[Everhusk]

To clarify it wasn't for my thesis but for a nuclear engineering course where we could research whatever. I know not all profs are the same, but generally I do think there is a bit of a herd mentality in academia. My point is that there have been roadblocks for LENR researchers in academia for quite some time, and I hope we can finally remove those.

[glitchc]

Most definitely concur with the herd mentality. It comes from the funding model, which is admittedly rather broken. Unique or off-the-wall ideas often don't receive funding, and once you've been funded for a mainstream idea, it's hard to advocate much for the unique idea without somehow discrediting your proposal or the time you've put in to date. It's a vicious Catch-22. Most researchers start out with unique ideas, then it gets drummed out of them. My area is computer vision, and I see machine learning eating everything, so I can empathize. There seems to be no effort any more in translating a physical phenomena into a quantitive, deterministic model and that's a shame. Neural networks are not an accurate representation of what our eyes and brains are doing. But, it's produced more promising results for the time being, and so we've entered a cycle of funding that promotes machine learning over other approaches. There is recognition of this fact usually, and small pools of money continue to exist for off-the-wall ideas, so the rest of us can make do until the phase passes. Science moves in fits and starts.

Research in high energy physics (cold fusion is a sub-category), is difficult to cobble together on small amounts however. That's why you see profs and labs banding together to raise sufficient resources just for a couple of experiments. And unfortunately for LENR, a great deal of money was spent in the 50s to 70s with no appreciable outcomes, therefore the funding bodies have become jaded and cynical about continuing to fund further research. The area will likely see a resurgence once those board members retire and bright-eyed folks revisit the field.