Composition engineering of short-range-ordered polyhedra in Ni-Mo-P-B metallic glass for electrochemical sensing

Metallic glasses (MGs), despite exhibiting superior electrochemical catalytic and sensing activity to crystalline solids, remain difficult to rationally design because the structural units that directly correlate to active sites are poorly resolved. Here, we address this challenge by showing that a small change in Ni content (±4 at%) in Ni-Mo-P-B MGs gives precise control of short‑range-ordered (SRO) polyhedral motifs and their medium‑range connections. Synchrotron X-ray analysis reveals that the Ni 64 Mo 16 P 16 B 4 (Ni 64 ) stabilizes ten-coordinated (Z10) bi-capped square archimedean antiprisms (BSAPs) as the dominant SRO polyhedral, whereas Ni 60 Mo 20 P 16 B 4 (Ni 60 ) and Ni 68 Mo 12 P 16 B 4 (Ni 68 ) are dominated by nine-coordinate (Z9) tricapped trigonal prisms (TTPs). Crucially, this engineered SRO dramatically enhances the electrochemical glucose sensing: Ni 64 delivers ultrahigh sensitivity, a wide linear range, and stable operation over seven days, whose performance is far superior to conventional crystalline probes. First-principles calculations reveal that only at a Ni/Mo ratio of 4 does short-range chemical ordering favor the highly symmetric Z10 BSAPs with two Mo atoms occupying the two polyhedral caps. These Mo‑capped Z10 clusters optimally modulate Mo-Ni electronic interactions, lowering the *OH adsorption barrier and boosting catalytic reactivity. A miniaturized glucose sensor was fabricated by integrated the MG with a screen-printed electrode, demonstrating the practical applicability. Notably, we found that the dominant polyhedra show homology to local building blocks of nearby crystalline phases, suggesting that amorphous structures inherit crystal-like motifs that govern both stability and properties. Our work establishes an atomic-scale structural engineering paradigm for MG design, bridging crystalline-amorphous structural homology with functional optimization, and deepening the understanding of structure–property correlations in MG systems.