Optical Modeling of Sea Salt Aerosols Using in situ Measured Size Distributions and the Impact of Larger Size Particles

Sea salt aerosols play a critical role in regulating the global climate through their interactions with solar radiation.The size distribution of these particles is crucial in determining their bulk optical properties.In this study,we analyzed in situ measured size distributions of sea salt aerosols from four field campaigns and used multi-mode lognormal size distributions to fit the data.We employed super-spheroids and coated super-spheroids to account for the particles’non-sphericity,inhomogeneity,and hysteresis effect during the deliquescence and crystallization processes.To compute the singlescattering properties of sea salt aerosols,we used the state-of-the-art invariant imbedding T-matrix method,which allows us to obtain accurate optical properties for sea salt aerosols with a maximum volume-equivalent diameter of 12μm at a wavelength of 532 nm.Our results demonstrated that the particle models developed in this study were successful in replicating both the measured depolarization and lidar ratios at various relative humidity(RH)levels.Importantly,we observed that large-size particles with diameters larger than 4μm had a substantial impact on the optical properties of sea salt aerosols,which has not been accounted for in previous studies.Specifically,excluding particles with diameters larger than 4μm led to underestimating the scattering and backscattering coefficients by 27%−38%and 43%−60%,respectively,for the ACE-Asia field campaign.Additionally,the depolarization ratios were underestimated by 0.15 within the 50%−70%RH range.These findings emphasize the necessity of considering large particle sizes for optical modeling of sea salt aerosols.

On the Radiative Properties of Ice Clouds:Light Scattering, Remote Sensing,and Radiation Parameterization

Presented is a review of the radiative properties of ice clouds from three perspectives： light scattering simulations, remote sensing applications, and broadband radiation parameterizations appropriate for numerical models. On the subject of light scattering simulations, several classical computational approaches are reviewed, including the conventional geometric-optics method and its improved forms, the finite-difference time domain technique, the pseudo-spectral time domain technique, the discrete dipole approximation method, and the T-matrix method, with specific applications to the computation of the singlescattering properties of individual ice crystals. The strengths and weaknesses associated with each approach are discussed.With reference to remote sensing, operational retrieval algorithms are reviewed for retrieving cloud optical depth and effective particle size based on solar or thermal infrared（IR） bands. To illustrate the performance of the current solar- and IR-based retrievals, two case studies are presented based on spaceborne observations. The need for a more realistic ice cloud optical model to obtain spectrally consistent retrievals is demonstrated. Furthermore, to complement ice cloud property studies based on passive radiometric measurements, the advantage of incorporating lidar and/or polarimetric measurements is discussed.The performance of ice cloud models based on the use of different ice habits to represent ice particles is illustrated by comparing model results with satellite observations. A summary is provided of a number of parameterization schemes for ice cloud radiative properties that were developed for application to broadband radiative transfer submodels within general circulation models（GCMs）. The availability of the single-scattering properties of complex ice habits has led to more accurate radiation parameterizations. In conclusion, the importance of using nonspherical ice particle models in GCM simulations for climate studies is proven.

Sediment recycling and indication of weathering proxies

As a result of recycling, the mineralogical and chemical compositions of riverine sediments may reflect the combined effects of the present-day weathering regime as well as previous weathering and diagenetic alteration history. River sediments can be interpreted as a mixture of non-weathered bedrock—of igneous, metamorphic, or sedimentary origin—and solids formed by the modern weathering system. The correlation between the weathering proxies chemical index of alteration and weathering index of Parker offers an approach to distinguish fine suspended particles, coarse bedload sediments, and recycled sediments under the influence of quartz dilution. Recycling of cation-depleted source rocks formed during past geological weathering episodes may have great impacts on the weathering indices of sediments from the Changjiang(Yangzte) and Zhuoshui Rivers. Special caution is required when using chemical weathering indices to investigate the intensity of chemical weathering registered in fluvial sediments. To minimize the effect of hydrodynamic sorting or sediment recycling, we suggest that the fine sediments(e.g.suspended particles and ﹤2 lm fractions of bedload sediments) in rivers better reflect the average of weatheredcrust in catchments and the terrigenous end-member in marginal seas.

Electrolyte materials for protonic ceramic electrochemical cells:Main limitations and potential solutions

Solid oxide fuel cells(SOFCs)and electrolysis cells(SOECs)are promising energy conversion devices,on whose basis green hydrogen energy technologies can be developed to support the transition to a carbon-free future.As compared with oxygen-conducting cells,the operational temperatures of protonic ceramic fuel cells(PCFCs)and electrolysis cells(PCECs)can be reduced by several hundreds of degrees(down to low-and intermediatetemperature ranges of 400–700C)while maintaining high performance and efficiency.This is due to the distinctive characteristics of charge carriers for proton-conducting electrolytes.However,despite achieving outstanding lab-scale performance,the prospects for industrial scaling of PCFCs and PCECs remain hazy,at least in the near future,in contrast to commercially available SOFCs and SOECs.In this review,we reveal the reasons for the delayed technological development,which need to be addressed in order to transfer fundamental findings into industrial processes.Possible solutions to the identified problems are also highlighted.

Application of a Neural Network to Store and Compute the Optical Properties of Non-Spherical Particles

Radiative transfer simulations and remote sensing studies fundamentally require accurate and efficient computation of the optical properties of non-spherical particles.This paper proposes a deep learning(DL)scheme in conjunction with an optical property database to achieve this goal.Deep neural network(DNN)architectures were obtained from a dataset of the optical properties of super-spheroids with extensive shape parameters,size parameters,and refractive indices.The dataset was computed through the invariant imbedding T-matrix method.Four separate DNN architectures were created to compute the extinction efficiency factor,single-scattering albedo,asymmetry factor,and phase matrix.The criterion for designing these neural networks was the achievement of the highest prediction accuracy with minimal DNN parameters.The numerical results demonstrate that the determination coefficients are greater than 0.999 between the prediction values from the neural networks and the truth values from the database,which indicates that the DNN can reproduce the optical properties in the dataset with high accuracy.In addition,the DNN model can robustly predict the optical properties of particles with high accuracy for shape parameters or refractive indices that are unavailable in the database.Importantly,the ratio of the database size(~127 GB)to that of the DNN parameters(~20 MB)is approximately 6810,implying that the DNN model can be treated as a highly compressed database that can be used as an alternative to the original database for real-time computing of the optical properties of non-spherical particles in radiative transfer and atmospheric models.

The 50 nm-thick yttrium iron garnet films with perpendicular magnetic anisotropy

Yttrium iron garnet(YIG) films possessing both perpendicular magnetic anisotropy(PMA) and low damping would serve as ideal candidates for high-speed energy-efficient spintronic and magnonic devices.However,it is still challenging to achieve PMA in YIG films thicker than 20 nm,which is a major bottleneck for their development.In this work,we demonstrate that this problem can be solved by using substrates with moderate lattice mismatch with YIG so as to suppress the excessive strain-induced stress release as increasing the YIG thickness.After carefully optimizing the growth and annealing conditions,we have achieved out-of-plane spontaneous magnetization in YIG films grown on sGGG substrates,even when they are as thick as 50 nm.Furthermore,ferromagnetic resonance and spin pumping induced inverse spin Hall effect measurements further verify the good spin transparency at the surface of our YIG films.

Biochemical sensing in graphene-enhanced microfiber resonators with individual molecule sensitivity and selectivity

Photonic sensors that are able to detect and track biochemical molecules offer powerful tools for information acquisition in applications ranging from environmental analysis to medical diagnosis.The ultimate aim of biochemical sensing is to achieve both quantitative sensitivity and selectivity.As atomically thick films with remarkable optoelectronic tunability,graphene and its derived materials have shown unique potential as a chemically tunable platform for sensing,thus enabling significant performance enhancement,versatile functionalization and flexible device integration.Here,we demonstrate a partially reduced graphene oxide(prGO)inner-coated and fiber-calibrated Fabry-Perot dye resonator for biochemical detection.Versatile functionalization in the prGO film enables the intracavity fluorescent resonance energy transfer(FRET)to be chemically selective in the visible band.Moreover,by measuring the intermode interference via noise canceled beat notes and locked-in heterodyne detection with Hz-level precision,we achieved individual molecule sensitivity for dopamine,nicotine and single-strand DNA detection.This work combines atomic-layer nanoscience and high-resolution optoelectronics,providing a way toward high-performance biochemical sensors and systems.

Enhanced conductivity and stability of Co_(0.98)Cu_(x)Mn_(2.02−x)O_(4)ceramics with dual phases and twin structures

Semiconductor materials with heterogeneous interfaces and twin structures generally demonstrate a higher concentration of carriers and better electrical stability.A variety of Cu-doped Co_(0.98)Cu_(x)Mn_(2.02−x)O_(4)(0≤x≤0.5)negative temperature coefficient(NTC)ceramics with dual phases and twin structures were successfully prepared in this study.Rietveld refinement indicates that the content of a cubic spinel phase increases with increasing Cu content.The addition of Cu can promote grain growth and densification.Atomic-level structural characterization reveals the evolution of twin morphology from large lamellae with internal fine lamellae(LIT lamellae)to large lamellae without internal fine lamellae(L lamellae)and the distribution of twin boundary defects.First-principles calculations reveal that the dual phases and twin structures have lower oxygen-vacancy formation energy than those in the case of the pure tetragonal and cubic spinel,thereby enhancing the transmission of carriers.Additionally,the three-dimensional charge-density difference shows that metal ions at the interface lose electrons and dwell in high valence states,thereby enhancing electrical stability of the NTC ceramics.Furthermore,the additional Cu ions engage in electron-exchange interactions with Mn and Co ions,thereby reducing resistivity.In comparison to previous Cu-containing systems,the Co_(0.98)Cu_(x)Mn_(2.02−x)O_(4)series exhibit superior stability(aging value≤2.84%),tunable room-temperature resistivity(ρ),and material constant(B)value(17.5Ω·cm≤ρ≤7325Ω·cm,2836 K≤B≤4315 K).These discoveries lay a foundation for designing and developing new NTC ceramics with ultra-high performance.

Advances in Atmospheric Radiation:Theories,Models,and Their Applications.PartⅠ:Atmospheric Gas Absorption and Particle Scattering

Atmospheric radiation is a major branch of atmospheric physics that encompasses the fundamental theories of atmospheric absorption,particle scattering(aerosols and clouds),and radiative transfer.Specifically,the simulations of atmospheric gaseous absorption and scattering properties of particles are the essential components of atmospheric radiative transfer models.Atmospheric radiation has important applications in weather,climate,data assimilation,remote sensing,and atmospheric detection studies.In PartⅠ,a comprehensive review of the progress in the field of gas absorption and particle scattering research over the past 30 years with a particular emphasis on the contributions from Chinese scientists is presented.The review of gas absorption includes the construction of absorption databases,the impact of different atmospheric absorption algorithms on radiative calculations,and their applications in weather and climate models and remote sensing.The review on particle scattering starts with the theoretical and computational methods and subsequently explores the optical modeling of aerosols and clouds in remote sensing and atmospheric models.Additionally,the paper discusses potential future research directions in this field.

Energy budget of cold and hot gas-solid fluidized beds through CFD-DEM simulations

Direct energy budget is carried out for both cold and hot flow in gas–solid fluidization systems.First,the energy paths are proposed from thermodynamic viewpoints.Energy consumption means total power input to the specific system,and it can be decomposed into energy retention and energy dissipation.Energy retention is the variation of accumulated mechanical energy in the system,and energy dissipation is the energy converted to heat by irreversible processes.Then based on the Computational Fluid Dynamics-Discrete Element Method(CFD-DEM)framework,different energy terms are quantified from the specific flow elements of fluid cells and particles as well as their interactions with the wall.In order to clarify the energy budget,it is important to identify which system is studied:the particle-fluid system or the particle sub-system.For the cold flow,the total energy consumption of the particle sub-system can well indicate the onset of bubbling and turbulent,while the variation of local energy consumption terms can reflect the evolution of heterogeneous structures.For the hot flow,different heat transfer mechanisms are analyzed and the solver is modified to reproduce the experimental results.The impact of the heat transfer mechanisms and heat production on energy consumption is also investigated.The proposed budget method has proven to be energy-conservative and easy to conduct,and it is hopeful to be applied to other multiphase flow systems.

A Transformer-Assisted Cascade Learning Network for Choroidal Vessel Segmentation

As a highly vascular eye part,the choroid is crucial in various eye disease diagnoses.However,limited research has focused on the inner structure of the choroid due to the challenges in obtaining sufficient accurate label data,particularly for the choroidal vessels.Meanwhile,the existing direct choroidal vessel segmentation methods for the intelligent diagnosis of vascular assisted ophthalmic diseases are still unsatisfactory due to noise data,while the synergistic segmentation methods compromise vessel segmentation performance for the choroid layer segmentation tasks.Common cascaded structures grapple with error propagation during training.To address these challenges,we propose a cascade learning segmentation method for the inner vessel structures of the choroid in this paper.Specifically,we propose TransformerAssisted Cascade Learning Network(TACLNet)for choroidal vessel segmentation,which comprises a two-stage training strategy:pre-training for choroid layer segmentation and joint training for choroid layer and choroidal vessel segmentation.We also enhance the skip connection structures by introducing a multi-scale subtraction connection module designated as MSC,capturing differential and detailed information simultaneously.Additionally,we implement an auxiliary Transformer branch named ATB to integrate global features into the segmentation process.Experimental results exhibit that our method achieves the state-of-the-art performance for choroidal vessel segmentation.Besides,we further validate the significant superiority of the proposed method for retinal fluid segmentation in optical coherence tomography(OCT)scans on a publicly available dataset.All these fully prove that our TACLNet contributes to the advancement of choroidal vessel segmentation and is of great significance for ophthalmic research and clinical application.

Efficient removal and upcycling of pollutants in wastewater:a strategy for reconciling environmental pollution and resource depletion crisis

Due to the relentless exploitation of non-renewable resources,humanity is faced with a resource depletion crisis in the coming decades and serious environmental issues.Achieving efficient removal and upcycling of pollutants(ERUP)may become a potential strategy to address these issues.Wastewater,characterized by its large production volume and fluidity,can easily cause widespread environmental pollution through natural water networks.Due to solubility constraints,pollutants in wastewater typically exhibit low concentrations and complex compositions,thereby impeding effective recovery.Therefore,achieving ERUP in wastewater is both highly significant and extremely challenging.Unlike conventional wastewater treatment strategies that are focused on removing pollutants,ERUP strategies can not only realize the efficient removal of pollutants from water but also convert pollutants into valuable and functional products.Herein,we enumerated the latest research progress on ERUP in wastewater and highlighted studies that demonstrate the simultaneous achievement of pollutant removal and the direct conversion of these contaminants into high-efficiency catalysts,hydrogen energy,electrical energy,and other high-value chemicals.Finally,we identified the problems and challenges in the development of ERUP in wastewater and outlined potential research directions for future studies.

La_(0.5−x)ScxSr_(0.5)MnO_(3−δ)cathodes for proton-conducting solid oxide fuel cells:Taking advantage of the secondary phase

Designing high-performance cathodes is crucial for proton-conducting solid oxide fuel cells(H-SOFCs),as the cathode heavily influences cell performance.Although manganate cathodes exhibit superior stability and thermal compatibility,their poor cathode performance at intermediate temperatures renders them unsuitable for H-SOFC applications.To address this issue,Sc is utilized as a dopant to modify the traditional La_(0.5)ScxSr_(0.5)MnO_(3) cathode at the La site.Although the solubility of Sc at the La site is restricted to 2.5%,this modest quantity of Sc doping can improve the material's oxygen and proton transport capabilities,hence improving cathode and fuel cell performance.Furthermore,when the doping concentration exceeds 2.5%,the secondary phase ScMnO3 forms in situ,resulting in La_(0.475)Sc_(0.025)Sr_(0.5)MnO_(3)(LScSM)+ScMnO_(3) nanocomposites.Although the secondary phase is often considered undesirable,the high protonation capacity of ScMnO_(3) can compensate for the low proton diffusion ability of LScSM.These two phases complement each other to provide high-performance cathodes.The nominal La_(0.4)Sc_(0.1)Sr_(0.5)MnO_(3) is the optimal composition,which takes advantage of the excellent electronic conductivity and fast oxygen diffusion rates of LScSM,as well as the good proton diffusion capacity of ScMnO_(3),to produce a high fuel cell output of 1529 mW·cm−2 at 700°C.Furthermore,the fuel cell exhibited good operational stability under working conditions,indicating that La_(0.4)Sc_(0.1)Sr_(0.5)MnO_(3) is a viable cathode choice for H-SOFCs.

Manipulating Nb-doped SrFeO_(3−δ)with excellent performance for proton-conducting solid oxide fuel cells

Nb-doped SrFeO_(3−δ)(SFO)is used as a cathode in proton-conducting solid oxide fuel cells(H-SOFCs).First-principles calculations show that the SrFe0.9Nb0.1O_(3−δ)(SFNO)cathode has a lower energy barrier in the cathode reaction for H-SOFCs than the Nb-free SrFeO_(3−δ)cathode.Subsequent experimental studies show that Nb doping substantially enhances the performance of the SrFeO_(3−δ)cathode.Then,oxygen vacancies(VO)were introduced into SFNO using the microwave sintering method,further improving the performance of the SFNO cathode.The mechanism behind the performance improvement owing to VO was revealed using first-principles calculations,with further optimization of the SFNO cathode achieved by developing a suitable wet chemical synthesis route to prepare nanosized SFNO materials.This method significantly reduces the grain size of SFNO compared with the conventional solid-state reaction method,although the solid-state reaction method is generally used for preparing Nb-containing oxides.As a result of defect engineering and synthesis approaches,the SFNO cathode achieved an attractive fuel cell performance,attaining an output of 1764 mW·cm−2 at 700℃ and operating for more than 200 h.The manipulation of Nb-doped SrFeO_(3−δ)can be seen as a“one stone,two birds”strategy,enhancing cathode performance while retaining good stability,thus providing an interesting approach for constructing high-performance cathodes for H-SOFCs.

Security estimation of LWE via BKW algorithms

The Learning With Errors(LWE)problem is widely used in lattice-based cryptography,which is the most promising post-quantum cryptography direction.There are a variety of LWE-solving methods,which can be classified into four groups:lattice methods,algebraic methods,combinatorial methods,and exhaustive searching.The Blum–Kalai–Wasserman(BKW)algorithm is an important variety of combinatorial algorithms,which was first presented for solving the Learning Parity With Noise(LPN)problem and then extended to solve LWE.In this paper,we give an overview of BKW algorithms for solving LWE.We introduce the framework and key techniques of BKW algorithms and make comparisons between different BKW algorithms and also with lattice methods by estimating concrete security of specific LWE instances.We also briefly discuss the current problems and potential future directions of BKW algorithms.

远程教育精准扶贫受众获得感测评

为探讨远程教育精准扶贫受众获得感水平,本研究采用入户调查的方式对安徽淮河文化、皖江文化、徽州文化地区进行抽样调查。数据分析发现:受众物质维度、精神维度和总体的获得感水平均较高;地域文化、经济水平、年龄段、致贫原因等不同的受众其获得感存在显著差异;家庭人口数、学历层次等不同的受众在获得感的精神维度上没有显著差异。在由脱贫攻坚向乡村振兴战略转型的进程中,远程教育精准扶贫实践对防止返贫、提升受众获得感具有重要意义。振兴路径选择应契合地方经济社会发展需要,振兴策略设计应适应受众差别化需求。

A high-entropy spinel ceramic oxide as the cathode for proton-conducting solid oxide fuel cells

A high-entropy ceramic oxide is used as the cathode for the first time for proton-conducting solid oxide fuel cells(H-SOFCs).The Fe_(0.6)Mn_(0.6)Co_(0.6)Ni_(0.6)Cr_(0.6)O_(4)(FMCNC)high-entropy spinel oxide has been successfully prepared,and the in situ chemical stability test demonstrates that the FMCNC material has good stability against CO_(2).The first-principles calculation indicates that the high-entropy structure enhances the properties of the FMCNC material that surpasses their individual components,leading to lower O_(2)adsorption energy for FMCNC than that for the individual components.The HSOFC using the FMCNC cathode reaches an encouraging peak power density(PPD)of 1052 mW·cm^(-2)at 700℃,which is higher than those of the H-SOFCs reported recently.Additional comparison was made between the high-entropy FMCNC cathode and the traditional Mn_(1.6)Cu_(1.4)O_(4)(MCO)spinel cathode without the high-entropy structure,revealing that the formation of the high-entropy material allows the enhanced protonation ability as well as the movement of the O p-band center closer to the Fermi level,thus improving the cathode catalytic activity.As a result,the high-entropy FMCNC has a much-decreased polarization resistance of 0.057Ω·cm^(2)at 700℃,which is half of that for the traditional MCO spinel cathode without the high-entropy design.The excellent performance of the FMCNC cell indicates that the high-entropy design makes a new life for the spinel oxide as the cathode for HSOFCs,offering a novel and promising route for the development of high-performance materials for H-SOFCs.

Tailoring Sr_(2)Fe_(1.5)Mo_(0.5)O_(6-δ)with Sc as a new single-phase cathode for proton-conducting solid oxide fuel cells

Sc-doped Sr_(2)Fe_(1.5)Mo_(0.5)O_(6-δ)(SFMSc)was successfully synthesized by partially substituting Mo in Sr_(2)Fe_(1.5)Mo_(0.5)O_(6-δ)(SFM)with Sc,resulting in a higher proton diffusion rate in the resultant SFMSc sample.Theoretical calculations showed that doping Sc into SFM lowered the oxygen vacancy formation energy,reduced the energy barrier for proton migration in the oxide,and increased the catalytic activity for oxygen reduction reaction.Next,a proton-conducting solid oxide fuel cell(H-SOFC)with a single-phase SFMSc cathode demonstrated significantly higher cell performance than that of cell based on an Sc-free SFM cathode,achieving 1258 mW cm^(−2)at 700℃.The performance also outperformed that of many other H-SOFCs based on single-phase cobalt-free cathodes.Furthermore,no trade-off between fuel cell performance and material stability was observed.The SFMSc material demonstrated good stability in both the CO_(2)-containing atmosphere and the fuel cell application.The combination of high performance and outstanding stability suggests that SFMSc is an excellent cathode material for H-SOFCs.

High-performance proton-conducting solid oxide fuel cells using the first-generation Sr-doped LaMnO_(3) cathode tailored with Zn ions

Sr-doped LaMnO_(3)(LSM)which is the firstgeneration cathode for solid oxide fuel cells(SOFC;)has been tailored with Zn ions,aiming to achieve improved protonation ability for proton-conducting SOFCs(H-SOFCs).The new Sr and Zn co-doped LaMnO_(3)(LSMZ)can be successfully synthesized.The first-principle studies indicate that the LSMZ improves the protonation of LSM and decreases the barriers for oxygen vacancy formation,leading to high performance of the LSMZ cathode-based cells.The proposed LSMZ cell shows the highest fuel cell performance among ever reported LSMbased H-SOFCs.In addition,the superior fuel cell performance does not impair its stability.LSMZ is stable against CO_(2),as demonstrated by both in-situ CO_(2)corrosion tests and the first-principles calculations,leading to good long-term stability of the cell.The Zn-doping strategy for the traditional LSM cathode with high performance and good stability brings back the LSM cathode to intermediate temperatures and paves a new way for the research on the LSM-based materials as cathodes for SOFCs.

Successful preparation of BaCo_(0.5)Fe_(0.5)O_(3–δ)cathode oxide by rapidly cooling allowing for high-performance proton-conducting solid oxide fuel cells

A pure phase BaCo_(0.5)Fe_(0.5)O_(3–δ)(BCF),which cannot be obtained before,is successfully prepared in this study by using the calcination method with a rapid cooling procedure.The successful preparation of BCF allows the evaluation of this material as a cathode for proton-conducting solid oxide fuel cells(H-SOFCs)for the first time.An H-SOFC using the BCF cathode achieves an encouraging fuel cell performance of 2012 mW·cm–2 at 700,two℃-fold higher than that of a similar cell using the classical high-performance Ba_(0.5)Sr_(0.5)Co_(0.8)Fe_(0.2)O_(3–δ)(BSCF)cathode.First-principles calculations reveal the mechanism for the performance enhancement,indicating that the new BCF cathode significantly lowers the energy barriers in the oxygen reduction reaction(ORR)compared with the BSCF cathode.Therefore,improved cathode performance and fuel cell output are obtained for the BCF cell.The fuel cell using the BCF cathode also shows excellent long-term stability that can work stably for nearly 900 h without noticeable degradations.The fuel cell performance and long-term stability of the current BCF cell are superior to most of the H-SOFCs reported in previous reports,suggesting that BCF is a promising cathode for H-SOFCs.