Scroll Top

Dobrynin, Andrey

Andrey Dobrynin

Andrey Dobrynin

Mackenzie Distinguished Professor

   Caudill Laboratories 119
   (919) 962-1580
   avd@email.unc.edu
  Group Website
  Curriculum Vitae


Research Interests

Theoretical/Computational materials chemistry, Polymer and soft matter theory, Physical chemistry


Research Synopsis

My research is focused on development of computational and theoretical models of network and gels, polyelectrolyte solutions and gels, charged polymers at surfaces and interfaces, electrostatic interactions in biological systems, wetting and adhesion, graphene based polymeric materials, nanocomposites, soft-matter physics and biophysics. New directions include development of computer models for 3D printing and advanced additive manufacturing, computationally driven and AI based materials design, statistical data analysis and “big” data visualization. The knowledge gained from these studies impacts numerous areas of Soft Matter and Polymer Science.

Professional Background

Andrey V. Dobrynin is Mackenzie Family Eminent Distinguished Professor of Chemistry. He received B.S. (1987) and Ph.D. (1991) degrees in Polymer Physics from the Moscow Institute of Physics and Technology, Moscow, Russia.

Before joining University of North Carolina at Chapel Hill in summer 2020, he was Alan N. Gent Ohio Research Scholar, Professor of Polymer Science at the College of Polymer Science and Polymer Engineering, University of Akron (2015-2020),  faculty at the Institute of Materials Science, University of Connecticut (2001-2015), served as a Program Director of the Condensed Matter and Materials Theory Program, Division of Materials Research at the  National Science Foundation (2013-2015).

Prof. Dobrynin is a Fellow of the American Physical Society, the American Association for the Advancement of Science, and the Polymer Division, the American Chemical Society and Member of the Connecticut Academy of Science and Engineering.


News & Publications

Herein, we develop a precise additive-free PSA design platform that predictably leverages polymer network architecture to empower comprehensive control over adhesive performance.

 

We studied the viscosity of semidilute aqueous solutions of sodium polystyrenesulfonate as a function of polymer and salt concentrations.

 

Privacy Preferences
When you visit our website, it may store information through your browser from specific services, usually in form of cookies. Here you can change your privacy preferences. Please note that blocking some types of cookies may impact your experience on our website and the services we offer.