DFT insights into the mechanical properties of NMs

NMs, whose dimensions are below 100 nm, provide unique mechanical properties from quantum effects, surface phenomena, and small-scale interactions that account for their importance in energy storage, biomedicine, nanoelectronics, etc. This review discusses computational prediction of mechanical properties (for example, elasticity, strength, and fracture behavior) in NMs, especially using Density Functional Theory as a central tool. By conducting DFT calculations, we can analyze how NMs will behave across different mechanical states, which is critical for designing properties for advanced applications. Problems related to the application of DFT (e.g., high computational cost and failure in modeling defects or exchange-correlation functionals) are discussed. Despite these challenges, DFT must provide insights that complement other tools and strategies. However, further development is essential for improving its quantitative predictability on temperature and multiscale models. Future work is needed to integrate ML with DFT furtherto refine the accuracy and computational efficiency, thereby extending the capability of DFT to accelerate the discovery of new NMs with superior mechanical properties.