The interchangeable operation of alkaline oxygen evolution and reduction using bifunctional electrocatalysts in devices consolidates the commercialization milestone of energy storage in hydrogen, and yet, it is usually limited by issues of carbon corrosion in electrocatalysts and inhomogeneous electrode fabrication. Here, we demonstrate a synthetic route toward carbon-free ternary rock salt oxide (i.e., NiO/CoO/FeO) hollow spheres with silver decoration on the surface for durable operation in bifunctional cells. These Ag-decorated ternary oxides exhibit an overall bifunctional potential gap (ΔE = E j10, OER – E jhalf, ORR) of 0.89 V. Operando Raman studies show that the rock salt structure shows the phenomenon of a highly reversible local environment during the charge–discharge OER cycles, a key characteristic for high durability in bifunctional devices. At equivalent content between Ni and Co, NiOOH is the main OER-active species with CoOOH and/or CoO2 as the cocatalyst, where the presence of the FeO dopant facilitates structural activation and reversibility. With the proof-of-concept performance in anion-exchange membrane (AEM) devices, the catalysts achieve a durable cyclic operation with a high current density (1000 mA cm–2) at smaller potentials (2.03 V) than RuO2 (2.16 V) under the electrolyzer mode, while it can yield two times greater power density (96.98 mW cm–2) than Pt/C (53.58 mW cm–2) in the fuel cell mode.

Establishment of vegetable soybean (edamame) [Glycine max (L.) Merr.] germplasms has been highly valued in Asia and the United States owing to the increasing market demand for edamame. The idea of core collection (CC) is to shorten the breeding program so as to improve the availability of germplasm resources. However, multidimensional phenotypes typically are highly correlated and have different levels of missing rate, often failing to capture the underlying pattern of germplasms and select CC precisely. These are commonly observed on correlated samples. To overcome such scenario, we introduced the “multiple imputation” (MI) method to iteratively impute missing phenotypes for 46 morphological traits and jointly analyzed high-dimensional imputed missing phenotypes (ECimpu) to explore population structure and relatedness among 200 Taiwanese vegetable soybean accessions. An advanced maximization strategy with a heuristic algorithm and PowerCore was used to evaluate the morphological diversity among the ECimpu. In total, 36 accessions (denoted as CCimpu) were efficiently selected representing high diversity and the entire coverage of the ECimpu. Only 4 (8.7%) traits showed slightly significant differences between the CCimpu and ECimpu. Compared to the ECimpu, 96% traits retained all characteristics or had a slight diversity loss in the CCimpu. The CCimpu exhibited a small percentage of significant mean difference (4.51%), and large coincidence rate (98.1%), variable rate (138.76%), and coverage (close to 100%), indicating the representativeness of the ECimpu. We noted that the CCimpu outperformed the CCraw in evaluation properties, suggesting that the multiple phenotype imputation method has the potential to deal with missing phenotypes in correlated samples efficiently and reliably without re-phenotyping accessions. Our results illustrated a significant role of imputed missing phenotypes in support of the MI-based framework for plant-breeding programs.

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