2019 MRS Spring Meeting & Exhibit

MRS Postdoctoral Awards

The MRS Postdoctoral Awards recognize postdoctoral scholars who show exceptional promise that may include, for example, excellence in scientific research, leadership, advocacy, outreach, or teaching during their postdoc assignment.

MRS acknowledges the Jiang Family Foundation and MTI Corporation for their generous contribution to support this award.

Kaifu Bian

Kaifu Bian
Sandia National Laboratories

for advancing the understanding of nanoparticle assemblies under stress” 

Nicholas Jackson

Nicholas E. Jackson
Argonne National Laboratory

"for foundational theoretical and computational contributions to the study of structure and transport in charged polymers and organic semiconductors” 

About Kaifu Bian

Kaifu Bian is a postdoctoral researcher in the Advanced Material Laboratory at Sandia National Laboratories, under the supervision and guidance of Hongyou Fan. Previously, Bian completed his PhD degree in chemical engineering and material science under the advisory of Professor Tobias Hanrath at Cornell University. 

Bian's research focuses on the exploration of the relationships between processing, structure and properties of self-assembled nanoparticles, especially under stress. During postdoc research, he further advanced the stress-induced synthesis method for high-dimensional nanostructures, which was originally invented by Fan's group. As reported by Science Advance, his work led to the fabrication of CdSe nanowires with high luminescence not achievable by traditional synthesis.

About Nicholas E. Jackson

Nicholas E. Jackson is a Postdoctoral Fellow in the Materials Science Division at Argonne National Laboratory, advised by Professor Juan de Pablo. In 2016, Jackson received his PhD degree in chemistry from Northwestern University, studying the formation of optoelectronic networks in organic semiconductors with Professors Mark Ratner and Lin Chen. He obtained a BA degree in physics from Wesleyan University in 2011.

Jackson is interested in the multiscale modeling of soft matter, with a focus on optically, electronically and ionically functional soft materials. His multiscale theoretical and computational research spans quantum-mechanical, coarse-grained and mesoscopic modeling techniques. Currently, his research concerns the development and application of hybrid machine learning and statistical mechanical methodologies to describe structural and conductivity phenomena in charged and semiconducting polymers.