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Title: Autonomous experimentation systems for materials development: A community perspective

Journal Article · · Matter (Online)
 [1];  [2];  [2];  [2];  [3];  [4];  [5];  [6];  [7];  [8];  [9];  [10];  [11];  [12];  [7];  [13];  [14];  [15];  [16];  [17] more »;  [18] « less
  1. Univ. of Pennsylvania, Philadelphia, PA (United States)
  2. National Inst. of Standards and Technology (NIST), Gaithersburg, MD (United States)
  3. Boston Univ., MA (United States)
  4. Univ. of Buffalo, NY (United States)
  5. Fordham Univ., The Bronx, NY (United States)
  6. Columbia Univ., New York, NY (United States); Brookhaven National Lab. (BNL), Upton, NY (United States)
  7. Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
  8. Argonne National Lab. (ANL), Argonne, IL (United States); Univ. of Chicago, IL (United States)
  9. Cornell Univ., Ithaca, NY (United States)
  10. California Institute of Technology (CalTech), Pasadena, CA (United States)
  11. SLAC National Accelerator Lab., Menlo Park, CA (United States)
  12. Toyota Research Institute, Los Altos, CA (United States)
  13. Florida State Univ., Tallahassee, FL (United States)
  14. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  15. Kebotix, Inc., Cambridge, MA (United Staets)
  16. The Moonshot Factory, Mountain View, CA (United States)
  17. Univ. of Maryland, College Park, MD (United States)
  18. Air Force Research Lab. (AFRL), Wright-Patterson AFB, OH (United States)

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.

Research Organization:
Argonne National Laboratory (ANL), Argonne, IL (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES); US Air Force Office of Scientific Research (AFOSR); National Science Foundation (NSF); Defense Advanced Research Projects Agency; Camille and Henry Dreyfus Foundation
Grant/Contract Number:
AC02-06CH11357; AC02-05CH11231; 19RXCOR322
OSTI ID:
1823639
Journal Information:
Matter (Online), Vol. 4, Issue 9; ISSN 2590-2385
Publisher:
Cell Press/ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

References (116)

Design of Experiments journal March 1936
A deep convolutional neural network approach to single-particle recognition in cryo-electron microscopy journal July 2017
Active Learning with Statistical Models journal January 1996
Organic synthesis in a modular robotic system driven by a chemical programming language journal November 2018
Deep learning journal May 2015
A data fusion approach to optimize compositional stability of halide perovskites journal April 2021
The collaboratory opportunity journal August 1993
Understanding important features of deep learning models for segmentation of high-resolution transmission electron microscopy images journal July 2020
Making the most of materials computations journal October 2016
Catalyst discovery through megalibraries of nanomaterials journal December 2018
Elucidating the Behavior of Nanophotonic Structures through Explainable Machine Learning Algorithms journal July 2020
Atomate: A high-level interface to generate, execute, and analyze computational materials science workflows journal November 2017
How To Optimize Materials and Devices via Design of Experiments and Machine Learning: Demonstration Using Organic Photovoltaics journal July 2018
Bayesian Hypothesis Testing: a Reference Approach journal December 2002
Robocrystallographer: automated crystal structure text descriptions and analysis journal July 2019
Materials science in the artificial intelligence age: high-throughput library generation, machine learning, and a pathway from correlations to the underpinning physics journal July 2019
Prediction of Nanoscale Friction for Two-Dimensional Materials Using a Machine Learning Approach journal April 2020
Synthetic biology—Engineering nature to make materials journal July 2018
Reconfigurable system for automated optimization of diverse chemical reactions journal September 2018
Self-driving laboratory for accelerated discovery of thin-film materials journal May 2020
Phase Segmentation in Atom-Probe Tomography Using Deep Learning-Based Edge Detection journal December 2019
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play journal December 2018
A framework for data-driven analysis of materials under uncertainty: Countering the curse of dimensionality journal June 2017
Applications of high throughput (combinatorial) methodologies to electronic, magnetic, optical, and energy-related materials journal June 2013
Machine Learning in Materials Discovery: Confirmed Predictions and Their Underlying Approaches journal July 2020
A Bayesian experimental autonomous researcher for mechanical design journal April 2020
Adaptive Optimization of Chemical Reactions with Minimal Experimental Information journal November 2020
Combinatorial search of thermoelastic shape-memory alloys with extremely small hysteresis width journal March 2006
Accelerated Development of Perovskite-Inspired Materials via High-Throughput Synthesis and Machine-Learning Diagnosis journal June 2019
A Brief History of Artificial Intelligence: On the Past, Present, and Future of Artificial Intelligence journal July 2019
Perspectives on The Rise and Fall of American Growth journal May 2016
Opportunities and Challenges for Machine Learning in Materials Science journal July 2020
Integrated computational materials engineering: A new paradigm for the global materials profession journal November 2006
Closing the Advanced Manufacturing Talent Gap journal January 2016
Network analysis of synthesizable materials discovery journal May 2019
Chemical Robotics Enabled Exploration of Stability in Multicomponent Lead Halide Perovskites via Machine Learning journal October 2020
A mobile robotic chemist journal July 2020
Accelerating the discovery of materials for clean energy in the era of smart automation journal April 2018
Beyond Ternary OPV: High‐Throughput Experimentation and Self‐Driving Laboratories Optimize Multicomponent Systems journal April 2020
Machine Ethics: The Design and Governance of Ethical AI and Autonomous Systems [Scanning the Issue] journal March 2019
The Harvard Clean Energy Project: Large-Scale Computational Screening and Design of Organic Photovoltaics on the World Community Grid journal August 2011
Machine learning approaches for the prediction of materials properties journal August 2020
Materials Acceleration Platforms: On the way to autonomous experimentation journal October 2020
A Survey on Deep Transfer Learning book January 2018
New frontiers for the materials genome initiative journal April 2019
Multi-fidelity machine learning models for accurate bandgap predictions of solids journal March 2017
Experiment Specification, Capture and Laboratory Automation Technology (ESCALATE): a software pipeline for automated chemical experimentation and data management journal June 2019
The FAIR Guiding Principles for scientific data management and stewardship journal March 2016
Recent advances and applications of machine learning in solid-state materials science journal August 2019
Reproducible, High-Throughput Synthesis of Colloidal Nanocrystals for Optimization in Multidimensional Parameter Space journal May 2010
Toward autonomous additive manufacturing: Bayesian optimization on a 3D printer journal April 2021
The Automation of Science journal April 2009
Combinatorial discovery of a lead-free morphotropic phase boundary in a thin-film piezoelectric perovskite journal May 2008
Scientific AI in materials science: a path to a sustainable and scalable paradigm journal July 2020
Machine Learning for Structural Materials journal July 2020
Intuition-Enabled Machine Learning Beats the Competition When Joint Human-Robot Teams Perform Inorganic Chemical Experiments journal April 2019
Strengthening advanced manufacturing innovation ecosystems: The case of Massachusetts journal November 2018
Statistical inference and adaptive design for materials discovery journal June 2017
Serendipity: Towards a taxonomy and a theory journal February 2018
Discovery of Wall-Selective Carbon Nanotube Growth Conditions via Automated Experimentation journal October 2014
Machine learning for molecular and materials science journal July 2018
In situ evidence for chirality-dependent growth rates of individual carbon nanotubes journal January 2012
PRISMS: An Integrated, Open-Source Framework for Accelerating Predictive Structural Materials Science journal August 2018
The origins of kriging journal April 1990
ChemOS: An orchestration software to democratize autonomous discovery journal April 2020
Toward “On‐Demand” Materials Synthesis and Scientific Discovery through Intelligent Robots journal February 2020
Active Reaction Control of Cu Redox State Based on Real-Time Feedback from In Situ Synchrotron Measurements journal October 2020
From DFT to machine learning: recent approaches to materials science–a review journal May 2019
A data ecosystem to support machine learning in materials science journal October 2019
Machine Learning for Materials Scientists: An Introductory Guide toward Best Practices journal May 2020
Deep learning microscopy journal January 2017
A robotic platform for flow synthesis of organic compounds informed by AI planning journal August 2019
Machine-Learning-Accelerated Perovskite Crystallization journal April 2020
Local Navigation Strategies for Multi-Robot Exploration: From Simulation to Experimentation with Mini-Robots journal January 2012
Human-level concept learning through probabilistic program induction journal December 2015
The high-throughput highway to computational materials design journal February 2013
Explainable and trustworthy artificial intelligence for correctable modeling in chemical sciences journal October 2020
Machine learning and artificial neural network accelerated computational discoveries in materials science journal November 2019
Evolving the Materials Genome: How Machine Learning Is Fueling the Next Generation of Materials Discovery journal July 2020
Machine learning in materials informatics: recent applications and prospects journal December 2017
Next-Generation Experimentation with Self-Driving Laboratories journal June 2019
Exploration of Near-Infrared-Emissive Colloidal Multinary Lead Halide Perovskite Nanocrystals Using an Automated Microfluidic Platform journal May 2018
Optimal Learning with Local Nonlinear Parametric Models over Continuous Designs journal January 2020
Closed-loop cycles of experiment design, execution, and learning accelerate systems biology model development in yeast journal August 2019
Artificial Chemist: An Autonomous Quantum Dot Synthesis Bot journal June 2020
Using simulation to accelerate autonomous experimentation: A case study using mechanics journal April 2021
Progress and prospects for accelerating materials science with automated and autonomous workflows journal January 2019
Autonomous intelligent agents for accelerated materials discovery journal January 2020
The Materials Genome Initiative, the interplay of experiment, theory and computation journal April 2014
Accelerated discovery of metallic glasses through iteration of machine learning and high-throughput experiments journal April 2018
Strategies for Multifidelity Optimization with Variable Dimensional Hierarchical Models
  • Robinson, Theresa; Eldred, Michael; Willcox, Karen
  • 47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference
    14th AIAA/ASME/AHS Adaptive Structures Conference
    7th
    https://doi.org/10.2514/6.2006-1819
conference June 2012
Synthesis of many different types of organic small molecules using one automated process journal March 2015
A curious formulation robot enables the discovery of a novel protocell behavior journal January 2020
A survey of transfer learning journal May 2016
AIR-Chem: Authentic Intelligent Robotics for Chemistry journal November 2018
Accelerating Materials Development via Automation, Machine Learning, and High-Performance Computing journal August 2018
Commentary: The Materials Project: A materials genome approach to accelerating materials innovation journal July 2013
Nested-Batch-Mode Learning and Stochastic Optimization with An Application to Sequential MultiStage Testing in Materials Science journal January 2015
The phase stability network of all inorganic materials journal February 2020
Artificial intelligence for materials discovery journal July 2019
The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design journal November 2020
Robot-Accelerated Perovskite Investigation and Discovery journal June 2020
Automating material image analysis for material discovery journal April 2019
AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations journal June 2012
On-the-fly closed-loop materials discovery via Bayesian active learning journal November 2020
Fulfilling the promise of the materials genome initiative with high-throughput experimental methodologies journal March 2017
Autonomy in materials research: a case study in carbon nanotube growth journal October 2016
A nanomaterials discovery robot for the Darwinian evolution of shape programmable gold nanoparticles journal June 2020
Machine-learning-assisted materials discovery using failed experiments journal May 2016
Children lose confidence in their potential to “be scientists,” but not in their capacity to “do science” journal March 2019
The Materials Data Facility: Data Services to Advance Materials Science Research journal July 2016
Towards Robot Scientists for autonomous scientific discovery journal January 2010
Planning chemical syntheses with deep neural networks and symbolic AI journal March 2018
The NOMAD laboratory: from data sharing to artificial intelligence journal May 2019
Optimal Learning in Experimental Design Using the Knowledge Gradient Policy with Application to Characterizing Nanoemulsion Stability journal January 2015
SNOBFIT -- Stable Noisy Optimization by Branch and Fit journal July 2008