Autonomy in Materials Research: A Case Study in Carbon Nanotube Growth (Postprint)

Abstract

Advances in materials are an important contributor to our technological progress, and yet the process of materials discovery and development itself is slow. Our current research process is human-centered, where human researchers design, conduct, analyze and interpret experiments, and then decide what to do next. We have built an Autonomous Research System (ARES)an autonomous research robot capable of first-of-its-kind closed-loop iterative materials experimentation. ARES exploits advances in autonomous robotics, artificial intelligence, data sciences, and high-throughput and in situ techniques, and is able to design, execute and analyze its own experiments orders of magnitude faster than current research methods. We applied ARES to study the synthesis of single-walled carbon nanotubes, and show that it successfully learned to grow them at targeted growth rates. ARES has broad implications for the future roles of humans and autonomous research robots, and for human-machine partnering. We believe autonomous research robots like ARES constitute a disruptive advance in our ability to understand and develop complex materials at an unprecedented rate.

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Document Details

Document Type
Technical Report
Publication Date
Oct 21, 2016
Accession Number
AD1033362

Entities

People

  • Benji Maruyama
  • Daylond Hooper
  • Frederick Webber
  • Jason Poleski
  • Kevin Decker
  • Michael Krein
  • Pavel Nikolaev
  • Rahul Rao
  • Rick Barto

Organizations

  • Air Force Research Laboratory Materials and Manufacturing Directorate

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Artificial Intelligence
  • Autonomous Systems
  • Autonomy
  • Carbon Nanotubes
  • Case Studies
  • Control Systems
  • Data Mining
  • Data Science
  • Electron Microscopy
  • Fullerenes
  • Materials
  • Materials Science
  • Robotics
  • Robots

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Defense Technology Research and Development.
  • Nanocomposite Materials Science

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy
  • Autonomy
  • Autonomy - Human-Robot Interaction