Demystifying the influence of ion-surface interface science for the effective design of hydrogen storage tanks

Hydrogen storage tank design has traditionally been described through separate mechanical, thermal, structural, and regulatory frameworks that share no common physical vocabulary. This review argues instead that these descriptions rest on a single underlying layer, the ion-surface interface, and develops that argument through an explicit four-tier dependency hierarchy rather than a flat enumeration of coupled interfaces. Tier 1 establishes the material-hydrogen interface as the domain in which ion-surface interface science applies in the literal, mechanistic sense, governed by hybridization-dependent dissociation barriers, defect-mediated trapping, and, only where a genuine electrolyte is present, electric-double-layer behavior; electric-double-layer language is deliberately withheld from dry gas-phase and solid-state systems, for which charge-transfer and orbital-hybridization descriptions are shown to be the physically correct alternative. Tier 2 establishes the thermodynamic interface as bidirectionally coupled to Tier 1 through Oriani-type local-equilibrium feedback between temperature, trap occupancy, and reaction kinetics. Tiers 3 and 4 are shown to be connected to this physical core only indirectly, as an engineering-response layer and a statistical risk-governance layer respectively, correcting the logical inconsistency of treating structural, safety, and regulatory constraints as coequal expressions of interfacial physics. Within this framework, hydrogen embrittlement is resolved mechanistically across hydrogen-enhanced decohesion, localized plasticity, strain-induced vacancy formation, and hydride-induced cracking, with condition-dependent thresholds established across four independent alloy systems, quantitative isosteric-heat and ionic-modifier comparisons are developed for material-based storage, and route-specific rate-limiting mechanisms are stated explicitly in place of a single blanket claim. The review closes by developing a cross-scale parameter-passing framework linking first-principles, atomistic, continuum, and data-driven methods, illustrated by a demonstrated closed-loop machine-learning materials-discovery example, and by identifying the specific, named gaps, in tank-level integration of physisorptive materials, in strategy-specific cost data, and in a fully quantitative design-rule synthesis, that remain open for the field.