基于ISSA-CNN-BiGRU-Attention的锂电池健康状态评估

健康状态(SOH)预测对于电池管理系统至关重要。针对电池健康状态评估建模复杂、预测误差大等问题,准确的SOH预测仍需要改进。本文结合容量增量分析(ICA)和差分电压分析(DVA)方法,提出了一种改进麻雀优化算法(ISSA)-卷积神经网络(CNN)-双向门控递归单元(BiGRU)-注意力机制(Attention)的锂电池健康状态评估方法。通过对容量增量(IC)曲线和差分电压(DV)曲线进行高斯滤波处理,避免了噪声的影响。通过马里兰大学先进的生命周期工程中心(CALCE)数据进行处理,从滤波后的IC和DV曲线上提取一组新的电池老化特征,所提4个老化特征与SOH之间的Pearson相关系数在0.9以上。使用ISSA-CNN-BiGRU-Attention方法来构建电池SOH的预测模型,将所提方法与CNN、BiGRU、CNN-BiGRU等方法进行比较,实验结果表明,该方法的MAE与RMSE误差最大值分别为0.00544和0.00717,对比其他模型,具有优秀的鲁棒性和准确性,具有更好的实际使用价值。

Determination of Carbon and Nitrogen Isotope Fractions in Tartaric Acid, Oxalic Acid, Glucose and Fructose—National Center of High Technologies of Georgia

Tartaric acid, oxalic acid, glucose, and fructose are highly important compounds. A comprehensive study of these substances is fascinating from a scientific perspective. They are key components found in wine, vegetables, and fruits. Understanding the isotopic compositions in organic compounds is crucial for comprehending various biochemical processes and the nature of substances present in different natural products. Tartaric acid, oxalic acid, glucose, and fructose are widely distributed compounds, including in vegetables and fruits. Tartaric acid plays a significant role in determining the quality and taste properties of wine, while oxalic acid is also prevalent but holds great interest for further research, especially in terms of carbon isotopic composition. We can unveil the mechanisms of processes that were previously impossible to study. Glucose and fructose are the most common monosaccharides in the hexose group, and both are found in fruits, with sweeter fruits containing higher amounts of these substances. In addition to fruits, wheat, barley, rye, onions, garlic, lentils, peppers, dried fruits, beans, broccoli, cabbage, tomatoes, and other foods are also rich sources of fructose and glucose. To determine the mass fraction of the carbon-13 isotope in these compounds, it is important to study their changes during natural synthesis. These compounds can be modified with a carbon center. According to the existing isotopic analysis method, these compounds are converted into carbon oxide or dioxide [1]. At this point, the average carbon content in the given compound is determined, but information about isotope-modified centers is lost. Dilution may occur through the transfer of other carbon-containing organic compounds in the sample or by dilution with natural carbon or carbon dioxide during the transfer process. This article discusses the possibility of carbon-13 isotope propagation directly in these compounds, both completely modified and modified with individual carbon centers. The literature provides information on determining carbon-13 substance in organic compounds, both with a general approach and for individual compounds [2] [3].

Relativistic Heavy Ion Collider and the Large Hadron Collider for Heavy Ion Fusion

Heavy Ion Fusion makes use of the Relativistic Heavy Ion Collider at Brookhaven National Lab and the Large Hadron Collider in Geneva, Switzerland for Inertial Confinement Fusion. Two Storage Rings, which may or may not initially be needed, added to each of the Colliders increases the intensity of the Heavy Ion Beams making it comparable to the Total Energy delivered to the DT target by the National Ignition Facility at the Lawrence Livermore Lab. The basic Physics involved gives Heavy Ion Fusion an advantage over Laser Fusion because heavy ions have greater penetration power than photons. The Relativistic Heavy Ion Collider can be used as a Prototype Heavy Ion Fusion Reactor for the Large Hadron Collider.

Geogenic Pollution of Groundwater Quality in Gampaha District, Sri Lanka: A Case Study of Groundwater Acidification from Rathupaswala

Over recent decades, Gampaha district, Sri Lanka, has experienced significant urbanisation and industrial growth, increasing groundwater demand due to limited and polluted surface water resources. In 2013, a community uprising in Rathupaswala, a village in Gampaha district, accused a latex glove manufacturing factory of causing groundwater acidity (pH < 4). This study evaluates the spatial and temporal changes in geochemical parameters across three transects in the southern part of Gampaha district to 1) assess the impact of geological formations on groundwater;2) compare temporal variations in groundwater;and 3) explain acidification via a geochemical model. Seventy-two sample locations were tested for pH, electrical conductivity (EC), and anion concentrations (sulphate, nitrate, chloride and fluoride). Depth to the water table and distance from the sea were measured to study variations across sandy, peaty, lateritic, and crystalline aquifers. Results showed pH readings around 7 for sandy and crystalline aquifers, below 7 for peaty aquifers, and below 5 for lateritic aquifers, with significant water table fluctuations near Rathupaswala area. Principal component analysis revealed three principal components (PCs) explaining 86.0% of the variance. PC1 (40.6%) correlated with pH, EC, and sulphate (saltwater intrusion), while PC2 (32.0%) correlated with nitrates and depth to the water table (anthropogenic nutrient pollution). A geochemical transport model indicated a cone of depression recharged by acidic groundwater from peat-soil aquifers, leading to acidic groundwater in Rathupaswala area. Previous attributions of acidic pH to the over-exploitation of groundwater by the latex factory have been reevaluated;the results suggest natural acidification from prolonged water-rock interactions with iron-rich lateritic aquifers. Groundwater pH is influenced by local climate, geology, topography, and drainage systems. It is recommended that similar water-rock interaction conditions may be present throughout the wet zone of Sri Lanka, warranting detailed studies to confirm this hypothesis.

Empowering the Future: Exploring the Construction and Characteristics of Lithium-Ion Batteries

Lithium element has attracted remarkable attraction for energy storage devices, over the past 30 years. Lithium is a light element and exhibits the low atomic number 3, just after hydrogen and helium in the periodic table. The lithium atom has a strong tendency to release one electron and constitute a positive charge, as Li . Initially, lithium metal was employed as a negative electrode, which released electrons. However, it was observed that its structure changed after the repetition of charge-discharge cycles. To remedy this, the cathode mainly consisted of layer metal oxide and olive, e.g., cobalt oxide, LiFePO4, etc., along with some contents of lithium, while the anode was assembled by graphite and silicon, etc. Moreover, the electrolyte was prepared using the lithium salt in a suitable solvent to attain a greater concentration of lithium ions. Owing to the lithium ions’ role, the battery’s name was mentioned as a lithium-ion battery. Herein, the presented work describes the working and operational mechanism of the lithium-ion battery. Further, the lithium-ion batteries’ general view and future prospects have also been elaborated.

Three-Dimensional Multi-Phase Microscopic Simulation of Service Life of Recycled Large Aggregate Self-Compacting Concrete

Recycled large aggregate self-compacting concrete (RLA-SCC) within multiple weak areas. These weak areas have poor resistance to chloride ion erosion, which affects the service life of RLA-SCC in the marine environment. A three-dimensional multi-phase mesoscopic numerical model of RLA-SCC was established to simulate the chloride ions transportation in concrete. Experiments of RLA-SCC immersing in chloride solution were carried out to verify the simulation results. The effects of recycled large aggregate (RLA) content and RLA particle size on the service life of concrete were explored. The results indicate that the mesoscopic numerical simulation results are in good agreement with the experimental results. At the same depth, the closer to the surface of the RLA, the greater the chloride ion concentration. The service life of RLA-SCC in marine environment decreases with the increase of RLA content. Compared with the service life of 20% content, the service life of 25% and 30% content decreased by 20% and 42% respectively. Increasing the particle size of RLA can effectively improve the service life of RLA-SCC in chloride environment. Compared with the service life of 50 mm particle size, the service life of 70 mm and 90 mm increased by 61% and 163%, respectively. .

基于LSTM&GRU-Attention多联合模型的锂离子电池SOH估计

锂离子电池的健康状态(state of health,SOH)准确估计对于储能电站的稳定高效运行至关重要。为了进一步提高数据驱动方法对SOH估计的精度,本团队提出了一种利用交叉验证训练的线性回归加权融合模型的方法。首先,从放电电压曲线、充电和放电温度曲线中提取了健康特征,并使用Pearson相关系数对所选特征进行了相关性分析,确定了网络模型输入的健康因子参数。随后,通过在LSTM与GRU中加入注意力机制,建立了LSTM-Attention与GRU-Attention模型,分别以NASA电池老化数据集B0005、B0006、B0007和B0018电池的前50%作为模型训练集,用剩余数据对模型进行验证,分别得到了模型对应的ŷ_(L-A)与ŷ_(G-A)估计值,然后使用所提融合模型方法对两个估计值进行线性回归加权,结果显示该方法的最大均方根误差和平均绝对误差分别为0.00291和0.00200。最后,为验证所提模型的抗干扰能力,在输入模型的健康因子中加入不同比例的高斯白噪声,实验结果显示融合模型的抗干扰能力较强,最大均方根误差和平均绝对误差仅为0.03562和0.02889。

基于并行CNN-Self attention&LSTM的锂电池RUL间接预测

针对锂离子电池难以在线测量直接健康因子(容量、内阻)进行剩余使用寿命(RUL)预测的现状,提出基于并行CNN-Self attention与LSTM组合的锂电池RUL间接预测方法。首先基于锂离子电池放电循环数据,利用灰度关联分析筛选出能够高度体现电池容量衰减的间接健康因子;然后分别对间接健康因子使用卷积神经网络(CNN)进行特征提取和自注意力机制(Self attention)调整特征权重得到对应的特征矩阵;最后融合特征矩阵,并使用长短期记忆(LSTM)网络进行锂电池RUL预测。使用NASA锂离子电池数据集进行实验,结果表明:与传统的CNN、LSTM和CNN-LSTM模型相比,并行CNN-Self attention&LSTM模型所得到的容量衰减曲线更接近实际容量衰减曲线,误差波动范围更小,在RMSE、MAE和R2系数3种评价指标上表现更优。

基于ResNet-Bi-LSTM-Attention的锂离子电池剩余使用寿命预测

锂离子电池剩余使用寿命(RUL)预测是锂离子电池研究的一个重要方向,通过对RUL的准确预测,可以降低锂离子电池出现事故的概率。针对锂离子电池RUL的准确预测,该研究提出一种综合残差神经网络(ResNet)和双向长短期记忆网络(Bi-LSTM)的优势,并且加入注意力机制(Attention)的锂离子电池RUL预测模型。首先选取能够表现电池寿命的特征参数作为输入量,利用ResNet提取输入数据的隐含特征信息,然后利用Bi-LSTM对时间序列信息进行预测,并且结合注意力机制对预测结果进行权重分配,得到最终的锂离子电池的RUL预测结果。通过美国马里兰大学(CALCE)提供的开源数据集进行锂离子电池RUL预测试验,并与现有的预测模型进行对比试验,对比模型的预测结果,试验结果表明提出的ResNet-Bi-LSTM-Attention模型能够准确地进行锂离子电池RUL预测,各项误差都比较低,具有较好的精度和准确性。最后使用美国航空航天局(NASA)提供的锂离子电池开源数据集进行泛化性实验,证明了ResNet-Bi-LSTM-Attention模型在不同电池RUL预测中具有良好的准确性,可以被广泛使用。

Ion Torrent半导体测序联合MLPA技术检测神经纤维瘤患者的致病突变

目的建立临床适用的神经纤维瘤病(NF)的分子遗传分析方法,对NF进行分子遗传诊断和遗传咨询,并对NF家庭进行产前诊断。方法以南京医科大学附属妇产医院遗传咨询门诊收治的18例NF患者为研究对象,收集患者及其家属的外周血标本并提取基因组DNA,应用Ion Torrent半导体测序技术进行NF1/NF2基因测序并结合多重连接探针扩增反应(MLPA)检测,筛选致病突变并用Sanger测序验证,结合亲子二代的分子遗传检测结果,制定适当的临床干预和随访计划。在NF家系母亲再次妊娠时,对胎儿进行产前诊断。结果应用Ion Torrent半导体测序技术检测出9例致病突变和1例可疑致病突变,其中包括3个未报道过的新突变;应用MLPA技术检测出1例拷贝数大片段缺失。对其中5个家系的孕妇行羊膜腔穿刺术抽取羊水进行产前诊断,其胎儿均不携带家系的致病突变。结论基于Ion Torrent半导体测序及MLPA技术建立的基因诊断方法可为NF临床诊断及遗传咨询提供分子遗传学依据,具有较高的临床应用价值。

壳聚糖复合水凝胶的制备方法及在水处理中的应用

壳聚糖由于来源广、吸附性能强和可自然降解等优点成为备受关注的天然吸附剂。壳聚糖复合水凝胶(CCH)材料是以壳聚糖为主要原料,通过化学、物理等方法改性后得到的新型复合材料。介绍了化学交联、物理交联以及互穿网络等合成壳聚糖复合水凝胶的主要方法。综述了近年来使用CCH对工业废水中常见染料、重金属离子和其他常见污染物的吸附机理和处理效果,讨论了当前利用CCH在处理工业废水中各种污染物时存在的问题及解决方法。最后对CCH在合成方法、选择性吸附、回收利用和智能改性等方面进行了展望,为深入研究提高CCH材料性能及拓宽其在工业废水处理中的应用范围提供了思路。

锂离子电池健康状态估计及寿命预测研究进展综述

随着锂离子电池的应用越来越广泛,锂电池健康状态的精确估计和剩余寿命的实时预测对于锂电池系统的安全运行和降低运维成本具有重要意义。锂电池内部复杂的物理化学反应和外部复杂工作条件,使得实现精准的健康状态估计和寿命预测具有挑战性。该文综述近年来锂电池健康状态估计和剩余使用寿命预测方法的研究现状,分析基于物理/数学模型、数据驱动、模型法和数据驱动融合,以及多种数据驱动融合的锂电池健康状态估计方法的优缺点及适用条件,并对比分析不同数据驱动类型的锂电池寿命预测方法。指出锂电池健康状态估计及寿命预测尚存在的问题,并对未来研究方向进行展望,对完善锂电池健康状态估计和寿命预测算法理论体系、指导实际应用技术具有重要意义。

离子注渗复合表面改性技术研究进展

综合国内外研究现状,目前针对离子注渗复合表面改性技术已开展了大量的研究工作,然而还缺少对其进行系统介绍的研究报道。首先,对离子渗技术(离子渗氮、离子渗碳和离子渗硫)、离子注入技术(氮离子注入、碳离子注入和金属离子注入)和离子注渗复合技术的原理进行了介绍。其次,对上述表面改性技术的研究进展进行了综述和总结。最后,针对目前离子注渗复合技术的不足之处,从改善硬件设备、强化作用机理、系统研究复合处理工艺和促进其工业化应用等方面进行解决,提出要充分利用注渗和镀膜技术复合的优势来实现材料结构功能一体化,推动多相复合强化技术的研究与开发,为工业化应用奠定理论基础。

纳米材料在食品重金属离子快速检测中的应用研究进展

纳米材料因具有比表面积大、良好稳定性、特殊的结构、易于修饰、良好的生物相容性等优点,已被广泛应用于食品中重金属离子检测领域。文章重点综述了碳纳米管、石墨烯、碳量子点、金属有机骨架、纳米酶等纳米材料在食品中重金属离子检测方面的研究与应用现状,并展望了纳米材料在食品中重金属离子检测领域面临的挑战和应用前景。

基于电化学阻抗谱的锂电池过充电阻抗特性与检测方法研究

目前以锂电池为主的电化学储能单元及系统应用日益广泛,而锂电池在实际使用中频发因过充电滥用引发电池故障的情况,因此实际电池的过充电状态准确检测一直是该领域的难点和瓶颈问题。针对此,该文采用电化学阻抗谱技术对单体电池过充电行为及过程开展检测研究,在实验室设计并制定电池过充电模拟循环实验,利用弛豫时间分布法对锂电池阻抗特性进行分析;在获得电池阻抗特性的基础上,对电池弛豫时间分布曲线进行解析;最后筛选阻抗特征参量为模型输入量,构建支持向量机模型进行电池过充电检测。结果表明,弛豫时间分布曲线中的极化峰P1对应锂离子在固态电解质界面(solid electrolyte interphase,SEI)膜中的扩散过程、极化峰P2对应电子在正极材料中的扩散过程、极化峰P3对应锂离子在电极界面的氧化还原反应。过充电会导致电池欧姆内阻、SEI膜内阻与电荷转移电阻的增长速率最大为正常循环的266%、360%和182%,其中固态电解质界面SEI膜内阻为主要因素。电化学阻抗谱的阻抗特征参量以及支持向量机模型可以用于锂电池过充电检测,估计精度达93.24%。不仅可掌握电池的运行状态,还可对过充电进行有效辨识。

电子舌和气相色谱-离子迁移谱技术分析炖煮时间对松茸鸡汤风味的影响

以雅江鲜松茸为试验材料,采用电子舌和气相色谱-离子迁移谱技术,使用主成分、正交偏最小二乘法判别分析,结合相对气味活度值分析炖煮时间对松茸鸡汤风味的影响。结果表明:鲜松茸对鸡汤滋味贡献很大,电子舌鲜味强度值从2.1提高到8.0。采用GC-IMS方法共检出45种化合物,加入松茸后醛类含量从47.88%下降到21.13%,由ROAV值(128.08)确认3-甲基-1-丁醇是松茸鸡汤的关键化合物。其中,伞花烃、3-辛醇、正辛醇是松茸鸡汤的特征化合物,使松茸鸡汤呈现独特的汽油味、苔藓清香、坚果香味、蘑菇气味和金属气味。炖煮5 min后,鸡汤中松茸特征风味最明显,达到最佳食用效果。研究结果为雅江松茸鸡汤风味特征研究提供参考。

淀粉基水凝胶St/CMC-g-PAA对Cu^(2+)的吸附性能研究

以玉米淀粉(St)、羧甲基纤维素钠(CMC)为原料,丙烯酸(AA)为接枝单体,通过接枝和交联反应合成了淀粉基水凝胶St/CMC-g-PAA。考察了投药量、pH、Cu^(2+)初始浓度(ρ0)、吸附时间对吸附效果的影响。结果表明,当ρ0=40 mg/L,投药量为300 mg/L,pH=5.2时,Cu^(2+)的去除率可达92.7%。实验数据拟合结果表明,水凝胶对Cu^(2+)的吸附过程符合Langmuir吸附模型和准二级动力学模型,属于单分子层的化学吸附过程。在25℃时,水凝胶对Cu^(2+)的饱和吸附容量qm=142.86 mg/g。水凝胶再生性能较好,经过4次吸附-脱附循环后,Cu^(2+)去除率仍可达到82.1%。

锂离子电池储能电站的热失控状态检测与安全防控技术研究进展

锂离子电池具有能量密度大、使用寿命长、工作温度范围宽、自放电小等优点,是中国电化学储能电站的主流电池技术。然而,在加热、过充等恶劣工况下,锂离子电池易发生热失控引发火灾甚至爆炸,因此其安全问题已逐渐成为锂离子电池储能电站建设及大规模应用的首要问题。该文系统分析了锂离子储能电池热失控的诱因、电池内部反应过程及外部特征参量的变化规律,重点总结了当前主要的电池热失控状态检测技术、智能诊断算法及储能电站安全防控技术,最后对储能电站热失控状态检测及安全防控技术进行了总结和展望。

锂离子电池电解液安全性的影响因素及改进措施

锂离子电池由于能量密度高、高电压和维护成本低等优点而被大家使用.但在使用它们的过程中存在燃烧、爆炸等安全问题.电解液是锂离子电池中最易燃的组分,所以其与锂电池的安全性息息相关.改进电解液是提高锂离子电池安全性的关键方法.首先探讨了影响锂离子电池电解液安全性的因素,然后提出了改善措施,主要包括添加阻燃剂和抗过充添加剂来降低风险.

干燥方式对苹果干品质特性及风味的影响

为探究提高静宁苹果干零食品质的加工方式,本研究探讨了5种干燥方式(热风干燥、太阳能干燥、真空冷冻干燥、微波-压差膨化干燥和热泵干燥)对苹果干能耗、抗氧化活性、微观结构和风味的影响。结果表明,和其它4种方式相比,在能耗方面,真空冷冻干燥的单位能耗最高(69.48±1.69 kW·h/kg),而太阳能干燥的单位能耗最低(19.60±1.36 kW·h/kg);在硬脆度方面,热风干燥的苹果干具有最高的硬度、最低的脆度,而真空冷冻干燥的苹果干硬度最低、脆度较高;在色差方面,真空冷冻干燥苹果干的L*值最高(72.91±0.59),ΔE值最接近鲜样(10.48±0.30);此外,真空冷冻干燥能有效降低苹果干中抗氧化物质的损失,与鲜样相比,其抗坏血酸、总酚和总黄酮的含量分别降低了35.22%、39.27%和32.02%。同时,总抗氧化能力、羟自由基清除率和超氧阴离子清除率也分别降低了23.50%、57.24%和10.56%;在微观结构方面,真空冷冻干燥的苹果干细胞层呈较规律的海绵状多孔性结构,质地较好;在风味方面,鉴定出5种干燥方式的苹果干有96种挥发性物质,其中真空冷冻干燥的苹果干更加芳香、口感更加丰富。综合考虑,真空冷冻干燥是提高苹果干零食品质特性和风味的推荐方法,对苹果干制品的工业化生产有现实的指导意义。