||Experimental measurements exhibit a certain degree of uncertainty that is described by their precision and accuracy. The same holds true for computational results, as, similarly to the limitation of measuring instruments, the models behind simulation methodologies and their numerical evaluations exhibit limitations. Moreover, in recent years, stochastic computational techniques and data analysis methods have advanced the study of materials in a wide variety of fields. To be interpreted correctly, results obtained using any of the above-mentioned methodologies, at any length scale, need a careful evaluation of their uncertainties. Moreover, a way to evaluate the predictability of simulation techniques is to validate their findings using other, experimental or computational, approaches.
This symposium will focus on stochastic methods, computational methodology validation, as well as uncertainty evaluation for computational approaches at various length scale, including methodologies, like density functional theory (DFT), empirical energy models, etc., whose results have traditionally been reported without error bars. The goal of the symposium is to cover these research topics in an interdisciplinary approach, which connects theory and experiment, with a view towards materials applications.
Topics and 4 planned sessions:
• Advancements in stochastic methodologies (for material discovery)
• Validation and uncertainty evaluation for DFT and other quantum-mechanical based methods
• Validation and uncertainty evaluation for empirical potential/force fields based simulation methodologies
• Validation and uncertainty evaluation for larger scale methodologies (finite element, mesoscale, etc.).