Understanding the Impact of Hydrogen Activation by SrCe0.8Zr0.2O3−δ Perovskite Membrane Material on Direct Non-Oxidative Methane Conversion

Direct non-oxidative methane conversion (DNMC) converts methane (CH4) in one step to olefin and aromatic hydrocarbons and hydrogen (H2) co-product. Membrane reactors comprising methane activation catalysts and H2-permeable membranes can enhance methane conversion by in situ H2 removal via Le Chatelier's principle. Rigorous description of H2 kinetic effects on both membrane and catalyst materials in the membrane reactor, however, has been rarely studied. In this work, we report the impact of hydrogen activation by hydrogen-permeable SrCe0.8Zr0.2O3−δ (SCZO) perovskite oxide material on DNMC over an iron/silica catalyst. The SCZO oxide has mixed ionic and electronic conductivity and is capable of H2 activation into protons and electrons for H2 permeation. In the fixed-bed reactor packed with a mixture of SCZO oxide and iron/silica catalyst, stable and high methane conversion and low coke selectivity in DNMC was achieved by co-feeding of H2 in methane stream. The characterizations show that SCZO activates H2 to favor “soft coke” formation on the catalyst. The SCZO could absorb H2in situ to lower its local concentration to mitigate the reverse reaction of DNMC in the tested conditions. The co-existence of H2 co-feed, SCZO oxide, and DNMC catalyst in the present study mimics the conditions of DNMC in the H2-permeable SCZO membrane reactor. The findings in this work offer the mechanistic understanding of and guidance for the design of H2-permeable membrane reactors for DNMC and other alkane dehydrogenation reactions.

Flash Light Sintered Lanthanum Strontium Cobalt Ferrite(LSCF) Electrode for High Performance IT-SOFCs

The high temperature(900oC~) thermal sintering process is necessary to fabricate the Solid oxide fuel cells(SOFCs). However, the chemical reaction has occurred between solid oxide material components, electrode and electrolyte. In the case of lanthanum strontium cobalt ferrite (La0.6Sr0.4Co0.2Fe0.8O3-δ, LSCF) electrode, the SrZrO3(SZO) secondary phase is produced at the electrolyte interface even when using the gadolinium doped ceria(GDC) buffer layer for blocking the strontium and zirconium diffusion. The SZO layer hinders the oxygen ion transfer and deteriorates fuel cell performance. By using a novel flash light sintering(FLS) method, we have successfully solved the problem of secondary phase formation in the conventional high temperature thermal sintering process. The microstructure and thickness of the LSCF electrode are analyzed using a field emission scanning electron microscope(FE-SEM). The strontium diffusion and secondary phase are confirmed by X-ray diffraction (XRD), energy dispersive spectrometer method of SEM, TEM (SEM-, TEM-EDS). The NiO-YSZ anode supported LSCF cathode cells are adopted for electro chemical analysis which is measured at 750oC. The maximum power density of the thermal sintered LSCF cathode at 1050oC is 699.6mW/cm2, while that of the flash light sintered LSCF cathode is 711.6mW/cm2. This result proves that the electrode was successfully sintered without a secondary phase using flash light sintering.

Enhanced Foam Stability Using Nanoparticle in High Salinity High Temperature Condition for Eor Application

The capability of commercial nanoparticles to perform as foam stabilizer were investigated at reservoir temperature of 96°C. Al2O3, Fe3O4, Co3O4, CuO, MgO, NiO, ZrO2, ZnO and SiO2 nanoparticles that were characterized using XRD, FTIR, FESEM-EDX, TEM and PSA, were blended in the in-house formulated surfactant named IVF respectively at a particular ratio. The test was performed with and without the presence of reservoir crude oil. Results showed that formulation with nanoparticles enhanced foam stability by having longer foam half-life than the IVF surfactant alone, especially in the absence of oil. Only SiO2 nanoparticles were observed to have improved the foam stability in both test conditions. The unique properties of SiO2 as a semi-metal oxide material may have contributed to the insensitivity of SiO2 nanoparticle towards crude oil which is known as a foam destabilizer. The physical barrier that was formed by SiO2 nanoparticles at the foam lamella were probably unaffected by the presence of crude oil, thus allowing the foams to maintain its stability. In thermal stability tests, we observed the instability of all nanoparticles in the IVF formulation at 96°C. Nanoparticles were observed to have separated and settled within 24 hours. Therefore, surface modification of nanoparticle was done to establish steric stabilization by grafting macro-molecule of polymer onto the surface of SiO2. This in-house developed polymer grafted silica nanoparticles are named ZPG nanoparticles. The ZPG nanoparticles passed the thermal stability test at 96°C for a duration of 3 months. In the foam wetness analysis, ZPG nanoparticles were observed to have produced more wet foams than IVF formulation alone, indicating that ZPG is suitable to be used as foam stabilizer for EOR process as it showed catalytic behaviour and thermally well-stable at reservoir temperature.

Rapid and flexible segmentation of electron microscopy data using few-shot machine learning

Automatic segmentation of key microstructural features in atomic-scale electron microscope images is critical to improved understanding of structure–property relationships in many important materials and chemical systems. However, the present paradigm involves time-intensive manual analysis that is inherently biased, error-prone, and unable to accommodate the large volumes of data produced by modern instrumentation. While more automated approaches have been proposed, many are not robust to a high variety of data, and do not generalize well to diverse microstructural features and material systems. Here, we present a flexible, semi-supervised few-shot machine learning approach for segmentation of scanning transmission electron microscopy images of three oxide material systems: (1) epitaxial heterostructures of SrTiO3/Ge, (2) La0.8Sr0.2FeO3 thin films, and (3) MoO3 nanoparticles. We demonstrate that the few-shot learning method is more robust against noise, more reconfigurable, and requires less data than conventional image analysis methods. This approach can enable rapid image classification and microstructural feature mapping needed for emerging high-throughput characterization and autonomous microscope platforms.

Iridium metallene oxide for acidic oxygen evolution catalysis

Exploring new materials is essential in the field of material science. Especially, searching for optimal materials with utmost atomic utilization, ideal activities and desirable stability for catalytic applications requires smart design of materials’ structures. Herein, we report iridium metallene oxide: 1 T phase-iridium dioxide (IrO2) by a synthetic strategy combining mechanochemistry and thermal treatment in a strong alkaline medium. This material demonstrates high activity for oxygen evolution reaction with a low overpotential of 197 millivolt in acidic electrolyte at 10 milliamperes per geometric square centimeter (mA cmgeo−2). Together, it achieves high turnover frequencies of 4.2 sUPD−1 (3.0 sBET−1) at 1.50 V vs. reversible hydrogen electrode. Furthermore, 1T-IrO2 also shows little degradation after 126 hours chronopotentiometry measurement under the high current density of 250 mA cmgeo−2 in proton exchange membrane device. Theoretical calculations reveal that the active site of Ir in 1T-IrO2 provides an optimal free energy uphill in *OH formation, leading to the enhanced performance. The discovery of this 1T-metallene oxide material will provide new opportunities for catalysis and other applications.