Machine learning for materials design and discovery
- Authors:
-
[1];
[2];
[3]
- The Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
- Materials Science and Technology Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
- Department of Materials Science and Engineering, University of Virginia, Charlottesville, Virginia 22904, USA, Department of Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, Virginia 22904, USA
- Publication Date:
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1766106
- Resource Type:
- Publisher's Accepted Manuscript
- Journal Name:
- Journal of Applied Physics
- Additional Journal Information:
- Journal Name: Journal of Applied Physics Journal Volume: 129 Journal Issue: 7; Journal ID: ISSN 0021-8979
- Publisher:
- American Institute of Physics
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Vasudevan, Rama, Pilania, Ghanshyam, and Balachandran, Prasanna V. Machine learning for materials design and discovery. United States: N. p., 2021.
Web. doi:10.1063/5.0043300.
Vasudevan, Rama, Pilania, Ghanshyam, & Balachandran, Prasanna V. Machine learning for materials design and discovery. United States. https://doi.org/10.1063/5.0043300
Vasudevan, Rama, Pilania, Ghanshyam, and Balachandran, Prasanna V. Sun .
"Machine learning for materials design and discovery". United States. https://doi.org/10.1063/5.0043300.
@article{osti_1766106,
title = {Machine learning for materials design and discovery},
author = {Vasudevan, Rama and Pilania, Ghanshyam and Balachandran, Prasanna V.},
abstractNote = {},
doi = {10.1063/5.0043300},
journal = {Journal of Applied Physics},
number = 7,
volume = 129,
place = {United States},
year = {Sun Feb 21 00:00:00 EST 2021},
month = {Sun Feb 21 00:00:00 EST 2021}
}
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1063/5.0043300
https://doi.org/10.1063/5.0043300
Other availability
Search WorldCat to find libraries that may hold this journal
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.
Works referenced in this record:
Lattice constant prediction of A 2 XY 6 cubic crystals (A = K, Cs, Rb, TI; X = tetravalent cation; Y = F, Cl, Br, I) using computational intelligence approach
journal, January 2020
- Alade, Ibrahim Olanrewaju; Olumegbon, Ismail Adewale; Bagudu, Aliyu
- Journal of Applied Physics, Vol. 127, Issue 1
Classification of platinum nanoparticle catalysts using machine learning
journal, July 2020
- Parker, A. J.; Opletal, G.; Barnard, A. S.
- Journal of Applied Physics, Vol. 128, Issue 1
The structural information filtered features (SIFF) potential: Maximizing information stored in machine-learning descriptors for materials prediction
journal, June 2020
- Zeledon, Jorge Arturo Hernandez; Romero, Aldo H.; Ren, Pengju
- Journal of Applied Physics, Vol. 127, Issue 21
Estimating the thermal insulating performance of multi-component refractory ceramic systems based on a machine learning surrogate model framework
journal, June 2020
- Santos, D. P.; Pelissari, P. I. B. G. B.; de Mello, R. F.
- Journal of Applied Physics, Vol. 127, Issue 21
Practicing deep learning in materials science: An evaluation for predicting the formation energies
journal, September 2020
- Huang, Liyuan; Ling, Chen
- Journal of Applied Physics, Vol. 128, Issue 12
Bayesian inference in band excitation scanning probe microscopy for optimal dynamic model selection in imaging
journal, August 2020
- Vasudevan, Rama K.; Kelley, Kyle P.; Eliseev, Eugene
- Journal of Applied Physics, Vol. 128, Issue 5
Application of machine learning methods for predicting new superhard materials
journal, August 2020
- Mazhnik, Efim; Oganov, Artem R.
- Journal of Applied Physics, Vol. 128, Issue 7
Machine Learning for Materials Scientists: An Introductory Guide toward Best Practices
journal, May 2020
- Wang, Anthony Yu-Tung; Murdock, Ryan J.; Kauwe, Steven K.
- Chemistry of Materials, Vol. 32, Issue 12
On representing chemical environments
journal, May 2013
- Bartók, Albert P.; Kondor, Risi; Csányi, Gábor
- Physical Review B, Vol. 87, Issue 18
Active learning in materials science with emphasis on adaptive sampling using uncertainties for targeted design
journal, February 2019
- Lookman, Turab; Balachandran, Prasanna V.; Xue, Dezhen
- npj Computational Materials, Vol. 5, Issue 1
Vibrational detection of delamination in composites using a combined finite element analysis and machine learning approach
journal, September 2020
- Jacobs, Eric W.; Yang, Charles; Demir, Kahraman G.
- Journal of Applied Physics, Vol. 128, Issue 12
Data-driven assessment of chemical vapor deposition grown MoS 2 monolayer thin films
journal, December 2020
- Costine, Anna; Delsa, Paige; Li, Tianxi
- Journal of Applied Physics, Vol. 128, Issue 23
Role of uncertainty estimation in accelerating materials development via active learning
journal, July 2020
- Tian, Yuan; Yuan, Ruihao; Xue, Dezhen
- Journal of Applied Physics, Vol. 128, Issue 1
Machine learning formation enthalpies of intermetallics
journal, September 2020
- Zhang, Zhaohan; Li, Mu; Flores, Katharine
- Journal of Applied Physics, Vol. 128, Issue 10
Refractive index prediction models for polymers using machine learning
journal, June 2020
- Lightstone, Jordan P.; Chen, Lihua; Kim, Chiho
- Journal of Applied Physics, Vol. 127, Issue 21
Machine learning in materials informatics: recent applications and prospects
journal, December 2017
- Ramprasad, Rampi; Batra, Rohit; Pilania, Ghanshyam
- npj Computational Materials, Vol. 3, Issue 1
Small data materials design with machine learning: When the average model knows best
journal, August 2020
- Vanpoucke, Danny E. P.; van Knippenberg, Onno S. J.; Hermans, Ko
- Journal of Applied Physics, Vol. 128, Issue 5
Computer-aided detection and morphological characterization of nanotube layers using scanning electron microscopy images
journal, March 2020
- Ciobanu, Adrian; Luca, Mihaela; Konrad-Soare, Claudia Teodora
- Journal of Applied Physics, Vol. 127, Issue 10
Uncovering electron scattering mechanisms in NiFeCoCrMn derived concentrated solid solution and high entropy alloys
journal, January 2019
- Mu, Sai; Samolyuk, German D.; Wimmer, Sebastian
- npj Computational Materials, Vol. 5, Issue 1
Machine Learning in Materials Discovery: Confirmed Predictions and Their Underlying Approaches
journal, July 2020
- Saal, James E.; Oliynyk, Anton O.; Meredig, Bryce
- Annual Review of Materials Research, Vol. 50, Issue 1
Materials Synthesis Insights from Scientific Literature via Text Extraction and Machine Learning
journal, October 2017
- Kim, Edward; Huang, Kevin; Saunders, Adam
- Chemistry of Materials, Vol. 29, Issue 21
Materials Informatics: Methods, Tools and Applications
September 2019
- Isayev, Olexandr; Tropsha, Alexander; Curtarolo, Stefano
Augmenting machine learning of energy landscapes with local structural information
journal, August 2020
- Honrao, Shreyas J.; Xie, Stephen R.; Hennig, Richard G.
- Journal of Applied Physics, Vol. 128, Issue 8
Opportunities and Challenges for Machine Learning in Materials Science
journal, July 2020
- Morgan, Dane; Jacobs, Ryan
- Annual Review of Materials Research, Vol. 50, Issue 1
Modeling the viscosity of nanofluids using artificial neural network and Bayesian support vector regression
journal, August 2020
- Alade, Ibrahim Olanrewaju; Rahman, Mohd Amiruddin Abd; Hassan, Amjed
- Journal of Applied Physics, Vol. 128, Issue 8
Machine learning 5d-level centroid shift of Ce 3+ inorganic phosphors
journal, July 2020
- Zhuo, Ya; Hariyani, Shruti; You, Shihai
- Journal of Applied Physics, Vol. 128, Issue 1
A machine learning-based model to estimate the density of nanofluids of nitrides in ethylene glycol
journal, May 2020
- Sahaluddin, Mirza; Alade, Ibrahim Olanrewaju; Oyedeji, Mojeed Opeyemi
- Journal of Applied Physics, Vol. 127, Issue 20
Data-Based Methods for Materials Design and Discovery: Basic Ideas and General Methods
journal, March 2020
- Pilania, Ghanshyam; Balachandran, Prasanna V.; Gubernatis, James E.
- Synthesis Lectures on Materials and Optics, Vol. 1, Issue 1
Optimization of depth-graded multilayer structure for x-ray optics using machine learning
journal, August 2020
- Dieb, Sae; Song, Zhilong; Yin, Wan-Jian
- Journal of Applied Physics, Vol. 128, Issue 7
Inverse design of acoustic metamaterials based on machine learning using a Gauss–Bayesian model
journal, October 2020
- Zheng, Bin; Yang, Jing; Liang, Bin
- Journal of Applied Physics, Vol. 128, Issue 13
Deep learning in heterogeneous materials: Targeting the thermo-mechanical response of unidirectional composites
journal, May 2020
- Chen, Qiang; Tu, Wenqiong; Ma, Meng
- Journal of Applied Physics, Vol. 127, Issue 17
Transferability of neural network potentials for varying stoichiometry: Phonons and thermal conductivity of Mn x Ge y compounds
journal, June 2020
- Mangold, Claudia; Chen, Shunda; Barbalinardo, Giuseppe
- Journal of Applied Physics, Vol. 127, Issue 24
Image-driven discriminative and generative machine learning algorithms for establishing microstructure–processing relationships
journal, October 2020
- Ma, W.; Kautz, E. J.; Baskaran, A.
- Journal of Applied Physics, Vol. 128, Issue 13
Multi-fidelity machine learning models for accurate bandgap predictions of solids
journal, March 2017
- Pilania, G.; Gubernatis, J. E.; Lookman, T.
- Computational Materials Science, Vol. 129
Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
journal, July 2013
- Jain, Anubhav; Ong, Shyue Ping; Hautier, Geoffroy
- APL Materials, Vol. 1, Issue 1
Deep materials informatics: Applications of deep learning in materials science
journal, June 2019
- Agrawal, Ankit; Choudhary, Alok
- MRS Communications, Vol. 9, Issue 3
Spectral neural network potentials for binary alloys
journal, July 2020
- Zagaceta, David; Yanxon, Howard; Zhu, Qiang
- Journal of Applied Physics, Vol. 128, Issue 4
Super-resolution and signal separation in contact Kelvin probe force microscopy of electrochemically active ferroelectric materials
journal, August 2020
- Ziatdinov, Maxim; Kim, Dohyung; Neumayer, Sabine
- Journal of Applied Physics, Vol. 128, Issue 5
Recent advances and applications of machine learning in solid-state materials science
journal, August 2019
- Schmidt, Jonathan; Marques, Mário R. G.; Botti, Silvana
- npj Computational Materials, Vol. 5, Issue 1
Extreme learning machine and support vector regression wear loss predictions for magnesium alloys coated using various spray coating methods
journal, May 2020
- Gurgenc, Turan; Altay, Osman; Ulas, Mustafa
- Journal of Applied Physics, Vol. 127, Issue 18
Screening billions of candidates for solid lithium-ion conductors: A transfer learning approach for small data
journal, June 2019
- Cubuk, Ekin D.; Sendek, Austin D.; Reed, Evan J.
- The Journal of Chemical Physics, Vol. 150, Issue 21
Feature engineering of material structure for AI-based materials knowledge systems
journal, July 2020
- Kalidindi, Surya R.
- Journal of Applied Physics, Vol. 128, Issue 4
Emerging materials intelligence ecosystems propelled by machine learning
journal, November 2020
- Batra, Rohit; Song, Le; Ramprasad, Rampi
- Nature Reviews Materials
Adaptive machine learning for efficient materials design
journal, July 2020
- Balachandran, Prasanna V.
- MRS Bulletin, Vol. 45, Issue 7
Deep neural networks for understanding noisy data applied to physical property extraction in scanning probe microscopy
journal, February 2019
- Borodinov, Nikolay; Neumayer, Sabine; Kalinin, Sergei V.
- npj Computational Materials, Vol. 5, Issue 1
Data Preprocessing in Data Mining
book, January 2015
- García, Salvador; Luengo, Julián; Herrera, Francisco
- Intelligent Systems Reference Library, Vol. 72
Machine learning for molecular and materials science
journal, July 2018
- Butler, Keith T.; Davies, Daniel W.; Cartwright, Hugh
- Nature, Vol. 559, Issue 7715
I.—Computing Machinery and Intelligence
journal, October 1950
- Turing, A. M.
- Mind, Vol. LIX, Issue 236
3-D Inorganic Crystal Structure Generation and Property Prediction via Representation Learning
journal, August 2020
- Court, Callum J.; Yildirim, Batuhan; Jain, Apoorv
- Journal of Chemical Information and Modeling, Vol. 60, Issue 10
A machine learning based approach for phononic crystal property discovery
journal, July 2020
- Sadat, Seid M.; Wang, Robert Y.
- Journal of Applied Physics, Vol. 128, Issue 2
Machine learning substitutional defect formation energies in ABO 3 perovskites
journal, July 2020
- Sharma, Vinit; Kumar, Pankaj; Dev, Pratibha
- Journal of Applied Physics, Vol. 128, Issue 3