Machine learning interatomic potential for predicting the thermal properties of uranium nitride

Chen, Beihan; Hua, Zilong; Watkins, Jennifer K.; Malakkal, Linu; Khafizov, Marat; Hurley, David H.; Jin, Miaomiao

doi:10.1063/5.0294389

Machine learning interatomic potential for predicting the thermal properties of uranium nitride

Journal Article · Mon Nov 24 00:00:00 EST 2025 · Journal of Applied Physics

DOI:https://doi.org/10.1063/5.0294389· OSTI ID:3013640

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Pennsylvania State Univ., University Park, PA (United States)
Idaho National Laboratory (INL), Idaho Falls, ID (United States)
The Ohio State Univ., Columbus, OH (United States)

We present a combined computational and experimental investigation of the thermal properties of uranium nitride (UN), focusing on the development of a machine learning interatomic potential (MLIP) using the moment tensor potential framework. The MLIP was trained on density functional theory (DFT) data and validated against various quantities including energies, forces, elastic constants, phonon dispersion, and defect formation energies, achieving excellent agreement with DFT calculations, prior experimental results, and our thermal conductivity measurement. The potential was then employed in molecular dynamics simulations to predict key thermal properties such as melting point, thermal expansion, specific heat, and lattice thermal conductivity. To further assess model accuracy, we fabricated a UN sample and performed new thermal conductivity measurements representative of single-crystal properties, which showed strong agreement with the MLIP predictions. This work confirms the reliability and predictive capability of the developed potential for determining the thermal properties of UN.

View Accepted Manuscript (DOE)

Research Organization:: Idaho National Laboratory (INL), Idaho Falls, ID (United States)

Sponsoring Organization:: USDOE Office of Nuclear Energy (NE); USDOE Office of Science (SC), Basic Energy Sciences (BES); USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)

Grant/Contract Number:: AC07-05ID14517

OSTI ID:: 3013640

Alternate ID(s):: OSTI ID: 3028247

Report Number(s):: INL/JOU--25-85882; INL/JOU-25-85882

Journal Information:: Journal of Applied Physics, Journal Name: Journal of Applied Physics Journal Issue: 20 Vol. 138; ISSN 0021-8979; ISSN 1089-7550

Publisher:: American Institute of Physics (AIP)Copyright Statement

Country of Publication:: United States

Language:: English

References (79)

Ueber die Wärme-Leitungsfähigkeit der Metalle Franz, R.; Wiedemann, G. Annalen der Physik und Chemie, Vol. 165, Issue 8 https://doi.org/10.1002/andp.18531650802	journal	January 1853
Bestimmung der Wärmegrade in absolutem Maasse Lorenz, L. Annalen der Physik und Chemie, Vol. 223, Issue 11 https://doi.org/10.1002/andp.18722231107	journal	January 1872
Electronic structure of crystalline uranium nitride: LCAO DFT calculations Evarestov, R. A.; Losev, M. V.; Panin, A. I. physica status solidi (b), Vol. 245, Issue 1 https://doi.org/10.1002/pssb.200743247	journal	January 2008
Hydrostatic pressure dependences of elastic constants and vibrational anharmonicity of uranium nitride Salleh, M. D.; MacDonald, J. E.; Saunders, G. A. Journal of Materials Science, Vol. 21, Issue 7 https://doi.org/10.1007/BF01114310	journal	July 1986
Nitride fuel for Gen IV nuclear power systems Ekberg, Christian; Ribeiro Costa, Diogo; Hedberg, Marcus Journal of Radioanalytical and Nuclear Chemistry, Vol. 318, Issue 3 https://doi.org/10.1007/s10967-018-6316-0	journal	November 2018
The chemical thermodynamic properties of nuclear materials I. Uranium mononitride Oetting, Franklin L.; Leitnaker, James M. The Journal of Chemical Thermodynamics, Vol. 4, Issue 2 https://doi.org/10.1016/0021-9614(72)90057-2	journal	March 1972
Uranium mononitride: Heat capacity and thermal conductivity from 298 to 1000 °K Takahashi, Y.; Murabayashi, M.; Akimoto, Y. Journal of Nuclear Materials, Vol. 38, Issue 3 https://doi.org/10.1016/0022-3115(71)90059-6	journal	March 1971
Thermal conductivity correlation for uranium nitride fuel between 10 and 1923 K Ross, Steven B.; El-Genk, Mohamed S.; Matthews, R. Bruce Journal of Nuclear Materials, Vol. 151, Issue 3 https://doi.org/10.1016/0022-3115(88)90026-8	journal	February 1988
Material property correlations for uranium mononitride Hayes, S. L.; Thomas, J. K.; Peddicord, K. L. Journal of Nuclear Materials, Vol. 171, Issue 2-3 https://doi.org/10.1016/0022-3115(90)90374-V	journal	May 1990
Material property correlations for uranium mononitride Hayes, S. L.; Thomas, J. K.; Peddicord, K. L. Journal of Nuclear Materials, Vol. 171, Issue 2-3 https://doi.org/10.1016/0022-3115(90)90375-W	journal	May 1990
Material property correlations for uranium mononitride Hayes, S. L.; Thomas, J. K.; Peddicord, K. L. Journal of Nuclear Materials, Vol. 171, Issue 2-3 https://doi.org/10.1016/0022-3115(90)90376-X	journal	May 1990
Material property correlations for uranium mononitride Hayes, S. L.; Thomas, J. K.; Peddicord, K. L. Journal of Nuclear Materials, Vol. 171, Issue 2-3 https://doi.org/10.1016/0022-3115(90)90377-Y	journal	May 1990
A simplified method for calculating the debye temperature from elastic constants Anderson, Orson L. Journal of Physics and Chemistry of Solids, Vol. 24, Issue 7 https://doi.org/10.1016/0022-3697(63)90067-2	journal	July 1963
An X-ray study of the structures of UN, UP, US and USe at cryogenic temperatures Marples, J. A. C. Journal of Physics and Chemistry of Solids, Vol. 31, Issue 11 https://doi.org/10.1016/0022-3697(70)90060-0	journal	November 1970
Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set Kresse, G.; Furthmüller, J. Computational Materials Science, Vol. 6, Issue 1, p. 15-50 https://doi.org/10.1016/0927-0256(96)00008-0	journal	July 1996
Thermodynamic modelling of the N–U system Chevalier, P. -Y.; Fischer, E.; Cheynet, B. Journal of Nuclear Materials, Vol. 280, Issue 2 https://doi.org/10.1016/S0022-3115(00)00043-X	journal	July 2000
A molecular dynamics study of the thermal conductivity of uranium mononitride Kurosaki, Ken; Yano, Kimihiko; Yamada, Kazuhiro Journal of Alloys and Compounds, Vol. 311, Issue 2 https://doi.org/10.1016/S0925-8388(00)01127-0	journal	October 2000
A molecular dynamics study of the heat capacity of uranium mononitride Kurosaki, Ken; Yano, Kimihiko; Yamada, Kazuhiro Journal of Alloys and Compounds, Vol. 297, Issue 1-2 https://doi.org/10.1016/S0925-8388(99)00561-7	journal	February 2000
A combined theoretical-experimental investigation of thermal transport in low-dose irradiated thorium dioxide Deskins, W. Ryan; Khanolkar, Amey; Mazumder, Sanjoy Acta Materialia, Vol. 241 https://doi.org/10.1016/j.actamat.2022.118379	journal	December 2022
Pressure dependence of elastic constants and related parameters for rocksalt MgO Gueddim, A.; Bouarissa, N.; Villesuzanne, A. Computational Materials Science, Vol. 48, Issue 3 https://doi.org/10.1016/j.commatsci.2010.02.010	journal	May 2010
Active learning of linearly parametrized interatomic potentials Podryabinkin, Evgeny V.; Shapeev, Alexander V. Computational Materials Science, Vol. 140 https://doi.org/10.1016/j.commatsci.2017.08.031	journal	December 2017
An updated version of wannier90: A tool for obtaining maximally-localised Wannier functions Mostofi, Arash A.; Yates, Jonathan R.; Pizzi, Giovanni Computer Physics Communications, Vol. 185, Issue 8 https://doi.org/10.1016/j.cpc.2014.05.003	journal	August 2014
EPW: Electron–phonon coupling, transport and superconducting properties using maximally localized Wannier functions Poncé, S.; Margine, E. R.; Verdi, C. Computer Physics Communications, Vol. 209 https://doi.org/10.1016/j.cpc.2016.07.028	journal	December 2016
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
FourPhonon: An extension module to ShengBTE for computing four-phonon scattering rates and thermal conductivity Han, Zherui; Yang, Xiaolong; Li, Wu Computer Physics Communications, Vol. 270 https://doi.org/10.1016/j.cpc.2021.108179	journal	January 2022
The diffusion of point defects in uranium mononitride: Combination of DFT and atomistic simulation with novel potential Kuksin, A. Yu.; Starikov, S. V.; Smirnova, D. E. Journal of Alloys and Compounds, Vol. 658 https://doi.org/10.1016/j.jallcom.2015.10.223	journal	February 2016
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
Comparison of interatomic potentials for UO2 Govers, K.; Lemehov, S.; Hou, M. Journal of Nuclear Materials, Vol. 376, Issue 1 https://doi.org/10.1016/j.jnucmat.2008.01.023	journal	May 2008
Ab initio interionic potentials for UN by multiple lattice inversion Chen, P. H.; Wang, X. L.; Lai, X. C. Journal of Nuclear Materials, Vol. 404, Issue 1 https://doi.org/10.1016/j.jnucmat.2010.06.017	journal	September 2010
First-principles study of structural, elastic, electronic, vibrational and thermodynamic properties of UN Mei, Zhi-Gang; Stan, Marius; Pichler, Benjamin Journal of Nuclear Materials, Vol. 440, Issue 1-3 https://doi.org/10.1016/j.jnucmat.2013.04.058	journal	September 2013
Melting point determination of uranium nitride and uranium plutonium nitride: A laser heating study Carvajal Nunez, U.; Prieur, D.; Bohler, R. Journal of Nuclear Materials, Vol. 449, Issue 1-3 https://doi.org/10.1016/j.jnucmat.2014.02.021	journal	June 2014
GGA+U study of uranium mononitride: A comparison of the U-ramping and occupation matrix schemes and incorporation energies of fission products Claisse, Antoine; Klipfel, Marco; Lindbom, Niclas Journal of Nuclear Materials, Vol. 478 https://doi.org/10.1016/j.jnucmat.2016.06.007	journal	September 2016
The atomistic simulation of pressure-induced phase transition in uranium mononitride Tseplyaev, V. I.; Starikov, S. V. Journal of Nuclear Materials, Vol. 480 https://doi.org/10.1016/j.jnucmat.2016.07.048	journal	November 2016
Intragranular thermal transport in U–50Zr Hua, Zilong; Yao, Tiankai; Khanolkar, Amey Journal of Nuclear Materials, Vol. 534 https://doi.org/10.1016/j.jnucmat.2020.152145	journal	June 2020
First-principles investigation of uranium mononitride (UN): Effect of magnetic ordering, spin-orbit interactions and exchange correlation functional Kocevski, Vancho; Rehn, Daniel A.; Cooper, Michael W. D. Journal of Nuclear Materials, Vol. 559 https://doi.org/10.1016/j.jnucmat.2021.153401	journal	February 2022
Development and application of a uranium mononitride (UN) potential: Thermomechanical properties and Xe diffusion Kocevski, Vancho; Cooper, Michael W. D.; Claisse, Antoine J. Journal of Nuclear Materials, Vol. 562 https://doi.org/10.1016/j.jnucmat.2022.153553	journal	April 2022
Thermal expansion and steam oxidation of uranium mononitride analysed via in situ neutron diffraction Liu, Jiatu; Gasparrini, Claudia; White, Joshua T. Journal of Nuclear Materials, Vol. 575 https://doi.org/10.1016/j.jnucmat.2022.154215	journal	March 2023
Assessment of uranium nitride interatomic potentials AbdulHameed, Mohamed; Beeler, Benjamin; Galvin, Conor O. T. Journal of Nuclear Materials, Vol. 600 https://doi.org/10.1016/j.jnucmat.2024.155247	journal	November 2024
First principles investigation of thermal transport of uranium mononitride Szpunar, Barbara; Ranasinghe, Jayangani I.; Malakkal, Linu Journal of Physics and Chemistry of Solids, Vol. 146 https://doi.org/10.1016/j.jpcs.2020.109636	journal	November 2020
A review of the reprocessability of uranium nitride based fuels Jones, Suzanne; Boxall, Colin; Maher, Chris Progress in Nuclear Energy, Vol. 165 https://doi.org/10.1016/j.pnucene.2023.104917	journal	November 2023
Methods for Classical-Mechanical Molecular Simulation in Chemistry: Achievements, Limitations, Perspectives van Gunsteren, Wilfred F.; Oostenbrink, Chris Journal of Chemical Information and Modeling, Vol. 64, Issue 16 https://doi.org/10.1021/acs.jcim.4c00823	journal	August 2024
Performance and Cost Assessment of Machine Learning Interatomic Potentials Zuo, Yunxing; Chen, Chi; Li, Xiangguo The Journal of Physical Chemistry A, Vol. 124, Issue 4 https://doi.org/10.1021/acs.jpca.9b08723	journal	October 2019
Electron–phonon physics from first principles using the EPW code Lee, Hyungjun; Poncé, Samuel; Bushick, Kyle npj Computational Materials, Vol. 9, Issue 1 https://doi.org/10.1038/s41524-023-01107-3	journal	August 2023
Neural network potential-energy surfaces in chemistry: a tool for large-scale simulations Behler, Jörg Physical Chemistry Chemical Physics, Vol. 13, Issue 40 https://doi.org/10.1039/c1cp21668f	journal	January 2011
The first-principles treatment of the electron-correlation and spin–orbital effects in uranium mononitride nuclear fuels Gryaznov, Denis; Heifets, Eugene; Kotomin, Eugene Physical Chemistry Chemical Physics, Vol. 14, Issue 13 https://doi.org/10.1039/c2cp40297a	journal	January 2012
Markoff Random Processes and the Statistical Mechanics of Time‐Dependent Phenomena. II. Irreversible Processes in Fluids Green, Melville S. The Journal of Chemical Physics, Vol. 22, Issue 3 https://doi.org/10.1063/1.1740082	journal	March 1954
A unified formulation of the constant temperature molecular dynamics methods Nosé, Shuichi The Journal of Chemical Physics, Vol. 81, Issue 1 https://doi.org/10.1063/1.447334	journal	July 1984
Spatially localized measurement of thermal conductivity using a hybrid photothermal technique Hua, Zilong; Ban, Heng; Khafizov, Marat Journal of Applied Physics, Vol. 111, Issue 10 https://doi.org/10.1063/1.4716474	journal	May 2012
First-principles DFT+U modeling of defect behaviors in anti-ferromagnetic uranium mononitride Lan, Jian-Hui; Zhao, Zi-Chen; Wu, Qiong Journal of Applied Physics, Vol. 114, Issue 22 https://doi.org/10.1063/1.4846217	journal	December 2013
Local measurement of thermal conductivity and diffusivity Hurley, David H.; Schley, Robert S.; Khafizov, Marat Review of Scientific Instruments, Vol. 86, Issue 12 https://doi.org/10.1063/1.4936213	journal	December 2015
Phonon anharmonic frequency shift induced by four-phonon scattering calculated from first principles Feng, Tianli; Yang, Xiaolong; Ruan, Xiulin Journal of Applied Physics, Vol. 124, Issue 14 https://doi.org/10.1063/1.5048799	journal	October 2018
The influence of lattice defects, recombination, and clustering on thermal transport in single crystal thorium dioxide Dennett, Cody A.; Hua, Zilong; Khanolkar, Amey APL Materials, Vol. 8, Issue 11 https://doi.org/10.1063/5.0025384	journal	November 2020
MLIP-3: Active learning on atomic environments with moment tensor potentials Podryabinkin, Evgeny; Garifullin, Kamil; Shapeev, Alexander The Journal of Chemical Physics, Vol. 159, Issue 8 https://doi.org/10.1063/5.0155887	journal	August 2023
The Compressibility of Media under Extreme Pressures Murnaghan, F. D. Proceedings of the National Academy of Sciences, Vol. 30, Issue 9 https://doi.org/10.1073/pnas.30.9.244	journal	September 1944
\mathcal{O}(N) methods in electronic structure calculations Bowler, D. R.; Miyazaki, T. Reports on Progress in Physics, Vol. 75, Issue 3 https://doi.org/10.1088/0034-4885/75/3/036503	journal	February 2012
The Elastic Behaviour of a Crystalline Aggregate Hill, R. Proceedings of the Physical Society. Section A, Vol. 65, Issue 5 https://doi.org/10.1088/0370-1298/65/5/307	journal	May 1952
Implementation strategies in phonopy and phono3py Togo, Atsushi; Chaput, Laurent; Tadano, Terumasa Journal of Physics: Condensed Matter, Vol. 35, Issue 35 https://doi.org/10.1088/1361-648X/acd831	journal	June 2023
Toward machine learning interatomic potentials for modeling uranium mononitride Alzate-Vargas, Lorena; Subedi, Kashi N.; Lubbers, Nicholas Machine Learning: Science and Technology, Vol. 6, Issue 3 https://doi.org/10.1088/2632-2153/ae0242	journal	September 2025
Canonical dynamics: Equilibrium phase-space distributions Hoover, William G. Physical Review A, Vol. 31, Issue 3 https://doi.org/10.1103/PhysRevA.31.1695	journal	March 1985
Systematic study of the lattice dynamics of the uranium rocksalt-structure compounds Jackman, J. A.; Holden, T. M.; Buyers, W. J. L. Physical Review B, Vol. 33, Issue 10 https://doi.org/10.1103/PhysRevB.33.7144	journal	May 1986
Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set Kresse, G.; Furthmüller, J. Physical Review B, Vol. 54, Issue 16, p. 11169-11186 https://doi.org/10.1103/PhysRevB.54.11169	journal	October 1996
Quantitative validation of the Boltzmann transport equation phonon thermal conductivity model under the single-mode relaxation time approximation McGaughey, A. J. H.; Kaviany, M. Physical Review B, Vol. 69, Issue 9 https://doi.org/10.1103/PhysRevB.69.094303	journal	March 2004
Electronic structure and magnetic and transport properties of single-crystalline UN Samsel-Czekała, M.; Talik, E.; de V. Du Plessis, P. Physical Review B, Vol. 76, Issue 14 https://doi.org/10.1103/PhysRevB.76.144426	journal	October 2007
Method to extract anharmonic force constants from first principles calculations Esfarjani, Keivan; Stokes, Harold T. Physical Review B, Vol. 77, Issue 14 https://doi.org/10.1103/PhysRevB.77.144112	journal	April 2008
First-principles phonon calculations of thermal expansion in Ti 3 SiC 2 , Ti 3 AlC 2 , and Ti 3 GeC 2 Togo, Atsushi; Chaput, Laurent; Tanaka, Isao Physical Review B, Vol. 81, Issue 17 https://doi.org/10.1103/PhysRevB.81.174301	journal	May 2010
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
Four-phonon scattering significantly reduces intrinsic thermal conductivity of solids Feng, Tianli; Lindsay, Lucas; Ruan, Xiulin Physical Review B, Vol. 96, Issue 16 https://doi.org/10.1103/PhysRevB.96.161201	journal	October 2017
Quantum-accurate spectral neighbor analysis potential models for Ni-Mo binary alloys and fcc metals Li, Xiang-Guo; Hu, Chongze; Chen, Chi Physical Review B, Vol. 98, Issue 9 https://doi.org/10.1103/PhysRevB.98.094104	journal	September 2018
Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons Bartók, Albert P.; Payne, Mike C.; Kondor, Risi Physical Review Letters, Vol. 104, Issue 13 https://doi.org/10.1103/PhysRevLett.104.136403	journal	April 2010
Generalized Gradient Approximation Made Simple Perdew, John P.; Burke, Kieron; Ernzerhof, Matthias Physical Review Letters, Vol. 77, Issue 18, p. 3865-3868 https://doi.org/10.1103/PhysRevLett.77.3865	journal	October 1996
Generalized Neural-Network Representation of High-Dimensional Potential-Energy Surfaces Behler, Jörg; Parrinello, Michele Physical Review Letters, Vol. 98, Issue 14 https://doi.org/10.1103/PhysRevLett.98.146401	journal	April 2007
Maximally localized Wannier functions: Theory and applications Marzari, Nicola; Mostofi, Arash A.; Yates, Jonathan R. Reviews of Modern Physics, Vol. 84, Issue 4 https://doi.org/10.1103/RevModPhys.84.1419	journal	October 2012
Sintering of UN as a Function of Temperature and N2 Pressure Tennery, V. J.; Godfrey, T. G.; Potter, R. A. Journal of the American Ceramic Society, Vol. 54, Issue 7 https://doi.org/10.1111/j.1151-2916.1971.tb12306.x	journal	July 1971
Active learning with moment tensor potentials to predict material properties: Ti0.5Al0.5N at elevated temperature Bock, F.; Tasnádi, F.; Abrikosov, I. A. Journal of Vacuum Science & Technology A, Vol. 42, Issue 1 https://doi.org/10.1116/6.0003260	journal	January 2024
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
Statistical-Mechanical Theory of Irreversible Processes. I. General Theory and Simple Applications to Magnetic and Conduction Problems Kubo, Ryogo Journal of the Physical Society of Japan, Vol. 12, Issue 6 https://doi.org/10.1143/JPSJ.12.570	journal	June 1957
Impact of Accident-Tolerant Fuels and Claddings on the Overall Fuel Cycle: A Preliminary Systems Analysis Youinou, Gilles J.; Sen, R. Sonat Nuclear Technology, Vol. 188, Issue 2 https://doi.org/10.13182/NT14-22	journal	November 2014
Density-Functional Perturbation Theory for Quasi-Harmonic Calculations Baroni, S.; Giannozzi, P.; Isaev, E. Reviews in Mineralogy and Geochemistry, Vol. 71, Issue 1 https://doi.org/10.2138/rmg.2010.71.3	journal	January 2010
First-principles Phonon Calculations with Phonopy and Phono3py Togo, Atsushi Journal of the Physical Society of Japan, Vol. 92, Issue 1 https://doi.org/10.7566/JPSJ.92.012001	journal	January 2023

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36 - MATERIALS SCIENCE
36 MATERIALS SCIENCE
Density functional theory
Elastic modulus
Interatomic potentials
Machine Learning interatomic potential
Machine learning
Materials properties
Molecular dynamics
Nitrides
Phonons
Thermal conductivity
Thermal effects
Thermal property
Uranium Nitride
phonon

Machine learning interatomic potential for predicting the thermal properties of uranium nitride

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