Autonomous experimentation systems for materials development: A community perspective

被引:159
|
作者
Stach, Eric [1 ,2 ]
DeCost, Brian [3 ]
Kusne, A. Gilad [3 ,4 ]
Hattrick-Simpers, Jason [3 ,23 ]
Brown, Keith A. [5 ]
Reyes, Kristofer G. [6 ]
Schrier, Joshua [7 ]
Billinge, Simon [8 ,9 ]
Buonassisi, Tonio [10 ]
Foster, Ian [11 ,12 ]
Gomes, Carla P. [13 ]
Gregoire, John M. [14 ]
Mehta, Apurva [15 ]
Montoya, Joseph [16 ]
Olivetti, Elsa [17 ]
Park, Chiwoo [18 ]
Rotenberg, Eli [19 ]
Saikin, Semion K. [20 ]
Smullin, Sylvia [21 ]
Stanev, Valentin [4 ]
Maruyama, Benji [22 ]
机构
[1] Univ Penn, Dept Mat Sci & Engn, Philadelphia, PA 19104 USA
[2] Univ Penn, Lab Res Struct Matter, Philadelphia, PA 19104 USA
[3] NIST, Gaithersburg, MD 20899 USA
[4] Univ Maryland, Dept Mat Sci & Engn, College Pk, MD 20742 USA
[5] Boston Univ, Dept Mech Engn, Boston, MA 02215 USA
[6] Univ Buffalo, Dept Mat Design & Innovat, Buffalo, NY 14260 USA
[7] Fordham Univ, Dept Chem, Bronx, NY 10458 USA
[8] Columbia Univ, Dept Appl Phys & Appl Math, New York, NY 10027 USA
[9] Brookhaven Natl Lab, Condensed Matter Phys & Mat Sci Dept, Upton, NY 11973 USA
[10] MIT, Dept Mech Engn, Cambridge, MA 02139 USA
[11] Argonne Natl Lab, Data Sci & Learning Div, Lemont, IL 60439 USA
[12] Univ Chicago, Dept Comp Sci, Chicago, IL 60637 USA
[13] Cornell Univ, Dept Comp Sci, Ithaca, NY 14850 USA
[14] CALTECH, Div Engn & Appl Sci, Pasadena, CA 91125 USA
[15] SLAC Natl Accelerator Lab, Stanford Synchrotron Radiat Lightsource, Menlo Pk, CA 94025 USA
[16] Toyota Res Inst, Los Altos, CA 94022 USA
[17] MIT, Dept Mat Sci & Engn, Cambridge, MA 02139 USA
[18] Florida State Univ, Dept Ind & Mfg Engn, Tallahassee, FL 32306 USA
[19] Lawrence Berkeley Natl Lab, Adv Light Source, Berkeley, CA 94720 USA
[20] Kebotix Inc, Cambridge, MA 02139 USA
[21] Form Energy Inc, Somerville, MA 02143 USA
[22] Air Force Res Lab, Mat & Mfg Directorate, Dayton, OH 45433 USA
[23] Univ Toronto, Dept Mat Sci & Engn, Toronto, ON, Canada
基金
美国国家科学基金会;
关键词
ARTIFICIAL-INTELLIGENCE; MATERIALS SCIENCE; MACHINE; OPTIMIZATION; DESIGN; AUTOMATION; EXPLORATION; GENERATION; STABILITY; DISCOVERY;
D O I
10.1016/j.matt.2021.06.036
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Solutions to many of the world's problems depend upon materials research and development. However, advanced materials can take decades to discover and decades more to fully deploy. Humans and robots have begun to partner to advance science and technology orders of magnitude faster than humans do today through the development and exploitation of closed-loop, autonomous experimentation systems. This review discusses the specific challenges and opportunities related to materials discovery and development that will emerge from this new paradigm. Our perspective incorporates input from stakeholders in academia, industry, government laboratories, and funding agencies. We outline the current status, barriers, and needed investments, culminating with a vision for the path forward. We intend the article to spark interest in this emerging research area and to motivate potential practitioners by illustrating early successes. We also aspire to encourage a creative reimagining of the next generation of materials science infrastructure. To this end, we frame future investments in materials science and technology, hardware and software infrastructure, artificial intelligence and autonomy methods, and critical workforce development for autonomous research.
引用
收藏
页码:2702 / 2726
页数:25
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