bluuebunny/crossref_metadata_2025_split huggingface dataset:
All-optical spatio-temporal metrology for isolated attosecond pulses
Authors: He Lixin , Hu Jianchang , Sun Siqi , He Yanqing , Deng Yu , Lan Pengfei , Lu Peixiang 
Published: September 2022

Abstract
Characterizing an isolated attosecond pulse (IAP) is essential for its potential applications. A complete characterization of an IAP ultimately requires the determination of its electric field in both time and space domains. However, previous methods, like the widely-used RABBITT and attosecond streaking, only measure the temporal profile of the attosecond pulse. Here we demonstrate an all-optical method for the measurement of the space-time properties of an IAP. By introducing a non-collinear perturbing pulse to the driving field, the process of IAP generation is modified both spatially and temporally, manifesting as a spatial and a frequency modulation in the harmonic spectrum. By using a FROG-like retrieval method, the spatio-spectral phases of the harmonic spectrum are faithfully extracted from the induced spatio-spectral modulations, which allows a thorough characterization of the IAP in both time and space. With this method, the spatio-temporal structures of the IAP generated in a two-color driving field in both the near- and far-field are fully reconstructed, from which a weak spatio-temporal coupling in the IAP generation is revealed. Our approach overcomes the limitation in the temporal measurement in conventional in situ scheme, providing a reliable and holistic metrology for IAP characterization.
Tuning the interfacial Dzyaloshinskii–Moriya interaction in perpendicularly magnetized CoFeB system
Authors: Ravi Kumar B , Guddeti Sreekar , Anil Kumar P S 
Published: September 2022

Abstract
Magnetic field driven domain-wall motion in the creep regime is investigated with Kerr microscopy in out-of-plane magnetized as-deposited and annealed Ta/Pt/CoFeB/Pt multilayers. In addition to the effect of thermal annealing on the quasi-static magnetic properties of Ta (3 nm)/Pt (3 nm)/CoFeB (

t

C
o
F
e
B

nm)/Pt (2 nm) film stacks where

t

C
o
F
e
B

=
{
0.72
,
0.93
}

, the study focuses on the modified interfacial Dzyaloshinskii–Moriya interaction (iDMI) that governs the dynamics of chiral domain walls. The strength of the iDMI decreases with an increase in both

t

C
o
F
e
B

at a fixed annealing temperature and annealing temperature for a fixed

t

C
o
F
e
B

. While the former behaviour arises due to the interfacial nature of iDMI, the latter correlates with the annealing induced suppression of magnetization and enhancement of interface roughness that could be, respectively, ascribed to B-segregation and Co-Fe-Pt intermixing.
Manipulating the magnetic and transport properties by CuIr thickness in CoFeB/CuIr/IrMn multilayers
Authors: Öztürk Mustafa , Demirci Erdem 
Published: September 2022

Abstract
In this study, it was investigated how the magnetic and electrical properties of the exchange biased multilayers are affected by the Pt and CuIr spacer layer thicknesses. For this purpose, CoFeB/NM/IrMn sample stacks which can be used as magnetic field sensors based on the anisotropic magnetoresistance and planar Hall effect (PHE) were designed. The magnetic and electrical results showed an unexpected behavior to the variations in the spacer layer thickness when a CuIr spacer layer was used instead of a Pt spacer layer in terms of the properties of exchange bias, anisotropic magneto-resistance voltage and PHE voltage. This phenomenon is explained by the layer interdiffusion between CuIr and IrMn layers.
Vacuum barrier induced large spin polarization, giant magnetoresistance, and pure spin photocurrent in ferromagnetic zigzag graphene nanoribbons
Authors: Song Lingling , Liu Lu , Wei Canglong , Zhang Yan , Zhao Han , Ye Runlong , Zheng Xiaohong 
Published: September 2022

Abstract
Based on first-principle calculations combined with non-equilibrium Green’s function method, we investigate the spin-polarized transport properties of a two-probe device which consists of a vacuum barrier sandwiched between two semi-infinite ferromagnetic zigzag graphene nanoribbons (ZGNRs). It is well known that any vacuum barrier itself is not spin-polarized, and meanwhile, the infinite pristine ferromagnetic ZGNR presents no spin polarization in the transmission function around the Fermi level. However, our computational results indicate that robust large spin polarization is found in the proposed device. More interestingly, giant magnetoresistance up to

3.0
×

10
8

%

can be obtained at low bias voltage. Furthermore, the photogalvanic effect-induced fully spin-polarized photocurrent or pure spin photocurrent can be generated in such device by illumination with polarized light, depending on the symmetry of structure. Consequently, our results indicate that vacuum barrier may show interesting spin-polarized transport properties in certain systems and should be taken into consideration in the construction of molecular junctions and spintronic devices.
Energy transfer in hybrid 0D-CdSe quantum dot/2D-WSe2 near-infrared photodetectors
Authors: Meng Haotong , Zhang Fen , Mo Zhangxun , Xia Qinglin , Zhong Mianzeng , He Jun 
Published: September 2022

Abstract
Due to the energy transfer at the interface, the quantum dots (QDs) modification of two-dimensional (2D) materials is an effective and convenient way to improve their optoelectronic properties. In this work, we have studied the influence of the CdSe QDs on the physical properties of the 2D WSe2. After the modification of CdSe QDs, the energy transfer is observed in heterostructures which confirmed by the photoluminescence and Raman results. The WSe2/CdSe QDs heterostructure based phototransistors exhibit an ambipolar characteristic, owing to the typical type-Ⅱ band alignment. Under the illumination of 638 nm light, the performance of the device significantly improved compared with the WSe2 based device: the responsivity increased from 3.6 A W−1 to 9.27 A W−1; the detectivity increased from 7.73 × 109 Jones to 4.38 × 1010 Jones. Meanwhile, the devices exhibit good photoresponse in a wide spectral range from visible light to near-infrared light. Our work suggests that hybridizing 0D QDs and 2D material is a suitable and effective way to enhance the photodetection ability of the device and realize the ambipolar photodetection. It is a potential way to build multifunctional optoelectronic devices with broadband and high photoresponse performances.
Noncollinear magnetism in two-dimensional CrTe2
Authors: Abuawwad Nihad , dos Santos Dias Manuel , Abusara Hazem , Lounis Samir 
Published: September 2022

Abstract
The discovery of two-dimensional (2D) van der Waals magnets opened unprecedented opportunities for the fundamental exploration of magnetism in quantum materials and the realization of next generation spintronic devices. Here, based on a multiscale modelling approach that combines first-principles calculations and a Heisenberg model supplied with ab-initio parameters, we report a strong magnetoelastic coupling in a free-standing monolayer of CrTe2. We demonstrate that different crystal structures of a single CrTe2 give rise to non-collinear magnetism through magnetic frustration and emergence of the Dzyaloshinskii–Moriya interaction. Utilizing atomistic spin dynamics, we perform a detailed investigation of the complex magnetic properties pertaining to this 2D material impacted by the presence of various types of structural distortions akin to charge density waves.
Influence of particle wettability on foam formation in honey
Authors: Tyowua Andrew T , Echendu Adebukola M , Adejo Sylvester O , Binks Bernard P 
Published: September 2022

Abstract
The rising level of obesity is often attributed to high sugar and/or fat consumption. Therefore, the food industry is constantly searching for ways to reduce or eliminate sugar or fat in food products. Therefore, honey foam, which contains little sugar and no fat, can be used as cake, cracker or bread spread instead of butter or margarine which contains a substantial amount of fat or jam that contains a substantial amount of sugar. Small solid particles (nanometers to micrometers) of suitable wettability are now considered outstanding foam-stabilizing agents. However, while the degree of particle wettability necessary to obtain very stable aqueous and nonaqueous foams is well-known, that needed to obtain very stable honey foam is unknown. In this study, the influence of the degree of wettability of fumed silica particles, indicated by their % SiOH (14–100), was investigated in honey in relation to foam formation and foam stability. The honephilic particles (61%–100% SiOH) formed particle dispersion in honey, while foams were obtained with the honephobic particles (14%–50% SiOH). The thread-off between particle dispersion and foam formation occurs at 50% SiOH, meaning foam formation in honey is possible when the particles are at least 50% honephobic. At relatively low particle concentration <1 wt.%, foam volume decreases with increasing honephobicity, but increases with honephobicity at relatively high concentration >1 wt.%. Also, as particle concentration increases, the shape of the air bubbles in the foam changes from spherical to non-spherical. After a little drainage, the foams remain stable to drainage and did not coalesce substantially for more than six months. These findings will guide the formulation of edible Pickering honey foams.
The quantum dynamics of two-component Bose–Einstein condensate: an

Sp(4,R)

symmetry approach
Authors: Wang Chang-Yan , He Yan 
Published: September 2022

Abstract
The compact groups such as SU(n) and SO(n) groups have been heavily studied and applied in the study of quantum many body systems. However, the non-compact groups such as the real symplectic groups are less touched. In this paper, it is revealed that the quantum dynamics of two-component Bose–Einstein condensate can be described by a non-compact real symplectic group

S
p
(
4
,
R
)

. With this group, an explicit form of the wavefunction in any time of the evolution can be given, meanwhile, this whole time evolution can be shown to correspond to a trajectory in a six-dimensional manifold. By introducing a polar coordinate, we can visualize this six-dimensional manifold in 2d unit disk and reveal the relation between the behavior of the trajectory in this manifold and the eigenenergies of the Hamiltonian. Furthermore, the time evolution of expectation value of a physical observable such as number operator is proven closely related to the behavior of the trajectory in this manifold.
Utilization of focused ultrasound for opening of the blood-nerve barrier
Authors: Umansky Daniel , Bing Chenchen , Chu Tak Ho , Alzahrani Saud , Dunn Jeff F. , Pichardo Samuel , Midha Rajiv 
Published: September 2022

Abstract

Objective. Focused ultrasound (FUS) use with and without microbubbles (MB) for investigation of the blood-nerve barrier (BNB) within the peripheral nervous system (PNS) has been performed in this study. We evaluate the feasibility of BNB opening in a rodent sciatic nerve model by direct vision FUS treatment and provide preliminary results of magnetic resonance guided FUS (MRgFUS). Approach. Twenty rodent bilateral sciatic nerves were investigated. Rodents were treated using a benchtop FUS system to directly visualize nerve FUS studies. Definity MB, Evans blue dye (EB) and latex micro beads were injected during studies. Selected animals underwent further compound muscle action potential (CMAP) studies. Sonication peak pressure (MPa), width, duty-cycle and duration as well as MB concentration were varied to investigate effective pressure threshold. Further preliminary MRgFUS studies were performed on selected animals. Immunohistochemistry and histological analysis under florescent microscopy were performed at termination of experiments to verify treatment outcomes. Main results. Three ultrasound pressures and three microbubble concentrations at a single sonication frequency (476.5 kHz) were performed under direct open targeting. Histological analysis demonstrated nerve internal architecture disruption at 1.2 MPa with 166.7 μl kg−1 while 0.3 MPa, with 40 μl kg−1 MB concentration was the lower threshold for consistently observed disruption of the BNB without anatomical microarchitecture disruption. EB leakage was confirmed at the target region in histological evaluation of nerve following MB injection and FUS sonication. Supra-harmonic emissions were detected during FUS exposures following MB injection but not at baseline reference, indicating effective MB response and stable cavitation. CMAP amplitudes showed delayed onset latency and lower amplitudes in sonicated nerves compared to control nerves without evidence of complete conduction block, suggesting a transient BNB disruption, while at lower limit pressure subtle conduction changes were observed. In MRgFUS, targeted nerves demonstrated further contrast agent leak as well as supra-harmonic frequency detection. Significance. Opening of the BNB in the PNS was achieved using FUS and MB in a rodent model. Ongoing work aims to refine FUS parameters for drug delivery into the nerve after experimental transient BNB disruption.
Development of a deep learning network for Alzheimer’s disease classification with evaluation of imaging modality and longitudinal data
Authors: Deatsch Alison , Perovnik Matej , Namías Mauro , Trošt Maja , Jeraj Robert 
Published: September 2022

Abstract

Objective. Neuroimaging uncovers important information about disease in the brain. Yet in Alzheimer’s disease (AD), there remains a clear clinical need for reliable tools to extract diagnoses from neuroimages. Significant work has been done to develop deep learning (DL) networks using neuroimaging for AD diagnosis. However, no particular model has emerged as optimal. Due to a lack of direct comparisons and evaluations on independent data, there is no consensus on which modality is best for diagnostic models or whether longitudinal information enhances performance. The purpose of this work was (1) to develop a generalizable DL model to distinguish neuroimaging scans of AD patients from controls and (2) to evaluate the influence of imaging modality and longitudinal data on performance. Approach. We trained a 2-class convolutional neural network (CNN) with and without a cascaded recurrent neural network (RNN). We used datasets of 772 (N
AD = 364, N
control = 408) 3D 18F-FDG PET scans and 780 (N
AD = 280, N
control = 500) T1-weighted volumetric-3D MR images (containing 131 and 144 patients with multiple timepoints) from the Alzheimer’s Disease Neuroimaging Initiative, plus an independent set of 104 (N
AD = 63, N
NC = 41) 18F-FDG PET scans (one per patient) for validation. Main Results. ROC analysis showed that PET-trained models outperformed MRI-trained, achieving maximum AUC with the CNN + RNN model of 0.93 ± 0.08, with accuracy 82.5 ± 8.9%. Adding longitudinal information offered significant improvement to performance on 18F-FDG PET, but not on T1-MRI. CNN model validation with an independent 18F-FDG PET dataset achieved AUC of 0.99. Layer-wise relevance propagation heatmaps added CNN interpretability. Significance. The development of a high-performing tool for AD diagnosis, with the direct evaluation of key influences, reveals the advantage of using 18F-FDG PET and longitudinal data over MRI and single timepoint analysis. This has significant implications for the potential of neuroimaging for future research on AD diagnosis and clinical management of suspected AD patients.
Investigation on performance degradation due to induced interface trapped charges on HSO based FDSOI NCFET and sustaining it through back-gate bias
Authors: Shaik Rameez Raja , Pradhan K P 
Published: September 2022

Abstract
In this article, a variant of doped HfO2 based ferroelectric capacitor i.e. silicon doped HfO2 (hafnia-silica/HSO) is investigated for analytical feasibility and viability for negative capacitance FET (NCFET) applications. Investigations are carried out extensively using well calibrated and validated numerical simulations to find out the optimum ferroelectric thickness (tf) of HSO thin-film for the NCFET to operate in hysteresis-free regime. The optimized NCFET is then subjected to the variation of back-gate bias (V

B

) to exploit threshold-voltage (

V

T
H

) shift phenomena might further improve NCFET performance. In continuance, the optimized NCFET has been introduced with interface trap (+Nit) charges at the oxide–semiconductor interface to emphasize on the reliability deflation caused at process level design. Hence, this has allowed us to concisely observe and analyse performance degradation aspect of the NCFET with numerical simulations. Also, a feasibility to recuperate the degraded performance caused by +Nit with utilizing −V

B

is carried out. The performance metrics used in the numerical simulation for the evaluation of HSO ferroelectric NCFET are: sub-threshold slope, charge variation with gate-voltage and ferro voltage, surface potential,

V

T
H

, drain-current and amplification factor.
A DFT study of gas molecules adsorption on intrinsic and Cu-doped graphene gas nanosensors
Authors: Tohidi T , Sattarian H , Tohidi S 
Published: September 2022

Abstract
In this study, first-principles calculations are performed to investigate the sensitivity of intrinsic graphene sheet (GS) and Cu-doped graphene sheet (Cu-GS) gas nanosensors for adsorbing CO, H2, and H2S gas molecules using QUANTUM ESPRESSO package. The density of states (DOS), net charge transfer, adsorption energy, partial density of states (PDOS), and the most stable adsorption configuration of these molecules on GS and Cu-GS are studied. The results show the weak physical adsorption of the three gas molecules on GS. The strength of interaction between the Cu-GS system and adsorbed gas molecules is higher due to the Cu doping. It is expected that the significant increase in charge transfer and adsorption energy leads to fundamental improvement in the electrical conductivity of the Cu-GS system. The results indicate that the introduction of Cu impurity can improve the gas sensing properties of graphene-based gas nanosensors. Therefore, Cu-GS is more appropriate for detecting gas molecules compared to pure GS. The results in this study are useful for developing the design of gas nanosensors.
Probing modified gravity with integrated Sachs-Wolfe CMB and galaxy cross-correlations
Authors: Kable Joshua A. , Benevento Giampaolo , Frusciante Noemi , De Felice Antonio , Tsujikawa Shinji 
Published: September 2022

Abstract
We use the cross-correlation power spectrum of the integrated Sachs-Wolfe (ISW) effect in
the cosmic microwave background (CMB) temperature anisotropy and galaxy fluctuations to probe the
physics of late-time cosmic acceleration. For this purpose, we focus on three models of dark
energy that belong to a sub-class of Horndeski theories with the speed of gravity equivalent to
that of light: Galileon Ghost Condensate (GGC), Generalized Cubic Covariant Galileon (GCCG), and
K-mouflage. In the GGC and GCCG models, the existence of cubic-order scalar self-interactions
allows a possibility for realizing negative ISW-galaxy cross-correlations, while the K-mouflage
model predicts a positive correlation similar to the Λ-cold-dark-matter (ΛCDM)
model. In our analysis, we fix the parameters of each model to their best-fit values derived from
a baseline likelihood analysis with observational data from CMB, baryon acoustic oscillations, and
supernovae type Ia. Then we fit those best-fit models to the ISW-galaxy cross-correlation power
spectrum extracted from a collection of photometric redshift surveys. We find that both GGC and
GCCG best-fit models degrade the fit to the ISW-galaxy cross-correlation data compared to
ΛCDM best-fit model. This is attributed to the fact that, for their best-fit values
constrained from the baseline likelihood, the cubic-order scalar self-interaction gives rise to
suppressed ISW tails relative to ΛCDM. The K-mouflage best-fit model is largely degenerate
with the ΛCDM best-fit model and has a positively correlated ISW-galaxy power close to
that of ΛCDM.
A general study of decaying scalar dark matter: existing limits and projected radio signals at the SKA
Authors: Dutta Koushik , Ghosh Avirup , Kar Arpan , Mukhopadhyaya Biswarup 
Published: September 2022

Abstract
We consider a decaying scalar dark matter (DM) with mass m
χ
in the range 10 GeV – 10 TeV and vary the branching ratios of all
possible two-body SM final states (excluding and including νν̅)
in the range 0%-100% to derive constraints on the total
decay width Γ using the data collected by several
astrophysical and cosmological observations. We find that,
Γ ≲ 10-26 - 10-27 s-1 (excluding νν̅)
and Γ ≲ 10-24 - 10-26 s-1 (including νν̅)
are allowed, depending on the values of m
χ, which are most
robust upper limits on Γ for a generic decaying scalar DM.
We then investigate the prospect of the upcoming Square Kilometre
Array (SKA) radio telescope in detecting the DM decay induced radio
signals originating inside the dwarf spheroidal (dSph) galaxies.
We have classified the DM parameter space, allowed by the existing
observations, independently of the branching ratio of each individual
two-body SM final state, based on the detectability at the SKA.
Excluding the νν̅ decay mode, we find that, throughout
the DM mass range considered,
Γ ≳ 10-30 s-1 - 10-29 s-1
is detectable for all possible branching ratio combinations
at the SKA (assuming 100 hours of observation time), with conservative
choices for the relevant astrophysical parameters.
On the other hand, when arbitrary branching ratios are allowed
also for the νν̅ decay mode, DM decays can be probed
independently of the branching ratio of each SM final state
for Γ ≳ 2 × 10-29 s-1,
provided DM masses are greater than a few hundreds of GeV.
A review on generative based methods for MRI reconstruction
Authors: Zhao Xiang , Yang Tiejun , Li Bingjie 
Published: September 2022

Abstract
Magnetic resonance imaging (MRI) is one of the most important methods for clinical diagnosis. However, the main drawback of MRI is the long imaging time, which will cause the moving artifact by patient movements. With the rapid development of the computing power of computer, deep learning is widely used in computer vision, natural language processing, visual recognition and so on. Meanwhile, a large number of reconstruction methods based on deep learning have also emerged. Recently, many generative models have been proposed to solve the perception quality problem that existed in fast MRI images. In this paper, we manage to survey the motivations and reconstruction strategies of generative-based methods published in journals and conferences over the past five years. First, the background and theoretical basis of MRI reconstruction are introduced. Secondly, the application of generative-based methods in MRI reconstruction field is comprehensively summarized and analyzed, including Generative Adversarial Network (GAN), Variational Autoencoder (VAE) and VAE-GAN. Then the advantages and disadvantages of the existing generative-based MRI reconstruction methods are discussed. Finally, several publicly available MR image datasets and evaluation metrics are presented, which can provide a reference for researchers and practitioners working in related domains. The conclusions and challenges are also given.