Atomistic simulation of hardening in bcc iron-based alloys caused by nanoprecipitates

Karavaev, A. V.; Chirkov, P. V.; Kichigin, Roman M.; Dremov, V. V.

doi:10.1016/j.commatsci.2023.112383

Cited by 1 publication

(1 citation statement)

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“…Atomistic modeling in quantum or classical molecular dynamics is currently capable of solving numerous problems of materials science-from the construction of equations of states (EOSs) to predicting the phase diagrams of materials at extremely high pressures and temperatures [3] and estimating the hardening of materials due to irradiation in nuclear power reactors [4]. This approach is free from macroscopic phenomenological parameters.…”

Section: Introductionmentioning

confidence: 99%

On the possibility of using quantum annealers to solve problems of computational materials science

Maletin,

Dremov,

Klebanov

2023

Laser Phys. Lett.

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A promising area of application of quantum computing is computational materials science. In addition to the actively discussed use of quantum computers as simulators for modeling quantum systems, the possibility of using quantum computing to solve the problems of determining the parameters of model multiparameter potentials of intermolecular interaction is of great interest. Especially attractive for these purposes is the method of quantum annealing, as currently the most developed quantum computing technology to solve complex optimization problems. As a first step, the paper presents the algorithms developed for determining the parameters of two classical potentials—Lennard-Jones and Buckingham, designed for implementation on a quantum annealer. We demonstrate mathematical methods for the development of such algorithms. One of them seems to be worthy for the further development and promising for solving more complex problems. Also, we evaluate the scalability of the presented algorithms and justify the possibility of their practical implementation on the current version of the D-Wave quantum annealer.

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Section: Introductionmentioning

confidence: 99%