
The Library
Browse by Warwick Author
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Number of items: 52.
2023
Klawohn, Sascha, Darby, James P., Kermode, James R., CsΓ‘nyi, GΓ‘bor, Caro, Miguel A. and BartΓ³k, Albert P. (2023) Gaussian Approximation Potentials : theory, software implementation and application examples. Journal of Chemical Physics, 159 . 174108. doi:10.1063/5.0160898 ISSN 0021-9606.
Witt, William C., van der Oord, Cas, GelΕΎinytΔ, Elena, JΓ€rvinen, Teemu, Ross, Andres, Darby, James P., Ho, Cheuk Hin, Baldwin, William J., Sachs, Matthias, Kermode, James R., Bernstein, Noam, CsΓ‘nyi, GΓ‘bor and Ortner, Christoph (2023) ACEpotentials.jl : a Julia implementation of the atomic cluster expansion. The Journal of Chemical Physics, 159 (16). 164101. doi:10.1063/5.0158783 ISSN 0021-9606.
Ghiringhelli, Luca M., Baldauf, Carsten, Bereau, Tristan, Brockhauser, Sandor, Carbogno, Christian, Chamanara, Javad, Cozzini, Stefano, Curtarolo, Stefano, Draxl, Claudia, Dwaraknath, Shyam et al.
(2023)
Shared metadata for data-centric materials science.
Scientific Data, 10
(1).
626.
doi:10.1038/s41597-023-02501-8
ISSN 2052-4463.
Grigorev, Petr, Goryaeva, Alexandra M., Marinica, Mihai-Cosmin, Kermode, James R. and Swinburne, Thomas D. (2023) Calculation of dislocation binding to helium-vacancy defects in tungsten using hybrid ab initio-machine learning methods. Acta Materialia, 247 . 118734. doi:10.1016/j.actamat.2023.118734 ISSN 1359-6454.
Klawohn, Sascha, Kermode, James R. and BartΓ³k, Albert P. (2023) Massively parallel fitting of Gaussian approximation potentials. Machine Learning: Science and Technology, 4 (1). 015020. doi:10.1088/2632-2153/aca743 ISSN 2632-2153.
2022
Anand, G., Ghosh, Swarnava, Zhang, Liwei, Anupam, Angesh, Freeman, Colin L., Ortner, Christoph, Eisenbach, Markus and Kermode, James R. (2022) Exploiting machine learning in multiscale modelling of materials. Journal of The Institution of Engineers (India) : Series D . doi:10.1007/s40033-022-00424-z ISSN 2250-2122. (In Press)
Darby, James P., Kermode, James R. and CsΓ‘nyi, GΓ‘bor (2022) Compressing local atomic neighbourhood descriptors. npj Computational Materials, 8 (1). 166. doi:10.1038/s41524-022-00847-y ISSN 2057-3960.
Zhang, Liwei, Onat, Berk, Dusson, Geneviève, McSloy, Adam, Anand, G., Maurer, Reinhard J., Ortner, Christoph and Kermode, James R. (2022) Equivariant analytical mapping of first principles Hamiltonians to accurate and transferable materials models. npj Computational Materials, 8 (1). 158. doi:10.1038/s41524-022-00843-2 ISSN 2057-3960.
Podgurschi, V., King, D. J. M., Smutna, J., Kermode, James R. and Wenman, M. R. (2022) Atomistic modelling of iodine-oxygen interactions in strained sub-oxides of zirconium. Journal of Nuclear Materials, 558 . 153394. doi:10.1016/j.jnucmat.2021.153394 ISSN 0022-3115.
2021
Goryaeva, Alexandra M., Dérès, Julien, Lapointe, Clovis, Grigorev, Petr, Swinburne, Thomas D., Kermode, James R., Ventelon, Lisa, Baima, Jacopo and Marinica, Mihai-Cosmin (2021) Efficient and transferable machine learning potentials for the simulation of crystal defects in bcc Fe and W. Physical Review Materials, 5 (10). 103803. doi:10.1103/PhysRevMaterials.5.103803 ISSN 2475-9953.
Buze, Maciej and Kermode, James R. (2021) Numerical-continuation-enhanced flexible boundary condition scheme applied to mode-I and mode-III fracture. Physical Review E, 103 (3). 033002 . doi:10.1103/PhysRevE.103.033002 ISSN 1539-3755.
Khosrownejad, S. Mostafa, Kermode, James R. and Pastewka, Lars (2021) Quantitative prediction of the fracture toughness of amorphous carbon from atomic-scale simulations. Physical Review Materials, 5 (2). 023602. doi:10.1103/PhysRevMaterials.5.023602 ISSN 2475-9953.
2020
Onat, Berk, Ortner, Christoph and Kermode, James R. (2020) Sensitivity and dimensionality of atomic environment representations used for machine learning interatomic potentials. The Journal of Chemical Physics, 153 (14). 144106. doi:10.1063/5.0016005 ISSN 0021-9606.
GoΕΔbiowski, Jacek R., Kermode, James R., Haynes, Peter D. and Mostofi, Arash A. (2020) Atomistic QM/MM simulations of the strength of covalent interfaces in carbon nanotube-polymer composites. Physical chemistry chemical physics : PCCP, 22 (21). pp. 12007-12014. doi:10.1039/d0cp01841d ISSN 1463-9084.
Kermode, James R. (2020) f90wrap : an automated tool for constructing deep Python interfaces to modern Fortran codes. Journal of Physics: Condensed Matter, 32 (30). 305901. doi:10.1088/1361-648x/ab82d2 ISSN 1361-648X.
Grigorev, Petr, Swinburne, T. D. and Kermode, James R. (2020) Data for Hybrid quantum/classical study of hydrogen-decorated screw dislocations in tungsten : ultrafast pipe diffusion, core reconstruction, and effects on glide mechanism. [Dataset]
Grigorev, Petr, Swinburne, T. D. and Kermode, James R. (2020) Hybrid quantum/classical study of hydrogen-decorated screw dislocations in tungsten : ultrafast pipe diffusion, core reconstruction, and effects on glide mechanism. Physical Review Materials, 4 . 023601 . doi:10.1103/PhysRevMaterials.4.023601 ISSN 2475-9953.
2019
Bianchini, F., Glielmo, A., Kermode, James R. and De Vita, A. (2019) Enabling QM-accurate simulation of dislocation motion in Ξ³βNi and Ξ±βFe using a hybrid multiscale approach. Physical Review Materials, 3 (4). 043605. doi:10.1103/PhysRevMaterials.3.043605 ISSN 2475-9953.
Bianchini, Federico, Glielmo, Aldo, Kermode, James R. and De Vita, Alessandro (2019) Data for Enabling QM-accurate simulation of dislocation motion in gamma-Ni and alpha-Fe using a hybrid multiscale approach. [Dataset]
Makri, Stela, Ortner, Christoph and Kermode, James R. (2019) A preconditioning scheme for minimum energy path finding methods. The Journal of Chemical Physics, 150 (9). 094109. doi:10.1063/1.5064465 ISSN 0021-9606.
2018
BartΓ³k, Albert P., Kermode, James R., Bernstein, Noam and CsΓ‘nyi, GΓ‘bor (2018) Machine learning a general-purpose interatomic potential for silicon. Physical Review X, 8 (4). 041048 . doi:10.1103/PhysRevX.8.041048 ISSN 2160-3308.
GoΕΔbiowski, Jacek R., Kermode, James R., Mostofi, Arash A. and Haynes, Peter D. (2018) Multiscale simulations of critical interfacial failure in carbon nanotube-polymer composites. The Journal of Chemical Physics, 149 (22). 224102. doi:10.1063/1.5035508 ISSN 0021-9606.
Stephenson, David, Kermode, James R. and Lockerby, Duncan A. (2018) Accelerating multiscale modelling of fluids with on-the-fly Gaussian process regression. Microfluidics and Nanofluidics, 22 . 139. doi:10.1007/s10404-018-2164-z ISSN 1613-4982.
Stephenson, David, Kermode, James R. and Lockerby, Duncan A. (2018) Accelerating multiscale modelling of fluids with on-the-fly Gaussian process regression. Microfluidics and Nanofluidics, 22 (12). 139. doi:10.1007/s10404-018-2164-z ISSN 1613-4982.
Lambert, H., Fekete, Adam, Kermode, James R. and De Vita, A. (2018) Imeall : a computational framework for the calculation of the atomistic properties of grain boundaries. Computer Physics Communications, 232 . pp. 256-263. doi:10.1016/j.cpc.2018.04.029 ISSN 0010-4655.
Barrera, O., Bombac, D., Chen, Y., Daff, T. D., Galindo-Nava, E., Gong, P., Haley, D., Horton, R., Katzarov, I., Kermode, James R., Liverani, C., Stopher, M. and Sweeney, F. (2018) Understanding and mitigating hydrogen embrittlement of steels : a review of experimental, modelling and design progress from atomistic to continuum. Journal of Materials Science, 53 . pp. 6251-6290. doi:10.1007/s10853-017-1978-5 ISSN 0022-2461.
2017
BartΓ³k, Albert P., De, Sandip, Poelking, Carl, Bernstein, Noam, Kermode, James R., CsΓ‘nyi, GΓ‘bor and Ceriotti, Michele (2017) Machine learning unifies the modeling of materials and molecules. Science Advances, 3 (12). e1701816. doi:10.1126/sciadv.1701816 ISSN 2375-2548.
Swinburne, Thomas and Kermode, James R. (2017) Computing energy barriers for rare events from hybrid quantum/classical simulations through the virtual work principle. Physical Review B (Condensed Matter and Materials Physics), 96 . 144102. ISSN 1098-0121.
Swinburne, T. D. and Kermode, James R. (2017) Data for Computing energy barriers for rare events from hybrid quantum/classical simulations through the virtual work principle. [Dataset]
Sernicola, Giorgio, Giovannini, Tommaso, Patel, Punitbhai, Kermode, James R., Balint, Daniel S., Britton, T. Ben and Giuliani, Finn (2017) In situ stable crack growth at the micron scale. Nature Communications, 8 (1). 108. doi:10.1038/s41467-017-00139-w ISSN 2041-1723.
Kermode, James R., Sernicola, Giorgio, Giovannini, Tommaso, Patel, Punitbhai, Balint, Daniel S., Britton, Ben and Giuliani, Finn (2017) Data for In situ stable crack growth at the micron scale. [Dataset]
Larsen, Ask, Mortensen, Jens, Blomqvist, Jakob, Castelli, Ivano, Christensen, Rune, Dulak, Marcin, Friis, Jesper, Groves, Michael, Hammer, Bjork, Hargus, Cory et al.
(2017)
The atomic simulation environment β a python library for working with atoms.
Journal of Physics: Condensed Matter
.
doi:10.1088/1361-648X/aa680e
ISSN 0953-8984.
2016
Caccin, Marco, Li, Zhenwei, Kermode, James R. and De Vita, Alessandro (2016) A framework for machine-learning-augmented multiscale atomistic simulations on parallel supercomputers. International Journal of Quantum Chemistry, 115 (16). pp. 1129-1139. doi:10.1002/qua.24952 ISSN 0020-7608.
Packwood, David, Kermode, James R., Mones, Letif, Bernstein, Noam, Woolley, John, Gould, Nicholas, Ortner, Christoph and Csanyi, Gabor (2016) Data for A universal preconditioner for simulating condensed phase materials. [Dataset]
Bianchini, Federico, Kermode, James R. and De Vita, Alessandro (2016) Modelling defects in Ni-Al with EAM and DFT calculations. Modelling and Simulation in Materials Science and Engineering, 24 (4). 045012. doi:10.1088/0965-0393/24/4/045012 ISSN 0965-0393.
Aldegunde, Manuel, Kermode, James R. and Zabaras , Nicholas (2016) Development of an exchangeβcorrelation functional with uncertainty quantification capabilities for density functional theory. Journal of Computational Physics, 311 . pp. 173-195. doi:10.1016/j.jcp.2016.01.034 ISSN 0021-9991.
Bianchini, Federico, Kermode, James R. and De Vita, Alessandro (2016) Data for Modelling defects in Ni-Al with EAM and DFT calculations. [Dataset]
Packwood, David, Kermode, James R., Mones, Letif, Bernstein, Noam, Woolley, John, Gould, Nicholas, Ortner, Christoph and Csanyi, Gabor (2016) A universal preconditioner for simulating condensed phase materials. Journal of Chemical Physics, 144 (16). 164109. doi:10.1063/1.4947024 ISSN 0021-9606.
2015
Kermode, James R., Gleizer, Anna, Kovel, Guy, Pastewka, Lars, Csanyi, Gabor, Sherman, Dov and De Vita, Alessandro (2015) Low speed crack propagation via kink formation and advance on the silicon (110) cleavage plane. Physical Review Letters, 115 (13). pp. 1-5. 135501. doi:10.1103/PhysRevLett.115.135501 ISSN 0031-9007.
Li, Zhenwei, Kermode, James R. and De Vita, Alessandro (2015) Molecular dynamics with on-the-fly machine learning of quantum-mechanical forces. Physical Review Letters, Volume 114 . Article number 096405. doi:10.1103/PhysRevLett.114.096405 ISSN 0031-9007.
Peguiron, Anke, Ciacchi, Lucio Colombi, De Vita, Alessandro, Kermode, James R. and Moras, Gianpietro (2015) Accuracy of buffered-force QM/MM simulations of silica. Journal of Chemical Physics, 142 . 064116. doi:10.1063/1.4907786 ISSN 0021-9606.
Bitzek, Erik, Kermode, James R. and Gumbsch, Peter (2015) Atomistic aspects of fracture. International Journal of Fracture, 191 (1). pp. 13-30. doi:10.1007/s10704-015-9988-2 ISSN 0376-9429.
Corbett, Greg, Kermode, James R., Jochym, Dominik Bogdan and Refson, Keith (2015) A Python interface to CASTEP. Rutherford Appleton Laboratory Technical Reports: Rutherford Appleton Laboratory.
2014
Singh, Gaurav, Kermode, James R., De Vita, Alessandro and Zimmerman, Robert W. (2014) Validity of linear elasticity in the crack-tip region of ideal brittle solids. International Journal of Fracture, 189 (1). pp. 103-110. doi:10.1007/s10704-014-9958-0 ISSN 0376-9429.
Kermode, James R., Peralta, Giovanni, Li, Zhenwei and De Vita, Alessandro (2014) Multiscale modelling of materials chemomechanics : brittle fracture of oxides and semiconductors. Procedia Materials Science, Volume 3 . pp. 1681-1686. doi:10.1016/j.mspro.2014.06.271 ISSN 2211-8128 .
Gleizer, Anna, Peralta, Giovanni, Kermode, James R., De Vita, Alessandro and Sherman, Dov (2014) Dissociative chemisorption of O2 inducing stress corrosion cracking in silicon crystals. Physical Review Letters, Volume 112 (Number 11). Article number 115501. doi:10.1103/PhysRevLett.112.115501 ISSN 0031-9007.
2013
Kermode, James R., Ben-Bashat, L., Atrash, F., Cilliers, J. J., Sherman, D. and De Vita, Alessandro (2013) Macroscopic scattering of cracks initiated at single impurity atoms. Nature Communications, Volume 4 . Article number 2441. doi:10.1038/ncomms3441 ISSN 2041-1723.
2010
Moras, Gianpietro, Choudhury, Rathin, Kermode, James R., Csanyi, Gabor, Payne, Mike C. and De Vita, Alessandro (2010) Hybrid quantum/classical modeling of material systems : the learn on the fly molecular dynamics scheme. In: Dumitrica, Traian , (ed.) Trends in Computational Nanomechanics : Transcending Length and Time Scales. Springer, pp. 1-23. ISBN 9781402097843
Kermode, James R., Cereda, Silva, Tangney, P. and De Vita, Alessandro (2010) A first principles based polarizable O(N) interatomic force field for bulk silica. Journal of chemical physics, Volume 133 (Number 9). Article number 094102. doi:10.1063/1.3475565 ISSN 0021-9606.
2009
Bernstein, Noam, Kermode, James R. and Csanyi, Gabor (2009) Hybrid atomistic simulation methods for materials systems. Reports on Progress in Physics, Volume 72 (Number 2). Article number 026501. doi:10.1088/0034-4885/72/2/026501 ISSN 0034-4885.
2008
Kermode, James R., Albaret, T., Sherman, Dov, Bernstein, Noam, Gumbsch, P., Payne, Mike C., CsΓ‘nyi, A. and De Vita, Alessandro (2008) Low-speed fracture instabilities in a brittle crystal. Nature, Volume 455 (Number 7217). pp. 1224-1227. doi:10.1038/nature07297 ISSN 0028-0836.
2007
Csanyi, Gabor, Moras, Gianpietro, Kermode, James R., Payne, Mike C., Mainwood, Alison and De Vita, Alessandro (2007) Multiscale modeling of defects in semiconductors : a novel molecular-dynamics scheme. In: Drabold , David A. and Estreicher , Stefan K., (eds.) Theory of Defects in Semiconductors. Topics in Applied Physics, Volume 104 . Berlin Heidelberg: Springer Berlin Heidelberg, pp. 193-212. ISBN 9783540334002
This list was generated on Thu Dec 7 05:55:07 2023 GMT.