Changing sample size during experiment? Will the significance and power levels hold constant if I don't see statistically significant results and decide to wait to allow for more samples to be collected?

No! This is a dangerous practice. In effect, you’re playing something like the following game.
Flip a coin, betting \$1000 on heads. It lands on tails (no rejection), a result you do not like. Now bet \$2000 on the next flip. It comes up heads, you collect your money, you walk away from the game, and you declare yourself a master coin-flip player since you won a bunch of money.
You can simulate this with a true null hypothesis to see how your type I error rate inflates. Just use some conditional (if/else) logic in a loop to keep adding observations to your sample until you either achieve a rejection ($p\le\alpha$) or reach some absolute maximum sample size. You will see a high error rate, much higher than the $\alpha$-level you deem acceptable.
