Quantification of uncertainty in first-principles predicted mechanical properties of solids: Application to solid ion conductors
Zeeshan Ahmad, Venkatasubramanian Viswanathan

TL;DR
This paper introduces a computationally efficient method to quantify uncertainty in first-principles predicted mechanical properties of solids, enhancing the reliability of materials screening processes.
Contribution
It proposes a novel ensemble-based approach that estimates uncertainty by perturbing exchange-correlation functional parameters, improving robustness over existing methods.
Findings
Uncertainty bounds successfully encompass values from multiple GGA functionals.
Method applied to silicon demonstrates reliable uncertainty quantification.
Ensemble approach is computationally efficient and robust.
Abstract
Computationally-guided material discovery is being increasingly employed using a descriptor-based screening through the calculation of a few properties of interest. A precise understanding of the uncertainty associated with first principles density functional theory calculated property values is important for the success of descriptor-based screening. Bayesian error estimation approach has been built-in to several recently developed exchange-correlation functionals, which allows an estimate of the uncertainty associated with properties related to the ground state energy, for e.g. adsorption energies. Here, we propose a robust and computationally efficient method for quantifying uncertainty in mechanical properties, which depends on the derivatives of the energy. The procedure involves calculating the energy around the equilibrium cell volume with different strains and fitting the…
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