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Designing alloys for additive manufacturing (AM) presents significant opportunities. Still, the chemical composition and processing conditions required for printability (ie., their suitability for fabrication via AM) are challenging to…
Aluminum scandium nitride (AlScN) has emerged as a highly promising material for high-temperature applications due to its robust piezoelectric, ferroelectric, and dielectric properties. This study investigates the behavior of Al0.7Sc0.3N…
Atomistic simulations provide insights into structure-property relations on an atomic size and length scale, that are complementary to the macroscopic observables that can be obtained from experiments. Quantitative predictions, however, are…
Reactor physics is the study of neutron properties, focusing on using models to examine the interactions between neutrons and materials in nuclear reactors. Artificial intelligence (AI) has made significant contributions to reactor physics,…
Since the discovery of high-$T_c$ cuprates the quest for new superconductors has shifted toward more anisotropic, strongly correlated materials with lower carrier densities and competing magnetic and charge density wave orders. While these…
Artificial intelligence (AI) has transformed materials discovery, enabling rapid exploration of chemical space through generative models and surrogate screening. Yet current AI workflows optimize performance first, deferring sustainability…
Modern advances in generating ultrabright electron beams have unlocked unprecedented experimental advances based on synchrotron radiation. Current challenges lie in improving the quality of electron sources with novel photocathode materials…
This work presents a modeling framework to represent the thermomechanical behavior of complex materials based on micromechanical dynamics. The framework is applied to nuclear fuel rod elements composed of Zircaloy-2 cladding tubes and…
It is important to develop sustainable processes in materials science and manufacturing that are environmentally friendly. AI can play a significant role in decision support here as evident from our earlier research leading to tools…
Ultra-high-temperature ceramics (UHTCs) are candidate structural materials for applications that require resiliency to extreme temperature (>2000{\deg}C), high mechanical loads, or aggressive oxidizing environments. Processing UHTC…
Nickel based superalloys display outstanding properties such as excellent creep strength, remarkable fracture toughness parameters, and corrosion resistance. For this reason, Ni based materials are considered as materials dedicated to the…
Understanding interfacial thermal transport is essential for improving thermal management in high-speed power electronic devices, where the efficient removal of excess heat is a critical challenge. In this study, a machine learning…
Advanced nuclear reactor systems face increasing cybersecurity threats as sophisticated attackers exploit cyber-physical interfaces to manipulate control systems while evading traditional IT security measures. This research presents a…
Positive temperature coefficient (PTC) materials are extensively utilized in self-regulating temperature applications. Nonetheless, their applicability is typically constrained to low-temperature ranges, rendering them ineffective in medium…
Thermoelectric materials offer a promising pathway to directly convert waste heat to electricity. However, achieving high performance remains challenging due to intrinsic trade-offs between electrical conductivity, the Seebeck coefficient,…
The concept of small modular reactor has changed the outlook for tackling future energy crises. This new reactor technology is very promising considering its lower investment requirements, modularity, design simplicity, and enhanced safety…
Lattice thermal conductivity (LTC) is a critical parameter for thermal transport properties, playing a pivotal role in advancing thermoelectric materials and thermal management technologies. Traditional computational methods, such as…
The discovery of superconducting materials has led to their use in technological marvels such as magnetic-field sensors in MRI machines, powerful research magnets, short transmission cables, and high-speed trains. Despite such applications,…
Inverse design is a central goal in much of science and engineering, including frequency-selective surfaces (FSS) that are critical to microelectronics for telecommunications and optical metamaterials. Traditional surrogate-assisted…
The affordable, robust, compact (ARC) reactor conceptual design study aims to reduce the size, cost, and complexity of a combined fusion nuclear science facility (FNSF) and demonstration fusion Pilot power plant. ARC is a 200-250 MWe…