Progress on Transition Metal Ions Dissolution Suppression Strategies in Prussian Blue Analogs for Aqueous Sodium-/Potassium-Ion Batteries

Aqueous sodium-ion batteries(ASIBs)and aqueous potassium-ion batteries(APIBs)present significant potential for large-scale energy storage due to their cost-effectiveness,safety,and environmental compatibility.Nonetheless,the intricate energy storage mechanisms in aqueous electrolytes place stringent require-ments on the host materials.Prussian blue analogs(PBAs),with their open three-dimensional framework and facile synthesis,stand out as leading candidates for aqueous energy storage.However,PBAs possess a swift capacity fade and limited cycle longevity,for their structural integrity is compromised by the pronounced dis-solution of transition metal(TM)ions in the aqueous milieu.This manuscript provides an exhaustive review of the recent advancements concerning PBAs in ASIBs and APIBs.The dissolution mechanisms of TM ions in PBAs,informed by their structural attributes and redox processes,are thoroughly examined.Moreover,this study delves into innovative design tactics to alleviate the dissolution issue of TM ions.In conclusion,the paper consolidates various strategies for suppressing the dissolution of TM ions in PBAs and posits avenues for prospective exploration of high-safety aqueous sodium-/potassium-ion batteries.

Oilfield analogy and productivity prediction based on machine learning: Field cases in PL oilfield, China

In the early time of oilfield development, insufficient production data and unclear understanding of oil production presented a challenge to reservoir engineers in devising effective development plans. To address this challenge, this study proposes a method using data mining technology to search for similar oil fields and predict well productivity. A query system of 135 analogy parameters is established based on geological and reservoir engineering research, and the weight values of these parameters are calculated using a data algorithm to establish an analogy system. The fuzzy matter-element algorithm is then used to calculate the similarity between oil fields, with fields having similarity greater than 70% identified as similar oil fields. Using similar oil fields as sample data, 8 important factors affecting well productivity are identified using the Pearson coefficient and mean decrease impurity(MDI) method. To establish productivity prediction models, linear regression(LR), random forest regression(RF), support vector regression(SVR), backpropagation(BP), extreme gradient boosting(XGBoost), and light gradient boosting machine(Light GBM) algorithms are used. Their performance is evaluated using the coefficient of determination(R^(2)), explained variance score(EV), mean squared error(MSE), and mean absolute error(MAE) metrics. The Light GBM model is selected to predict the productivity of 30 wells in the PL field with an average error of only 6.31%, which significantly improves the accuracy of the productivity prediction and meets the application requirements in the field. Finally, a software platform integrating data query,oil field analogy, productivity prediction, and knowledge base is established to identify patterns in massive reservoir development data and provide valuable technical references for new reservoir development.

The Analogy between the Immune System and Human Life

The immune system operates as a complex organization with distinct roles and functions. Excitingly we recognized the similarities between the cellular dynamics of the immune system and our lives, activities, and behaviors. Observing the immune system can guide how to respond to various daily situations, including when to react, tolerate, or ignore. Recognizing this analogy between our lives and the immune system should motivate us to adopt a wisdom-based approach when investigating the mechanisms and future discoveries related to this system and to deepen our understanding of this complex system with newfound respect. In this context, the present review examines several integral biological processes of the immune system by drawing parallels between them and human life, activities, and behaviors to learn how we must behave based on the insights offered by this complex organization. The literature search was conducted in international databases such as PubMed/MEDLINE and Google Scholar search engine using English equivalent keywords from 1998 up to April 2023. The search strategy used the following subject heading terms: Immune system, analogy, human life, cellular dynamics, memory, tolerance, and ignorance. In conclusion, the immune system is a complex organization comprising various cells interacting within specific sites and networks, communicating, drawing experiences, and learning how to tolerate certain conditions that make it share certain similarities with human life.

Discovery of a geomorphological analog to Martian araneiforms in the Qaidam Basin, Tibetan Plateau

Araneiforms are spider-like ground patterns that are widespread in the southern polar regions of Mars.A gas erosion process driven by the seasonal sublimation of CO_(2) ice was proposed as an explanation for their formation,which cannot occur on Earth due to the high climatic temperature.In this study,we propose an alternative mechanism that attrib-utes the araneiform formation to the erosion of upwelling salt water from the subsurface,relying on the identification of the first terrestrial analog found in a playa of the Qaidam Basin on the northern Tibetan Plateau.Morphological analysis indicates that the structures in the Qaidam Basin have fractal features comparable to araneiforms on Mars.A numerical model is developed to investigate the araneiform formation driven by the water-diffusion mechanism.The simulation res-ults indicate that the water-diffusion process,under varying ground conditions,may be responsible for the diverse aranei-form morphologies observed on both Earth and Mars.Our numerical simulations also demonstrate that the orientations of the saltwater diffusion networks are controlled by pre-existing polygonal cracks,which is consistent with observations of araneiforms on Mars and Earth.Our study thus suggests that a saltwater-related origin of the araneiform is possible and has significant implications for water searches on Mars.

An analogical study of wave equations,physical quantities,conservation and reciprocity equations between electromagnetic and elastic waves

This paper presents an analogical study between electromagnetic and elastic wave fields,with a one-to-one correspondence principle established regarding the basic wave equations,the physical quantities and the differential operations.Using the electromagnetic-to-elastic substitution,the analogous relations of the conservation laws of energy and momentum are investigated between these two physical fields.Moreover,the energy-based and momentum-based reciprocity theorems for an elastic wave are also derived in the time-harmonic state,which describe the interaction between two elastic wave systems from the perspectives of energy and momentum,respectively.The theoretical results obtained in this analysis can not only improve our understanding of the similarities of these two linear systems,but also find potential applications in relevant fields such as medical imaging,non-destructive evaluation,acoustic microscopy,seismology and exploratory geophysics.

Experimental and computational optimization of Prussian blue analogues as high-performance cathodes for sodium-ion batteries:A review

In this review,we discuss the electrochemical properties of Prussian blue(PB)for Na^(+)storage by combining structural engineering and electrolyte modifications.We integrated experimental data and density functional theory(DFT)in sodium-ion battery(SIB)research to refine the atomic arrangements and crystal lattices and introduce substitutions and dopants.These changes affect the lattice stability,intercalation,electronic and ionic conductivities,and electrochemical performance.We unraveled the intricate structure-electrochemical behavior relationship by combining experimental data with computational models,including first-principles calculations.This holistic approach identified techniques for optimizing PB and Prussian blue analog(PBA)structu ral properties for SIBs.We also discuss the tuning of electrolytes by systematically adjusting their composition,concentration,and additives using a combination of molecular dynamics(MD)simulations and DFT computations.Our review offers a comprehensive assessment of strategies for enhancing the electrochemical properties of PB and PBAs through structural engineering and electrolyte modifications,combining experimental insights with advanced computational simulations,and paving the way for next-generation energy storage systems.

Investigation on Analog and Digital Modulations Recognition Using Machine Learning Algorithms

In the field of radiocommunication, modulation type identification is one of the most important characteristics in signal processing. This study aims to implement a modulation recognition system on two approaches to machine learning techniques, the K-Nearest Neighbors (KNN) and Artificial Neural Networks (ANN). From a statistical and spectral analysis of signals, nine key differentiation features are extracted and used as input vectors for each trained model. The feature extraction is performed by using the Hilbert transform, the forward and inverse Fourier transforms. The experiments with the AMC Master dataset classify ten (10) types of analog and digital modulations. AM_DSB_FC, AM_DSB_SC, AM_USB, AM_LSB, FM, MPSK, 2PSK, MASK, 2ASK, MQAM are put forward in this article. For the simulation of the chosen model, signals are polluted by the Additive White Gaussian Noise (AWGN). The simulation results show that the best identification rate is the MLP neuronal method with 90.5% of accuracy after 10 dB signal-to-noise ratio value, with a shift of more than 15% from the k-nearest neighbors’ algorithm.

An Adaptive Control Strategy for Energy Storage Interface Converter Based on Analogous Virtual Synchronous Generator

In the DC microgrid,the lack of inertia and damping in power electronic converters results in poor stability of DC bus voltage and low inertia of the DC microgrid during fluctuations in load and photovoltaic power.To address this issue,the application of a virtual synchronous generator(VSG)in grid-connected inverters control is referenced and proposes a control strategy called the analogous virtual synchronous generator(AVSG)control strategy for the interface DC/DC converter of the battery in the microgrid.Besides,a flexible parameter adaptive control method is introduced to further enhance the inertial behavior of the AVSG control.Firstly,a theoretical analysis is conducted on the various components of the DC microgrid,the structure of analogous virtual synchronous generator,and the control structure’s main parameters related to the DC microgrid’s inertial behavior.Secondly,the voltage change rate tracking coefficient is introduced to adjust the change of the virtual capacitance and damping coefficient flexibility,which further strengthens the inertia trend of the DC microgrid.Additionally,a small-signal modeling approach is used to analyze the approximate range of the AVSG’s main parameters ensuring system stability.Finally,conduct a simulation analysis by building the model of the DC microgrid system with photovoltaic(PV)and battery energy storage(BES)in MATLAB/Simulink.Simulation results from different scenarios have verified that the AVSG control introduces fixed inertia and damping into the droop control of the battery,resulting in a certain level of inertia enhancement.Furthermore,the additional adaptive control strategy built upon the AVSG control provides better and flexible inertial support for the DC microgrid,further enhances the stability of the DC bus voltage,and has a more positive impact on the battery performance.

Design of a 14-Bit 1 MS/s Successive Approximation Analog-to-Digital Converter

A 14-bit successive approximation analog-to-digital converter (SAR ADC) with capacitive calibration has been designed based on the SMIC. 18 μm CMOS process. The overall architecture is in fully differential form to eliminate the effect caused by common mode noise. Meanwhile, the digital-to-analog converter (DAC) is a two-stage structure, which can greatly reduce the area of the capacitor array compared with the traditional DAC structure. The capacitance calibration module is mainly divided into the mismatch voltage acquisition phase and the calibration code backfill phase, which effectively reduces the impact of the DAC mismatch on the accuracy of the SAR ADC. The design of this paper is based on cadence platform simulation verification, simulation results show that when the sampling rate is 1 MS/s, the power supply voltage is 5 V and the reference voltage is 4.096 V, the effective number of bits (ENOB) of the ADC is 13.49 bit, and the signal-to-noise ratio (SNR) is 83.3 dB.

一种前后台结合的Pipelined ADC校准技术

针对Pipelined模数转换器(ADC)中采样电容失配和运放增益误差带来的非线性问题,提出了一种前后台结合的Pipelined ADC校准技术。前台校准技术通过对ADC量化结果的余量分析,补偿相应流水级的量化结果,后台校准技术基于伪随机(PN)注入的方式,利用PN的统计特性校准增益误差。本校准技术在系统级建模和RTL级电路设计的基础上,实现了现场可编程门阵列(FPGA)验证并成功流片。测试结果显示,在1 GS/s采样速率下,校准精度为14 bit的Pipelined ADC的有效位数从9.30 bit提高到9.99 bit,信噪比提高约4 dB,无杂散动态范围提高9.5 dB,积分非线性(INL)降低约10 LSB。

新型局部浸润麻醉应用于人工全膝关节置换的早期效果评估

背景:全膝关节置换后患者会经历明显的疼痛,这对功能恢复存在负面影响,探索并寻求有效的镇痛手段具有重要的临床价值。目的:为探求全膝关节置换患者有效的围术期镇痛策略,首次提出了一种由吗啡、氟比洛芬酯和复方倍他米松配置而成的新型局部浸润麻醉制剂,同时探讨该方案的有效性及安全性。方法:对2023年11月至2024年4月在安徽医科大学第一附属医院关节外科接受初次单侧全膝关节置换60例患者的临床资料进行回顾性分析,根据置换过程中是否使用局部浸润麻醉将患者分为对照组与研究组,每组30例。研究组在全膝关节置换过程中关节腔周围注射吗啡、氟比洛芬酯及复方倍他米松配置而成的局部浸润麻醉制剂,而对照组术中未使用任何镇痛药物作为空白对照。记录并比较两组患者在术后不同时间节点的疼痛目测类比评分、膝关节活动度、膝关节学会评分、术后膝关节肿胀程度及术后并发症的发生情况。结果与结论:①与对照组相比,研究组患者置换后6,12及24 h的疼痛目测类比评分更低,差异有显著性意义(Z=-2.367,-2.906,-4.199,P<0.05);但在术后48,72 h,两组患者的疼痛目测类比评分并无显著性差异(Z=-1.287,-1.478,P>0.05);②置换后第3天,研究组患者的膝关节活动度和膝关节学会评分均优于对照组,差异有显著性意义(t=-2.519,-8.027,P<0.05);③研究组患者术后的膝关节肿胀程度轻于对照组,差异有显著性意义(Z=-2.818,P<0.05);④在术后早期,两组患者的发热发生率相比无显著性差异(P>0.05),两组均未发生切口愈合不良及假体周围感染;⑤结果表明:在全膝关节置换过程中应用由吗啡、氟比洛芬酯及复方倍他米松组成的局部浸润麻醉制剂,可以明显减轻患者术后早期疼痛,并显示出较高的安全性,但仍需大样本的前瞻性研究提供数据支持。

无轴泵喷推进器内流致噪声仿真计算

基于Lighthill声比拟理论,采用混合数值模拟方法分析了流量变化对无轴泵喷推进器内流致噪声的声压级频域特性和总声压级等的影响及其与内流场的关系.研究结果表明:声压级主频均为轴频,并可见2倍轴频的谐频.小流量和设计流量下,主频处声压级幅值沿流向先下降后上升再下降,沿径向先上升后下降,并存在叶频及其倍频的谐频;大流量下,其沿流向下降,沿径向先下降后上升,未见叶频或其倍频的谐频分布.出口段靠近叶轮区域的主频处声压级幅值随流量增加上升,而远离该区域则先上升后下降;轴线附近区域的噪声逐渐增强.总声压级随流量增加而上升;流向上,总声压级逐渐降低,且在大流量下噪声衰减速度更为缓慢;径向上,总声压级最高值随着径向区域所在的流向距离增加而逐渐靠近轴线.影响不同流量下无轴泵喷推进器噪声分布的主要因素是出口段靠近叶轮区域的速度梯度和2个旋涡的大小和位置.

基于Monte-Carlo方法的土石围堰挡水导流风险分析

运用Monte -Carlo方法模拟施工洪水入库过程和导流建筑物泄流的随机性 ,通过仿真分析确定上游围堰堰前水位变化过程及其分布函数。在此基础上 ,根据导流建筑物的设计规模确定导流系统的风险。通过实例验证分析说明 ,研究方法和计算模型是可靠的、适用的。

基于Neumann展开Monte-Carlo有限元法的随机温度场分析

利用Neumann展开Monte-Carlo随机有限元法,对导热系数、换热系数、热流密度、环境温度以及内热源等物理参数同时具有随机性的温度场问题进行了分析,给出了节点温度响应的均值、变异系数和节点温度落在某一区间内的概率计算公式.通过算例考察了各随机变量的变异性大小对节点温度响应的影响,并表明随着结构的自由度数目增大,文中方法呈现出计算效率高的优点.

Monte-Carlo随机有限元结构可靠度分析新方法

基于条件抽样、对偶抽样及Neumann展开技术,同时,为试图一定程度地解决"计算模型的不确定性"问题,考虑到岩石、混凝土等材料的单轴抗压强度σc和双轴等压强度σcc不同的特性,将3参数统一强度理论引入随机有限元程序,建立了Monte-Carlo三维非线性随机有限元结构可靠性分析模型。模拟成果表明,采用该模型的模拟收敛性良好,模拟效率较高、成本较低,可靠指标β值精度满足实用要求,在大型复杂结构的设计及可靠度分析研究中具有实用价值。

轮盘疲劳可靠性分析的Monte-Carlo数字仿真

低循环多轴疲劳失效是航空发动机低压压气机轮盘的主要失效形式。轮盘是一种价格昂贵的部件,对其进行部件的可靠性试验在经济上难以承受。据此以临界平面法为基础,通过Ansys有限元分析与材料的应变疲劳试验相结合,利用Monte-Carlo数字仿真方法,确定了轮盘寿命的分布形式,建立了轮盘疲劳可靠性模型,并编制了轮盘疲劳可靠性分析软件,对某型轮盘进行了疲劳可靠性分析。与传统的确定性方法相比更加符合轮盘的失效状况,与基于真实轮盘的试验相比则可以有效降低试验费用,缩短试验周期。

基于Monte-Carlo法的滑坡稳定可靠性分析

简述了可靠性分析的 Ｍｏｎｔｅ－Ｃａｒｌｏ法，结合简化的 Ｂｉｓｈｏｐ法提出了滑坡稳定可靠性分析的状态函数，并通过实例进行了计算分析。证明Ｍｏｎｔｅ－Ｃａｒｌｏ法是求解滑坡稳定可靠性指标和破坏概率的行之有效的方法。

球罐BLEVE碎片抛射的Monte-Carlo分析

多米诺效应是引发化工厂发生重大灾害性事故的主要原因之一,其总后果的严重性远远超过初始事故后果的严重性。目前研究多米诺效应主要考虑热辐射、超压和碎片3种扩展向量,其中爆炸碎片具有很大的随机性,而且破坏后果常常很严重。对爆炸碎片的研究是个热点和难题。本文以墨西哥城液化石油气爆炸事故中球罐发生沸腾液体扩展为蒸气云爆炸(BLEVE)为例,通过Monte-Carlo方法模拟,利用有关的数据和资料确定爆炸碎片产生和飞行中的不确定性参数的概率密度分布,从而计算出碎片的抛射范围。并在此基础上,考虑目标容器和风的影响,将二维轨迹方程扩展为三维方程,并计算得到在给定位置处的目标容器受到碎片冲击的概率。本文的研究结果对于定量评价球罐发生BLEVE之后碎片所造成的危险分析具有重要意义。

基于Monte-Carlo方法的施工导流系统综合风险分析

施工期导流动态风险不仅与水文不确定性、水力不确定性有关,而且与坝体施工进度及其完工工期的不确定性有关。以风险分析为核心,将各种不确定性因素耦合起来研究施工导流系统的综合风险,提出施工进度计划风险分析模型和假定坝体施工进度确定条件下的施工导流风险分析模型,在此基础上,建立基于Monte-Carlo方法全面考虑水文水力不确定性以及施工进度不确定性的施工导流系统综合风险分析模型。实例分析说明,该施工导流系统综合风险研究方法和分析模型是可靠的、适用的。

基于Monte-Carlo方法的风电功率预测不确定性估计

风电功率预测的不确定性估计是实现对风电场优化调度的基础。为此,提出了1种定性分析风电功率预测敏感气象因子的方法,采用2种方式分别对敏感气象因子的误差分布函数进行了估计,并采用Monte-Carlo随机抽样实现了对风电功率预测不确定性的估计,最后进行了算例验证。研究结果表明:不同预报时刻对应气象参数预报误差的不确定性差别较大;基于气象参数不确定性随机抽样的方法可实现对功率预测的不确定性估计,且在相同的置信度下,逐小时样本估计优于总体样本估计。与传统风电功率预测不确定性估计方法相比,该方法对风电场历史运行数据要求低,且不需要单独建模,具有较高的工程实用性。