Researchers, Cleantech

Name Research interests
Prof. Doron Aurbach
972-3-531-8317
Website
  • High Energy Density Batteries
  • Li batteries
  •  Lithium–Sulfur batteries
  • Li-Air batteries
  • Sodium ion batteries
  • Magnesium batteries
  •  EDLC - Supercapacitors
  • EQCM-D- Advances spectroscopic and nanoscopic measurements of electrochemical systems
  • CDI- Water desalination by electrochemical means
  • Energy storage & Conversion
  • Power Sources for Electrical Vehicles
  • Energy Storage for Load Leveling Applications
  • Load leveling electrorganic Synthesis
  • General Surface and Materials Science
  • Electrochemistry of Carbonaceous Materials
Prof. Ehud Banin
972-3-531-7288
Website

Bacterial Biofilms

Biofilms are microbial communities embedded in a self-produced extracellular polymeric matrix. It is now well recognized that cells undergo profound changes in the transition from free-living to matrix-embedded (biofilm) communities. An important characteristic of microbial biofilms is their innate resistance to immune system- and antibiotic-killing. This has made microbial biofilms a common and difficult-to-treat cause of medical infections. Several chronic infections have been shown to be mediated by biofilms such as the respiratory infections caused by Pseudomonas aeruginosa in the cystic fibrosis (CF) lung and Staphylococcal lesions in endocarditis. Biofilms are also a major cause of infections associated with medical implants mainly by Staphylococcus epidermidisStaphylococcus aureus, and P. aeruginosa. It has been estimated that 65% of the bacterial infections treated in hospitals are caused by bacterial biofilms. Thus, there is an urgent need to discover innovative treatments for biofilm-associated infections. The current understanding of how biofilms develop and how they acquire increased resistance is still in its initial stages. Our research focuses on understanding the basic aspects of the signals and processes involved in biofilm development with a goal of finding new methods of treating biofilm-related infections. The aims are:

1) To characterize how biofilms develop, with a focus on the role of iron as a signal in biofilm development.

2) To understand the mechanisms by which biofilms obtain increased resistance to antimicrobial therapy.

3) To understand the role of inter- and intra-species cell-cell communication in mixed species biofilm interactions.

4) To discover novel compounds that effectively eradicate biofilms.

We implement an array of physiological, biochemical, and genetic tools combined with novel technologies that allow controlled and reproducible biofilm growth to characterize bacterial biofilms and compare them to the non-biofilm communities.

Aharon Gedanken
Prof. Aharon Gedanken
972-3-531-8315
Website
 

Methods for preparing nanomatic materials

Sonochemistry, sonochemistry, the use of microwave radiation and a method called a rupture in which a part of a chemical laboratory becomes an autoclave.

We deal with a variety of uses of materials we have prepared.

Yaari Gur
Prof. Gur Yaari
972-3-738-4625
Website

Computational systems biology:

Using immune repertoires as diagnostic and prognostic tools for diseases.

 

1. Development of nano-technologies (e.g. lab on a chip) for identification of immune repertoire patterns for diagnostics and prognostics of diseases.

2. Computational investigation of antibody-antigen interactions for antibody engineering.

3. Development and usage of advanced machine learning approaches in various fields.

Lab on a chip, investigation of nano-scale interactions and machine learning applications fit well the nano technology field

 

Behind the phenomenal success of the human immune system in fighting countless evolving threats lies its ability to diversify, adapt and form long term memory. Specificity is achieved by the dynamic B cells that undergo affinity maturation in response to antigens. Thus, the antibody repertoire stores information about threats that the body has encountered, and can be harnessed to provide valuable information about diseases. We develop computational pipelines tailored for antibody repertoire analyses, and apply them to samples from different clinical conditions to shed light on new disease mechanisms and improve diagnostics and prognostics.