Steven J. Koester of Electrical & Computer Engineering, University of Minnesota

Two-dimensional (2D) materials are layered crystals, defined by strong intra-layer covalent bonds and
weak inter-layer van der Waals coupling, that possess many unique and interesting properties. In this
talk, I describe recent advancements on 2D materials, and discuss new device concepts in electronics,
photonics, spintronics and sensing, with a focus on applications where these materials can provide
improved performance or enable new functionality compared to conventional materials. Graphene is a 2D
sheet of sp2-bonded carbon atoms, and while it has limited usefulness for field-effect transistors, graphene
has applications in a wide range of other fields. Graphene is an excellent sensor material due to its high
surface sensitivity, and we have gone beyond conventional sensors and shown that this sensing capability
can be transduced into the wireless domain by utilizing the quantum capacitance effect. More recently,
we have shown that metal-oxide-graphene devices can be used to create atomically sharp “tweezers”
for trapping biomolecules such as DNA at voltages as low as 700 mV, making them suitable for integration
with CMOS readout circuits. We have also developed novel graphene-based spintronic devices, include
devices for hard drive read heads and low-power spin- neuromorphic computing architectures. 2D
semiconductors also have a multitude of uses as integrated electronic and photonic elements. In
particular, we have shown that MoS2, a transition metal dichalcogenide (TMD), is ideal for dynamic
random access memories (DRAMs), where the wide band gap and heavy effective mass make it an ideal
platform for ultra-low leakage access transistors. On the other hand, black phosphorus (BP), with its
narrow band gap and low effective mass is ideal for use in high-speed photodetectors, high-performance
MOSFETs and tunneling field-effect transistors.

Biography:

Dr. Koester received his Ph.D. in 1995 from the University of California, Santa Barbara. From 1997
to 2010 he was a research staff member at the IBM T. J. Watson Research Center and performed
research on a wide variety of electronic and optoelectronic devices, with an emphasis on those utilizing
the Si/SiGe material system. Since 2010, he has been a Professor of Electrical & Computer Engineering
at the University of Minnesota where his research focuses on novel electronic, photonic and sensing
device concepts with an emphasis on 2D materials. Dr. Koester has authored or co-authored over 250
technical publications, conference presentations, and book chapters, and holds 68 United States patents.
He is a Fellow of the IEEE.

Address:University of Minnesota, Electrical & Computer Engineering

Nathaniel C. Cady of Colleges of Nanoscale Science & Engineering, SUNY Polytechnic Institute

Neuromorphic computing systems can achieve learning and adaptation in both software and
hardware. The human brain achieves these functions via modulation of synaptic connections
between neurons. Memristors, which can be implemented as resistive random access memory
(RRAM), are a novel form of non-volatile memory expected to replace a variety of current
memory technologies and enabling the design of new circuit architectures. These devices are a
prime candidate for so-called “synaptic devices” to be used in neuromorphic hardware
implementations. A variety of challenges persist, however, for integrating memristors with
CMOS, as well as for tuning device electrical performance. My research group has developed a
fully CMOS-compatible integration strategy for RRAM-based memristors on a 300mm wafer
platform, which can be implemented in both front end of the line (FEOL) and back end of the
line (BEOL) configurations. With regard to memristor performance, we are focusing on
strategies to reduce stochastic behavior during both binary and analog device switching. This is
a key metric for neuromorphic applications, as variability in device conductance state directly
influences the ultimate number of levels (weights) that can be implemented per synapse.

Biography:

Prof. Nathaniel Cady received his BA and PhD from Cornell University and has been a professor
at SUNY Polytechnic Institute (in Albany, NY) sine 2006. His research spans the fields of biology
and biosensors to nanoelectronics. His current work includes development of biosensors for
Lyme disease diagnosis and nanoelectronics hardware for neuromorphic systems.