Electric field switching of antiferromagnetic domains in YMn2O5: a probe of the multiferroic mechanism

We employ neutron spherical polarimetry to determine the nature and population of the coexisting antiferromagnetic domains in multiferroic YMn2O5. By applying an electric field, we prove that reversing the electrical polarization results in the population inversion of two types of in-plane domains, related to each other by inversion. Our results are completely consistent with the exchange-striction mechanism of ferroelectricity, and support a unified model where cycloidal ordering is induced by coupling to the main magnetic order parameter.     

Ferroelectricity in an ising chain magnet

We report discovery of collinear-magnetism-driven ferroelectricity in the Ising chain magnet Ca3Co2-xMn(x)O6 (x approximately 0.96). Neutron diffraction shows that Co2+ and Mn4+ ions alternating along the chains exhibit an up-up-down-down ( upward arrow upward arrow downward arrow downward arrow) magnetic order. The ferroelectricity results from the inversion symmetry breaking in the upward arrow upward arrow downward arrow downward arrow spin chain with an alternating charge order. Unlike in spiral magnetoelectrics where antisymmetric exchange coupling is active, the symmetry breaking in Ca3(Co,Mn)2O6 occurs through exchange striction associated with symmetric superexchange.     

Formation of pancakelike Ising domains and giant magnetic coercivity in ferrimagnetic LuFe2O4

We have studied quasi-two-dimensional multiferroic LuFe2O4 with strong charge-spin-lattice coupling, in which low-temperature coercivity approaches an extraordinary value of 9 T in single crystals. The enhancement of the coercivity is connected to the collective freezing of nanoscale pancakelike ferrimagnetic domains with large uniaxial magnetic anisotropy ("Ising pancakes"). Our results suggest that collective freezing in low-dimensional magnets with large uniaxial anisotropy provides an effective mechanism to achieve enhanced coercivity. This observation may help identify novel approaches for synthesis of magnets with enhanced properties.     

Three‐Dimensional Branched and Faceted Gold–Ruthenium Nanoparticles: Using Nanostructure to Improve Stability in Oxygen Evolution Electrocatalysis

Achieving stability with highly active Ru nanoparticles for electrocatalysis is a major challenge for the oxygen evolution reaction. As improved stability of Ru catalysts has been shown for bulk surfaces with low‐index facets, there is an opportunity to incorporate these stable facets into Ru nanoparticles. Now, a new solution synthesis is presented in which hexagonal close‐packed structured Ru is grown on Au to form nanoparticles with 3D branches. Exposing low‐index facets on these 3D branches creates stable reaction kinetics to achieve high activity and the highest stability observed for Ru nanoparticle oxygen evolution reaction catalysts. These design principles provide a synthetic strategy to achieve stable and active electrocatalysts.     

Multilevel Deep Feature Generation Framework for Automated Detection of Retinal Abnormalities Using OCT Images

Optical coherence tomography (OCT) images coupled with many learning techniques have been developed to diagnose retinal disorders. This work aims to develop a novel framework for extracting deep features from 18 pre-trained convolutional neural networks (CNN) and to attain high performance using OCT images. In this work, we have developed a new framework for automated detection of retinal disorders using transfer learning. This model consists of three phases: deep fused and multilevel feature extraction, using 18 pre-trained networks and tent maximal pooling, feature selection with ReliefF, and classification using the optimized classifier. The novelty of this proposed framework is the feature generation using widely used CNNs and to select the most suitable features for classification. The extracted features using our proposed intelligent feature extractor are fed to iterative ReliefF (IRF) to automatically select the best feature vector. The quadratic support vector machine (QSVM) is utilized as a classifier in this work. We have developed our model using two public OCT image datasets, and they are named database 1 (DB1) and database 2 (DB2). The proposed framework can attain 97.40% and 100% classification accuracies using the two OCT datasets, DB1 and DB2, respectively. These results illustrate the success of our model.     

Ultrathin Fe‐N‐C Nanosheets Coordinated Fe‐Doped CoNi Alloy Nanoparticles for Electrochemical Water Splitting

The development of highly active and cost‐effective catalyst materials toward electrochemical water splitting is of great importance for converting and storing the intermittent solar energy in the form of hydrogen. Herein, for the first time, an ultrathin Fe and N‐co‐doped carbon nanosheet encapsulated Fe‐doped CoNi alloy nanoparticle (FeCoNi@FeNC) composite is obtained and applied as a bifunctional catalyst for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). This catalyst exhibits prominent catalytic performances for both HER and OER, which only requires overpotentials of 102 and 330 mV, respectively, to reach a current density of 10 mA cm^?2 in alkaline media. The high catalytic activity is intrinsically associated with the presence of Fe in both nanosheets and nanoparticles, which has triggered the occurrence of coordinative effects between Fe‐N‐C and FeCoNi that are beneficial for HER and OER, as revealed by electrochemical techniques. In an overall water splitting electrolyzer, FeCoNi@FeNC is employed as both the cathode and anode catalysts, achieving 12 mA cm^?2 at 1.63 V for a duration of more than 12 h.     

Mid-infrared heterodyne phase-sensitive dispersion spectroscopy in flame measurements

We present the first demonstration of heterodyne phase-sensitive dispersion spectroscopy (HPSDS) for in situ, non-intrusive and quantitative CO₂ concentration measurements in flames. Dispersion spectroscopy retrieves gas properties by measuring the refractive index in the vicinity of a molecular resonance. The HPSDS scheme features a significant diagnostic advantage of the intrinsic immunity to laser power fluctuations caused by beam steering, thermal radiation and soot scattering in combustion environments, and thus no extra calibration process is required. In this work, we described the spectroscopic fundamentals for measuring heterodyne phase signals in flames. As a proof of principle, we used a mid-infrared interband cascade laser (ICL) near 4183?nm to exploit the strong CO₂ transitions in the R-branch of the v₃ fundamental band. The HPSDS signals of four CO₂ lines, R(76), R(78), R(80) and R(82), were measured in CH₄/air flames to obtain CO₂ concentrations at different equivalence ratios (Φ?=?0.8–1.2), yielding a good agreement with the simultaneous laser absorption measurements using the same ICL. With its immunity to laser power fluctuations verified experimentally, the HPSDS sensor was successfully implemented to measure CO₂ concentrations in C₂H₄/air sooting flames (Φ?=?1.78–2.38). Laser dispersion spectroscopy proves to be a promising and alternative diagnostic tool for combustion measurements.