Epitaxial Cu2O and epitaxial Cu are usually accessed from chemically distinct electrodeposition baths. Here, we show that both can be obtained from a single alkaline Cu(II) electrolyte without added organic complexing ligands by exploiting Cu(II) amphoterism in 3 M NaOH. Speciation and solubility calculations show that a 5 mM Cu(II)/3 M NaOH bath can support dissolved Cu(II) and that Cu(OH)42– is the dominant dissolved mononuclear Cu(II) species. Voltammetry identifies distinct cathodic regimes for Cu2O deposition, Cu deposition, and reduction of pre-existing Cu2O films: deposition at −0.35 V vs Ag/AgCl yields Cu2O, whereas deposition at −0.80 V vs Ag/AgCl yields Cu, and film reduction occurs at −1.1 V vs Ag/AgCl. Hydrodynamic voltammetry shows that Cu deposition is strongly mass-transport dependent, whereas Cu2O deposition is only weakly dependent on rotation rate, indicating different transport and interfacial constraints in the two regimes. X-ray diffraction shows that the Cu2O regime yields single-domain epitaxial Cu2O(111) on Au(111), whereas the Cu regime yields epitaxial Cu(111) with twin in-plane domains. Switching the applied potential further enables sequential epitaxial Cu/Cu2O bilayer growth while retaining the Cu2O underlayer. These results establish a chemically simple route to potential-programmed epitaxial oxide/metal growth from a single alkaline Cu(II) electrolyte.
Abstract Microbial contamination remains a persistent challenge across healthcare, environmental, and food production sectors, contributing to delayed wound healing, increased healthcare costs, and the spread of water- and foodborne diseases. The growing prevalence of antimicrobial resistance further highlights the need for alternative strategies to effectively control pathogenic microorganisms. Antimicrobial sponges have emerged as promising platforms because of their high porosity, large surface area, and ability to incorporate a wide range of antimicrobial agents. These materials can be constructed from natural and synthetic polymers as well as hybrid matrices, enabling the integration of disinfectants, essential oils, metal-based agents, and other bioactive compounds to enhance antimicrobial performance. This Review summarizes recent advances in the design and development of antimicrobial sponge materials, with particular emphasis on how material composition and antimicrobial strategies influence performance across different applications. Applications across biomedical, dental, environmental, and food-related fields are discussed to highlight the versatility of the sponge-based antimicrobial platforms. Finally, current challenges and future directions aimed at improving the performance, functionality, and translational potential are outlined.
Abstract Molecular and ionic transport through nanopores in two-dimensional (2D) materials, which govern seawater desalination, are complex phenomena influenced by material chemistry, functional groups, and electrostatic interactions. We present a unified picture of nanoscale transport in 2D nanopores, demonstrating a pervasive principle valid across graphene, hexagonal boron nitride (hBN), and molybdenum disulfide (MoS2). That is, low edge charge effectively sieves ions, while positive edge charge excludes boron, which is regarded as the Achilles heel of seawater desalination. Quantum-mechanical calculations reveal that functional groups, such as hydrogen, hydroxyl, and oxo, modulate edge charges, tuning salt/boron rejection and water flux. Molecular simulations indicate that hydrogen-functionalized boron-terminated nanopores and oxygen-functionalized nitrogen-terminated hBN nanopores demonstrate superior salt rejection of close to 100%, due to roughly neutral edge atoms, which offer balanced ion rejection. This finding is found to persist with MoS2 and graphene nanopores, wherein low edge charge correlates with better salt rejection. Furthermore, hydrogen-functionalized nitrogen-terminated nanopores completely reject boron, a neutral contaminant that is difficult to remove from seawater, due to their positive edge charge. However, excessive positive charge compromises anion rejection and water permeance, despite repelling boric acid. These charge- and chemistry-mediated mechanisms provide a predictive basis and design rules for nanoporous 2D desalination membranes with high selectivity.
Abstract Materials artificial intelligence (AI) is increasingly used to support claims that extend beyond property prediction, including physical interpretation, mechanism identification, and design guidance. As the claim shifts from prediction to understanding, the required evidence must shift accordingly. In this Perspective, we argue that physical meaning in materials AI should be treated as a claim-evidence relationship rather than as a property conferred by model architecture or explanation method. Predictive accuracy establishes performance within a tested domain, physical consistency shows compatibility with constraints, and model interpretation reveals how information is used. These are necessary forms of evidence, but they have boundaries, and none by itself justifies a mechanism or design principle. We use a claim-evidence map and validation ladder to identify where evidence boundaries arise and what additional support is required for stronger claims. Examples from out-of-distribution property prediction, text-mined synthesis data, and machine-learned interatomic potentials show how validation domain, data set history, and sampled configuration regime can limit the physical claims a model can support. We then use defect-chemistry-guided materials AI in proton-conducting oxides as a case analysis, where physically defined defect variables allow model outputs to be evaluated across prediction, interpretation, transport mechanism, and domain-limited design descriptors. The central argument is that physical meaning depends on aligning the strength of a materials claim with the evidence available to support it. Progress in materials AI should not be judged by predictive performance alone, but whether models make physical meaning testable.
