Achieving Active and Stable Amorphous IrVOxOHy for Water Splitting.

Evaluating the structural and electronic-state characteristics of long-range disordered amorphous iridium (Ir)-based oxides is still unsatisfying. Compared with the benchmark IrO2, the higher oxygen evolution reaction (OER) performance brought by IrOxOHy was normally considered to be associated with the pristine IrIII-containing species. However, such a conclusion conflicts with the opinion that high-valence metals can create excellent OER activity. To resolve such contradictions, we synthesized a pure amorphous Lu1.25IrOxOHy (Lu = lutetium) catalyst in this work. In combination with the comprehensive electrochemical evaluation in alkaline and acidic media, ex situ Ir L3-edge and O K-edge X-ray absorption spectroscopy and theoretical calculations revealed that the ultrahigh OER performance of reconstructed IrOx/Lu1.25IrOxOHy in acidic media was identified to be driven by the more d-hole-containing electronic state of IrV created by cationic vacancies. The pristine properties of IrIII-containing Lu1.25IrOxOHy conversely inhibit the OER activity in alkaline media. Additionally, the high edge-shared [IrOx]-[IrOx] motif proportion structure in amorphous Lu1.25IrOxOHy achieves a stable OER process, which exhibits a high S-number stability index similar to IrO2. We demonstrate that the key factor of the edge-shared [IrOx]-[IrOx] motif with cationic vacancies in IrVOxOHy could rationally reveal the source for most of the high-performance Ir-based materials.

Surface Reconstruction for Forming the [IrO6]-[IrO6] Framework: Key Structure for Stable and Activated OER Performance in Acidic Media.

The surface reconstruction of iridium-based derivatives (AxIryOz) was extensively demonstrated to have an excellent oxygen evolution reaction (OER) performance in an acidic medium. It is urgent to use various spectroscopy and computational methods to explore the electronic state changes in the surface reconstruction process. Herein, the underestimated Lu2Ir2O7 was synthesized and investigated. Four typical forms of electrochemistry impedance spectra involved in the reconstruction process revealed three dominating forms of reconstructed pyrochlore in the OER stage, including the inner intact pyrochlore, mid metastable [IrO6]-[IrO6] framework, and the outer collapse amorphous layer. The enhancing electron transport efficiency of the corner-shared [IrO6]-[IrO6] framework was revealed as a critical role in acidic systems. The density of state (DOS) for the constructed [IrO6]-[IrO6] framework corroborated the enhancement of Ir-O hybridization and the downshift of the d-band center. Additionally, we contrast the pristine and reconstruction properties of the Pr2Ir2O7, Eu2Ir2O7, and Lu2Ir2O7 in alkaline and acidic media. The DOS and the XANES results reveal the scale relationship between the O 2p band center and the intrinsic activity for bulk pyrochlore in alkaline media. The highest O 2p center and the highest Ir-O hybridization of Lu2Ir2O7 exhibited the best OER performance among the Ir-based pyrochlore, up to a ninefold improvement in Ir-mass activity compared to IrO2. Our findings emphasize the electrochemical behavior of the reconstruction process for activated water-splitting performance.

A novel support vector machine with globality-locality preserving.

Support vector machine (SVM) is regarded as a powerful method for pattern classification. However, the solution of the primal optimal model of SVM is susceptible for class distribution and may result in a nonrobust solution. In order to overcome this shortcoming, an improved model, support vector machine with globality-locality preserving (GLPSVM), is proposed. It introduces globality-locality preserving into the standard SVM, which can preserve the manifold structure of the data space. We complete rich experiments on the UCI machine learning data sets. The results validate the effectiveness of the proposed model, especially on the Wine and Iris databases; the recognition rate is above 97% and outperforms all the algorithms that were developed from SVM.