From atomic mechanisms to multiscale and machine learning assisted modeling: understanding the sintering limit in high purity refractory metals

• Systematically reviews multi-scale modeling approaches, from DFT and MD to ReaxFF and machine-learning interatomic potentials. • Highlights the distinct roles of diffusion, grain-boundary migration, and impurity segregation in the high-density regime. • Discusses the limitations of conventional interatomic potentials in describing late-stage sintering behavior. • Identifies structure-aware, unified potential-energy modeling as a promising direction for understanding sintering limits. High-purity refractory metals are widely used in aerospace, nuclear energy, and semiconductor applications. During sintering, however, these materials frequently exhibit kinetic slowdown and densification stagnation at high relative densities. Unlike impurity-containing systems, high-purity refractory metals generally lack solute pinning effects and second-phase-assisted diffusion pathways. As a result, densification is primarily governed by the coupled effects of lattice diffusion, grain-boundary migration, and localized chemical reactions, which become increasingly critical in the high-density regime. Direct experimental observation of sub-nanometer interfacial evolution during sintering remains extremely challenging, limiting the ability of conventional models to accurately describe the attenuation of driving forces at advanced densification stages. This review summarizes recent progress in multi-scale computational modeling of high-purity refractory-metal sintering, with a focus on density functional theory (DFT), molecular dynamics (MD), reactive force fields (ReaxFF), and machine-learning interatomic potentials (MLIPs). The capabilities and limitations of these approaches at elevated temperatures and high densities are discussed, particularly with respect to their complementary roles in describing diffusion processes, grain-boundary behavior, and pore evolution. Overall, recent studies highlight a growing interest in structure-aware, multi-scale potential-energy modeling. Such approaches provide valuable insight into densification limits in high-purity refractory metals-especially under hydrogen atmospheres-and offer guidance for optimizing high-precision sintering processes.