bluuebunny/crossref_metadata_2025_split huggingface dataset:
A gridded inventory of Canada’s anthropogenic methane emissions
Authors: Scarpelli Tia R , Jacob Daniel J , Moran Michael , Reuland Frances , Gordon Deborah 
Published: December 2021

Abstract
Canada’s anthropogenic methane emissions are reported annually to the United Nations Framework Convention on Climate Change through Canada’s National Inventory Report (NIR). Evaluation of this policy-relevant inventory using observations of atmospheric methane requires prior information on the spatial distribution of emissions but that information is lacking in the NIR. Here we spatially allocate the NIR methane emissions for 2018 on a 0.1° × 0.1° grid (≈10 km × 10 km) for individual source sectors and subsectors, with further resolution by source type for the oil/gas sector, using an ensemble of national and provincial geospatial datasets and including facility-level information from Canada’s Greenhouse Gas Reporting Program. The highest emissions are from oil/gas production and livestock in western Canada, and landfills in eastern Canada. We find 11 hotspots emitting more than 1 metric ton h−1 on the 0.1° × 0.1° grid. Oil sands mines in northeast Alberta contribute 3 of these hotspots even though oil sands contribute only 4% of national oil/gas emissions. Our gridded inventory shows large spatial differences with the EDGAR v5 inventory commonly used for inversions of atmospheric methane observations, which may reflect EDGAR’s reliance on global geospatial datasets. Comparison of our spatially resolved inventory to atmospheric measurements in oil/gas production fields suggests that the NIR underestimates these emissions. We also find strong spatial overlap between oil/gas, livestock, and wetland emissions in western Canada that may complicate source attribution in inversions of atmospheric data.
Geometric block-coherence and quantum state discrimination
Authors: Tang Danting , Li Ping , Ye Mingfei , Li Yongming 
Published: December 2021

Abstract
Quantum coherence with respect to orthonormal bases has been studied extensively in the past few years. From the perspective of operational meaning, geometric coherence can be equal to the minimum error probability to discriminate a set of pure states (2018 J. Phys. A: Math. Theor.
51 414005). By regarding coherence as a physical resource, Baumgratz et al (2014 Phys. Rev. Lett. 113 140401) presented a comprehensive framework for coherence. Recently, geometric block-coherence as an effective block-coherence measure has been proposed. In this paper, we reveal an equivalence relationship between mixed quantum state discrimination (QSD) task and geometric block-coherence, which provides an operational interpretation for geometric block-coherence and generalizes the main result in coherence resource theory. Meanwhile, we show that partial coherence is a special case of block-coherence. By linking the relationship between geometric partial coherence and QSD tasks, we show that the value range of the two measures is the same. Finally, we reveal the relationship between geometric positive operator-valued measure-based coherence and QSD task.
Nonlocality of a type of multi-star-shaped quantum networks
Authors: Yang Ying , Xiao Shu , Cao Huaixin 
Published: December 2021

Abstract
The correlations in quantum networks have attracted strong interest due to the fact that linear Bell inequalities derived from one source are useless for characterizing multipartite correlations of general quantum networks. In this paper, a type of multi-star-shaped quantum networks are introduced and discussed. Such a network consists of three-grade nodes: the first grade is named party (node) A, the second one consists of m nodes marked B
1, B
2, …, B

m
, which are stars of A and the third one consists of m
2 nodes

C

k

j

(

j
,
k
=
1
,
2
,
…
,
m

)

, where

C

k

j

(

k
=
1
,
2
,
…
,
m

)

are stars of B

j
. We call such a network a three-grade m-star quantum network and denoted by SQN(3, m), being as a natural extension of bilocal networks and star-shaped networks. We introduce and discussed the locality and strong locality of a SQN(3, m) and derive the related nonlinear Bell inequalities, called (3, m)-locality inequalities and (3, m)-strong locality inequalities. To compare with the bipartite locality of quantum states, we define the separability of SQN(3, m) that imply the locality and then locality of SQN(3, m). When all of the shared states of the network are pure ones, we prove that SQN(3, m) is nonlocal if and only if it is entangled.
Machine learning assisted GaAsN circular polarimeter
Authors: Aguirre-Perez A , Joshya R S , Carrère H , Marie X , Amand T , Balocchi A , Kunold A 
Published: December 2021

Abstract
We demonstrate the application of a two stage machine learning algorithm that enables one to correlate the electrical signals from a GaAs
x
N

1
−
x

circular polarimeter with the intensity, degree of circular polarization (DCP) and handedness of an incident light beam. Specifically, we employ a multimodal logistic regression to discriminate the handedness of light and a six-layer neural network (NN) to establish the relationship between the input voltages, the intensity and DCP. We have developed a particular NN training strategy that substantially improves the accuracy of the device. The algorithm was trained and tested on theoretically generated photoconductivity and on photoluminescence experimental results. Even for a small training experimental dataset (70 instances), it is shown that the proposed algorithm correctly predicts linear, right and left circularly polarized light, misclassifying less than

1.5
%

of the cases and attaining an accuracy larger than

97
%

in the vast majority of the predictions (

92
%

) for intensity and DCP. These numbers are significantly improved with larger theoretically generated datasets (4851 instances). The algorithm is versatile enough that it can be easily adjusted to other device configurations where a map needs to be established between the input parameters and the device response. Training and testing data files as well as the algorithm are provided as supplementary material.
Direct ink writing of 2D material-based supercapacitors
Authors: Tian Xiaocong 
Published: December 2021

Abstract
Atomically thin two-dimensional (2D) materials are excellent supercapacitor electrode candidates with intriguing physical and chemical properties. As a typical three-dimensional printing technique, direct ink writing (DIW) provides a new platform to bridge the gap between 2D materials and advanced supercapacitor electrodes. In the current review, recent progresses in DIW of 2D materials for supercapacitor applications are systematically presented, in which basic DIW processes, key scientific/technical points and corresponding strategies are highlighted. Ink fabrication and optimization based on 2D materials are discussed for supercapacitors, and recent advances in DIW of a variety of 2D material (including graphene, transition metal carbides and/or nitride (MXene), transition metal dichalcogenide and others)-based supercapacitor electrodes are offered. Furthermore, conclusions along with a brief discussion on challenges and opportunities of DIW-manufactured 2D materials are also provided for future supercapacitor applications.
Higher-order topological superconductivity from repulsive interactions in kagome and honeycomb systems
Authors: Li Tommy , Geier Max , Ingham Julian , D Scammell Harley 
Published: December 2021

AbstractWe discuss a pairing mechanism in interacting two-dimensional multipartite lattices that intrinsically leads to a second order topological superconducting state with a spatially modulated gap. When the chemical potential is close to Dirac points, oppositely moving electrons on the Fermi surface undergo an interference phenomenon in which the Berry phase converts a repulsive electron–electron interaction into an effective attraction. The topology of the superconducting phase manifests as gapped edge modes in the quasiparticle spectrum and Majorana Kramers pairs at the corners. We present symmetry arguments which constrain the possible form of the electron–electron interactions in these systems and classify the possible superconducting phases which result. Exact diagonalization of the Bogoliubov-de Gennes Hamiltonian confirms the existence of gapped edge states and Majorana corner states, which strongly depend on the spatial structure of the gap. Possible applications to vanadium-based superconducting kagome metals AV3Sb5(A = K, Rb, Cs) are discussed.
Role of enhanced surface grain refinement and hardness improvement induced by the combined effect of friction stir processing and ultrasonic impact treatment on slurry abrasive wear performance of silicon carbide particle reinforced A356 composites
Authors: Gençer Gökçe Mehmet , Kahraman Fatih , Yolcu Coşkun 
Published: December 2021

Abstract
In this study, the slurry abrasive wear behavior of silicon carbide particle reinforced A356 composite alloy was investigated after the different surface mechanical attrition treatments. It is known that the aluminum matrix composites produced by the stir casting method have some deficiencies (e.g unfavorable microstructure formation, particle clustering, porosity formation, etc). These kinds of drawbacks of the composites adversely affect the surface mechanical properties of materials such as wear resistance. For this purpose, the surface properties of the silicon carbide reinforced A356 matrix composites fabricated through the stir casting method were improved by using friction stir processing (FSP) and ultrasonic impact treatment (UIT) in the study. The results indicated that a remarkable increase was observed in the hardness and wear resistance of the cast composite via FSP and ultrasonic impact treatment following friction stir processing (FSP + UIT). The hardness of the stir zone after FSP and FSP + UIT was determined as 82.7+−2 HV and 101.9 +−3 HV0.2, respectively. The stir zone showed a similar tendency also in slurry abrasive wear resistance. FSP increased the wear resistance in the stir zone at the rate of 33.9% while it was determined as 35.5% for FSP + UIT. The microstructural modification of the cast composite that occurred after FSP was clearly demonstrated via optical microscope and scanning electron microscopy (SEM) examinations. Enhanced grain refinement after FSP + UIT was indicated especially by x-ray diffraction analysis (XRD). According to the findings, it was observed that the application of ultrasonic impact treatment following the friction stir processing can be used to obtain an enhanced microstructure and extra hardness increment in the surface of the SiC reinforced A356 alloy, thus resulting in slurry abrasive wear resistance increment.
Effect of homogenization on microstructure evolution and mechanical properties of aged Mg-Nd-Sm-Zn-Zr alloy
Authors: Ma Tao , Zhao Sicong , Wang Liping , Wang Zhiwei , Guo Erjun , Feng Yicheng , Liu Dongrong , Wu Changtong , Li Jingfang 
Published: December 2021

Abstract
As an indispensable pre-treatment for aging, homogenization treatment has a significant effect on precipitation behavior of the Mg-RE alloys. Herein, the influence of homogenization temperature on the microstructure evolution and mechanical performance of a novel Mg-2.0Nd-2.0Sm-0.4Zn-0.4Zr (wt.%) alloy has been studied systematically. The results indicated that the as-cast alloy was mainly composed of α-Mg matrix, β-Mg12(Nd,Sm,Zn) phase and Zr-containing particles. Upon increasing the homogenization temperature from 500 °C to 525 °C for 8 h, the average grain size of as-homogenized alloy increased from 76 μm to 156 μm, and the content of β phase decreased gradually. It was worth noting that the homogenization temperature exceeded 515 °C, the β phase at the grain boundaries was completely dissolved. After aging at 200 °C for 18 h, numerous of plate-like β′ phases were observed in α-Mg matrix. The rise in homogenization temperature was conducive to nucleation and growth of the β′ phase. However, excessive homogenization temperature significantly coarsened grain size. The aged alloy under homogenization treatment at 515 °C for 8 h achieved optimal mechanical properties. The values of ultimate tensile strength, yield strength and elongation were 261 MPa, 154 MPa and 5.8%, respectively. The fracture mode of the aged alloy mainly exhibited a typical transgranular cleavage fracture.
Structural stabilities, electronic structures, photocatalysis and optical properties of γ-GeN and α-SnP monolayers: a first-principles study
Authors: Liu Liming , Yan Cuixia , Gao Lei , Shangguan Wei , Dai Jianqing , Cai Jinming 
Published: December 2021

Abstract
Exploring two-dimensional materials with excellent photoelectricity properties is of great theoretical significance and practical value for developing new photocatalysts, electronics and photonic devices. Here, using first-principle calculations, we designed and analyzed systematically a series of α, β and γ phase structures of two-dimensional group IV-V monolayers (IV-V, IV = C, Si, Ge, Sn, Pb; V = N, P, As, Sb, Bi), most of them are semiconductors. Among them, γ-GeN and α-SnP monolayers with thermodynamic and kinetic stability (at 300 K) have been further studied due to their wide range of energy band gaps (γ-GeN: 2.54 eV, α-SnP:1.34 eV). The two band gaps are greater than the free energy for water splitting (1.23 eV), which are crucial for photocatalytic decomposition of water. The γ-GeN and α-SnP monolayers present excellent photocatalystics properties in pH = 0/7 and pH = 10 environments, respectively. Moreover, both of the monolayers show strong light absorption coefficients greater than 105 cm−1 in the visible and ultraviolet regions. In addition, it is found that the band edge positions and band gap sizes of γ-GeN and α-SnP monolayers can be regulated by biaxial strain. Benefitting from the wide selection of energy band gaps and high absorption coefficients, the γ-GeN and α-SnP monolayers are the next generation of promising candidate materials for photocatalysts, nanoelectronics and optoelectronics.
Mesoscopic simulation of overlapping behavior in laser powder bed additive manufacturing
Authors: Lu Pan , Tong Liu , Wen-Hao Wang , Yu Gao , Cheng-Lin Zhang , Jiang-Lin Liu 
Published: December 2021

Abstract
The prediction of the flow behavior of Metal micro-molten pool is prerequisite for high-quality Laser Powder Bed Fusion (L-PBF). In this study, mesoscopic scale numerical simulation modelling for L-PBF process was used to help understand the melting process of pure copper micro-melt pool. In this study, the orthogonal test was designed to study the influence of laser power, laser scanning velocity, hatching space on the flow behavior of molten pool and the overlapping rate of adjacent molten tracks. The results shows that laser scanning speed has the greatest influence on both the size and overlapping rate of the molten pool, and the overall trend was that the size of molten pool continues to increase as the volume energy density increases, and the maximum molten pool size was 243.6 um × 110 um with volume energy density 370.037 J mm−3, overlapping rate of adjacent molten tracks was 48.84% with volume energy density 285.71 J/mm3. The optimized pure copper laser process parameters were obtained: laser power 300 KW, laser scanning speed 500 mm/s, hatching space 0.07 mm, overlapping rate 48.84%.
Garment-integrated thermoelectric generator arrays for wearable body heat harvesting
Authors: Allison Linden K , Andrew Trisha L 
Published: December 2021

Abstract
Wearable thermoelectric generator arrays have the potential to use waste body heat to power on-body sensors and create, for example, self-powered health monitoring systems. In this work, we demonstrate that a surface coating of a conducting polymer poly(3,4-ethylenedioxythiophene) (PEDOT-Cl), created on one face of a wool felt using a chemical vapor deposition method was able to manifest a Seebeck voltage when subjected to a temperature gradient. The wool felt devices can produce voltage outputs of up to 120 mV when measured on a human body. Herein, we present a strategy to create arrays of polymer-coated fabric thermopiles and to integrate such arrays into familiar garments that could become a part of a consumer’s daily wardrobe. Using wool felt as the substrate fabric onto which the conducting polymer coating is created allowed for a higher mass loading of the polymer on the fabric surface and shorter thermoelectric legs, as compared to our previous iteration. Six or eight of these PEDOT-Cl coated wool felt swatches were sewed onto a backing/support fabric and interconnected with silver threads to create a coupled array, which was then patched onto the collar of a commercial three-quarter zip jacket. The observed power output from a six-leg array while worn by a healthy person at room temperature (ΔT = 15 °C) was 2 µW, which is the highest value currently reported for a polymer thermoelectric device measured at room temperature.
Prediction of the number of heatstroke patients transported by ambulance in Japan’s 47 prefectures: proposal of heat acclimatization consideration
Authors: Oka Kazutaka , Hijioka Yasuaki 
Published: December 2021

Abstract
The incidence of heatstroke is affected by various meteorological variables. However, previous studies in Japan have mainly investigated and adopted a single temperature metric or composite index for their analyses. Herein, we conducted a time series study through multivariate analysis of different weather conditions simultaneously, in order to analyze the relative importance of meteorological variables to determine the number of heatstroke patients transported by ambulance in all of Japan’s 47 prefectures. We proposed a method that considers heat acclimatization, which has been found to impact the heatstroke, by manipulating certain meteorological variables. For the heatstroke data, we utilized the secondary data provided by the Fire and Disaster Management Agency, Japan. The time period considered was from May 2015 to September 2019. All calculations were performed using R 3.5.1. For the analysis, the machine learning method of random forest (RF) was applied. The results showed that the relative temperature (RelTemp), which represents heat acclimatization, had the highest ranking among all the meteorological variables studied. Then, we developed the exponential model and the RF model to predict the number of heatstroke patients transported by ambulance by adopting the highly ranked meteorological variables including RelTemp as explanatory variables. To confirm the effectiveness of heat acclimatization, we also developed the exponential model and the RF model both without RelTemp (instead, with maximum temperature). According to the results, the R2 values of the exponential and the RF models, including RelTemp, were 0.76 and 0.74, respectively, and those of the exponential and the RF models, excluding RelTemp, were 0.68 and 0.67, respectively. We confirmed the effectiveness of considering heat acclimatization via RelTemp and found that the exponential model with RelTemp provided the higher accuracy. Better predictions by the exponential model with RelTemp would contribute to better preemptive allocation of ambulances and medical staff in medical facilities.
Contrasting scaling relationships of extreme precipitation and streamflow to temperature across the United States
Authors: Shen Mingxi , Chui Ting Fong May 
Published: December 2021

Abstract
Recent studies have reached inconsistent conclusions from scaling analysis about whether flood or extreme precipitation is more sensitive to warming climate. To explain the reasons behind the inconsistency, here we first used scaling analysis to illustrate how extreme daily precipitation and streamflow scale with daily air temperature across the Continental United States (CONUS). We found both similar and opposite scaling in extreme precipitation and streamflow. It indicates based on scaling analysis, the sensitivity of extreme streamflow to warming climate can be either similar, higher or lower to that of extreme precipitation. We further explored why there are contrasting scaling relationships in the CONUS. Generally, the similar scaling was found in regions where the timing of extreme precipitation and streamflow is correspondent, as well as with similar temporal evolution in extreme event timing and magnitude, e.g., the west coast and southern plains, implying extreme precipitation is the dominant driver of local floods. However, for regions with dissimilar scaling in extreme precipitation and streamflow (e.g., Rocky Mountains, southern plains), the characteristics of extreme streamflow show large difference to those of extreme precipitation, and the temporal evolution of extreme streamflow timing and magnitude are more correlated with factors/processes such as soil moisture and snowmelt. This study reflects that the contrasting scaling relationships of extreme precipitation and streamflow are oriented from the local hydro-climatological specifics. Using scaling analysis to compare the sensitivity of extreme precipitation and streamflow to warming climate is not suitable. Instead, we should focus more on local flood generating mechanisms or flood drivers when investigating floods in the changing climate.
Guided acceleration of nanoparticles by laser irradiated parallel gold nanorods
Authors: Yadav Mamta , Kumar Ashok , Mandal Subhayan 
Published: December 2021

Abstract
Laser irradiated parallel gold nanorods with interspersed deuterium nanoparticles are shown to offer guided acceleration of nanoparticles. The laser pulse of intensity exceeding 1018 W cm−2 at 1 μm wavelength and pulse duration ∼30 fs causes full ionization of nanoparticles and high state ionization of gold atoms and pushes out the free electrons via the ponderomotive force. The charged nanorods have an electric field that has transverse component towards the axis of symmetry and axial field outwards. Thus the nanoparticles are accelerated axially while confined transversely. Deuterium beam of a few MeV energy can be produced by this technique.
Study of the effect of nano ZrO2 and TiO2 and rotation speed on friction behavior of rotary friction welding of HIPS and PP
Authors: Afzali Mohammad , Asghari Vahid 
Published: December 2021

Abstract
The purpose of this project was to introduce a way to improve the mechanical properties of dissimilar welded material, which provides benefits such as affordability, high speed, and a suitable bond property. This experimental project applies the friction welding method, including combining parameters, such as a numerical control machine, two different speeds, and three different cross sections, including flat, cone, and step surfaces. When the welding process was done, samples were implemented and prepared via a bending test of materials. The results have shown that, besides increasing the machining velocity, the surface friction increased, and so did the temperature. Considering the stated experimental facts, the melting temperature of composite materials increased. This provides the possibility of having a better blend of nanomaterial compared to the base melted plastics. Thus, the result showed that, besides increasing the weight percentage of nanomaterial contents and machining velocity, the mechanical properties increased on the welded area for all three types of samples. This enhancement is due to the better melting process on the welded area with the attendance of various nanoparticle contents. Also, the results showed that the shape of the welding area could play a significant role, and the results also change drastically where the shape changes. Optimum shape in the welding process has been dedicated to the step surface. The temperature causes the melting process, which is a significant factor in the friction welding process.