- Ph.D., Institute for Physical Chemistry, Bulgarian Academy of Sciences, 1998
- M.S., University of Sofia, Bulgaria, 1991
- Associate Principal Scientist, National Institute of Aerospace,2015-present
- Senior Researcher, National Institute of Aerospace,2003-2015
- Post-Doctoral Researcher, Argonne National Laboratory, 2001-2003
- Visiting Scientist, Argonne National Laboratory, 1999-2001
- Post-Doctoral Researcher, Research Center Karlsruhe, Germany, 1999-2001
- Visiting Scientist, Max-Planck-Institute for Polymer Research, 1997, 1999
- Staff Scientist, Institute for Physical Chemistry, Bulgarian Academy of Sciences, 1995-1999
- Staff Scientist, Central Laboratory of Mineralogy and Crystallography, Bulgarian Academy of Sciences, 1991-1995
- Deformation and fracture mechanisms in metals and nanocrystalline materials
- Solid-state phase transformations in shape memory alloys
- Multiscale modeling: atomistic molecular-dynamics coupled with continuum finite-element modeling for representing fracture processes in metal and metal-composite systems
- Molecular simulations of mechanical and electroactive properties of boron-nitride nanotubes and their application in metal matrix composites
Applying Machine Learning Algorithms In Developing Artificial Neural Networks Based Atomistic Simulations
When properly trained, artificial neural networks (ANNs) are shown to successfully emulate the complex atomic energy landscape as defined by quantum mechanics (QM), while achieving orders of magnitude faster performance compared to QM derived calculations. The relatively simple functional form of ANNs, composed of series of matrix operations, allows them to scale very well on multicore machines with graphic card accelerators, reaching the speed of the classical empirical atomic potentials. Thus, the use of ANNs opens the possibility for simulating multi-million atoms systems, achievable so far only by classical potentials, while preserving the accuracy of QM-based calculations.
Atomistic Simulations in Additive Manufacturing
Additive manufacturing is a relatively recent, but very promising technique of creating machine components of complex structure in a fast and cheap way. As a new technique, its understanding relies heavily on the precise modeling of the processes of rapid melting and solidification of the employed materials. Atomistic simulations become crucial in revealing these complex physical processes at fundamental level.
Rohmann, C., Yamakov, V.I., Park, C., Fay, C., Hankel, M., Searles, D.J., “Interaction of Boron Nitride Nanotubes with Aluminium: A Computational Study,” The Journal of Physical Chemistry C, 122, (2018) 15226-15240.
Yamakov, V.I., Park, C., Kang, J.H., Chen, X., Ke, C., Fay, C., “Piezoelectric and Elastic Properties of Multiwall Boron-Nitride Nanotubes and Their Fibers: A Molecular Dynamics Model,” Comp. Mat. Sci., 135 (2017) 29-42.
Yamakov, V., Hochhalter, J.D., Leser, W.P., Warner, J.E., Newman, J.A., Purja Pun, G.P., Mishin, Y., “Multiscale Modeling of Sensory Properties of Co-Ni-Al Shape Memory Particles Embedded in an Al Metal Matrix,” Journal of Materials Science, 51 (2016) 1204-1216.
Kang, J.H., Sauti, G., Park, C., Yamakov, V.I., Wise, K.E., Lowther, S.E., Fay, C.C., Thiebeault, S.A., Bryant, R.G., “Multifunctional Electroactive Nanocomposites Based on Piezoelectric Boron Nitride Nanotubes,” ACSNano, 9 (2015) 11942-11950.
Purja Pun, G.P., Yamakov, V., Mishin, Y., “Interatomic potential for the ternary Ni-Al-Co system and application to atomistic modeling of the B2-L10 martensitic transformation,” Modelling Simul. Mater. Sci. Eng., 23 (2015) 065006-1-23.
Yamakov, V., Park, C., Kang, J.H., Wise, K.E., Fay, C., “Piezoelectric Molecular Dynamics Model for Boron Nitride Nanotubes,” Comp. Mat. Sci., 95 (2014) 362-370.
Yamakov, V., Warner, D.H., Zamora, R.J., Saether, E., Curtin, W.A., Glaessgen, E.H., “Investigation of Crack Tip Dislocation Emission in Aluminum using Multiscale Molecular Dynamics Simulation and Continuum Modeling,” J. Mech. Phys. Solids, 65 (2014) 35-53.
Saether, E., Yamakov, V., Glaessgen, E.H., “An Embedded Statistical Method for Coupling Molecular Dynamics and Finite Element Analyses,” International Journal for Numerical Methods in Engineering, 78 (2009) 1292-1319.
Millett, P.C., T. Desai, Yamakov, V., Wolf, D., “Atomistic Simulations of Diffusional Creep in a Nanocrystalline BCC Material,” Acta Materialia, 56(2008) 3688-3698.
Yamakov, V., Saether, E., Phillips, D.R., Glaessgen, E.H., “Molecular-Dynamics Simulation-Based Cohesive Zone Representation of Intergranular Fracture Processes in Aluminum,” J. Mech. Phys. Solids, 54 (2006) 1899-1928.
Yamakov, V., Saether, E., Phillips, D.R., Glaessgen, E.H., “Dynamic Instability in Intergranular Fracture,” Phys. Rev. Lettrs., 95 (2005), 015502-1-4.
Wolf, D., Yamakov, V., Phillpot, S.R., Mukherjee, A., Gleiter, H., “Deformation of Nanocrystalline Materials by Molecular-Dynamics Simulation: Relationship to Experiments?” Acta Mater., 53 (2005), 1-40.
Yamakov, V., Wolf, D., Phillpot, S.R., Mukherjee, A., Gleiter, H., “Deformation-mechanism map for nanocrystalline metals by molecular-dynamics simulation,” Nature Materials,3 (2004), 43-47.
Yamakov, V., Wolf, D., Phillpot, S.R., Mukherjee, A., Gleiter, H., “Dislocation processes in the deformation of nanocrystalline Al by molecular-dynamics simulation,” Nature Materials,1 (2002), 45-48.
Milchev, A., Yamakov, V., and Binder, K., “Escape transition of a polymer chain: phenomenological theory and Monte Carlo simulations,” Phys. Chem. Chem. Phys., 1 (1999), 2083-2091.
Yamakov, V., Milchev, A. and Binder, K., “Inter-chain structure factors of flexible polymers in solutions: a Monte Carlo investigation,” J. Phys. II France, 7 (1997), 1123-1139.