They spend a lot of text describing the fact that it wouldn’t be possible without Frontier, so I think they are aware of the cost. The whole ecosystem of little, easy to apply for compute credit grants, and then larger grants (like the one they mention applying for at the end) is part of the solution to that problem. It doesn’t seem like ignorance, but rather a choice to emphasize in the writing that they are part of the solution.

Yes supercomputer time is scarce and expensive.

Physical laboratory time, materials, and workers are also scarce and expensive. And physical lab tests can consume a lot of calendar time.

So, even with the constraints and costs, using the supercomputer to run 1,000 or 10,000 tests and then physical lab tests on only the few most promising results can still less costly in both funds and especially calendar time than the costs and time to run a similar number of physical lab tests to produce the results.

It is literally a balancing of the scarcity and costs of each mode of getting to the results, and those experts in the field, with their own labs, are making the claim that this is the way their research should proceed. Do you have actual information and specific knowledge that in fact proves them wrong (b/c that comment seems a lot more hand-wavey vs theirs)?

> Not to mention, even if your supercomputer has an idea you still need a lab that can confirm the idea.

I think this is the critical aspect. You don't need to own a supercomputer to run simulations in supercomputers. Sometimes you don't even need supercomputers at all. It might be a challenge but it's not prohibitive.

What's clearly a blocker is the verification & validation work to assess if a specific model actually works. You need to run experimental tests to check if your module is any good, and you need to run experimental tests to check if the output of your computational models correlate with reality. That costs both time and money.

Supercomputers are becoming more accessible. There's a large gap between research and real-world use, such numerical models need to be thoroughly tested for robustness before they can be deployed.

And according to experience, such studies are usually conducted simultaneously with Laboratory experiments, or already have Lab results they can compare with. If not, such study acts as a new source of synthetic MD data which can be picked up by the experimental folks.

I do agree that people who write such blogs tends to sell these ideas or studies as finished products which they are far from. The product of such studies are usually a paper or in other cases a patent. An idea others can build upon, like lego bricks.

I haven't heard of carbon fiber itself causing much cancer. There's a little chatter about carbon nanotubes potentially causing cancer but that's more of a "this looks sus" thing than a "this def causes cancer" thing. I'm sure you could use CF with cancerous plastics or whatever but that seems like a stretch.

But then I realized people screech about asbestos far in excess of the actual risk it poses, and here someone is screeching about CF. So it kind of is like asbestos in that way.

Task failed successfully I guess.

Isn't this true for regular old fiberglass as well?

We often see people working with those materials wear protective equipment (full coveralls, breathing / eye protection).