https://asianresassoc.org/journals/index.php/nanonext <p><strong>NanoNEXT (ISSN 2582-8622, Online)</strong> is a quarterly, peer-reviewed, open access international journal publishing high-quality research in nanoscience and nanotechnology. The journal primarily focuses on nanomaterials and nanoscale systems, including synthesis, characterization, theoretical modelling and simulation, nanostructures, nano thin films, nanocomposites, magnetic nanomaterials, nanoelectronics, nanoscale devices, molecular electronics, nanophotonics, plasmonics, catalysis, nanosensors, quantum-confined materials, nanotubes, biomimetic materials, nanobiotechnology, bionanomaterials, and nanomedicine.</p> Asian Research Association en-US NanoNEXT 2582-8622 https://asianresassoc.org/journals/index.php/nanonext/article/view/8688 <p>High-entropy oxides (HEOs) are an important class of compositionally complex oxide materials for energy storage and electrocatalysis. Their significance does not arise solely from the presence of five or more cations; multication disorder also influences phase stability, defect chemistry, oxygen-vacancy formation, local lattice strain, redox activity, and surface reconstruction. Since the first experimental demonstration of entropy-stabilized rocksalt (MgCoNiCuZn)O, the field has expanded to include rocksalt, spinel, perovskite, fluorite, pyrochlore, layered, and mixed-anion oxide frameworks. These structures are now being explored for solid electrolytes, supercapacitors, oxygen evolution, oxygen reduction, hydrogen evolution, lithium-ion and sodium-ion batteries, and bifunctional water-splitting systems. This review examines the thermodynamic basis of HEO formation, the role of crystal structure in compositional design, the impact of synthesis techniques on phase purity and defect populations, and the mechanistic links between local disorder and electrochemical function. Particular attention is given to oxygen vacancies, mixed-valence cations, short-range ordering, operando surface reconstruction, and descriptor-based catalyst design. The review also assesses how density functional theory, CALPHAD, machine learning, active learning, and inverse design are accelerating HEO development. One key conclusion is that future progress will depend more on designing the right type of disorder for a specific function than on simply adding more components. Standardized terminology, reproducible synthesis protocols, improved local and operando characterization, morphology-matched benchmarking, open datasets, and device-level validation are all required for the field to advance reliably.</p> Pradeep I Balaprabhakaran S Copyright (c) 2026 Pradeep I, Balaprabhakaran S https://creativecommons.org/licenses/by/4.0 2026-08-08 2026-08-08 7 3 1 38 10.54392/nnxt2631