Kavli Invited Talk : Solving Global Problems with Fundamental Science

ORAL  · Invited

Abstract

More than five decades ago, President Kennedy exhorted the nation to rise up and meet the biggest challenges of that period, amongst them being the Race to the Moon, that led to the "Moonshot", and the establishment of the Apollo program. It is quite likely that we, as a nation (and the world), are once again at crossroads, from many perspectives. I will use Energy and Computing as a "Clear and Present" example of where we need to rise up and meet the challenges that we are faced with. An area that has not received sufficient attention until recently relates to the exponential growth of electronics, driven by the proliferation of AI and the Internet of Things. A decade ago, we had made some simple calculations and had suggested that it was quite possible that ~20% of primary energy could be used in Computing, globally. More recently, this was also reflected in the Semiconductor Research Corporation's Decadal Report. Thus, there is an urgent need to find pathways to significantly reduce the energy consumption in electronics, mainly logic and memory elements. Although the problems are at the macroscopic global scale, powerful solutions can emerge from fundamental science, as reflected in the transition from bipolar to CMOS in the early 1980's. There is a belief that a similar "transition" is required to enhance the energy efficiency of electronics. In this talk, I will attempt to take you through from the "Macro", global energy economics down to what fundamental materials physics in the form of Quantum Materials can do to help solve the key problems in Energy Efficient Electronics.

*I gratefully acknowledge support from many federal agncies and industry funded projects, specifically : the DOE- Quantum Materials program at LBNL; the NSF-FUSE program through Rice University; and the DARPA-NGMM program. Prior work was supported by the SRC-JUMP program ( ASCENT). Some of my early work on multiferroics was funded by Intel. Funding from Kepler Computing is gratefully acknowledged.

Presenters

  • Ramamoorthy Ramesh

    • University of California, Berkeley

Authors

  • Ramamoorthy Ramesh

    • University of California, Berkeley