Computational Modeling of Materials and Components for Next-generation Energy Infrastructure Applications

Emerging technologies based on modern power cycles (H2, CO2, etc.) are critical for the development of modern energy generation infrastructure using alternative low-carbon sources such as solar, wind, and nuclear. Improving the performance of crucial components such as turbine blades, thermal and environmental barrier coatings, and cladding materials in nuclear reactors is essential to improve the efficiency of these technologies.

Since materials employed in these applications are routinely exposed to extreme environments such as aqueous and gas corrosion, severe temperature and pressure conditions, cyclic stresses, intense radiation damage, etc., there is tremendous research focus on trying to understand and predict materials’ response under such stimuli.

This Research Topic will accept original articles, letters, and reviews that tackle materials discovery, development, and performance challenges using computational modeling and computation-accelerated experimental approaches. The scope covers various simulation scales ranging from atomistic/molecular (DFT, MD) to mesoscale (CALPHAD, FEA). Topics include, but are not limited to:

• Alloying effect on the mechanical properties of metals, refractory multi-component alloys, ceramics, etc.
• Interfacial properties of dissimilar materials.
• Stability of high-temperature coatings in chemically aggressive environments.
• Modeling and machine learning-enhanced additive manufacturing
• Multiscale models for mechanical behavior in extreme conditions
• Multi-property optimization for coatings (thermal conductivity, mechanical strength, etc.)