Temperature-dependent bias-stress-induced electrical instability of amorphous indium-gallium-zinc-oxide thin-film transistors

The time and temperature dependence of threshold voltage shift under positive-bias stress（PBS） and the following recovery process are investigated in amorphous indium-gallium-zinc-oxide（a-IGZO） thin-film transistors. It is found that the time dependence of threshold voltage shift can be well described by a stretched exponential equation in which the time constant τ is found to be temperature dependent. Based on Arrhenius plots, an average effective energy barrier Eτ stress= 0.72 eV for the PBS process and an average effective energy barrier Eτ recovery= 0.58 eV for the recovery process are extracted respectively. A charge trapping/detrapping model is used to explain the threshold voltage shift in both the PBS and the recovery process. The influence of gate bias stress on transistor performance is one of the most critical issues for practical device development.

Assessment of the Southern Ocean Sea Surface Temperature Biases in CMIP5 and CMIP6 Models

This work evaluates the performances of climate models in simulating the Southern Ocean(SO)sea surface temperature(SST)by a large ensemble from phases 5 and 6 of the Coupled Model Intercomparison Project(CMIP5 and CMIP6).By combining models from the same community sharing highly similar SO SST biases and eliminating the effect of global-mean biases on local SST biases,the results reveal that the ensemble-mean SO SST bias at 70°-30°S decreases from 0.38℃ in CMIP5 to 0.28℃ in CMIP6,together with increased intermodel consistency.The dominant mode of the intermodel variations in the zonal-mean SST biases is characterized as a meridional uniform warm bias pattern,explaining 79.1% of the intermodel variance and exhibiting positive principal values for most models.The ocean mixed layer heat budget further demonstrates that the SST biases at 70°-50°S primarily result from the excessive summertime heating effect from surface net heat flux.The biases in surface net heat flux south of 50°S are largely impacted by surface shortwave radiation from cloud and clear sky components at different latitudes.North of 50°S,the underestimated westerlies reduce the northward Ekman transport and hence northward cold advection in models,leading to warm SST biases year-round.In addition,the westerly biases are primarily traced back to the atmosphere-alone model simulations forced by the observed SST and sea ice.These results disclose the thermal origin at the high latitude and dynamical origin at the low latitude of the SO SST biases and underscore the significance of the deficiencies of atmospheric models in producing the SO SST biases.

Revealing the Multifunctional Electrocatalysis of Indium-Modulated Phthalocyanine for High-Performance Lithium-Sulfur Batteries

The sluggish kinetics of complicated multiphase conversions and the severe shuttling effect of lithium polysulfides(LiPSs)significantly hinder the applications of Li-S battery,which is one of the most promising candidates for the next-generation energy storage system.Herein,a bifunctional electrocatalyst,indium phthalocyanine self-assembled with carbon nanotubes(InPc@CNT)composite material,is proposed to promote the conversion kinetics of both reduction and oxidation processes,demonstrating a bidirectional catalytic effect on both nucleation and dissolution of Li_(2)S species.The theoretical calculation shows that the unique electronic configuration of InPc@CNT is conducive to trapping soluble polysulfides in the reduction process,as well as the modulation of electron transfer dynamics also endows the dissolution of Li_(2)S in the oxidation reaction,which will accelerate the effectiveness of catalytic conversion and facilitate sulfur utilization.Moreover,the InPc@CNT modified separator displays lower overpotential for polysulfide transformation,alleviating polarization of electrode during cycling.The integrated spectroscopy analysis,HRTEM,and electrochemical study reveal that the InPc@CNT acts as an efficient multifunctional catalytic center to satisfy the requirements of accelerating charging and discharging processes.Therefore,the Li-S battery with InPc@CNT-modified separator obtains a discharge-specific capacity of 1415 mAh g^(-1)at a high rate of 0.5 C.Additionally,the 2 Ah Li-S pouch cells deliver 315 Wh kg^(-1)and achieved 80%capacity retention after 50 cycles at 0.1 C with a high sulfur loading of 10 mg cm^(-2).Our study provides a practical method to introduce bifunctional electrocatalysts for boosting the electrochemical properties of Li-S batteries.

Multiple factors influencing high-purity indium electrolytic refining

The effects of various contaminants in the electrolytic refinement of indium were investigated using a glow discharge mass spectrometer(GDMS).The effects of several factors such as the indium ion(In3+)concentration,the sodium chloride(NaCl)concentration,the current density,the gelatin concentration,the pH,and the electrode distance,were examined.Significant variations in impurity levels concerning gelatin concentration were observed.Both the gelatin and In3+concentration were moderately positively correlated with the Pb content.The Sb concentration was associated positively with the NaCl concentration,while the Ti concentration had an adverse correlation with the NaCl concentration.The Bi element content was positively linked to the electrode distance.As the current density increased,Cu,Pb,and Bi impurities initially rose and then eventually declined.Notably,a critical current density of 45 A·m^(-2) was identified in this behavior.

Vibration and noise mechanism of a 110 kV transformer under DC bias based on finite element method

Global energy and environmental issues are becoming increasingly problematic,and the vibration and noise problem of 110 kV transformers,which are the most widely distributed,have attracted widespread attention from both inside and outside the industry.DC bias is one of the main contributing factors to vibration noise during the normal operation of transformers.To clarify the vibration and noise mechanism of a 110 kV transformer under a DC bias,a multi-field coupling model of a 110 kV transformer was established using the finite element method.The electromagnetic,vibration,and noise characteristics during the DC bias process were compared and quantified through field circuit coupling in parallel with the power frequency of AC,harmonic,and DC power sources.It was found that a DC bias can cause significant distortions in the magnetic flux density,force,and displacement distributions of the core and winding.The contributions of the DC bias effect to the core and winding are different at Kdc=0.85.At this point,the core approached saturation,and the increase in the core force and displacement slowed.However,the saturation of the core increased the leakage flux,and the stress and displacement of the winding increased faster.The sound field distribution characteristics of the 110 kV transformer under a DC bias are related to the force characteristics.When the DC bias coefficient was 1.25,the noise sound pressure level reached 73.6 dB.

Why ecosystem characteristics predicted from remotely sensed data are unbiased and biased at the same time-and how this affects applications

Remotely sensed data are frequently used for predicting and mapping ecosystem characteristics,and spatially explicit wall-to-wall information is sometimes proposed as the best possible source of information for decisionmaking.However,wall-to-wall information typically relies on model-based prediction,and several features of model-based prediction should be understood before extensively relying on this type of information.One such feature is that model-based predictors can be considered both unbiased and biased at the same time,which has important implications in several areas of application.In this discussion paper,we first describe the conventional model-unbiasedness paradigm that underpins most prediction techniques using remotely sensed(or other)auxiliary data.From this point of view,model-based predictors are typically unbiased.Secondly,we show that for specific domains,identified based on their true values,the same model-based predictors can be considered biased,and sometimes severely so.We suggest distinguishing between conventional model-bias,defined in the statistical literature as the difference between the expected value of a predictor and the expected value of the quantity being predicted,and design-bias of model-based estimators,defined as the difference between the expected value of a model-based estimator and the true value of the quantity being predicted.We show that model-based estimators(or predictors)are typically design-biased,and that there is a trend in the design-bias from overestimating small true values to underestimating large true values.Further,we give examples of applications where this is important to acknowledge and to potentially make adjustments to correct for the design-bias trend.We argue that relying entirely on conventional model-unbiasedness may lead to mistakes in several areas of application that use predictions from remotely sensed data.

Tailoring Ni based catalysts by indium for the dehydrogenative coupling of ethanol into ethyl acetate

Exploring stable and robust catalysts to replace the current toxic CuCr based catalysts for dehydrogenative coupling of ethanol to ethyl acetate is a challenging but promising task.Herein,novel NiIn based catalysts were developed by tailoring Ni catalysts with Indium(In)for this reaction.Over the optimal Ni0.1Zn0.7Al0.3InOx catalyst,the ethyl acetate selectivity reached 90.1%at 46.2%ethanol conversion under the conditions of 548 K and a weight hourly space velocity of 1.9 h^(-1)in the 370 h time on stream.Moreover,the ethyl acetate productivity surpassed 1.1 g_(ethyl acetate)g_(catalyst)^(-1)h^(-1),,one of the best performance in current works.According to catalyst characterizations and conditional experiments,the active sites for dehydrogenative coupling of ethanol to ethyl acetate were proved to be Ni4In alloys.The presence of In tailored the chemical properties of Ni,and subsequently inhibited the C-C cracking and/or condensation reactions during ethanol conversions.Over Ni4In alloy sites,ethanol was dehydrogenated into acetaldehyde,and then transformed into acetyl species with the removal of H atoms.Finally,the coupling between acetyl species and surface-abundant ethoxyde species into ethyl acetate was achieved,affording a high ethyl acetate selectivity and catalyst stability.

Stable photocurrent-voltage characteristics of perovskite single crystal detectors obtained by pulsed bias

Photocurrent-voltage characterization is a crucial method for assessing key parameters in x-ray or y-ray semiconductor detectors,especially the carrier mobility lifetime product.However,the high biases during photocurrent measurements tend to cause severe ion migration,which can lead to the instability and inaccuracy of the test results.Given the mixed electronic-ionic charac teristics,it is imperative to devise novel methods capable of precisely measuring photocurrentvoltage characteristics under high bias conditions,free from interference caused by ion migration.In this paper,pulsed bias is employed to explore the photocurrent-voltage characteristics of MAPbBr_(3) single crystals.The method yields stable photocurrent-voltage characteristics at a pulsed bias of up to 30 V,proving to be effective in mitigating ion migration.Through fitting the modified Hecht equation,we determined the mobility lifetime products of 1.0×10^(2) cm^(2)·V^(-1)for hole and 2.78×10~(-3)cm^(2)·V^(-1)for electron.This approach offers a promising solution for accurately measuring the transport properties of carriers in perovskite.

A News Media Bias and Factuality Profiling Framework Assisted by Modeling Correlation

News media profiling is helpful in preventing the spread of fake news at the source and maintaining a good media and news ecosystem.Most previous works only extract features and evaluate media from one dimension independently,ignoring the interconnections between different aspects.This paper proposes a novel news media bias and factuality profiling framework assisted by correlated features.This framework models the relationship and interaction between media bias and factuality,utilizing this relationship to assist in the prediction of profiling results.Our approach extracts features independently while aligning and fusing them through recursive convolu-tion and attention mechanisms,thus harnessing multi-scale interactive information across different dimensions and levels.This method improves the effectiveness of news media evaluation.Experimental results indicate that our proposed framework significantly outperforms existing methods,achieving the best performance in Accuracy and F1 score,improving by at least 1%compared to other methods.This paper further analyzes and discusses based on the experimental results.

Influence of exchange bias on spin torque ferromagnetic resonance for quantification of spin–orbit torque efficiency

Antiferromagnet(AFM)/ferromagnet(FM)heterostructure is a popular system for studying the spin–orbit torque(SOT)of AFMs.However,the interfacial exchange bias field induces that the magnetization in FM layer is noncollinear to the external magnetic field,namely the magnetic moment drag effect,which further influences the characteristic of SOT efficiency.In this work,we study the SOT efficiencies of IrMn/NiFe bilayers with strong interfacial exchange bias by using spin-torque ferromagnetic resonance(ST-FMR)method.A full analysis on the AFM/FM systems with exchange bias is performed,and the angular dependence of magnetization on external magnetic field is determined through the minimum rule of free energy.The ST-FMR results can be well fitted by this model.We obtained the relative accurate SOT efficiencyξ_(DL)=0.058 for the IrMn film.This work provides a useful method to analyze the angular dependence of ST-FMR results and facilitates the accurate measurement of SOT efficiency for the AFM/FM heterostructures with strong exchange bias.

Inward particle transport driven by biased endplate in a cylindrical magnetized plasma

The inward particle transport is associated with the formation of peaked density profiles,which contributes to improve the fusion rate and the realization of steady-state discharge.The active control of inward particle transport is considered as one of the most critical issues of magnetic confinement fusion.Recently,it is realized preliminarily by adding a biased endplate in the Peking University Plasma Test(PPT)device.The results reveal that the inward particle flux increases with the bias voltage of the endplate.It is also found that the profile of radial electric field(Er)shear is flattened by the increased bias voltage.Radial velocity fluctuations affect the inward particle more than density fluctuations,and the frequency of the dominant mode driving inward particle flux increases with the biased voltage applied to the endplate.The experimental results in the PPT device provide a method to actively control the inward particle flux using a biased endplate and enrich the understanding of the relationship between E_(r)×B shear and turbulence transport.

Assessing the Performance of a Dynamical Downscaling Simulation Driven by a Bias-Corrected CMIP6 Dataset for Asian Climate

In this study,we aim to assess dynamical downscaling simulations by utilizing a novel bias-corrected global climate model(GCM)data to drive a regional climate model(RCM)over the Asia-western North Pacific region.Three simulations were conducted with a 25-km grid spacing for the period 1980–2014.The first simulation(WRF_ERA5)was driven by the European Centre for Medium-Range Weather Forecasts Reanalysis 5(ERA5)dataset and served as the validation dataset.The original GCM dataset(MPI-ESM1-2-HR model)was used to drive the second simulation(WRF_GCM),while the third simulation(WRF_GCMbc)was driven by the bias-corrected GCM dataset.The bias-corrected GCM data has an ERA5-based mean and interannual variance and long-term trends derived from the ensemble mean of 18 CMIP6 models.Results demonstrate that the WRF_GCMbc significantly reduced the root-mean-square errors(RMSEs)of the climatological mean of downscaled variables,including temperature,precipitation,snow,wind,relative humidity,and planetary boundary layer height by 50%–90%compared to the WRF_GCM.Similarly,the RMSEs of interannual-tointerdecadal variances of downscaled variables were reduced by 30%–60%.Furthermore,the WRF_GCMbc better captured the annual cycle of the monsoon circulation and intraseasonal and day-to-day variabilities.The leading empirical orthogonal function(EOF)shows a monopole precipitation mode in the WRF_GCM.In contrast,the WRF_GCMbc successfully reproduced the observed tri-pole mode of summer precipitation over eastern China.This improvement could be attributed to a better-simulated location of the western North Pacific subtropical high in the WRF_GCMbc after GCM bias correction.

Bias in Generative AI Systems:A 3-Layer Response and Liability Determination

The risk of bias is widely noticed in the entire process of generative artificial intelligence(generative AI)systems.To protect the rights of the public and improve the effectiveness of AI regulations,feasible measures to address the bias problem in the context of large data should be proposed as soon as possible.Since bias originates in every part and various aspects of AI product lifecycles,laws and technical measures should consider each of these layers and take different causes of bias into account,from data training,modeling,and application design.The Interim Measures for the Administration of Generative AI Service(the Interim Measures),formulated by the Office of the Central Cyberspace Affairs Commission(CAC)and other departments have taken the initiatives to govern AI.However,it lacks specific details on issues such as how to prevent the risk of bias and reduce the effect of bias in decision-making.The Interim Measures also fail to take causes of bias into account,and several principles must be further interpreted.Meanwhile,regulations on generative AI at the global level are still in their early stages.By forming a governance framework,this paper could provide the community with useful experiences and play a leading role.The framework includes at least three parts:first,determining the realm of governance and unifying related concepts;second,developing measures for different layers to identify the causes and specific aspects of bias;third,identifying parties with the skills to take responsibility for detecting bias intrusions and proposing a program for the allocation of liabilities among the large-scale platform developers.

Stacking-dependent exchange bias in two-dimensional ferromagnetic/antiferromagnetic bilayers

A clear microscopic understanding of exchange bias is crucial for its application in magnetic recording, and further progress in this area is desired. Based on the results of our first-principles calculations and Monte Carlo simulations,we present a theoretical proposal for a stacking-dependent exchange bias in two-dimensional compensated van der Waals ferromagnetic/antiferromagnetic bilayer heterostructures. The exchange bias effect emerges in stacking registries that accommodate inhomogeneous interlayer magnetic interactions between the ferromagnetic layer and different spin sublattices of the antiferromagnetic layer. Moreover, the on/off switching and polarity reversal of the exchange bias can be achieved by interlayer sliding, and the strength can be modulated using an external electric field. Our findings push the limits of exchange bias systems to extreme bilayer thickness in two-dimensional van der Waals heterostructures, potentially stimulating new experimental investigations and applications.

Vector magnetometry in zero bias magnetic field using nitrogen-vacancy ensembles

The application of the vector magnetometry based on nitrogen-vacancy(NV)ensembles has been widely investigatedin multiple areas.It has the superiority of high sensitivity and high stability in ambient conditions with microscale spatialresolution.However,a bias magnetic field is necessary to fully separate the resonance lines of optically detected magneticresonance(ODMR)spectrum of NV ensembles.This brings disturbances in samples being detected and limits the rangeof application.Here,we demonstrate a method of vector magnetometry in zero bias magnetic field using NV ensembles.By utilizing the anisotropy property of fluorescence excited from NV centers,we analyzed the ODMR spectrum of NVensembles under various polarized angles of excitation laser in zero bias magnetic field with a quantitative numerical modeland reconstructed the magnetic field vector.The minimum magnetic field modulus that can be resolved accurately is downto~0.64 G theoretically depending on the ODMR spectral line width(1.8 MHz),and~2 G experimentally due to noisesin fluorescence signals and errors in calibration.By using 13C purified and low nitrogen concentration diamond combinedwith improving calibration of unknown parameters,the ODMR spectral line width can be further decreased below 0.5 MHz,corresponding to~0.18 G minimum resolvable magnetic field modulus.

Study of bias voltage effect on the performance of ta-C coating prepared by high power impulse magnetron sputtering

The mechanical and frictional properties of ta-C coatings deposited on the substrate surface affect applications in the field of cutting tools and wear-resistant components.In this paper,the effect of bias parameters on the performance of ta-C coatings was investigated based on high power impulse magnetron sputtering(HiPIMS)technology.The results show that bias voltage has a significant effect on the deposition rate,structure,and wear resistance of the coating.In the range of bias voltage−50 V to−200 V,the ta-C coating performance was the best under bias voltage−150 V.The thickness reached 530.4 nm,the hardness value reached 35.996 GPa,and the bonding force in-creased to 14.2 N.The maximum sp3 bond content was 59.53% at this condition.

Phase composition,conductivity,and sensor properties of cerium-doped indium oxide

The hydrothermal synthesis of In_(2)O_(3)and CeO_(2)–In_(2)O_(3)is investigated as well as the properties of sensor layers based on these compounds.During the synthesis of In_(2)O_(3),intermediate products In(OH)_(3)and InOOH are formed,which are the precursors of stable cubic(c-In_(2)O_(3))and metastable rhombohedral(rh-In_(2)O_(3))phases,respectively.A transition from c-In_(2)O_(3)to rh-In_(2)O_(3)is observed with the addition of CeO_(2).The introduction of cerium into rh-In_(2)O_(3)results in a decrease in the sensor response to hydrogen,while it increases in composites based on c-In_(2)O_(3).The data on the sensor activity of the composites correlate with XPS results in which CeO_(2)causes a decrease in the concentrations of chemisorbed oxygen and oxygen vacancies in rh-In_(2)O_(3).The reverse situation is observed in composites based on c-In_(2)O_(3).Compared to In_(2)O_(3)and CeO_(2)–In_(2)O_(3)obtained by other methods,the synthesized composites demonstrate maximum response to H_(2)at low temperatures by 70–100℃,and have short response time(0.2–0.5 s),short recovery time(6–7 s),and long-term stability.A model is proposed for the dependence of sensitivity on the direction of electron transfer between In_(2)O_(3)and CeO_(2).

Is Peer Victimization Associated with Higher Online Trolling among Adolescents?The Mediation of Hostile Attribution Bias and the Moderation of Trait Mindfulness

Background:In recent years,online trolling has garnered significant attention due to its detrimental effects on mental health and social well-being.The current study examined the influence of peer victimization on adolescent online trolling behavior,proposing that hostile attribution bias mediated this relationship and that trait mindfulness moderated both the direct and indirect effects.Methods:A total of 833 Chinese adolescents completed the measurements of peer victimization,hostile attribution bias,trait mindfulness,and online trolling.Moderated mediation analysis was performed to examine the relationships between these variables.Results:After controlling for gender and residential address,the study found a significant positive correlation between peer victimization and online trolling,with hostile attribution bias serving as a mediator.In addition,trait mindfulness moderated the direct relationship between peer victimization and online trolling.Specifically,the effect of peer victimization on online trolling was attenuated when adolescents had high levels of trait mindfulness.The results of the study emphasized the joint role of peer and personal factors in adolescents’online trolling behavior and provide certain strategies for intervening in adolescents’online trolling behavior.Conclusion:The results of the study suggest that strategies focusing on peer support and mindfulness training can have a positive impact on reducing online trolling behavior,promoting adolescents’mental health,and their long-term development.

Soil Profile Concentration Distributions of Aluminum, Gallium, Indium and Thallium across Southeastern Missouri

The soil chemistry of gallium, indium, and thallium is not well defined, particularly with emerging evidence that these elements have toxic properties and may influence food safety. The purpose of this investigation was to estimate the soil concentrations of gallium, indium, and thallium and determine if these elements have a soil chemistry like aluminum and therefore demonstrate significant concentration correlations with aluminum. Twenty-seven soil series were selected, and the elemental concentrations were determined using aqua regia digestion with analytical determination performed using inductively coupled plasma emission-mass spectroscopy. The concentrations of gallium, indium, and thallium generally compared with the known literature. Aluminum-gallium and aluminum-thallium exhibited significant concentration correlations across the soil horizons of the sampled soils. Aluminum, gallium, and thallium did demonstrate concentration increases in soil horizons having illuviation of phyllosilicates, implying these phyllosilicates have adsorption and isomorphic substitution behaviors involving these elements.

Sex bias in FGFR3 somatic mutations in bladder cancer

Background:Strong sex disparities have been observed among patients with bladder cancer(BCa).FGFR3 is one of the most frequently mutated genes in bladder cancer,and there are inconsistencies in its frequency in male and female patients.Methods:Here,we conducted a meta-analysis comparing the FGFR3 somatic mutation frequency in men and women among 7351 patients with BCa from 18 cohorts.Results:We showed that female patients had a 1.32 times higher risk of having FGFR3 somatic mutations than males.This difference was attributed to mutations occurring at the 2 most frequently mutated sites,S249 and Y375.Additionally,nonsense mutations were more likely to be found in women,whereas indel/frameshift mutations were almost exclusively found in men;however,no difference was noted for missense mutations.Conclusions:A female sex bias in FGFR3 somatic mutationswas observed in BCa.Well-powered individual participant data analyses addressing the possible confounding effects of other factors(eg,age,ethnicity,smoking status,muscle invasiveness,and molecular subtype),as well as analyses integrating omics and functional investigations,are warranted to further validate and explain the mechanisms of the current findings.