Learning from metastable symmetric-tilt grain boundaries using physics-based descriptors

Mishra, Avanish; Suresh, Sumit Athikavil; Fensin, Saryu Jindal; Mathew, Nithin; Kober, Edward Martin

doi:10.1103/physrevmaterials.8.123605

Title: Learning from metastable symmetric-tilt grain boundaries using physics-based descriptors

Journal Article · 22 December 2024 · Physical Review Materials

DOI: https://doi.org/10.1103/physrevmaterials.8.123605 · OSTI ID:2496657

^[1];

^[1]

Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Grain boundaries (GBs) govern critical properties of polycrystalline materials. Although significant advancements have been made in characterizing minimum energy and ordered GBs, real GBs are seldom found in such well-defined states. This diversity of atomic arrangements in metastable states makes it challenging to establish structure-property relationships with physical insights. Here, to address this challenge, we use data-driven methods to explore these relationships and examine the underlying physics. In this study, we utilize a large atomistic database (~5000) of minimum energy and metastable states of symmetric-tilt copper GBs, combined with physically motivated local atomic environment (LAE) descriptors [strain functional descriptors (SFDs)], to predict GB properties and gain physical insights. Our regression models exhibit robust predictive capabilities using only 19 descriptors, generalizing to atomic environments in nanocrystals. A significant highlight of our work is the integration of an unsupervised method with SFDs to elucidate LAEs at GBs and their role in determining properties. The model, trained on these minimum energy and metastable GBs using SFDs, predicts the properties of unseen nanocrystals with good accuracy. Our research underscores the role of a physics-based representation of LAEs and the efficacy of data-driven methods in establishing GB structure-property relationships.

View Accepted Manuscript (DOE)

Cite

Export

Save

Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE Laboratory Directed Research and Development (LDRD) Program; USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: 89233218CNA000001

OSTI ID:: 2496657

Report Number(s):: LA-UR--22-32270

Journal Information:: Physical Review Materials, Journal Name: Physical Review Materials Journal Issue: 12 Vol. 8; ISSN 2475-9953

Publisher:: American Physical Society (APS)Copyright Statement

Country of Publication:: United States

Language:: English

References (71)

Fast Parallel Algorithms for Short-Range Molecular Dynamics Plimpton, Steve Journal of Computational Physics, Vol. 117, Issue 1 https://doi.org/10.1006/jcph.1995.1039	journal	March 1995
Gaussian Mixture Models Reynolds, Douglas Encyclopedia of Biometrics https://doi.org/10.1007/978-0-387-73003-5_196	book	January 2009
Data-driven prediction of the mechanical behavior of nanocrystalline graphene using a deep convolutional neural network with PCA Shin, Wonjun; Jang, Seongwoo; Hwang, Yunhyoung Engineering with Computers https://doi.org/10.1007/s00366-024-02074-z	journal	October 2024
Weld decay-resistant austenitic stainless steel by grain boundary engineering Kokawa, H. Journal of Materials Science, Vol. 40, Issue 4 https://doi.org/10.1007/s10853-005-6511-6	journal	February 2005
Grain boundary energy anisotropy: a review Rohrer, Gregory S. Journal of Materials Science, Vol. 46, Issue 18 https://doi.org/10.1007/s10853-011-5677-3	journal	September 2011
The spectrum of atomic excess free volume in grain boundaries Pal, Snehanshu; Reddy, K. Vijay; Yu, Tingting Journal of Materials Science, Vol. 56, Issue 19 https://doi.org/10.1007/s10853-021-06028-4	journal	March 2021
Applications for grain boundary engineered materials Palumbo, G.; Lehockey, E. M.; Lin, P. JOM, Vol. 50, Issue 2 https://doi.org/10.1007/s11837-998-0248-z	journal	February 1998
A coincidence — Ledge — Dislocation description of grain boundaries Bishop, G. H.; Chalmers, B. Scripta Metallurgica, Vol. 2, Issue 2 https://doi.org/10.1016/0036-9748(68)90085-9	journal	February 1968
A read-shockley model for high-angle grain boundaries Wolf, D. Scripta Metallurgica, Vol. 23, Issue 10 https://doi.org/10.1016/0036-9748(89)90348-7	journal	October 1989
On the structural unit/grain boundary dislocation model for grain boundary structure Balluffi, R. W.; Bristowe, P. D. Surface Science, Vol. 144, Issue 1 https://doi.org/10.1016/0039-6028(84)90701-5	journal	August 1984
Structure-energy correlation for grain boundaries in F.C.C. metals—III. Symmetrical tilt boundaries Wolf, D. Acta Metallurgica et Materialia, Vol. 38, Issue 5 https://doi.org/10.1016/0956-7151(90)90030-K	journal	May 1990
Relation between ductility and grain boundary character distributions in Ni3Al Chiba, A.; Hanada, S.; Watanabe, S. Acta Metallurgica et Materialia, Vol. 42, Issue 5 https://doi.org/10.1016/0956-7151(94)90383-2	journal	May 1994
Influence of grain boundary character distribution on sensitization and intergranular corrosion of alloy 600 Lin, P.; Palumbo, G.; Erb, U. Scripta Metallurgica et Materialia, Vol. 33, Issue 9 https://doi.org/10.1016/0956-716X(95)00420-Z	journal	November 1995
Enhanced specific grain boundary conductivity in nanocrystalline Y2O3-stabilized zirconia Mondal, P. Solid State Ionics, Vol. 118, Issue 3-4 https://doi.org/10.1016/S0167-2738(98)00452-4	journal	March 1999
On improving the corrosion and growth resistance of positive Pb-acid battery grids by grain boundary engineering Lehockey, E. M.; Limoges, D.; Palumbo, G. Journal of Power Sources, Vol. 78, Issue 1-2 https://doi.org/10.1016/S0378-7753(99)00015-4	journal	March 1999
A dislocation-based description of grain boundary dissociation: application to a 90° 〈110〉 tilt boundary in gold Medlin, D. L.; Foiles, S. M.; Cohen, D. Acta Materialia, Vol. 49, Issue 18 https://doi.org/10.1016/S1359-6454(01)00284-1	journal	October 2001
Interfacial thermal resistance in nanocrystalline yttria-stabilized zirconia Yang, Ho-Soon; Bai, G. -R.; Thompson, L. J. Acta Materialia, Vol. 50, Issue 9 https://doi.org/10.1016/S1359-6454(02)00057-5	journal	May 2002
Optimization of grain boundary character distribution for intergranular corrosion resistant 304 stainless steel by twin-induced grain boundary engineering Shimada, M.; Kokawa, H.; Wang, Z. J. Acta Materialia, Vol. 50, Issue 9 https://doi.org/10.1016/S1359-6454(02)00064-2	journal	May 2002
Improvement in the ductility of molybdenum alloys due to grain boundary segregation Miller, M. K.; Kenik, E. A.; Mousa, M. S. Scripta Materialia, Vol. 46, Issue 4 https://doi.org/10.1016/S1359-6462(01)01242-8	journal	February 2002
Enhanced ductility of nanomaterials through optimization of grain boundary sliding and diffusion processes Ovid’ko, I. A.; Sheinerman, A. G. Acta Materialia, Vol. 57, Issue 7 https://doi.org/10.1016/j.actamat.2009.01.030	journal	April 2009
Grain-boundary engineering markedly reduces susceptibility to intergranular hydrogen embrittlement in metallic materials Bechtle, S.; Kumar, M.; Somerday, B. P. Acta Materialia, Vol. 57, Issue 14 https://doi.org/10.1016/j.actamat.2009.05.012	journal	August 2009
Grain boundary energy function for fcc metals Bulatov, Vasily V.; Reed, Bryan W.; Kumar, Mukul Acta Materialia, Vol. 65 https://doi.org/10.1016/j.actamat.2013.10.057	journal	February 2014
Control of grain boundary connectivity based on fractal analysis for improvement of intergranular corrosion resistance in SUS316L austenitic stainless steel Kobayashi, Shigeaki; Kobayashi, Ryosuke; Watanabe, Tadao Acta Materialia, Vol. 102 https://doi.org/10.1016/j.actamat.2015.08.075	journal	January 2016
The grain-boundary structural unit model redux Han, Jian; Vitek, Vaclav; Srolovitz, David J. Acta Materialia, Vol. 133 https://doi.org/10.1016/j.actamat.2017.05.002	journal	July 2017
Grain boundary properties of elemental metals Zheng, Hui; Li, Xiang-Guo; Tran, Richard Acta Materialia, Vol. 186 https://doi.org/10.1016/j.actamat.2019.12.030	journal	March 2020
Examination of computed aluminum grain boundary structures and energies that span the 5D space of crystallographic character Homer, Eric R.; Hart, Gus L. W.; Braxton Owens, C. Acta Materialia, Vol. 234 https://doi.org/10.1016/j.actamat.2022.118006	journal	August 2022
Sensitivity of Dislocation-GB interactions to simulation setups in atomistic models Suresh, Sumit; Dang, Khanh; Fensin, Saryu J. Computational Materials Science, Vol. 221 https://doi.org/10.1016/j.commatsci.2023.112085	journal	March 2023
Atomsk: A tool for manipulating and converting atomic data files Hirel, Pierre Computer Physics Communications, Vol. 197 https://doi.org/10.1016/j.cpc.2015.07.012	journal	December 2015
LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales Thompson, Aidan P.; Aktulga, H. Metin; Berger, Richard Computer Physics Communications, Vol. 271 https://doi.org/10.1016/j.cpc.2021.108171	journal	February 2022
Spectral neighbor analysis method for automated generation of quantum-accurate interatomic potentials Thompson, A. P.; Swiler, L. P.; Trott, C. R. Journal of Computational Physics, Vol. 285 https://doi.org/10.1016/j.jcp.2014.12.018	journal	March 2015
Mechanical properties of nanocrystalline materials Meyers, M. A.; Mishra, A.; Benson, D. J. Progress in Materials Science, Vol. 51, Issue 4 https://doi.org/10.1016/j.pmatsci.2005.08.003	journal	May 2006
Hall–Petch relation and boundary strengthening Hansen, Niels Scripta Materialia, Vol. 51, Issue 8 https://doi.org/10.1016/j.scriptamat.2004.06.002	journal	October 2004
Molecular dynamics study of melting and freezing of small Lennard-Jones clusters Honeycutt, J. Dana.; Andersen, Hans C. The Journal of Physical Chemistry, Vol. 91, Issue 19, p. 4950-4963 https://doi.org/10.1021/j100303a014	journal	September 1987
Thermal transport across Twin Grain Boundaries in Polycrystalline Graphene from Nonequilibrium Molecular Dynamics Simulations Bagri, Akbar; Kim, Sang-Pil; Ruoff, Rodney S. Nano Letters, Vol. 11, Issue 9 https://doi.org/10.1021/nl202118d	journal	September 2011
High-performance bulk thermoelectrics with all-scale hierarchical architectures Biswas, Kanishka; He, Jiaqing; Blum, Ivan D. Nature, Vol. 489, Issue 7416, p. 414-418 https://doi.org/10.1038/nature11439	journal	September 2012
High-performance thermoelectric nanocomposites from nanocrystal building blocks Ibáñez, Maria; Luo, Zhishan; Genç, Aziz Nature Communications, Vol. 7, Issue 1 https://doi.org/10.1038/ncomms10766	journal	March 2016
Quantitative prediction of grain boundary thermal conductivities from local atomic environments Fujii, Susumu; Yokoi, Tatsuya; Fisher, Craig A. J. Nature Communications, Vol. 11, Issue 1 https://doi.org/10.1038/s41467-020-15619-9	journal	April 2020
Learning grain boundary segregation energy spectra in polycrystals Wagih, Malik; Larsen, Peter M.; Schuh, Christopher A. Nature Communications, Vol. 11, Issue 1 https://doi.org/10.1038/s41467-020-20083-6	journal	December 2020
A three-dimensional polyhedral unit model for grain boundary structure in fcc metals Banadaki, Arash Dehghan; Patala, Srikanth npj Computational Materials, Vol. 3, Issue 1 https://doi.org/10.1038/s41524-017-0016-0	journal	March 2017
Discovering the building blocks of atomic systems using machine learning: application to grain boundaries Rosenbrock, Conrad W.; Homer, Eric R.; Csányi, Gábor npj Computational Materials, Vol. 3, Issue 1 https://doi.org/10.1038/s41524-017-0027-x	journal	August 2017
A machine learning approach to model solute grain boundary segregation Huber, Liam; Hadian, Raheleh; Grabowski, Blazej npj Computational Materials, Vol. 4, Issue 1 https://doi.org/10.1038/s41524-018-0122-7	journal	November 2018
Grain Boundary Plane Orientation Fundamental Zones and Structure-Property Relationships Homer, Eric R.; Patala, Srikanth; Priedeman, Jonathan L. Scientific Reports, Vol. 5, Issue 1 https://doi.org/10.1038/srep15476	journal	October 2015
Data-driven prediction of grain boundary segregation and disordering in high-entropy alloys in a 5D space Hu, Chongze; Luo, Jian Materials Horizons, Vol. 9, Issue 3 https://doi.org/10.1039/D1MH01204E	journal	January 2022
Nonrandom percolation behavior of grain boundary networks in high-Tc superconductors Frary, M.; Schuh, C. A. Applied Physics Letters, Vol. 83, Issue 18 https://doi.org/10.1063/1.1624490	journal	November 2003
Influence of grain boundary properties on spall strength: Grain boundary energy and excess volume Fensin, S. J.; Valone, S. M.; Cerreta, E. K. Journal of Applied Physics, Vol. 112, Issue 8 https://doi.org/10.1063/1.4761816	journal	October 2012
Extending the accuracy of the SNAP interatomic potential form Wood, Mitchell A.; Thompson, Aidan P. The Journal of Chemical Physics, Vol. 148, Issue 24 https://doi.org/10.1063/1.5017641	journal	June 2018
Understanding and predicting damage and failure at grain boundaries in BCC Ta Chen, J.; Hahn, E. N.; Dongare, A. M. Journal of Applied Physics, Vol. 126, Issue 16 https://doi.org/10.1063/1.5111837	journal	October 2019
A dendrite method for cluster analysis Calinski, T.; Harabasz, J. Communications in Statistics - Theory and Methods, Vol. 3, Issue 1 https://doi.org/10.1080/03610927408827101	journal	January 1974
On the structural unit model of grain boundary structure Sutton, A. P. Philosophical Magazine Letters, Vol. 59, Issue 2 https://doi.org/10.1080/09500838908214777	journal	February 1989
The Deformation and Ageing of Mild Steel: III Discussion of Results Hall, E. O. Proceedings of the Physical Society. Section B, Vol. 64, Issue 9 https://doi.org/10.1088/0370-1301/64/9/303	journal	September 1951
Robust structural identification via polyhedral template matching Larsen, Peter Mahler; Schmidt, Søren; Schiøtz, Jakob Modelling and Simulation in Materials Science and Engineering, Vol. 24, Issue 5 https://doi.org/10.1088/0965-0393/24/5/055007	journal	May 2016
A machine learning framework for the prediction of grain boundary segregation in chemically complex environments Aksoy, Doruk; Luo, Jian; Cao, Penghui Modelling and Simulation in Materials Science and Engineering, Vol. 32, Issue 6 https://doi.org/10.1088/1361-651X/ad585f	journal	June 2024
Dislocation Models of Crystal Grain Boundaries Read, W. T.; Shockley, W. Physical Review, Vol. 78, Issue 3 https://doi.org/10.1103/PhysRev.78.275	journal	May 1950
Structural stability and lattice defects in copper: Ab initio , tight-binding, and embedded-atom calculations Mishin, Y.; Mehl, M. J.; Papaconstantopoulos, D. A. Physical Review B, Vol. 63, Issue 22 https://doi.org/10.1103/PhysRevB.63.224106	journal	May 2001
Theoretical tensile strength of an Al grain boundary Lu, Guang-Hong; Deng, Shenghua; Wang, Tianmin Physical Review B, Vol. 69, Issue 13 https://doi.org/10.1103/PhysRevB.69.134106	journal	April 2004
Influence of grain boundary scattering on the electrical and thermal conductivities of polycrystalline gold nanofilms Zhang, Q. G.; Cao, B. Y.; Zhang, X. Physical Review B, Vol. 74, Issue 13 https://doi.org/10.1103/PhysRevB.74.134109	journal	October 2006
On representing chemical environments Bartók, Albert P.; Kondor, Risi; Csányi, Gábor Physical Review B, Vol. 87, Issue 18 https://doi.org/10.1103/PhysRevB.87.184115	journal	May 2013
Erratum: On representing chemical environments [Phys. Rev. B 87 , 184115 (2013)] Bartók, Albert P.; Kondor, Risi; Csányi, Gábor Physical Review B, Vol. 96, Issue 1 https://doi.org/10.1103/PhysRevB.96.019902	journal	July 2017
Atomic cluster expansion for accurate and transferable interatomic potentials Drautz, Ralf Physical Review B, Vol. 99, Issue 1 https://doi.org/10.1103/PhysRevB.99.014104	journal	January 2019
Atomic-Scale Quantification of Grain Boundary Segregation in Nanocrystalline Material Herbig, M.; Raabe, D.; Li, Y. J. Physical Review Letters, Vol. 112, Issue 12 https://doi.org/10.1103/PhysRevLett.112.126103	journal	March 2014
Atomic energy in grain boundaries studied by machine learning Song, Xinyuan; Deng, Chuang Physical Review Materials, Vol. 6, Issue 4 https://doi.org/10.1103/PhysRevMaterials.6.043601	journal	April 2022
A Cluster Separation Measure Davies, David L.; Bouldin, Donald W. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-1, Issue 2 https://doi.org/10.1109/TPAMI.1979.4766909	journal	April 1979
High-Thermoelectric Performance of Nanostructured Bismuth Antimony Telluride Bulk Alloys Poudel, B.; Hao, Q.; Ma, Y. Science, Vol. 320, Issue 5876, p. 634-638 https://doi.org/10.1126/science.1156446	journal	May 2008
Revealing Extraordinary Intrinsic Tensile Plasticity in Gradient Nano-Grained Copper Fang, T. H.; Li, W. L.; Tao, N. R. Science, Vol. 331, Issue 6024 https://doi.org/10.1126/science.1200177	journal	February 2011
First Principles Determination of the Effects of Phosphorus and Boron on Iron Grain Boundary Cohesion Wu, R.; Freeman, A. J.; Olson, G. B. Science, Vol. 265, Issue 5170 https://doi.org/10.1126/science.265.5170.376	journal	July 1994
Dense dislocation arrays embedded in grain boundaries for high-performance bulk thermoelectrics Kim, Sang Il; Lee, Kyu Hyoung; Mun, Hyeon A. Science, Vol. 348, Issue 6230 https://doi.org/10.1126/science.aaa4166	journal	April 2015
Ultrahigh-strength and ductile superlattice alloys with nanoscale disordered interfaces Yang, T.; Zhao, Y. L.; Li, W. P. Science, Vol. 369, Issue 6502 https://doi.org/10.1126/science.abb6830	journal	July 2020
Moment Tensor Potentials: A Class of Systematically Improvable Interatomic Potentials Shapeev, Alexander V. Multiscale Modeling & Simulation, Vol. 14, Issue 3 https://doi.org/10.1137/15M1054183	journal	January 2016
The Nature of Grain Boundaries in the High-Tc Superconductors Babcock, S. E.; Vargas, J. L. Annual Review of Materials Science, Vol. 25, Issue 1 https://doi.org/10.1146/annurev.ms.25.080195.001205	journal	August 1995
Grain boundary engineering: an overview after 25 years Randle, V. Materials Science and Technology, Vol. 26, Issue 3 https://doi.org/10.1179/026708309X12601952777747	journal	March 2010
Symmetric and asymmetric tilt grain boundary structure and energy in Cu and Al (and transferability to other fcc metals) Tschopp, Mark A.; Coleman, Shawn P.; McDowell, David L. Integrating Materials and Manufacturing Innovation, Vol. 4, Issue 1 https://doi.org/10.1186/s40192-015-0040-1	journal	October 2015

Similar Records

Learning grain boundary segregation behavior through fingerprinting complex atomic environments

Journal Article · 2024 · Communications Materials · OSTI ID:2440302

Tavenner, Jacob P.; Gupta, Ankit; Thompson, Gregory B.; +2 more

Development of activity–descriptor relationships for supported metal ion hydrogenation catalysts on silica

Journal Article · 2018 · Polyhedron · OSTI ID:1462737

Liu, Cong; Camacho-Bunquin, Jeffrey; Ferrandon, Magali; +13 more

Predicting permeation of compounds across the outer membrane of P. aeruginosa using molecular descriptors

Journal Article · 2024 · Communications Chemistry · OSTI ID:2470486

Manrique, Pedro D.; Leus, Inga V.; López, César A.; +12 more

Related Subjects

36 MATERIALS SCIENCE
defects
grain boundaries
machine learning
molecular dynamics
strain

Title: Learning from metastable symmetric-tilt grain boundaries using physics-based descriptors

Citation Formats

References (71)

Similar Records

Related Subjects