In the “Beyond Moore’s Law” era with increasing edge intelligence, domain-specific computers in heterogeneous fabrics will rule the roost. Algorithms accelerating NP-hard (i.e., provably complex) applications or pre-compute processes that do not demand exact precision will run on tailored hardware. The hardware performance, rather than the algorithmic or software efficiency, may dictate solution speed, energy cost, footprint, and cyber-resilience. Clever hardware innovations for application-specific integrated circuits (ASICs) are no longer a rarity, but they all employ conventional material platforms like silicon, insulators, and compound semiconductors. This proposal will explore a new prospect – the use of quantum materials with exotic properties – to elicit computational activity with unprecedented size, weight, and power (SWaP). Additionally, innovative technologies and methods to train students in lab procedures through virtual platforms (e.g. GoPro video sessions, kid-friendly Minecraft and Roblox design challenges) will be developed and posted on YouTube and Vimeo for the public. Students selected through online exercises will be evaluated using rubrics developed by learning centers at the universities and sent to the Army Research Laboratory (ARL) and the National Institute of Standards and Technology (NIST). For the hardware needs of modern computing and artificial intelligence to be “self-contained”, all the data and resources needed to execute a computing t