Using DFT when it's not appropriate
There's a famous quote:
"When you give someone a hammer, everything to them looks like a nail"
Many beginners only know DFT and try to use it on everything, even when the system is small enough to use CCSD(T) or some other method that is more accurate and not too expensive for small enough systems.
Furthermore, many people use DFT as a black box, without knowing in detail how it works, when it works, and when it's expected to fail.
For the transition-metal-containing system in this post, 8 different fairly decent hybrid functionals were used, and the energy gap of interest ranged from -14.6 to +9.6 kcal/mol (a 25 kcal/mol range for a number that was estimated to be at most 15 kcal/mol in magnitude), and only 3 out of 8 functionals even gave the correct sign for this energy gap. For reference, the term "chemical accuracy" means an accuracy of +/- 1 kcal/mol, so 8 different fairly decent hybrid functionals give energy gaps spanning a range of 25 kcal/mol, it's quite bad.
- Use CCSD(T) or MRCI+Q if you can. Sometimes CCSD(T) is also bad, but in those cases you'll often know because it won't likely converge.
- Don't just check one functional, because in the mentioned example, one functional gave an energy gap of -14.6 kcal/mol and another one gave +9.6 kcal/mol for the same system. Try many functionals and check to see if they are giving values in agreement.
- Check ahead of time to see if the system you're studying is multi-reference, strongly correlated, or just poorly suited for DFT. For example if you're studying anions, then the "density-driven error" in DFT is known to be particularly bad and you might want to use Density-Corrected DFT.
- Check to see if the functional you are using has been optimized on a dataset containing molecules similar to the one you're studying: Don't use a functional that was optimized only for organic systems, on a transition-metal-containing inorganic complex.
- Perhaps do an a priori search for functionals that are well suited for your system.