Fast and Balanced Charge Transport Enabled by Solution-Processed Metal Oxide Layers for Efficient and Stable Inverted Perovskite Solar Cells

Metal oxide charge transport materials are preferable for realizing long-term stable and potentially low-cost perovskite solar cells(PSCs).However,due to some technical difficulties(e.g.,intricate fabrication protocols,high-temperature heating process,incompatible solvents,etc.),it is still challenging to achieve efficient and reliable all-metal-oxide-based devices.Here,we developed efficient inverted PSCs(IPSCs)based on solution-processed nickel oxide(NiO_(x))and tin oxide(SnO_(2))nanoparticles,working as hole and electron transport materials respectively,enabling a fast and balanced charge transfer for photogenerated charge carriers.Through further understanding and optimizing the perovskite/metal oxide interfaces,we have realized an outstanding power conversion efficiency(PCE)of 23.5%(the bandgap of the perovskite is 1.62 eV),which is the highest efficiency among IPSCs based on all-metal-oxide charge transport materials.Thanks to these stable metal oxides and improved interface properties,ambient stability(retaining 95%of initial PCE after 1 month),thermal stability(retaining 80%of initial PCE after 2 weeks)and light stability(retaining 90%of initial PCE after 1000 hours aging)of resultant devices are enhanced significantly.In addition,owing to the low-temperature fabrication procedures of the entire device,we have obtained a PCE of over 21%for flexible IPSCs with enhanced operational stability.

Low rank optimization for efficient deep learning:making a balance between compact architecture and fast training

Deep neural networks(DNNs)have achieved great success in many data processing applications.However,high computational complexity and storage cost make deep learning difficult to be used on resource-constrained devices,and it is not environmental-friendly with much power cost.In this paper,we focus on low-rank optimization for efficient deep learning techniques.In the space domain,DNNs are compressed by low rank approximation of the network parameters,which directly reduces the storage requirement with a smaller number of network parameters.In the time domain,the network parameters can be trained in a few subspaces,which enables efficient training for fast convergence.The model compression in the spatial domain is summarized into three categories as pre-train,pre-set,and compression-aware methods,respectively.With a series of integrable techniques discussed,such as sparse pruning,quantization,and entropy coding,we can ensemble them in an integration framework with lower computational complexity and storage.In addition to summary of recent technical advances,we have two findings for motivating future works.One is that the effective rank,derived from the Shannon entropy of the normalized singular values,outperforms other conventional sparse measures such as the?_1 norm for network compression.The other is a spatial and temporal balance for tensorized neural networks.For accelerating the training of tensorized neural networks,it is crucial to leverage redundancy for both model compression and subspace training.

Fast,simple,efficient Agrobacterium rhizogenes-mediated transformation system to non-heading Chinese cabbage with transgenic roots

Non-heading Chinese cabbage, a variety of Brassica campestris, is an important vegetable crop in the Yangtze River Basin of China. However,the immaturity of its stable transformation system and its low transformation efficiency limit gene function research on non-heading Chinese cabbage. Agrobacterium rhizogenes-mediated(ARM) transgenic technology is a rapid and effective transformation method that has not yet been established for non-heading Chinese cabbage plants. Here, we optimized conventional ARM approaches(one-step and two-step transformation methods) suitable for living non-heading Chinese cabbage plants in nonsterile environments. Transgenic roots in composite non-heading Chinese cabbage plants were identified using phenotypic detection, fluorescence observation, and PCR analysis. The transformation efficiency of a two-step method on four five-day-old non-heading Chinese cabbage seedlings(Suzhouqing, Huangmeigui, Wuyueman, and Sijiu Caixin) was 43.33%-51.09%, whereas using the stout hypocotyl resulted in a transformation efficiency of 54.88% for the 30-day-old Sijiu Caixin.The one-step method outperformed the two-step method;the transformation efficiency of different varieties was above 60%, and both methods can be used to obtain transgenic roots for functional studies within one month. Finally, optimized ARM transformation methods can easily,quickly, and effectively produce composite non-heading Chinese cabbage plants with transgenic roots, providing a reliable foundation for gene function research and non-heading Chinese cabbage genetic improvement breeding.

Efficient analysis of dielectric radomes using multilevel fast multipole algorithm with CRWG basis

A full-wave analysis of the electromagnetic problem of a three-dimensional （3-D） antenna radiating through a 3-D dielectric radome is preserued. The problem is formulated using the Poggio-Miller-Chang-Harrington- Wu（PMCHW） approach for homogeneous dielectric objects and the electric field integral equation for conducting objects. The integral equations are discretized by the method of moment （MoM）, in which the conducting and dielectric surface/interfaces are represented by curvilinear triangular patches and the unknown equivalent electric and magnetic currents are expanded using curvilinear RWG basis functions. The resultant matrix equation is then solved by the multilevel fast multipole algorithm （MLFMA） and fast far-field approximation （FAFFA） is used to further accelerate the computation. The radiation patterns of dipole arrays in the presence of radomes are presented. The numerical results demonstrate the accuracy and versatility of this method.

General and efficient parallel approach of finite element-boundary integral-multilevel fast multipole algorithm

A general and efficient parallel approach is proposed for the first time to parallelize the hybrid finiteelement-boundary-integral-multi-level fast multipole algorithm （FE-BI-MLFMA）. Among many algorithms of FE-BI-MLFMA, the decomposition algorithm （DA） is chosen as a basis for the parallelization of FE-BI-MLFMA because of its distinct numerical characteristics suitable for parallelization. On the basis of the DA, the parallelization of FE-BI-MLFMA is carried out by employing the parallelized multi-frontal method for the matrix from the finiteelement method and the parallelized MLFMA for the matrix from the boundary integral method respectively. The programming and numerical experiments of the proposed parallel approach are carried out in the high perfor- mance computing platform CEMS-Liuhui. Numerical experiments demonstrate that FE-BI-MLFMA is efficiently parallelized and its computational capacity is greatly improved without losing accuracy, efficiency, and generality.

Substrate participation ultrafast synthesis of amorphous NiFe nanosheets on iron foam at room temperature toward highly efficient oxygen evolution reaction

The earth-abundant transition metal based nanomaterials are regarded as state-of-the-art oxygen evolution reaction(OER) electrocatalyst. Recent studies have shown that amorphous materials are more active than their crystalline forms. Herein, we demonstrate a facile and rapid substrate participation method to fabricate amorphous NiFe nanosheets on iron foam(a-NiFe NS/IF) at ambient temperature as a highly efficient electrocatalyst for OER. This method only takes 200 s to fabricate the a-NiFe NS/IF and the electrocatalyst possesses excellent catalytic activities which only needs overpotentials of about 211 and 240 m V to reach 10 and 100 mA cm-2 current densities in 1.0 M KOH.

A fast approach to optimize dye loading of photoanode via ultrasonic technique for highly efficient dye-sensitized solar cells

A distinctive method is proposed by simply utilizing ultrasonic technique in Ti02 electrode fabrication in order to improve the optoelectronic performance of dye-sensitized solar cells （DSSCs）. Dye molecules are at random and single molecular state in the ultrasonic field and the ultrasonic wave favors the diffusion and adsorption processes of dye molecules. As a result, the introduction of ultrasonic technique at room temperature leads to faster and more well-distributed dye adsorption on TiO2 as well as higher cell efficiency than regular deposition, thus the fabrication time is markedly reduced. It is found that the device based on 40 kHz ultrasonic （within 1 h） with N719 exhibits a Voc of 789 mV, Jsc of 14.94 mA]cm2 and fill factor （FF） of 69.3, yielding power conversion efficiency （PCE） of 8.16%, which is higher than device regularly dyed for 12 h （PCE = 8.06%）. In addition, the DSSC devices obtain the best efficiency （PCE = 8.68%） when the ultrasonic deposition time increases to 2.5 h. The DSSCs fabricated via ultrasonic technique presents more dye loading, larger photocurrent, less charge recombination and higher photovoltage. The charge extraction and electron impedance spectroscopy （EIS） were performed to understand the influence of ultrasonic technique on the electron recombination and performance of DSSCs.

Efficient Fast Independent Component Analysis Algorithm with Fifth-Order Convergence

Independent component analysis （ICA） is the primary statistical method for solving the problems of blind source separation. The fast ICA is a famous and excellent algorithm and its contrast function is optimized by the quadratic convergence of Newton iteration method. In order to improve the convergence speed and the separation precision of the fast ICA, an improved fast ICA algorithm is presented. The algorithm introduces an efficient Newton＇s iterative method with fifth-order convergence for optimizing the contrast function and gives the detail derivation process and the corresponding condition. The experimental results demonstrate that the convergence speed and the separation precision of the improved algorithm are better than that of the fast ICA.

THE RADIAL DISTRIBUTION OF HEAT TRANSFER COEFFICIENT IN FAST FLUIDIZED BED

This paper presents an experimental study on the axial and radial distributions of heat transfer coefficients in a fastfluidized bed operated at ambient temperature.The following formula is recommended to correlate the local heat transfer coefficients in fast fluidized beds:where a,n1 and n2 are functions of radial positions.

Efficient Fast Multiplication Free Integer Transformation for the 1-D DCT of the H.265 Standard

In this paper, efficient one-dimensional (1-D) fast integer transform algorithms of the DCT matrix for the H.265 stan-dard is proposed. Based on the symmetric property of the integer transform matrix and the matrix operations, which denote the row/column permutations and the matrix decompositions, along with using the dyadic symmetry modification on the standard matrix, the efficient fast 1-D integer transform algorithms are developed. Therefore, the computational complexities of the proposed fast integer transform are smaller than those of the direct method. In addition to computational complexity reduction one of the proposed algorithms provides transformation quality improvement, while the other provides more computational complexity reduction while maintaining almost the same transformation quality. With lower complexity and better transformation quality, the first proposed fast algorithm is suitable to accelerate the quality-demanding video coding computations. On the other hand, with the significant lower complexity, the second proposed fast algorithm is suitable to accelerate the video coding computations.

基于灰度均值的自适应FAST角点检测优化算法

光照不均、突变引起的灰度变化会影响图像特征检测效果。为此,设计一种基于灰度均值的自适应FAST-9-12角点检测算法。首先,利用特征点的延展性设计一种小面积双重检测模板,减少像素点与中心点的比较次数,提高区域正检率和检测速度;其次,依据图像局部灰度均值,在每个像素点检测模板内自适应调整阈值,避免灰度变化影响检测效果;最后,根据柔性非极大值抑制的思想设计角点半径抑制原则,筛选鲁棒性更强的角点。在Inria遥感影像数据集上的实验结果表明,FAST-9-12角点检测速度比FAST-12-16,FAST-9-16两种模板提高22%左右,因自适应阈值的提取方式不易受光照影响,检测准确率分别提高4.16和3.11个百分点,实现了图像特征快速和精准检测。

ORPA:a fast and efficient phylogenetic analysis method for constructing genome-wide alignments of organelle genomes

Creating a multi-gene alignment matrix for phylogenetic analysis using organelle genomes involves aligning single-gene datasets manually,a process that can be time-consuming and prone to errors.The HomBlocks pipeline has been created to eliminate the inaccuracies arising from manual operations.The processing of a large number of sequences,however,remains a time-consuming task.To conquer this challenge,we develop a speedy and efficient method called Organelle Genomes for Phylogenetic Analysis(ORPA).ORPA can quickly generate multiple sequence alignments for whole-genome comparisons by parsing the result files of NCBI BLAST,completing the task just in 1 min.With increasing data volume,the efficiency of ORPA is even more pronounced,over 300 times faster than HomBlocks in aligning 60 high-plant chloroplast genomes.The phylogenetic tree outputs from ORPA are equivalent to HomBlocks,indicating its outstanding efficiency.Due to its speed and accuracy,ORPA can identify species-level evolutionary conflicts,providing valuable insights into evolutionary cognition.

Intermittent fasting and the liver: Focus on the Ramadan model

Intermittent fasting(IF)is an intervention that involves not only dietary modific-ations but also behavioral changes with the main core being a period of fasting alternating with a period of controlled feeding.The duration of fasting differs from one regimen to another.Ramadan fasting(RF)is a religious fasting for Muslims,it lasts for only one month every one lunar year.In this model of fasting,observers abstain from food and water for a period that extends from dawn to sunset.The period of daily fasting is variable(12-18 hours)as Ramadan rotates in all seasons of the year.Consequently,longer duration of daily fasting is observed during the summer.In fact,RF is a peculiar type of IF.It is a dry IF as no water is allowed during the fasting hours,also there are no calorie restrictions during feeding hours,and the mealtime is exclusively nighttime.These three variables of the RF model are believed to have a variable impact on different liver diseases.RF was evaluated by different observational and interventional studies among patients with non-alcoholic fatty liver disease and it was associated with improve-ments in anthropometric measures,metabolic profile,and liver biochemistry regardless of the calorie restriction among lean and obese patients.The situation is rather different for patients with liver cirrhosis.RF was associated with adverse events among patients with liver cirrhosis irrespective of the underlying etiology of cirrhosis.Cirrhotic patients developed new ascites,ascites were increased,had higher serum bilirubin levels after Ramadan,and frequently developed hepatic encephalopathy and acute upper gastrointestinal bleeding.These complications were higher among patients with Child class B and C cirrhosis,and some fatalities occurred due to fasting.Liver transplant recipients as a special group of patients,are vulnerable to dehydration,fluctuation in blood immunosuppressive levels,likelihood of deterioration and hence observing RF without special precautions could represent a real danger for them.Patients with Gilbert syndrome can safely observe RF despite the minor elevations in serum bilirubin reported during the early days of fasting.

面向FAST的卫星电磁干扰监测技术研究与实现

来自人造卫星的信号是射电天文观测面临的主要射频干扰(radio frequency interference,RFI)之一,这些RFI会将天文信号掩埋,为天文信号的搜寻和分析带来困扰。为了缓减卫星对天文观测的影响,我们在之前的工作中为500 m口径球面射电望远镜(Five-hundred-meter Aperture Spherical radio Telescope,FAST)开发了卫星电磁干扰监测软件,主要包括卫星数据库、观测模块和监测模块。近年来随着多个巨型卫星星座的规划发射以及望远镜观测模式的增多,卫星对射电天文观测的影响更为复杂,已有的软件已经不能满足实际的需要。为此,本文在单个卫星干扰分析的基础上提出了卫星星座的干扰评估方法,并对已有监测软件进行了升级,升级后卫星数据库覆盖更多的在轨卫星及星座信息且能够自动化更新,观测模块能够支持更多种观测模式下的卫星过境预测和干扰评估。在实际天文观测中,通过接在FAST接收机上的频谱仪数据对软件的干扰预测结果进行了实验验证,结果证明升级后的软件能够在多种观测模式下预测可能威胁的卫星以及对应的过境时间,为望远镜观测规划的调整、卫星干扰的规避和接收系统的保护提供重要的支撑。

500m口径射电望远镜(FAST)索网结构风致破坏概率评估

大跨空间索网结构风敏感性突出,极易遭受风荷载影响。针对目前缺乏此类结构抗风性能评估方法的问题,以大跨空间索网结构FAST为例,提出一种基于实测风场数据的风致破坏概率分析方法。采集1971年~2020年结构所处地区的大量实测风速数据,通过概率分布拟合建立场地的风灾危险性模型。建立FAST的精细化有限元分析模型并模拟风荷载时程输入,采用非线性动力时程分析对结构的风振反应进行计算,基于概率性需求模型绘制易损性曲线。最后,结合得出的风灾危险性和结构易损性,计算得出FAST结构在所处场地实际风灾环境中的破坏概率。研究表明:该地极限风速为17m/s,风速在0~10m/s的概率最大;在120°、210°和300°风向角下,下拉索均为易损构件,210°风向角上吸风对索网结构最不利;在最不利风向角下,结构达到轻微破坏、中等破坏和严重破坏的总破坏概率分别为1.8359×10^(-4)、1.1499×10^(-5)和1.3202×10^(-6)。

基于BP神经网络的FAST馈源舱融合测量预测研究

500 m口径球面射电望远镜(Five-hundred-meter Aperture Spherical Radio Telescope,FAST)的跟踪观测需要馈源的空间运动配合,馈源舱主要用于实现馈源的精调定位,因此馈源舱位置的高精度测量对FAST望远镜的高效运行意义重大。但当全站仪设备失效时,无法对采用Kalman算法的GPS/IMU融合测量结果进行修正,导致馈源舱测量精度下降。为了解决这个问题,设计了基于BP(back propagation)神经网络的预测模型,包括数据预处理、模型设计和模型训练验证。模型训练数据为FAST真实测量数据,数据量为40 GB左右。为了验证模型的泛化能力,选取三种运动轨迹数据对模型预测精度进行测试,结果显示,三种运动轨迹下精度都满足15 mm要求。

基于Kano-FAST-FBS的智能扫地机改良设计研究

目的智能扫地机是智能家居生活中不可或缺的产品,但现有扫地机交互性和功能性趋于一致,为了有效识别居家清扫需求,进一步提升交互性和趣味性,并将其科学转化为产品的功能要素及结构参数,提出一种基于Kano-FAST-FBS模型的产品改良设计方法,以提升智能家居产品的满意度。方法首先,基于Kano模型量化评估智能家居产品的用户需求属性,获得用户需求优先级;其次,运用功能分析系统技术(FAST)将用户需求分别转化为对应的产品功能要素;最后,以功能-行为-结构(FBS)设计模型为基础,实现了产品功能到结构参数的合理映射,进而得到改良产品的各个结构模块,输出最终设计方案。结果以扫地机器人为例,验证了基于Kano-FAST-FBS模型的设计流程。结论在该方法指导下的产品设计能系统地解决用户需求和功能结构模块之间的匹配问题,从而得出更符合用户功能预期的设计方案,并可以为其他类似产品设计提供参考思路。

FAST所受PMT基站电磁干扰及用频防护方法综述

为确定500 m口径球面射电望远镜(Five-hundred-meter Aperture Spherical radio Telescope,FAST)与其周边公众移动通信(Public Mobile Telecommunications,PMT)系统的电磁兼容(electromagnetic compatibility,EMC)特性,本文综合论述了FAST宁静区内中国移动、中国联通和中国电信三大运营商所属PMT基站对其产生的电磁干扰。首先,从射电天文业务的频谱划分谈起,论述了射电天文业务干扰源类型,引出了其运行保护标准,进而针对FAST详细说明了FAST宁静区的用频法规和保护要求;其次,分析了ITU-R建议电波传播预测与干扰分析方法,并通过实地测量验证了该方法的适用性,进一步针对性地分析了PMT基站的电磁辐射传播特性,综合评估了FAST宁静区内PMT基站的干扰情况:FAST宁静区域90.24%的PMT基站在一定程度上均会对FAST产生干扰,而在所选分析条件下,仅有43.14%的数据符合FAST保护要求;最后,针对PMT基站干扰信号的抑制和消除,分析了常用的射电天文射频干扰抑制方法,同时为保障FAST免受PMT基站干扰,从FAST和PMT基站的角度出发论述了可行的用频防护措施,并基于实施难度、经济成本、策略收益和通信质量4类指标建立了防护方法的评估体系,对所提防护方法进行了实例说明。上述研究成果可为保障FAST的安全观测提供技术基础。

Unraveling the Fundamental Mechanism of Interface Conductive Network Influence on the Fast‑Charging Performance of SiO‑Based Anode for Lithium‑Ion Batteries

Progress in the fast charging of high-capacity silicon monoxide(SiO)-based anode is currently hindered by insufficient conductivity and notable volume expansion.The construction of an interface conductive network effectively addresses the aforementioned problems;however,the impact of its quality on lithium-ion transfer and structure durability is yet to be explored.Herein,the influence of an interface conductive network on ionic transport and mechanical stability under fast charging is explored for the first time.2D modeling simulation and Cryo-transmission electron microscopy precisely reveal the mitigation of interface polarization owing to a higher fraction of conductive inorganic species formation in bilayer solid electrolyte interphase is mainly responsible for a linear decrease in ionic diffusion energy barrier.Furthermore,atomic force microscopy and Raman shift exhibit substantial stress dissipation generated by a complete conductive network,which is critical to the linear reduction of electrode residual stress.This study provides insights into the rational design of optimized interface SiO-based anodes with reinforced fast-charging performance.

Dual-single-atoms of Pt-Co boost sulfur redox kinetics for ultrafast Li-S batteries

Applications of lithium-sulfur(Li-S)batteries are still limited by the sluggish conversion kinetics from polysulfide to Li_(2)S.Although various single-atom catalysts are available for improving the conversion kinetics,the sulfur redox kinetics for Li-S batteries is still not ultrafast.Herein,in this work,a catalyst with dual-single-atom Pt-Co embedded in N-doped carbon nanotubes(Pt&Co@NCNT)was proposed by the atomic layer deposition method to suppress the shuttle effect and synergistically improve the interconversion kinetics from polysulfides to Li_(2)S.The X-ray absorption near edge curves indicated the reversible conversion of Li_(2)Sx on the S/Pt&Co@NCNT electrode.Meanwhile,density functional theory demonstrated that the Pt&Co@NCNT promoted the free energy of the phase transition of sulfur species and reduced the oxidative decomposition energy of Li_(2)S.As a result,the batteries assembled with S/Pt&Co@NCNT electrodes exhibited a high capacity retention of 80%at 100 cycles at a current density of 1.3 mA cm^(−2)(S loading:2.5 mg cm^(−2)).More importantly,an excellent rate performance was achieved with a high capacity of 822.1 mAh g^(−1) at a high current density of 12.7 mA cm^(−2).This work opens a new direction to boost the sulfur redox kinetics for ultrafast Li-S batteries.