Capacitive deionization (CDI) of brackish water has the main challenge: finding the electrode frameworks that can handle long-term electrochemical cycling without losing crystallinity. We are studying Prussian Blue Analogues (PBAs) and their high-entropy variants (HEPBAs) because both applications use the same multi-metal cyanide framework — in CDI as a reversible positive ions host A PC-scale pilot has compared single-metal Na₂MnFe(CN)₆ with a five-metal (Mn, Fe, Co, Ni, Cu)[Fe(CN)₆] HEPBA modelled after Feng et al. (Nano Energy 2025). A step-response molecular dynamics experiment with GFN1-xTB shows that HEPBA exhibits about 40% smaller peak-force oscillation amplitude and a roughly threefold tighter M–Fe cube-edge bond-length distribution than the single-metal PBA under the same Na perturbation. A per-atom analysis identified the Ni–N and Cu–N coordination shells as the most deforming links, providing a concrete target for substitution design. What we cannot do on a PC scale, and what we are asking the NAISS allocation for: (i) DFT validation of the xTB findings on a small set of HEPBA snapshots using Quantum ESPRESSO 7.5 (PBE+U, ortho-atomic projectors); (ii) fine-tuning of a universal machine-learning interatomic potential (MACE-MP-0) on this DFT data, then nanosecond-scale fatigue MD on 500-atom cells beyond xTB's reach; (iii) screening of HEPBA composition variants — Cr or Zn replacing the weak-link Ni and Cu. (iv) training and validation of machine learning models for expedited and large-scale Digital Twins.