A review of displacement cascade simulations using molecular dynamics emphasizing interatomic potentials for TPBAR components
Ankit Roy, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Ram Devanathan, Ayoub Soulami
Abstract
Abstract This review explores molecular dynamics simulations for studying radiation damage in Tritium Producing Burnable Absorber Rod (TPBAR) materials, emphasizing the role of interatomic potentials in displacement cascades. Recent machine learning potentials (MLPs), trained on quantum data, enhance prediction accuracy over traditional models like EAM. We highlight temperature, PKA energy, and composition effects on damage evolution in TPBAR components, recommending suitable potentials and discussing advancements for materials in extreme radiation environments.
Topics & Concepts
Molecular dynamicsCascadeInteratomic potentialDisplacement (psychology)Radiation damageQuantumComputer sciencePhysicsRadiationStatistical physicsMaterials scienceChemistryComputational chemistryNuclear physicsQuantum mechanicsChromatographyPsychologyPsychotherapistNuclear Materials and PropertiesFusion materials and technologiesIon-surface interactions and analysis