[thearn4]

1. Aerospace

2.1 Access to energy / energy density of fuels (batteries included). This is the case across a wide range of industries and problem areas of course, not just transportation. But incremental optimizations in efficiency have lead to squeezing more performance out of the margins, but no Moore's-law type growth will ever happen without some kind of energy breakthrough.

2.2 Going forward, tightly coupled systems will be the norm. The traditional tube-and-wing aircraft with bolted on nacelles is a bit of a dead end for civil aviation. Systems to enable a more complex design workflow (e.g. graph based dataflow with accurate gradients) will be more paramount.

3. Research into the next generation of energy storage materials, and improved large-scale gradient-based numerical optimization algorithms.