Cita APA

Mortazavi, B., Podryabinkin, E. V., Roche, S., Rabczuk, T., Zhuang, X., & Shapeev, A. V. (2020). Machine-learning interatomic potentials enable first-principles multiscale modeling of lattice thermal conductivity in graphene/borophene heterostructures.

Citación estilo Chicago

Mortazavi, Bohayra|||0000-0003-3031-5057, Evgeny V. Podryabinkin, Stephan|||0000-0003-0323-4665 Roche, Timon Rabczuk, Xiaoying|||0000-0001-6562-2618 Zhuang, y Alexander V. Shapeev. Machine-learning Interatomic Potentials Enable First-principles Multiscale Modeling of Lattice Thermal Conductivity in Graphene/borophene Heterostructures. 2020.

Cita MLA

Mortazavi, Bohayra|||0000-0003-3031-5057, et al. Machine-learning Interatomic Potentials Enable First-principles Multiscale Modeling of Lattice Thermal Conductivity in Graphene/borophene Heterostructures. 2020.