  Polyphenols are natural molecules of crucial importance in many applications,
of which tannic acid (TA) is one of the most abundant and established. Most
high-value applications require precise control of TA interactions with the
system of interest. However, the molecular structure of TA is still not
comprehended at the atomic level, of which all electronic and reactivity
properties depend. Here, we combine an enhanced sampling global optimization
method with density functional theory (DFT)-based calculations to explore the
conformational space of TA assisted by unsupervised machine learning
visualization, and then investigate its lowest energy conformers. We study the
external environment's effect on the TA structure and properties. We find that
vacuum favors compact structures by stabilizing peripheral atoms' weak
interactions, while in water, the molecule adopts more open conformations. The
frontier molecular orbitals of the conformers with lowest harmonic vibrational
free energy have a HOMO-LUMO energy gap of 2.21 (3.27) eV, increasing to 2.82
(3.88) eV in water, at the DFT generalized gradient approximation (and hybrid)
level of theory. Structural differences also change the distribution of
potential reactive sites. We establish the fundamental importance of accurate
structural consideration in determining TA and related polyphenols interactions
in relevant technological applications.
