Simplified quantitative analysis method and its application in the insitu synthesized copper-based azide chips

Copper-based azide(Cu(N_(3))2 or CuN_(3),CA)chips synthesized by in-situ azide reaction and utilized in miniaturized explosive systems has become a hot research topic in recent years.However,the advantages of in-situ synthesis method,including small size and low dosage,bring about difficulties in quantitative analysis and differences in ignition capabilities of CA chips.The aim of present work is to develop a simplified quantitative analysis method for accurate and safe analysis of components in CA chips to evaluate and investigate the corresponding ignition ability.In this work,Cu(N_(3))2 and CuN_(3)components in CA chips were separated through dissolution and distillation by utilizing the difference in solubility and corresponding content was obtained by measuring N_(3)-concentration through spectrophotometry.The spectrophotometry method was optimized by studying influencing factors and the recovery rate of different separation methods was studied,ensuring the accuracy and reproducibility of test results.The optimized method is linear in range from 1.0-25.0 mg/L,with a correlation coefficient R^(2)=0.9998,which meets the requirements of CA chips with a milligram-level content test.Compared with the existing ICP method,component analysis results of CA chips obtained by spectrophotometry are closer to real component content in samples and have satisfactory accuracy.Moreover,as its application in miniaturized explosive systems,the ignition ability of CA chips with different component contents for direct ink writing CL-20 and the corresponding mechanism was studied.This study provided a basis and idea for the design and performance evaluation of CA chips in miniaturized explosive systems.

Metal-organic-framework-derived copper-based catalyst for multicomponent C-S coupling reaction

Copper-based metal-organic frameworks(Cu-MOFs)are a promising multiphase catalyst for catalyzing C-S coupling reactions by virtue of their diverse structures and functions.However,the unpleasant odor and instability of the organosulfur,as well as the mass-transfer resistance that exists in multiphase catalysis,have often limited the catalytic application of Cu-MOFs in C-S coupling reactions.In this paper,a Cu-MOFs catalyst modified by cetyltrimethylammonium bromide(CTAB)was designed to enhance mass transfer by increasing the adsorption of organic substrates using the long alkanes of CTAB.Concurrently,elemental sulfur was used to replace organosulfur to achieve a highly efficient and atom-economical multicomponent C-S coupling reaction.

Catalytic combustion of methane over nano ZrO_2-supported copper-based catalysts

The nano ZrO2-supported copper-based catalysts for methane combustion were investigated by means of N2 adsorption, TEM, XRD, H2-TPR techniques and the test of methane oxidation. Two kinds of ZrO2 were used as support, one （ZrO2-1） was obtained from the commercial ZrO2 and the other （ZrO2-2） was issued from the thermal decomposition of zirconium nitrate. It was found that the CuO/ZrO2-2 catalyst was more active than CuO/ZrO2-1. N2 adsorption, H2-TPR and XRD measurements showed that larger surface area, better reduction property, presence of tetragonal ZrO2 and higher dispersion of active component for CuO/ZrO2-2 than that of CuO/ZrO2-1. These factors could be the dominating reasons for its higher activity for methane combustion.

Effect of preparation methods of aluminum emulsions on catalytic performance of copper-based catalysts for methanol synthesis from syngas

Various Cu/ZnO/Al2O3 catalysts have been synthesized by different aluminum emulsions as aluminum sources and their pertormances tor methanol synthesis from syngas have been investigated. The influences of preparation methods of aluminum emulsions on physicochemical and catalytic properties of catalysts were studied by XRD, SEM, XPS,N2 adsorption-desorption techniques and methanol synthesis from syngas. The preparation methods of aluminum emulsions were found to influence the catalytic activity, CuO crystallite size, surface area and Cu0 surface area and reduction process. The results show that the catalyst CN using the aluminum source prepared by addition the ammonia into the aluminum nitrate （NP） exhibited the best catalytic performance for methanol synthesis from syngas.

A highly hydrothermal stable copper-based catalyst for catalytic wet air oxidation of m-cresol in coal chemical wastewater

Catalytic wet air oxidation(CWAO) can degrade some refractory pollutants at a low cost to improve the biodegradability of wastewater. However, in the presence of high temperature and high pressure and strong oxidizing free radicals, the stability of catalysts is often insufficient, which has become a bottleneck in the application of CWAO. In this paper, a copper-based catalyst with excellent hydrothermal stability was designed and prepared. TiO_(2) with excellent stability was used as the carrier to ensure the longterm anchoring of copper and reduce the leaching of the catalyst. The one pot sol–gel method was used to ensure the super dispersion and uniform distribution of copper nanoparticles on the carrier, so as to ensure that more active centers could be retained in a longer period. Experiments show that the catalyst prepared by this method has good stability and catalytic activity, and the catalytic effect is not significantly reduced after 10 cycles of use. The oxidation degradation experiment of m-cresol with the strongest biological toxicity and the most difficult to degrade in coal chemical wastewater was carried out with this catalyst. The results showed that under the conditions of 140℃, 2 MPa and 2 h, m-cresol with a concentration of up to 1000 mg·L^(-1) could be completely degraded, and the COD removal rate could reach 79.15%. The biological toxicity of wastewater was significantly reduced. The development of the catalyst system has greatly improved the feasibility of CWAO in the treatment of refractory wastewater such as coal chemical wastewater.

Comprehensive first-principles studies on phase stability of copper-based halide perovskite derivatives A_lCu_mX_n(A = Rb and Cs;X = Cl, Br, and I)

Recently,inorganic copper-based halide perovskites and their derivatives(CHPs)with chemical formulas AlCumXn(A=Rb and Cs;X=Cl,Br and I;l,m,and n are integers.),have received increasing attention in the photoluminescence field,due to their lead-free,cost-effective,earth-abundant and low electronic dimensionality.Ascribed to flexible valence charge of Cu(Cu1+and Cu2+)and complex competing phases,the crystal structures and phase stabilities of CHPs are complicated and ambiguous,which limits their experimental applications.Via comprehensive first-principles calculations,we have investigated thermodynamic stabilities of possible crystal phases for AlCumXn by considering all the possible secondary phases existing in inorganic crystal structure database(ICSD).Our results are in agreement with existing experiments and further predicted the existence of 10 stable CHPs,i.e.Rb3 Cu2 Br5,Rb3 Cu2 I5,Rb Cu2 Cl3,Rb2 Cu I3,Rb2 Cu Br4,Rb Cu Br3,Rb3 Cu2 Br7,Cs3 Cu2 Br7,Cs3 Cu2 Cl7 and Cs4 Cu5 Cl9,which have not yet been reported in experiments.This work provides a phase and compositional map that may guide experiments to synthesize more novel inorganic CHPs with diverse properties for potential functional applications.

Migration of sulfur in in-situ gasification chemical looping combustion of Beisu coal with iron-and copper-based oxygen carriers

Chemical looping combustion(CLC)is an energy conversion technology with high efficiency and inherent separation of CO_(2).The existence of sulfur in coal may affect the CO_(2) purity and the performance of oxygen carrier due to the interactions between sulfur contaminants and oxygen carrier.The migration of sulfur in Beisu coal during the in-situ gasification chemical looping combustion(i G-CLC)process using two oxygen carriers(iron ore and Cu O/Si O_(2))was investigated respectively.The thermodynamic analysis results showed the formation of metal sulfides was thermodynamically favored at low temperatures and low oxygen excess coefficients,while they were obviously inhibited and the production of SO_(2) was significantly promoted with an increase in temperature and oxygen excess coefficient.Moreover,part of sulfur was captured and fixed in the forms of alkali/alkaline earth metal sulfate due to the high amount of alkali/alkaline earth metal oxides in the coal ash or/and oxygen carrier.The experimental results showed that the sulfur in coal mainly released in the form of SO_(2),and the sulfur conversion efficiency(XS)in the reduction stage were 51.04%and 48.24%when using iron ore and Cu O/Si O_(2) respectively.The existence of metal sulfides was observed in the reduced oxygen carriers.The values of XSin the reoxidation process reached 3.80%and 7.64%when using iron ore and Cu O/Si O_(2) respectively.The residue and accumulation of sulfur were also found on the surfaces of two oxygen carriers.

Effects of Copper-based Nutritional Foliar Fertilizers on Photosynthetic Characteristics,Yield and Disease Control Efficiency of Cotton

[Objectives] The effects of copper-based nutrient foliar fertilizer on photosynthetic characteristics,yield,accumulation and distribution of trace elements in various organs,disease prevention effect and soil enzyme activity were studied,so as to provide a theoretical basis for the application of foliar fertilizers in cotton production. [Methods]Through two years of field experiments,six treatments were set in total,namely spraying water( CK),traditional Bordeaux mixture( BDM),Kocide 2000( KCD),copper-based nutrient foliar fertilizer( CF),iron-copper-based nutrient foliar fertilizer( CFFe),and zinc-boron-copper-based nutrient foliar fertilizer( CFZnB). Randomized block arrangement was adopted. Chlorophyll content in leaves was measured at each growth stage of the cotton. Photosynthetic characteristics of leaves were measured at the peak bolling stage. Plants were sampled at initial boll opening stage. The whole plant was divided into root,stem,leaf and cotton boll parts,in which the total copper,total zinc,total iron contents and accumulations were determined. Soil samples were collected from each plot,followed by the determination of soil enzyme activity. Disease index was investigated at bud,flowering and boll-forming and boll opening stage. [Results]( 1) Spraying CFFe,CFZnB,CF and KCD could significantly improve chlorophyll content of cotton leaves,and the CFFe treatment had the highest increase up to13. 30%,followed by the CFZnB treatment,which was 11. 40% higher than the CK; and photosynthetic rate,stomata conductance and transpiration rate could be improved significantly,and the CFFe treatment showed the highest photosynthetic rate,which increased by 26. 35% compared with the CK,followed by the CFZnB treatment,which increased by 17. 96% compared with CK; and intercellular CO2 concentration was significantly reduced.( 2) Spraying BDM,KCD,CF,CFFe and CFZnB can significantly increase total copper content and accumulation in various cotton organs( except the total copper content in the stem part of the CFZnB treatment; the CFZnB and CFFe treatments can significantly increase total zinc content and accumulation in various cotton organs; and spraying CFFe,CFZnB and CF can significantly increase total iron content and accumulation in various cotton organs( except the total iron content in the stem part of the CF treatment).( 3)Spraying CFFe,CFZnB,CF,KCD and BDM greatly reduced the disease index at flowering and boll-forming and boll opening stages.( 4) The CFZnB and CFFe treatments had the highest soil urease activity,which was 7. 14% higher than that of the CK,but the difference from the CK was not significant; the catalase activity of each treatment was significantly higher than that of the BDM treatment; and the sucrase activity of each treatment was significantly higher than that of the CK.( 5) Spraying CFFe,CFZnB,CF and KCD significantly improved lint yield of cotton,and the CFZnB treatment showed the highest yield increase up to 12. 34%,followed by the CFFe treatment,with an increase in the range of 8. 77%-10. 20%. [Conclusions]Copper-based nutrient foliar fertilizers have dual functions of disease control and prevention and plant nutrition and health care,and not only can significantly increase cotton yield,but also has certain disease prevention effect.It is recommended to use copper-based nutrient foliar fertilizers.

Deep learning-based inpainting of saturation artifacts in optical coherence tomography images

Limited by the dynamic range of the detector,saturation artifacts usually occur in optical coherence tomography(OCT)imaging for high scattering media.The available methods are difficult to remove saturation artifacts and restore texture completely in OCT images.We proposed a deep learning-based inpainting method of saturation artifacts in this paper.The generation mechanism of saturation artifacts was analyzed,and experimental and simulated datasets were built based on the mechanism.Enhanced super-resolution generative adversarial networks were trained by the clear–saturated phantom image pairs.The perfect reconstructed results of experimental zebrafish and thyroid OCT images proved its feasibility,strong generalization,and robustness.

Tarnish Testing of Copper-Based Alloys Coated with SiO_2-Like Films by PECVD

The tarnishing test in the presence of hydrogen sulfide（H2S） vapors has been used to investigate the tarnish resistance capability of copper-based alloys coated with Si02-like films by means of plasma-enhanced chemical vapor deposition（PECVD） fed with a tetraethoxysilane/oxygen mixture.The chemical and morphological properties of the films have been characterized by using infrared absorption spectroscopy（IR） and scanning electron microscopy（SEM）with energy disperse spectroscopy（EDS）.The corrosion products of the samples after the tarnishing test have been identified by X-ray diffraction analysis（XRD）.It has been found that SiO2-like films formed via PECVD with a high O2 flow rate could protect copper-based alloys from H2S vapor tarnishing.The alloys coated at the O2 flow rate of 20 sccm remain uncorroded after 54days of H2S vapor tarnish testing.The corrosion products for the alloys deposited at a low O2flow rate after 54 days of tarnish testing are mainly composed of brochantite.

Dynamic Kinetics of Methanol Synthesis over a Commercial Copper-Based Catalyst

Adsorption, surface reaction and process dynamics on the surface of a commercial copper-based catalyst for methanol synthesis from CO/CO2/H2 were systematically studied by means of temperature programmed desorption (TPD), temperature programmed surface reaction (TPSR), in-situ Fourier transform-inferred spec-troscopy(FTIR) and stimulus-response techniques. As a part of results, an elementary step sequence was suggested and a group of ordinary differential equations (ODEs) for describing transient conversations relevant to all species on the catalyst surface and in the gas phase in a micro-fixed-bed reactor was derived. The values of the parameters referred to dynamic kinetics were estimated by fitting the solution of the ODEs with the transient response data obtained by the stimulus-response technique with a FTIR analyzer as an on-line detector.

Common Artifacts and Remedies in Histological Preparations

The importance of the accuracy of preparing biological specimen as histological sections that can be examined under a microscope lies in reflecting a true image of the tissue that includes all its components, which are used in scientific research or for the purpose of diagnosing various diseases of the body. Despite this, some cellular structures within the tissue may suffer from some alterations that result from the appearance of defects during any stage of preparing these microscopic sections, which alter or interfere with the precise cellular structures and morphology that constitute the tissue and thus give a different image for tissue features and cause confusion in the work histopathologist in the diagnosis. There are several reasons that can cause a misdiagnosis of the sample that occurs during the surgical separation process or after separation during the stages of microscopic preparation techniques from fixation stage, tissue processing, embedding or microtomy, staining until mounting procedures. The constant need to identify these defects and their causes in addition to try to reduce them is one of the biggest challenges evident in pathology laboratories. Therefore, this study aims to review the most common defects that occur in any stage of tissue processing, with an explanation of their causes and appropriate ways to avoid them.

GPU-accelerated OCT imaging: Real-time data processing and artifact suppression for enhanced monitoring of 3D bioprinted tissues and vascular-like networks

Optical coherence tomography(OCT)imaging technology has significant advantages in in situ and noninvasive monitoring of biological tissues.However,it still faces the following challenges:including data processing speed,image quality,and improvements in three-dimensional(3D)visualization effects.OCT technology,especially functional imaging techniques like optical coherence tomography angiography(OCTA),requires a long acquisition time and a large data size.Despite the substantial increase in the acquisition speed of swept source optical coherence tomography(SS-OCT),it still poses significant challenges for data processing.Additionally,during in situ acquisition,image artifacts resulting from interface reflections or strong reflections from biological tissues and culturing containers present obstacles to data visualization and further analysis.Firstly,a customized frequency domainfilter with anti-banding suppression parameters was designed to suppress artifact noises.Then,this study proposed a graphics processing unit(GPU)-based real-time data processing pipeline for SS-OCT,achieving a measured line-process rate of 800 kHz for 3D fast and high-quality data visualization.Furthermore,a GPU-based realtime data processing for CC-OCTA was integrated to acquire dynamic information.Moreover,a vascular-like network chip was prepared using extrusion-based 3D printing and sacrificial materials,with sacrificial material being printed at the desired vascular network locations and then removed to form the vascular-like network.OCTA imaging technology was used to monitor the progression of sacrificial material removal and vascular-like network formation.Therefore,GPU-based OCT enables real-time processing and visualization with artifact suppression,making it particularly suitable for in situ noninvasive longitudinal monitoring of 3D bioprinting tissue and vascular-like networks in microfluidic chips.

AI-Driven Prioritization and Filtering of Windows Artifacts for Enhanced Digital Forensics

Digital forensics aims to uncover evidence of cybercrimes within compromised systems.These cybercrimes are often perpetrated through the deployment of malware,which inevitably leaves discernible traces within the compromised systems.Forensic analysts are tasked with extracting and subsequently analyzing data,termed as artifacts,from these systems to gather evidence.Therefore,forensic analysts must sift through extensive datasets to isolate pertinent evidence.However,manually identifying suspicious traces among numerous artifacts is time-consuming and labor-intensive.Previous studies addressed such inefficiencies by integrating artificial intelligence(AI)technologies into digital forensics.Despite the efforts in previous studies,artifacts were analyzed without considering the nature of the data within them and failed to prove their efficiency through specific evaluations.In this study,we propose a system to prioritize suspicious artifacts from compromised systems infected with malware to facilitate efficient digital forensics.Our system introduces a double-checking method that recognizes the nature of data within target artifacts and employs algorithms ideal for anomaly detection.The key ideas of this method are:(1)prioritize suspicious artifacts and filter remaining artifacts using autoencoder and(2)further prioritize suspicious artifacts and filter remaining artifacts using logarithmic entropy.Our evaluation demonstrates that our system can identify malicious artifacts with high accuracy and that its double-checking method is more efficient than alternative approaches.Our system can significantly reduce the time required for forensic analysis and serve as a reference for future studies.

Fetal MRI Artifacts: Semi-Supervised Generative Adversarial Neural Network for Motion Artifacts Reducing in Fetal Magnetic Resonance Images

This study addresses challenges in fetal magnetic resonance imaging (MRI) related to motion artifacts, maternal respiration, and hardware limitations. To enhance MRI quality, we employ deep learning techniques, specifically utilizing Cycle GAN. Synthetic pairs of images, simulating artifacts in fetal MRI, are generated to train the model. Our primary contribution is the use of Cycle GAN for fetal MRI restoration, augmented by artificially corrupted data. We compare three approaches (supervised Cycle GAN, Pix2Pix, and Mobile Unet) for artifact removal. Experimental results demonstrate that the proposed supervised Cycle GAN effectively removes artifacts while preserving image details, as validated through Structural Similarity Index Measure (SSIM) and normalized Mean Absolute Error (MAE). The method proves comparable to alternatives but avoids the generation of spurious regions, which is crucial for medical accuracy.

Energy consumption forecasting for laser manufacturing of large artifacts based on fusionable transfer learning

This study presents an energy consumption(EC)forecasting method for laser melting manufacturing of metal artifacts based on fusionable transfer learning(FTL).To predict the EC of manufacturing products,particularly from scale-down to scale-up,a general paradigm was first developed by categorizing the overall process into three main sub-steps.The operating electrical power was further formulated as a combinatorial function,based on which an operator learning network was adopted to fit the nonlinear relations between the fabricating arguments and EC.Parallel-arranged networks were constructed to investigate the impacts of fabrication variables and devices on power.Considering the interconnections among these factors,the outputs of the neural networks were blended and fused to jointly predict the electrical power.Most innovatively,large artifacts can be decomposed into timedependent laser-scanning trajectories,which can be further transformed into fusionable information via neural networks,inspired by large language model.Accordingly,transfer learning can deal with either scale-down or scale-up forecasting,namely,FTL with scalability within artifact structures.The effectiveness of the proposed FTL was verified through physical fabrication experiments via laser powder bed fusion.The relative error of the average and overall EC predictions based on FTL was maintained below 0.83%.The melting fusion quality was examined using metallographic diagrams.The proposed FTL framework can forecast the EC of scaled structures,which is particularly helpful in price estimation and quotation of large metal products towards carbon peaking and carbon neutrality.

基于注意力机制的高光谱图像降维在纸质文物霉斑识别的研究

纸质文物作为文物传承的重要工具,用于记录不同时期人类历史及人文风貌,其在保存过程中极易受到霉菌等微生物的侵害。霉菌会加速纤维素的降解,在纸张表面生成霉斑,并且散落的孢子会随空气流动大范围传播,增加其他纸质文物发生霉变的风险。因此,定期对纸质文物进行霉斑检测对了解纸质文物现状和纸质文物修复至关重要。高光谱成像技术是一种非接触性、非破坏性的检测技术,能同时获得空间数据和光谱数据,与计算机技术结合可以实现纸质文物的大批次实时无损检测。针对黑曲霉这一广泛出现的霉菌,提出一种基于注意力机制的高光谱数据降维方法,通过采集其高光谱数据,实现了高光谱冗余数据的自适应预处理。采集了来自重庆中国三峡博物馆提供的20份纸质文物黑曲霉霉斑样本,使用ENVI软件分析得出在413~855 nm波段范围内,黑曲霉霉斑感染区域和健康区域的平均光谱曲线,平均反射率差异明显;在855~1021 nm波段范围内,黑曲霉霉斑感染区域和墨迹区域的平均光谱曲线,平均反射率差异明显。文中将所提出方法与传统主成分分析和独立成分分析预处理方法分别处理原始高光谱数据,并将结果在经典U-Net、SegNet、DeepLabV3+和PSPNet四个语义分割网络上进行了对比。结果表明,该算法预处理的数据在U-Net和SegNet经典网络中有明显优势,相较于主成分分析法和独立成分分析法,霉斑识别精度取得了较大提升达到89.49%和88.46%,验证了本文所提出算法的有效性,为文物保护领域提供有效的支撑和新的思路。

诠释学视域下技术人工物结构—功能关系研究

自荷兰学者克劳斯提出技术人工物结构—功能关系的“逻辑鸿沟”问题以来,学者们试图从逻辑关系、认识论和本体论等视域来跨越鸿沟,但都未能建立起技术人工物结构—功能之间的因果性关系.根据海德格尔理解与存在同一的思想,人作为结构与功能相互指向的中间载体是不可或缺的,所以技术人工物结构—功能是一种诠释学的关系.诠释学的完整内涵要以阐释、应用和说明形成统一体.在诠释学内涵的基础上,揭示了技术人工物结构—功能之间的诠释过程,为跨越技术人工物结构—功能关系的“逻辑鸿沟”问题提出了新的视角.

考虑结构和展柜实际动力特性的浮放文物地震响应分析

目前评估文物地震安全性时,未充分考虑博物馆和展柜的实际动力特性对文物地震运动响应的影响。对某实际博物馆进行了现场环境振动测试,识别得到了符合现状的结构动力特性;对某实际独立展柜进行了现场锤击测试,识别得到了其自振频率。建立了结构实测动力特性修正前后的2种线性有限元模型、不考虑和考虑结构周期折减的2种非线性有限元模型,分析了不同地震波下4种模型中楼层相对于地面的加速度放大效应;建立了展柜的有限元模型,分析了不同楼层波下展柜相对于楼层的加速度放大效应;考虑文物与展柜台面间接触界面的非线性,建立了纯滑移、纯摇摆和滑移-摇摆耦合文物的有限元模型,并与理论运动方程所得响应进行了对比,分析了不同结构模型中位于不同楼层的展柜对浮放文物运动响应的影响。结果表明:相比另外3种模型,经实际动力特性修正后的线性结构模型中,展柜相对楼层的峰值加速度放大系数均值在小震和中震下均为最大,且大部分情况下该结构模型中文物的响应最大。

基于Artifact快照序列的行为一致性检测方法

Artifact行为的一致性检测,是在流程建模、运行之后亟待解决的关键问题之一.针对现有一致性检测技术忽略数据操作方面检测的问题,提出了一种基于Artifact快照序列的行为一致性检测方法.首先,利用全序Artifact快照序列定义了Artifact的行为模式,该行为模式不仅体现了服务的运行轨迹,也描述出了Artifact数据属性赋值的状态变化;然后,将Artifact行为一致性检测问题转换为语言可判定问题,证明了该问题是一个可判定问题,该过程中,设计一台判定该语言的图灵机作为一致性验证模型,该模型不仅检测了Artifact生命周期中服务路径的一致性,同时也检测了生命周期中Artifact属性赋值的正确性;进一步地,利用服务-快照关联矩阵的等价转换,给出了行为一致性量化指标中确切度的精确计算方法;最后,通过实例分析及实验对所提出的方法进行了验证.