Robustness of the intrinsic anomalous Hall effect in Fe3GeTe2 to a uniaxial strain

Fe3GeTe2 (FGT), a ferromagnetic van der Waals topological nodal line semimetal, has recently been studied. Using first-principles calculations and symmetry analysis, we investigate the effect of a uniaxial tensile strain on the nodal line and the resultant intrinsic anomalous Hall effect (AHE). Our results reveal their robustness to the in-plane strain. Moreover, the intrinsic AHE remains robust even for artificial adjustment of the atomic positions introduced to break the crystalline symmetries of FGT. When the spin-orbit coupling is absent, the nodal line degeneracy remains intact as long as the inversion symmetry or the two-fold screw symmetry is maintained, which reveal that the nodal line may emerge much more easily than previously predicted. This strong robustness is surprising and disagrees with the previous experimental report [Y. Wang et al., Adv. Mater. 32, 2004533 (2020)], which reports that a uniaxial strain of less than 1 % of the in-plane lattice constant can double the anomalous Hall resistance. This discrepancy implies that the present understanding of the AHE in FGT is incomplete. The possible origins of this discrepancy are discussed.Comment: 7 pages, 3 figure

Improvement of Aerosol Optical Depth Retrieval over Hong Kong from a Geostationary Meteorological Satellite Using Critical Reflectance with Background Optical Depth Correction

Despite continuous efforts to retrieve aerosol optical depth (AOD) using a conventional 5-channelmeteorological imager in geostationary orbit, the accuracy in urban areas has been poorer than other areas primarily due to complex urban surface properties and mixed aerosol types from different emission sources. The two largest error sources in aerosol retrieval have been aerosol type selection and surface reflectance. In selecting the aerosol type from a single visible channel, the season-dependent aerosol optical properties were adopted from longterm measurements of Aerosol Robotic Network (AERONET) sun-photometers. With the aerosol optical properties obtained fromthe AERONET inversion data, look-up tableswere calculated by using a radiative transfer code: the Second Simulation of the Satellite Signal in the Solar Spectrum (6S). Surface reflectance was estimated using the clear sky composite method, awidely used technique for geostationary retrievals. Over East Asia, the AOD retrieved from the Meteorological Imager showed good agreement, although the values were affected by cloud contamination errors. However, the conventional retrieval of the AOD over Hong Kong was largely underestimated due to the lack of information on the aerosol type and surface properties. To detect spatial and temporal variation of aerosol type over the area, the critical reflectance method, a technique to retrieve single scattering albedo (SSA), was applied. Additionally, the background aerosol effect was corrected to improve the accuracy of the surface reflectance over Hong Kong. The AOD retrieved froma modified algorithmwas compared to the collocated data measured by AERONET in Hong Kong. The comparison showed that the new aerosol type selection using the critical reflectance and the corrected surface reflectance significantly improved the accuracy of AODs in Hong Kong areas,with a correlation coefficient increase from0.65 to 0.76 and a regression line change from MI [basic algorithm] = 0.41AERONET + 0.16 to MI [new algorithm] = 0.70AERONET + 0.01

GOCI Yonsei Aerosol Retrieval (YAER) algorithm and validation during the DRAGON-NE Asia 2012 campaign

The Geostationary Ocean Color Imager (GOCI) onboard the Communication, Ocean, and Meteorological Satellite (COMS) is the first multi-channel ocean color imager in geostationary orbit. Hourly GOCI top-of-atmosphere radiance has been available for the retrieval of aerosol optical properties over East Asia since March 2011. This study presents improvements made to the GOCI Yonsei Aerosol Retrieval (YAER) algorithm together with validation results during the Distributed Regional Aerosol Gridded Observation Networks - Northeast Asia 2012 campaign (DRAGON-NE Asia 2012 campaign). The evaluation during the spring season over East Asia is important because of high aerosol concentrations and diverse types of Asian dust and haze. Optical properties of aerosol are retrieved from the GOCI YAER algorithm including aerosol optical depth (AOD) at 550 nm, fine-mode fraction (FMF) at 550 nm, single-scattering albedo (SSA) at 440 nm, Angstrom exponent (AE) between 440 and 860 nm, and aerosol type. The aerosol models are created based on a global analysis of the Aerosol Robotic Networks (AERONET) inversion data, and covers a broad range of size distribution and absorptivity, including nonspherical dust properties. The Cox-Munk ocean bidirectional reflectance distribution function (BRDF) model is used over ocean, and an improved minimum reflectance technique is used over land. Because turbid water is persistent over the Yellow Sea, the land algorithm is used for such cases. The aerosol products are evaluated against AERONET observations and MODIS Collection 6 aerosol products retrieved from Dark Target (DT) and Deep Blue (DB) algorithms during the DRAGON-NE Asia 2012 campaign conducted from March to May 2012. Comparison of AOD from GOCI and AERONET resulted in a Pearson correlation coefficient of 0.881 and a linear regression equation with GOCI AOD = 1.083 x AERONET AOD -0.042. The correlation between GOCI and MODIS AODs is higher over ocean than land. GOCI AOD shows better agreement with MODIS DB than MODIS DT. The other GOCI YAER products (AE, FMF, and SSA) show lower correlation with AERONET than AOD, but still show some skills for qualitative use.open1

Synergistic use of hyperspectral uv-visible omi and broadband meteorological imager modis data for a merged aerosol product

The retrieval of optimal aerosol datasets by the synergistic use of hyperspectral ultraviolet (UV)-visible and broadband meteorological imager (MI) techniques was investigated. The Aura Ozone Monitoring Instrument (OMI) Level 1B (L1B) was used as a proxy for hyperspectral UV-visible instrument data to which the Geostationary Environment Monitoring Spectrometer (GEMS) aerosol algorithm was applied. Moderate-Resolution Imaging Spectroradiometer (MODIS) L1B and dark target aerosol Level 2 (L2) data were used with a broadband MI to take advantage of the consistent time gap between the MODIS and the OMI. First, the use of cloud mask information from the MI infrared (IR) channel was tested for synergy. High-spatial-resolution and IR channels of the MI helped mask cirrus and sub-pixel cloud contamination of GEMS aerosol, as clearly seen in aerosol optical depth (AOD) validation with Aerosol Robotic Network (AERONET) data. Second, dust aerosols were distinguished in the GEMS aerosol-type classification algorithm by calculating the total dust confidence index (TDCI) from MODIS L1B IR channels. Statistical analysis indicates that the Probability of Correct Detection (POCD) between the forward and inversion aerosol dust models (DS) was increased from 72% to 94% by use of the TDCI for GEMS aerosol-type classification, and updated aerosol types were then applied to the GEMS algorithm. Use of the TDCI for DS type classification in the GEMS retrieval procedure gave improved single-scattering albedo (SSA) values for absorbing fine pollution particles (BC) and DS aerosols. Aerosol layer height (ALH) retrieved from GEMS was compared with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data, which provides high-resolution vertical aerosol profile information. The CALIOP ALH was calculated from total attenuated backscatter data at 1064 nm, which is identical to the definition of GEMS ALH. Application of the TDCI value reduced the median bias of GEMS ALH data slightly. The GEMS ALH bias approximates zero, especially for GEMS AOD values of >similar to 0.4 and GEMS SSA values of <similar to 0.95. Finally, the AOD products from the GEMS algorithm and MI were used in aerosol merging with the maximum-likelihood estimation method, based on a weighting factor derived from the standard deviation of the original AOD products. With the advantage of the UV-visible channel in retrieving aerosol properties over bright surfaces, the combined AOD products demonstrated better spatial data availability than the original AOD products, with comparable accuracy. Furthermore, pixel-level error analysis of GEMS AOD data indicates improvement through MI synergy

Spin-memory loss induced by bulk spin–orbit coupling at ferromagnet/heavy-metal interfaces

A spin current through a ferromagnet/heavy-metal interface may shrink due to the spin-flip at the interface, resulting in the spin-memory loss. Here, we propose a mechanism of the spin-memory loss. In contrast to other mechanisms based on interfacial spin–orbit coupling, our mechanism is based on the bulk spin–orbit coupling in a heavy metal. We demonstrate that the bulk spin–orbit coupling induces the entanglement between the spin and orbital degrees of freedom and this spin-orbital entanglement can give rise to sizable spin-flip at the interface even when the interfacial spin–orbit coupling is weak. Our mechanism emphasizes crucial roles of the atomic orbital degree of freedom and induces the strong spin-memory loss near band crossing points between bands of different orbital characters.11Nsciescopu

Interfacial polymerization of polyamide-aluminosilicate SWNT nanocomposite membranes for reverse osmosis

AbstractA new method of single-pass flow which incorporates aluminosilicate single-walled nanotubes (SWNT) in a polyamide matrix was developed to fabricate thin film nanocomposite (TFN) membranes for low pressure reverse osmosis (RO) via interfacial polymerization. The TFN membranes were characterized using attenuated total reflectance–Fourier transform infrared (ATR–FTIR) and X-ray photoelectron spectroscopy (XPS) for the analysis of functional groups as well as composition of SWNTs. The typical morphology of polyamide layers was observed using atomic force microscopy (AFM) and scanning electron microscopy (SEM). The introduction of SWNTs in polyamide active layer is evident with the proliferation of aluminum and silicon elements from XPS analysis. All membranes show the rugose structure with “leaf-like” outgrowths and the “ridge-and-valley” structure commonly observed in polyamide RO membranes. The hydrophilicity was increased as observed in the enhancement in water flux and pure water permeance, due to the presence of hydrophilic nanotubes. With the incorporation of the single-walled aluminosilicate nanotubes, higher permeate flux was achieved while sustaining high rejection of monovalent and divalent ions, typical of polyamide RO membrane

Operational Parameters for Sub-Nano Tesla Field Resolution of PHMR Sensors in Harsh Environments

The resolution of planar-Hall magnetoresistive (PHMR) sensors was investigated in the frequency range from 0.5 Hz to 200 Hz in terms of its sensitivity, average noise level, and detectivity. Analysis of the sensor sensitivity and voltage noise response was performed by varying operational parameters such as sensor geometrical architectures, sensor configurations, sensing currents, and temperature. All the measurements of PHMR sensors were carried out under both constant current (CC) and constant voltage (CV) modes. In the present study, Barkhausen noise was revealed in 1/f noise component and found less significant in the PHMR sensor configuration. Under measured noise spectral density at optimized conditions, the best magnetic field detectivity was achieved better than 550 pT/√Hz at 100 Hz and close to 1.1 nT/√Hz at 10 Hz for a tri-layer multi-ring PHMR sensor in an unshielded environment. Furthermore, the promising feasibility and possible routes for further improvement of the sensor resolution are discussed

Operational Parameters for Sub-Nano Tesla Field Resolution of PHMR Sensors in Harsh Environments

The resolution of planar-Hall magnetoresistive (PHMR) sensors was investigated in the frequency range from 0.5 Hz to 200 Hz in terms of its sensitivity, average noise level, and detectivity. Analysis of the sensor sensitivity and voltage noise response was performed by varying operational parameters such as sensor geometrical architectures, sensor configurations, sensing currents, and temperature. All the measurements of PHMR sensors were carried out under both constant current (CC) and constant voltage (CV) modes. In the present study, Barkhausen noise was revealed in 1/f noise component and found less significant in the PHMR sensor configuration. Under measured noise spectral density at optimized conditions, the best magnetic field detectivity was achieved better than 550 pT/√Hz at 100 Hz and close to 1.1 nT/√Hz at 10 Hz for a tri-layer multi-ring PHMR sensor in an unshielded environment. Furthermore, the promising feasibility and possible routes for further improvement of the sensor resolution are discussed

Effect of Scan Time on Neuro F-18-Fluorodeoxyglucose Positron Emission Tomography Image Generated Using Deep Learning

The purpose of this study was to generate the PET images with high signal-to-noise ratio (SNR) acquired for typical scan durations (H-PET) from short scan time PET images with low SNR (L-PET) using deep learning and to evaluate the effect of scan time on the quality of predicted PET image. A convolutional neural network (CNN) with a concatenated connection and residual learning framework was implemented. PET data from 27 patients were acquired for 900 s, starting 60 minutes after the intravenous administration of FDG using a commercial PET/CT scanner. To investigate the effect of scan time on the quality of the predicted H-PETs, 10 s, 30 s, 60 s, and 120 s PET data were generated by sorting the 900 s LMF data into the LMF data acquired for each scan time. Twenty-three of the 27 patient images were used for training of the proposed CNN and the remaining four patient images were used for test of the CNN. The predicted H-PETs generated by the CNN were compared to ground-truth H-PETs, L-PETS, and filtered L-PETS processed with four commonly used denoising algorithms. The peak signal-to-noise ratios (PSNRs), normalized root mean square errors (NRMSEs), and average region-of-interest (ROI) differences as a function of scan time were calculated. The quality of the predicted H-PETs generated by the CNN was superior to that of the L-PETs and filtered L-PETs. Lower NRMSEs and higher PSNRs were also obtained from predicted H-PETs compared to the L-PETS and filtered L-PETS. ROI differences in the predicted H-PETs were smaller than those of the L-PETS. The quality of the predicted H-PETs gradually improved with increasing scan times. The lowest NRMSEs, highest PSNRs, and smallest ROI differences were obtained using the predicted H-PETs for 120 s. Various performance test results for the proposed CNN indicate that it is possible to generate H-PETs from neuro FDG L-PETS using the proposed CNN method, which might allow reductions in both scan time and injection dose.11Nsci

Thyrotoxic Periodic Paralysis and Polymorphisms of the , , and Genes in Men with Graves Disease

BackgroundThyrotoxic periodic paralysis (TPP) is a rare complication of thyrotoxicosis characterized by acute attacks of muscle weakness and hypokalemia. Recently, variation in several genes was suggested to be associated with TPP. This study evaluated the genetic predisposition to TPP in terms of the β2-adrenergic receptor (ADRB2), androgen receptor (AR), and γ-aminobutyric acid receptor α3 subunit (GABRA3) genes.MethodsThis study enrolled 48 men with Graves disease (GD) and TPP, and 48 GD patients without TPP. We compared the frequencies of candidate polymorphisms between the two groups.ResultsThe frequency of the Gly16/Gly16 genotype in ADRB2 was not significantly associated with TPP (P=0.32). More CAG repeats (≥26) in the AR gene were not correlated with TPP (odds ratio [OR], 2.46; 95% confidence interval [CI], 0.81 to 8.09; P=0.08). The allele frequency of the TT genotype in the GABRA3 gene was not associated with TPP (OR, 1.83; 95% CI, 0.54 to 6.74; P=0.41).ConclusionThe polymorphisms in the ADRB2, AR, and GABRA3 genes could not explain the genetic susceptibility to TPP in Korean men with GD