Collection
Artificial Intelligence
- Submission status
- Closed
Papers published in Vol. 9, No. 2 - 4 and Vol. 10, No. 1 of MRS Communications
Editors
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Rigoberto C. Advincula
MRS Communications Editor-in-Chief Case Western Reserve University, USA
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Keith A. Brown
Boston University, USA
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Kristofer Reyes
University at Buffalo, USA
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Sergei V. Kalinin
Oak Ridge National Laboratory, USA
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Ankit Agrawal
Northwestern University, USA
Articles (26 in this collection)
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A picture is worth a thousand words: applying natural language processing tools for creating a quantum materials database map
Authors
- Vineeth Venugopal
- Scott R. Broderick
- Krishna Rajan
- Content type: Artificial Intelligence Research Letter
- Published: 25 September 2019
- Pages: 1134 - 1141
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Artificial neural network correction for density-functional tight-binding molecular dynamics simulations
Authors (first, second and last of 4)
- Junmian Zhu
- Van Quan Vuong
- Stephan Irle
- Content type: Artificial Intelligence Research Letter
- Published: 20 September 2019
- Pages: 867 - 873
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Active-learning and materials design: the example of high glass transition temperature polymers
Authors (first, second and last of 4)
- Chiho Kim
- Anand Chandrasekaran
- Rampi Ramprasad
- Content type: OriginalPaper
- Published: 20 September 2019
- Pages: 860 - 866
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Robocrystallographer: automated crystal structure text descriptions and analysis
Authors
- Alex M. Ganose
- Anubhav Jain
- Content type: Artificial Intelligence Research Letter
- Published: 20 September 2019
- Pages: 874 - 881
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Deep materials informatics: Applications of deep learning in materials science
Authors
- Ankit Agrawal
- Alok Choudhary
- Content type: Artificial Intelligence Prospective
- Open Access
- Published: 20 September 2019
- Pages: 779 - 792
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Symbolic regression in materials science
Authors
- Yiqun Wang
- Nicholas Wagner
- James M. Rondinelli
- Content type: Artificial Intelligence Prospective
- Published: 20 September 2019
- Pages: 793 - 805
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Materials science in the artificial intelligence age: high-throughput library generation, machine learning, and a pathway from correlations to the underpinning physics
Authors (first, second and last of 10)
- Rama K. Vasudevan
- Kamal Choudhary
- Jason Hattrick-Simpers
- Content type: Artificial Intelligence Prospective
- Published: 20 September 2019
- Pages: 821 - 838
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An informatics software stack for point defect-derived opto-electronic properties: the Asphalt Project
Authors (first, second and last of 4)
- Jonathon N. Baker
- Preston C. Bowes
- Douglas L. Irving
- Content type: Artificial Intelligence Prospective
- Published: 20 September 2019
- Pages: 839 - 845
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Experiment Specification, Capture and Laboratory Automation Technology (ESCALATE): a software pipeline for automated chemical experimentation and data management
Authors (first, second and last of 8)
- Ian M. Pendleton
- Gary Cattabriga
- Joshua Schrier
- Content type: Artificial Intelligence Research Letter
- Published: 20 September 2019
- Pages: 846 - 859
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A data ecosystem to support machine learning in materials science
Authors (first, second and last of 8)
- Ben Blaiszik
- Logan Ward
- Ian Foster
- Content type: Artificial Intelligence Research Letter
- Published: 20 September 2019
- Pages: 1125 - 1133
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Embedding domain knowledge for machine learning of complex material systems
Authors
- Christopher M. Childs
- Newell R. Washburn
- Content type: Artificial Intelligence Prospective
- Published: 20 September 2019
- Pages: 806 - 820
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Prediction of new iodine-containing apatites using machine learning and density functional theory
Authors
- Timothy Q. Hartnett
- Mukil V. Ayyasamy
- Prasanna V. Balachandran
- Content type: Artificial Intelligence Research Letter
- Published: 20 September 2019
- Pages: 882 - 890
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Machine learning prediction of accurate atomization energies of organic molecules from low-fidelity quantum chemical calculations
Authors (first, second and last of 6)
- Logan Ward
- Ben Blaiszik
- Larry Curtiss
- Content type: Artificial Intelligence Research Letter
- Published: 20 September 2019
- Pages: 891 - 899
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Monte Carlo tree search for materials design and discovery
Authors (first, second and last of 4)
- Thaer M. Dieb
- Shenghong Ju
- Koji Tsuda
- Content type: Artificial Intelligence Prospective
- Open Access
- Published: 20 June 2019
- Pages: 532 - 536
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Challenges and opportunities of polymer design with machine learning and high throughput experimentation
Authors
- Jatin N. Kumar
- Qianxiao Li
- Ye Jun
- Content type: Artificial Intelligence Prospective
- Published: 20 June 2019
- Pages: 537 - 544
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Designing heterogeneous hierarchical material systems: a holistic approach to structural and materials design
Authors (first, second and last of 6)
- Emily Ryan
- Zoe A. Pollard
- Jillian L. Goldfarb
- Content type: Artificial Intelligence Research Letter
- Published: 20 June 2019
- Pages: 628 - 636
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Parameterization of empirical forcefields for glassy silica using machine learning
Authors (first, second and last of 5)
- Han Liu
- Zipeng Fu
- Mathieu Bauchy
- Content type: Artificial Intelligence Research Letter
- Published: 20 June 2019
- Pages: 593 - 599
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Exploring effective charge in electromigration using machine learning
Authors (first, second and last of 5)
- Yu-chen Liu
- Benjamin Afflerbach
- Dane Morgan
- Content type: Artificial Intelligence Research Letter
- Published: 20 June 2019
- Pages: 567 - 575
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Convolutional neural networks for grazing incidence x-ray scattering patterns: thin film structure identification
Authors (first, second and last of 9)
- Shuai Liu
- Charles N. Melton
- Daniela M. Ushizima
- Content type: Artificial Intelligence Research Letter
- Published: 20 June 2019
- Pages: 586 - 592
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Machine learning for composite materials
Authors
- Chun-Teh Chen
- Grace X. Gu
- Content type: Artificial Intelligence Prospective
- Published: 20 June 2019
- Pages: 556 - 566
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CRYSTAL: a multi-agent AI system for automated mapping of materials’ crystal structures
Authors (first, second and last of 11)
- Carla P. Gomes
- Junwen Bai
- John M. Gregoire
- Content type: Artificial Intelligence Research Letter
- Published: 20 June 2019
- Pages: 600 - 608
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Automating material image analysis for material discovery
Authors
- Chiwoo Park
- Yu Ding
- Content type: Artificial Intelligence Prospective
- Published: 20 June 2019
- Pages: 545 - 555
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A Bayesian framework for materials knowledge systems
Authors
- Surya R. Kalidindi
- Content type: Artificial Intelligence Prospective
- Published: 20 June 2019
- Pages: 518 - 531
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Using convolutional neural networks to predict composite properties beyond the elastic limit
Authors (first, second and last of 4)
- Charles Yang
- Youngsoo Kim
- Grace X. Gu
- Content type: Artificial Intelligence Research Letter
- Published: 20 June 2019
- Pages: 609 - 617
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ESPEI for efficient thermodynamic database development, modification, and uncertainty quantification: application to Cu–Mg
Authors (first, second and last of 6)
- Brandon Bocklund
- Richard Otis
- Zi-Kui Liu
- Content type: Artificial Intelligence Research Letter
- Published: 20 June 2019
- Pages: 618 - 627