I wanted to address that in the second paragraph, which I ultimately deleted before submitting, because I couldn't phrase it right. But since you brought it up: I'd consider this an effect of specialization.
In the process of improving your object-level "how things work" goals, you end up generalizing and stacking increasingly complex theoretical models. Soon enough, you end up with people working high up the stack - not knowing or caring about the initial goals. Those people end up growing the "mound of knowledge" both upwards and sideways. The work is sort of self-justifying, but really, it's also self-similar. Where early materials science may have been driven by, say, desire for better/cheaper weapons, soon enough, you have people doing materials science because they desire to solve a puzzle. Whether the practitioners are smelting different combinations of ores to find one that will win them the war, or they're mixing up different kinds of equations to figure out a clean solution to a theoretical conundrum - it's the same process, same motivation. And it always involves play.
The kind of methodical, boring approach, with hypotheses and control groups and peer-reviewed papers? That's the boring part you have to do after play.
See also (with no implied judgement in this context): software developers that lose sight of (or care little about) business goals, and instead aim for theoretical markers of what "good code" is, and/or solve abstract puzzles of algorithms and architecture. Or the MBAs that view companies as abstract money-printing processes, running them by the rulebook that's entirely independent of whatever it is the business is actually doing or selling. Both are cases of growing complexity creating a new field of work that's independent of what brought it into existence.
It is also a specific purpose, a deliberate endeavour. We are in front of a world, we have to digest its phenomena, we try to understand it - it is a primal process, i.e. mental digestion. In some ways it could be argued that the "scientific drive" is anterior to the technical one: first you assess, then you act. Consistently, science started as "natural philosophy".
It is relevant, in the framework of "scientific drive as (development from the natural process of) mental digestion", that terminologically "science" is not just "the realm where false statements start to exist (and are tried to be avoided)" ("discriminate" - ex scindere), but also, before that, an activity of sorting, of "separating" conceptual elements - mental digestion. The "scient" (as a participle of scire, used as "to know") is a "distinguishing" mind.
We not only «desire to solve a puzzle» - it is our nature (as per the above) as minds dealing with a phenomenical world we need to grasp, as part of the activity of "seeing" it, already before action.
«Play[ing]» is a process that both allows to refine knowledge of the world, physically (in the physical play), and to refine the grasping of the world, mentally (in the mental play).
> growing complexity
Or just abstraction, enabled by a refined framework (following which, other areas become primary, topical - in the synthetic effort which is part of the above said process).
In the process of improving your object-level "how things work" goals, you end up generalizing and stacking increasingly complex theoretical models. Soon enough, you end up with people working high up the stack - not knowing or caring about the initial goals. Those people end up growing the "mound of knowledge" both upwards and sideways. The work is sort of self-justifying, but really, it's also self-similar. Where early materials science may have been driven by, say, desire for better/cheaper weapons, soon enough, you have people doing materials science because they desire to solve a puzzle. Whether the practitioners are smelting different combinations of ores to find one that will win them the war, or they're mixing up different kinds of equations to figure out a clean solution to a theoretical conundrum - it's the same process, same motivation. And it always involves play.
The kind of methodical, boring approach, with hypotheses and control groups and peer-reviewed papers? That's the boring part you have to do after play.
See also (with no implied judgement in this context): software developers that lose sight of (or care little about) business goals, and instead aim for theoretical markers of what "good code" is, and/or solve abstract puzzles of algorithms and architecture. Or the MBAs that view companies as abstract money-printing processes, running them by the rulebook that's entirely independent of whatever it is the business is actually doing or selling. Both are cases of growing complexity creating a new field of work that's independent of what brought it into existence.