining important body parameters – biomarkers specific for a certain disease. The project is aimed at using the hybrid SWCNT/graphene devices to determine the concentrations of biomarkers in parallel and correlate the acquired signal that would help the medical staff to rapidly (within 20 minutes!) and correctly diagnose the patient with sepsis and apply the appropriate therapeutic approach. We expect that with our novel hybrid nanomaterial we will achieve this goal and help decrease the death toll of sepsis.

 

Magdalena Flont, The application of Cell-on-a-chip microsystems to study the course and monitoring of the treatment of peripheral autoimmune demyelinating diseases

The aim of the proposed project is to develop a new cellular model based on human cells of the peripheral nervous system through the use of microfluidic bioanalytical systems. According to statistical data, neurological disorders are the leading cause of disability and the second leading cause of death in the world. The human nervous system is very complex, and despite considerable efforts by scientists, neuroscience still remains one of the most failure-prone areas of research. In response to an important social problem of rare autoimmune demyelinating diseases, also known as peripheral neuropathies (e.g. Guillaina-Barré syndrome, chronic inflammatory demyelinating polyneuropathy, multifocal motor neuropathy) we propose research to create a completely new cellular model that will better mimic the growth conditions and cellular processes occurring in the neural network.

 

Piotr Wiśniewski, Study of properties of silicon-oxide-based RRAM devices for neuromorphic engineering

One of the main problems of modern microelectronics and computer systems dominated by ubiquitous embedded systems is the undesired increase in power dissipation in integrated circuits (IC). It results from the growth of the complexity and operation frequency of IC. By processing large amounts of complex data, modern processors require almost constant communication with external Random Access Memory (RAM). Thus the effective speed of IC is limited and power consumption is increased. Interest in different computing paradigm, allowing for increased performance and reduced power consumption, has been growing for many years. The most efficient processing unit known to mankind is a human brain. In real-time it can perform complicated tasks such as image or speech recognition, or other operations that allow the body to function, with a relatively low power consumption of approximately 20 W. In order to achieve such superior performance, different novel computing paradigms have been tested, e.g., in-memory computing, stochastic computing, and neuromorphic computing. Resistive RAM is an electronic component that shows properties necessary to build such systems. One can alter the structure’s resistance by changing the voltage between electrodes, which is reversible, and the stored information in non-volatile. RRAM structures can be relatively easily fabricated in a crossbar array configuration. This project aims to develop fabrication technology the RRAM structures with silicon oxide as a resistive switching material. Devices will be studied using electrical characterization based mainly on static, small-signal and impulse measurements. On this basis, device models will be developed, its underlying physical phenomena will be investigated and the potential of this technology will be verified.