Porous metal oxides in the role of electrochemical CO_(2) reduction reaction

The global energy-related CO_(2) emissions have rapidly increased as the world economy heavily relied on fossil fuels.This paper explores the pressing challenge of CO_(2) emissions and highlights the role of porous metal oxide materials in the electrocatalytic reduction of CO_(2)(CO_(2)RR).The focus is on the development of robust and selective catalysts,particularly metal and metal-oxide-based materials.Porous metal oxides offer high surface area,enhancing the accessibility to active sites and improving reaction kinetics.The tunability of these materials allows for tailored catalytic behavior,targeting optimized reaction mechanisms for CO_(2)RR.The work also discusses the various synthesis strategies and identifies key structural and compositional features,addressing challenges like high overpotential,poor selectivity,and low stability.Based on these insights,we suggest avenues for future research on porous metal oxide materials for electrochemical CO_(2) reduction.

Panoptic UAV:Panoptic Segmentation of UAV Images for Marine Environment Monitoring

UAV marine monitoring plays an essential role in marine environmental protection because of its flexibility and convenience,low cost and convenient maintenance.In marine environmental monitoring,the similarity between objects such as oil spill and sea surface,Spartina alterniflora and algae is high,and the effect of the general segmentation algorithm is poor,which brings new challenges to the segmentation of UAV marine images.Panoramic segmentation can do object detection and semantic segmentation at the same time,which can well solve the polymorphism problem of objects in UAV ocean images.Currently,there are few studies on UAV marine image recognition with panoptic segmentation.In addition,there are no publicly available panoptic segmentation datasets for UAV images.In this work,we collect and annotate UAV images to form a panoptic segmentation UAV dataset named UAV-OUC-SEG and propose a panoptic segmentation method named PanopticUAV.First,to deal with the large intraclass variability in scale,deformable convolution and CBAM attention mechanism are employed in the backbone to obtain more accurate features.Second,due to the complexity and diversity of marine images,boundary masks by the Laplacian operator equation from the ground truth are merged into feature maps to improve boundary segmentation precision.Experiments demonstrate the advantages of PanopticUAV beyond the most other advanced approaches on the UAV-OUC-SEG dataset.

DynamicMechanical and Chemorheology Analysis for the Blended Epoxy System with Polyurethane Modified Resin

As the important matrix material,epoxy resin has been widely used in the composites for various fields.On account of the poor toughness of epoxy resin limiting their suitability for advanced applications,considerable interests have been conducted to modify the epoxy resin to meet the engineering requirements.In this study,the bio-based polyurethane(PU)modified resin was adopted to modify the pure bisphenol-A epoxy by blending method with various proportions.Aiming to illuminate the curing behavior,mechanical and thermal properties,the blended epoxy systems were characterized by viscosity-time analysis,dynamic mechanical analysis(DMA)at different frequencies and temperatures,mechanical tensile test,thermogravimetric analysis(TGA)and Fourier transform infrared(FT-IR)spectroscopy.The results indicated that the introduction of PU modified epoxy was found to significantly inhibit the viscosity growth rates especially when the content of PU modified epoxy resin is higher than 60%.Notwithstanding the dynamic modulus and T_(g)reduced with the increment of PU modified epoxy,remarkable increment on the elongation at break was found and the flexibility was greatly promoted with the introduction of PU modified epoxy.The proportion of PU modified epoxy in the blends should be put balance considerations to obtain optimal mechanical properties.TGA results and FTIR spectrum demonstrated that the addition of PU modified epoxy did not change the thermal decomposition mechanism and chemical reaction mechanism,but the addition of PU modified epoxy inhibits the curing reaction of epoxy resin by measured and calculated the damping temperature domain
T from 35.7℃ to 48.9℃.

Application of local Monte Carlo method in neutronics calculation of EAST radial neutron camera

The Local Monte Carlo(LMC)method is used to solve the problems of deep penetration and long time in the neutronics calculation of the radial neutron camera(RNC)diagnostic system on the experimental advanced superconducting tokamak(EAST),and the radiation distribution of the RNC and the neutron flux at the detector positions of each channel are obtained.Compared with the results calculated by the global variance reduction method,it is shown that the LMC calculation is reliable within the reasonable error range.The calculation process of LMC is analyzed in detail,and the transport process of radiation particles is simulated in two steps.In the first step,an integrated neutronics model considering the complex window environment and a neutron source model based on EAST plasma shape are used to support the calculation.The particle information on the equivalent surface is analyzed to evaluate the rationality of settings of equivalent surface source and boundary.Based on the characteristic that only a local geometric model is needed in the second step,it is shown that the LMC is an advantageous calculation method for the nuclear shielding design of tokamak diagnostic systems.

Reconstructions of velocity distributions from fast-ion D-alpha(FIDA)measurements on EAST

2D fast-ion velocity-space distributions have been reconstructed from two-view fast-ion D-alpha(FIDA)measurements on experimental advanced superconducting tokamak(EAST).To make up for the sparse data and incomplete velocity-space coverage with the dual-view,we use nonnegativity and null-measurements as prior information to reconstruct the velocity distribution in experiments with co-and counter-current neutral beam injection.An improved reconstructed fast-ion distribution is achieved by combining the existing O-and B-port FIDA measurements with the proposed A-port FIDA view.To further improve the reliability of FIDA-based reconstructions on EAST,based on real multi-view FIDA measurements on EAST in the near future,various bases will be studied further.

Simulations of scattered neutrons for the time-of-flight enhanced diagnostics(TOFED)neutron spectrometer on EAST

The time-of-flight enhanced diagnostics(TOFED)neutron spectrometer has been installed in TOFED house,which is a newly-built neutron diagnostic lab outside the EAST experimental hall.The line of sight(LOS)of TOFED is defined by the collimator going through the 150 cm biological shielding wall,which can reduce background neutrons very effectively for the neutron spectral measurements.The Monte Carlo code MCNP5 is used in the simulations to characterize collimation effects and the radiation safety of the new house.The collimator makes neutron flux almost fully perpendicular to S 1 detectors.In addition,the proportion of scattered neutrons in the LOS of the TOFED is obtained for the measured spectral data interpretation.The simulation results show that the TOFED house satisfies the requirement for the TOFED operations at EAST and gives a safe environment for personnel access during the EAST operation.

Excitation of RSAEs during Sawteeth-Like Oscillation in EAST

The excitation condition of reversed shear Alfven eigenmodes(RSAEs)has been investigated during sawtoothlike oscillation in the EAST tokamak.The sawtooth-like phenomena can be reproduced in the configuration of reversed magnetic shear,and the threshold gradient of electron temperature is formed accordingly,together with the increasing of the confinement of thermal particles.The distribution function of energetic ions density is altered dramatically when the neutral beam is switched from NBI1 L(tangent)to NBI1 R(perpendicular),which can be captured by the measurement of radial neutron camera.The RSAEs are excited easily in the vicinity of q_(min)(1.99 m≤R≤2.06 m)for the injection of neutral beam with perpendicular direction,which should be excited by the steep gradient of energetic ions density.Furthermore,the excitation of RSAEs and the formation of threshold gradient of electron temperature can take place concurrently,which means that the neutral beam with perpendicular injection is beneficial for the establishment of internal transport barrier.

稀土基中子和伽马复合屏蔽材料

随着航空航天、核技术等领域的发展和核能的广泛利用,对核辐射屏蔽材料的性能也提出更高的要求。核反应中产生的中子、伽马射线的穿透能力较强,危害较大,所以对于中子、伽马辐射屏蔽材料的研究成为辐射防护研究的重点。稀土元素具有较高的中子吸收截面和高原子序数,逐渐被科研人员重视并应用于中子、伽马辐射屏蔽材料的研发中。本文简述了稀土材料在辐射屏蔽材料领域的应用,介绍了稀土元素与中子和伽马射线的作用原理;根据基体材料的类别将稀土基中子和伽马辐射屏蔽材料分为稀土金属基、稀土聚合物基、稀土玻璃基三类,分别介绍了三类稀土基复合屏蔽材料的研究进展,并分析了稀土材料用于中子、伽马辐射屏蔽存在的问题与展望。

Review on electrochemical carbon dioxide capture and transformation with bipolar membranes

Anthropogenic carbon dioxide(CO_(2))emission from the combustion of fossil fuels aggravates the global greenhouse effect.The implementation of CO_(2)capture and transformation technologies have recently received great attention for providing a pathway in dealing with global climate change.Among these technologies,electrochemical CO_(2)capture technology has attracted wide attention because of its environmental friendliness and flexible operating processes.Bipolar membranes(BPMs)are considered as one of the key components in electrochemical devices,especially for electrochemical CO_(2)reduction and electrodialysis devices.BPMs create an alkaline environment for CO_(2)capture and a stable pH environment for electrocatalysis on a single electrode.The key to CO_(2)capture in these devices is to understand the water dissociation mechanism occurring in BPMs,which could be used for optimizing the operating conditions for CO_(2)capture and transformation.In this paper,the references and technologies of electrochemical CO_(2)capture based on BPMs are reviewed in detail,thus the challenges and opportunities are also discussed for the development of more efficient,sustainable and practical CO_(2)capture and transformation based on BPMs.

Size-transformable nanoparticles with sequentially triggered drug release and enhanced penetration for anticancer therapy

There are several limitations to the application of nanoparticles in the treatment of cancer,including their low drug loading,poor colloidal stability,insufficient tumor penetration,and uncontrolled release of the drug.Herein,gelatin/laponite(LP)/doxorubicin(GLD)nanoparticles are developed by crosslinking LP with gelatin for doxorubicin delivery.GLD shows high doxorubicin encapsulation efficacy(99%)and strong colloidal stability,as seen from the unchanged size over the past 21 days and reduced protein absorption by 48-fold compared with unmodified laponite/doxorubicin nanoparticles.When gelatin from 115 nm GLD reaches the tumor site,matrix metallopeptidase-2(MMP-2)from the tumor environment breaks it down to release smaller 40 nm LP nanoparticles for effective tumor cell endocytosis.As demonstrated by superior penetration in both in vitro three-dimensional(3D)tumor spheroids(138-fold increase compared to the free drug)and in vivo tumor models.The intracellular low pH and MMP-2 further cause doxorubicin release after endocytosis by tumor cells,leading to a higher inhibitory potential against cancer cells.The improved anticancer effectiveness and strong in vivo biocompatibility of GLD have been confirmed using a mouse tumor-bearing model.MMP-2/pH sequentially triggered anticancer drug delivery is made possible by the logical design of tumor-penetrating GLD,offering a useful method for anticancer therapy.

Tandem hidden Markov models using deep belief networks for offline handwriting recognition

Unconstrained offiine handwriting recognition is a challenging task in the areas of document analysis and pattern recognition. In recent years, to sufficiently exploit the supervisory information hidden in document images, much effort has been made to integrate multi-layer perceptrons （MLPs） in either a hybrid or a tandem fashion into hidden Markov models （HMMs）. However, due to the weak learnability of MLPs, the learnt features are not necessarily optimal for subsequent recognition tasks. In this paper, we propose a deep architecture-based tandem approach for unconstrained offiine handwriting recognition. In the proposed model, deep belief networks arc adopted to learn the compact representations of sequential data, while HMMs are applied for （sub-）word recognition. We evaluate the proposed model on two publicly available datasets, i.e., RIMES and IFN/ENIT, which are based on Latin and Arabic languages respectively, and one dataset collected by ourselves called Devanagari （all Indian script）. Extensive experiments show the advantage of the proposed model, especially over the MLP-HMMs taudem approaches.