Artificial Intelligence
Artificial Intelligence Prospective Article
Growing field of materials informatics: databases and artificial intelligence
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- MRS Communications / Volume 10 / Issue 1 / March 2020
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- 14 January 2020, pp. 1-10
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Artificial Intelligence Prospectives
A Bayesian framework for materials knowledge systems
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- MRS Communications / Volume 9 / Issue 2 / 2019
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- 07 May 2019, pp. 518-531
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Monte Carlo tree search for materials design and discovery
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- MRS Communications / Volume 9 / Issue 2 / June 2019
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- 03 May 2019, pp. 532-536
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Challenges and opportunities of polymer design with machine learning and high throughput experimentation
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- MRS Communications / Volume 9 / Issue 2 / 2019
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- 03 May 2019, pp. 537-544
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Automating material image analysis for material discovery
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- MRS Communications / Volume 9 / Issue 2 / 2019
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- 24 April 2019, pp. 545-555
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Machine learning for composite materials
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- MRS Communications / Volume 9 / Issue 2 / 2019
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- 27 March 2019, pp. 556-566
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Artificial Intelligence Research Letters
Exploring effective charge in electromigration using machine learning
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- MRS Communications / Volume 9 / Issue 2 / 2019
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- 27 May 2019, pp. 567-575
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Machine learning prediction of elastic properties and glass-forming ability of bulk metallic glasses
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- MRS Communications / Volume 9 / Issue 2 / June 2019
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- 24 April 2019, pp. 576-585
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Convolutional neural networks for grazing incidence x-ray scattering patterns: thin film structure identification
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- MRS Communications / Volume 9 / Issue 2 / 2019
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- 15 March 2019, pp. 586-592
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Parameterization of empirical forcefields for glassy silica using machine learning
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- MRS Communications / Volume 9 / Issue 2 / June 2019
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- 23 May 2019, pp. 593-599
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CRYSTAL: a multi-agent AI system for automated mapping of materials' crystal structures
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- MRS Communications / Volume 9 / Issue 2 / 2019
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- 24 April 2019, pp. 600-608
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Using convolutional neural networks to predict composite properties beyond the elastic limit
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- MRS Communications / Volume 9 / Issue 2 / 2019
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- 25 April 2019, pp. 609-617
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ESPEI for efficient thermodynamic database development, modification, and uncertainty quantification: application to Cu–Mg
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- MRS Communications / Volume 9 / Issue 2 / 2019
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- 04 June 2019, pp. 618-627
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Designing heterogeneous hierarchical material systems: a holistic approach to structural and materials design
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- MRS Communications / Volume 9 / Issue 2 / 2019
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- 07 June 2019, pp. 628-636
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Artificial Intelligence Prospectives
Deep materials informatics: Applications of deep learning in materials science
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- MRS Communications / Volume 9 / Issue 3 / 2019
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- 13 June 2019, pp. 779-792
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Symbolic regression in materials science
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- MRS Communications / Volume 9 / Issue 3 / September 2019
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- 21 June 2019, pp. 793-805
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Embedding domain knowledge for machine learning of complex material systems
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- MRS Communications / Volume 9 / Issue 3 / September 2019
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- 10 July 2019, pp. 806-820
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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
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- MRS Communications / Volume 9 / Issue 3 / 2019
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- 22 July 2019, pp. 821-838
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An informatics software stack for point defect-derived opto-electronic properties: the Asphalt Project
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- MRS Communications / Volume 9 / Issue 3 / September 2019
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- 02 September 2019, pp. 839-845
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Artificial Intelligence Research Letters
Experiment Specification, Capture and Laboratory Automation Technology (ESCALATE): a software pipeline for automated chemical experimentation and data management
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- MRS Communications / Volume 9 / Issue 3 / September 2019
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- 04 June 2019, pp. 846-859
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