2020 MRS Spring Meeting

Call for Papers

Symposium S.EL07-Fundamental Mechanisms and Materials Discovery for Brain-Inspired Computing—Theory and Experiment

The human brain provides a highly-efficient model for adaptive learning, information processing, and energy efficient computation. Unlike von Neumann computing architectures, where a central processor fetches data from a separate memory unit, neural elements use distributed, constantly evolving, and interacting weights stored across a dense, highly interconnected network. Efforts to replicate neuromorphic circuitry are reliant on the understanding of the essential materials concepts to achieve this goal, theoretical modeling and simulations of the mechanisms, discovery of new materials, and the design of novel architectures. The goal of this symposium is to bring together theoreticians and experimentalists seeking to elucidate fundamental materials design principles underpinning neuromorphic function with the emerging community of researchers interested in expanding the palette of materials exhibiting neuromorphic functionality. The symposium will focus on the mechanistic origins of memristive behavior spanning the range from atomistic understanding to mesoscale phenomena, encompassing state-of-the-art as well as emerging materials, with a strong emphasis on using simulations and theory to gain in-depth insight and predict new material properties/mechanisms. The symposium will comprise invited lectures from established technical leaders in the field as well as provide opportunities for early career researchers to present their research. The planned symposium will allow for development of a roadmap of this rapidly emerging area that holds promise for revolutionizing information processing.

Topics will include:

  • Design principles and mechanistic underpinnings of memristors: Atomistic descriptors, connecting theory and experiment, operando characterization
  • Deep learning and its implication on materials research
  • Electronic instabilities by design: metal—insulator transition materials
  • Tunable ferroelectric materials with controllable phase-transitions
  • Exploiting inhomogeneities in materials: metallic filaments and ion diffusion
  • Memristive switching and physics for materials discovery for neuromorphic functionality
  • Multiscale modeling of materials for neuromorphic applications
  • Theory of electrically configurable materials including, but not limited to, redox, phase change, ferroelectric, spintronic, 2D electron gas, organic, Mott transition, carbon-based and hybrid materials.
  • Emerging new materials that display neuromorphic characteristics (e.g., transport phenomena in 2D materials)
  • Combining logic and memory using phase change materials
  • Dynamical evolution of internal fields in multiferroic materials and their utilization for logic operations
  • A tutorial complementing this symposium is tentatively planned.

Invited Speakers:

  • Jeehwan Kim (Massachusetts Institute of Technology, USA)
  • Long-Qing Chen (Pennsylvania State University, USA)
  • Deji Akinwande (University of Texas at Austin, USA)
  • Francis Balestra (Université Grenoble Alpes, France)
  • ChunNing Jeanie Lau (The Ohio State University, USA)
  • Qi Liu (Institute of Microelectronics, Chinese Academy of Science, China)
  • Alexander Shluger (University College London, United Kingdom)
  • Susan Troiler-McKinstry (The Pennsylvania State University, USA)
  • Ilia Valov (Forschungszentrum Jülich GmbH, Germany)
  • R. Stanley Wiliams (Texas A&M University, USA)

Symposium Organizers

Sanjini Nanayakkara
National Renewable Energy Laboratory
Materials Science Center

Sarbajit Banerjee
Texas A&M University
Departments of Chemistry and Materials Science and Engineering

Huaqiang Wu
Tsinghua University
Institute of Microelectronics

J. Joshua Yang
University of Southern California

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