Computational Alchemy: Atomic Impedance as a Unifying Principle for Chemical Behavior

This work proposes “atomic impedance” as a unifying quantity that links chemical bonding, metal toxicity, enzymatic catalysis, and even ancient metallurgical traditions. Using only three standard atomic properties—first ionization energy, Pauling electronegativity, and covalent radius—the framework defines an impedance value that cleanly separates elements into Givers (electron donors), Takers (electron acceptors), and Bridges (catalytic transformers). Across a 23-compound set, impedance-based ratios predict bond type (ionic, covalent, metallic) with 82.6% accuracy, outperforming the classic electronegativity-difference model, especially for hydrogen-containing bonds. The most striking result is that the seven classical “planetary metals” (Au, Ag, Hg, Cu, Fe, Sn, Pb) form an extraordinarily tight cluster in impedance space (p = 0.00005 via 100k Monte Carlo trials), aligning with the same “Bridge” window that hosts biological metal cofactors such as Zn, Cu, Fe, and Mn. The framework naturally explains heavy metal toxicity as impedance mimicry (e.g., Pb and Hg substituting for Cu at enzyme sites) and offers a quantitative account of lithium’s clinical action via near-perfect impedance matching with sodium (R = 0.992), enabling Li⁺ to permeate Na⁺ channels. While the model does not capture all forms of toxicity or evolutionary contingency, it provides a simple, falsifiable, and computationally transparent way to view elements as participants in impedance-matching networks—from atomic bonds to biological signaling.