Negative results are still results!
In my career, I’ve had a lot of ideas that have worked out, and also a lot of ideas that have not worked out. But when you’ve spent a lot of time on a project, you’ve almost always learned some things, even if they weren’t the things you hoped for. Share that knowledge with others!
I always think that the saddest possible fate for a piece of work you’ve poured a lot of time and effort into is to have it die quietly in the dark. Instead, you can at least write a paper as a grave marker to mourn its passing:
Let me tell you about the life of my friend, Nifty New Graph Model (NNGM). NNGM was a bright and promising idea, full of energy and wanting to help people with [relevant application here]. When NNGM was young, it seemed full of promise, all the way up to around 15 nodes. But as it scaled, everything seemed to go wrong. And when we did tests, we got the fatal diagnosis: Bad Big O. Well, we knew then that NNGM didn’t have the future we’d all hoped for, and so we’re putting it into cryogenic storage. But we wanted to tell its story here: maybe others can learn from our experiences, or maybe even figure out how to cure NNGM’s problems and bring it out of storage in the future.
Silly? A little, maybe, but I find that publishing a story like this (in more professional language, of course) really helps me to let go and move on. You won’t put it in a glamour journal, but there’s always solid society-level publications or megajournals that are happy to accept results that are true but not exciting.
And sometimes these articles really can be helpful to others too! Some of my own “gravestone” publications have dozens of citations, clearly having picked up an afterlife that I had never envisioned for them.
Bottom line: publish the sad things that you’ve learned, and then move on.