MatSE News

Sottos Leads Group Working to Improve Lifecycle of Materials

Published Date:December 14, 2016

When most living creatures get hurt, they can self-heal and recover from the injury. But, when damage occurs to inanimate objects, they don’t have that same ability and typically either lose functionality or have their useful lifecycle reduced. Researchers at the Beckman Institute for Advanced Science and Technology are working to change that.

Published Date: December 14, 2016


Winner of the Annual Innovation Award for Outstanding Ph.D. Thesis from Durgam and Subha Chakrapani Family Trust

Published Date:December 14, 2016

The award is in recognition of an outstanding Ph.D. thesis characterized by innovation and potential for commercialization in the field of materials science and engineering.

Published Date: December 14, 2016


Braun Leads Group That Creates Novel Approach for Making 3-D Micro-Optics

Author: Rick Kubetz

Published Date:November 28, 2016

A multi-institutional research collaboration has created a novel approach for fabricating three-dimensional micro-optics through the shape-defined formation of porous silicon (PSi), with broad impacts in integrated optoelectronics, imaging, and photovoltaics.

Published Date: November 28, 2016


Cheng Named A 2016 Fellow of the American Association for the Advancement of Science

Published Date:November 21, 2016

Jianjun Cheng, the Hans Thurnauer Professor of Materials Science and Engineering, was recognized as a 2016 Fellow of the American Associateion for the Advancement of Science “for the discovery, development and clinical translation of nanomedicines and biomaterials, especially for targeted cancer therapies.”

Published Date: November 21, 2016


Ferguson Helps Group Reach Machine-Learning Discovery & Design of Membrane-Active Peptides for Biomedicine

Author: Rick Kubetz

Published Date:November 15, 2016

There are approximately 1100 known antimicrobial peptides (AMP) with diverse sequences that can permeate microbial membranes. To help discover the “blueprint” for natural AMP sequences, researchers from the University of Illinois at Urbana-Champaign - led by assistant professor of materials science and engineering Andrew Ferguson - and the University of California, Los Angeles, have developed a new machine learning approach to discover and design ⍺-helical membrane active peptides based on their physicochemical properties.

Published Date: November 15, 2016