电感耦合等离子体发射光谱(ICP-OES)法测定陕西眉县猕猴桃矿物质含量及相关营养评价

为探究陕西眉县所产猕猴桃中矿物质含量及评价其相关营养价值。利用电感耦合等离子体发射光谱(ICP-OES)法对陕西眉县主产的徐香、翠香、红心、黄心四个品种猕猴桃中9种矿物质含量进行测定,并采用营养质量指数法(Index of nutritional quality,INQ)对矿物质元素进行营养评价,同时应用SPSS软件对9种矿物质和能量进行相关性分析。陕西眉县四个品种猕猴桃矿物质均以钾、磷、钙、镁四种元素为主,约占总矿物质的99.8%,四个品种中INQ均大于1的矿物质有钙、钾、镁、铜,其中钾的INQ最高在3.89~5.19。矿物总量最高的品种为翠香328 mg/100g,但营养质量指数最高的为徐香16.78(INQ_(总))。通过相关性分析表明各元素间存在着不同程度的相关性,其中钾与能量的相关系数最高为0.982。猕猴桃是一种高钾低钠的优质食品,不同品种猕猴桃矿物质元素的营养价值差异明显,矿物质营养密度最高的为翠香,其次为红心、黄心、徐香,但从营养价值指数方面来看,徐香最高,翠香次之,红心和黄心猕猴桃矿物营养水平稍逊。

电感耦合等离子体发射光谱(ICP-OES)法测定污水中锌含量的不确定度评定

通过建立不确定度数学模型,对ICP-OES测定污水中锌含量实验中各不确定度分量进行评估,计算相对标准不确定度和扩展不确定度。实验结果中的不确定度来源主要有标准工作曲线拟合、标准溶液配制和仪器稳定性等。通过合成各不确定度分量,可得ICP-OES法测定污水中锌含量的标准不确定度为0.079 mg/L,扩展不确定度为0.16 mg/L。当置信水平达到95%时,该污水中锌的含量为(8.69±0.16)mg/L。

ICP-OES测定新疆塔里木河金属离子含量及维护保养措施

新疆塔里木河水体中富含钾、钠、钙、镁等高浓度的金属离子。文章建立了ICP-OES测定新疆塔里木河中钾、钠、钙、镁含量的方法,采用称重法配制标准曲线溶液,相比较传统的移液管方法,采用称重法计算出的稀释倍数会更加准确,标准曲线的线性相关系数更好。采用垂直观测方式测试了该方法的检出限、精密度和准确度,实验结果较好,说明ICP-OES进样系统的维护保养措施有效。

沉淀分离ICP-OES法测定水质中的重金属

以沉淀分离法降低水样中固溶物含量,达到ICP-OES同心型雾化器盐含量(TDS<1%)要求,降低同心型雾化器在使用过程积盐,提高检测灵敏度。处理后的水样进行ICP-OES测定,研究表明,重金属砷、铅、镉、铬重金属元素线性相关系数>0.999,相对标准偏差(RSD)小于5%,检出限在0.8~9.5μg/L之间,加标回收率≥95%,满足地表水环境质量标准和地下水质量标准的分析要求。

微波消解-电感耦合等离子体发射光谱(ICP-OES)法测定固体中兽药制剂中金属元素

传统的中兽药制剂中金属元素检测主要为原子吸收光谱法或原子荧光光谱法等单一元素检测方法,为提高检测效率,实现对固体中兽药制剂中金属元素的准确测定,使用硝酸-过氧化氢及微波消解进行样品前处理,消解后置消解管于赶酸仪中170℃赶酸,采用微波消解-电感耦合等离子体发射光谱(ICP-OES)法相结合对固体兽药制剂中铬、砷、镉、铅、钠、镁、钾、锰、铁、铜、锌、硒、钙、磷等14种元素同时测定,轴向观测方向,内标法定量。消解及赶酸效果理想,整个过程安全、高效、无损。对消解方式进行了考察,并对消解酸体系及消解温度进行了优化,选择了最优的赶酸温度及元素分析谱线,同时也通过试剂加标回收、样品加标回收、样品处理液加标回收相比较的方式验证了方法的可行性。结果表明,铅、镉、铬、砷在0.001~0.01μg/mL,锰、铜、硒在0.002~0.02μg/mL,铁、锌在0.1~1.0μg/mL,镁、钙在1.0~10.0μg/mL,钠、钾、磷在2.0~50.0μg/mL线性关系良好,相关系数(r)均大于0.999,各元素方法检出限在0.1~1.0 mg/kg,平均回收率在90.0%~110%,精密度RSD小于10%(n=5)。方法前处理简便快捷、干扰小、重现性好、灵敏度高,可同时测定多种元素,满足批量测定固体中兽药制剂中铬、砷、镉、铅、钠、镁、钾、锰、铁、铜、锌、硒、钙、磷等14种元素定量分析的要求。

利用ICP-OES测定磷酸铁锂中复杂金属杂质的方法实践

随着锂离子电池产业的蓬勃发展,废旧锂离子电池及锂离子电池生产过程中的报废体量剧增,锂离子电池相关的回收产业发展迅猛,其中磷酸铁锂电池的市场最大。无论哪种回收路径,回料中的金属杂质成分都比较复杂,而金属杂质的准确测定,对锂离子电池回收产业至关重要。文中通过高温热解法对样品进行前处理,建立了一种用ICP-OES测量复杂基体中多种金属元素的分析方法。将高温热解得到的磷酸铁锂回料进行高温下的酸消解,然后在ICP-OES中对不同的观测位进行比较。将得到的数据进行测量系统分析,通过计算精度/容差(%P/T)评估最佳的检验能力组合。经过对比,发现270℃的高温消解更利于金属异物的充分溶出,Al(径向)、Na(径向)、Ni(径向)、Mn(径向)、Cr(轴向)、Zn(径向)的ICP-OES观测方位组合能更准确、稳定地分析复杂基体的金属杂质元素组分。该分析方法简单、高效、计算量小,便于快速评估检验能力。在利用ICP-OES进行复杂基体的金属异物分析方面,此方法具有很好的借鉴意义。

Multi-Compartment SCFA Quantification in Human

Short-chain fatty acids (SCFA) play an important role in human biochemistry. They originate primarily from the digestive system through carbohydrates microbial fermentation. Most SCFA produced in the colon are absorbed by the intestinal wall and enter the bloodstream to be distributed throughout the body for multiple purposes. At the intestinal level, SCFA play a role in controlling fat storage and fatty acid metabolism. The effects of these beneficial compounds therefore concern overall health. They facilitate energy expenditure and are valuable allies in the fight against obesity and diabetes. SCFA are also involved in the regulation of the levels of several neurotransmitters such as GABA (γ-aminobutyric acid), glutamate, serotonin, dopamine, and norepinephrine. Their role is also highlighted in many inflammatory and neurodegenerative diseases such as Alzheimer’s disease (AD) or Parkinson’s disease (PD). To have a realistic picture of the distribution of SCFA in different biological compartments of the human body, we propose to study SCFA simultaneously in five human biological samples: feces, saliva, serum, cerebrospinal fluid (CSF), and urine, as well as in Dried Blood Spot (DBS). To evaluate their concentration and repeatability, we used 10 aliquots from pooled samples, analyzed by 3-nitrophenylhydrazine (3-NPH) derivation and liquid chromatography coupled with high sensitivity mass spectrometry (LC-QqQ-MS). We also evaluated the SCFA assay on Dried Blood Spot (DBS). In this work, we adapted the pre-analytical parts for each sample to be able to use a common calibration curve, thus facilitating multi-assay quantification studies and so being less time-consuming. Moreover, we proposed new daughter ions from the same neutral loss (43 Da) to quantify SCFAs, thus improving the sensitivity. In conclusion, our methodology, based on a unique calibration curve for all samples for each SCFA, is well-suited to quantified them in a clinical context.

Investigation on mechanical properties regulation of rock-like specimens based on 3D printing and similarity quantification

3D printing is widely adopted to quickly produce rock mass models with complex structures in batches,improving the consistency and repeatability of physical modeling.It is necessary to regulate the mechanical properties of 3D-printed specimens to make them proportionally similar to natural rocks.This study investigates mechanical properties of 3D-printed rock analogues prepared by furan resin-bonded silica sand particles.The mechanical property regulation of 3D-printed specimens is realized through quantifying its similarity to sandstone,so that analogous deformation characteristics and failure mode are acquired.Considering similarity conversion,uniaxial compressive strength,cohesion and stress–strain relationship curve of 3D-printed specimen are similar to those of sandstone.In the study ranges,the strength of 3D-printed specimen is positively correlated with the additive content,negatively correlated with the sand particle size,and first increases then decreases with the increase of curing temperature.The regulation scheme with optimal similarity quantification index,that is the sand type of 70/140,additive content of 2.5‰and curing temperature of 81.6℃,is determined for preparing 3D-printed sandstone analogues and models.The effectiveness of mechanical property regulation is proved through uniaxial compression contrast tests.This study provides a reference for preparing rock-like specimens and engineering models using 3D printing technology.

Uncertainty quantification of inverse analysis for geomaterials using probabilistic programming

Uncertainty is an essentially challenging for safe construction and long-term stability of geotechnical engineering.The inverse analysis is commonly utilized to determine the physico-mechanical parameters.However,conventional inverse analysis cannot deal with uncertainty in geotechnical and geological systems.In this study,a framework was developed to evaluate and quantify uncertainty in inverse analysis based on the reduced-order model(ROM)and probabilistic programming.The ROM was utilized to capture the mechanical and deformation properties of surrounding rock mass in geomechanical problems.Probabilistic programming was employed to evaluate uncertainty during construction in geotechnical engineering.A circular tunnel was then used to illustrate the proposed framework using analytical and numerical solution.The results show that the geomechanical parameters and associated uncertainty can be properly obtained and the proposed framework can capture the mechanical behaviors under uncertainty.Then,a slope case was employed to demonstrate the performance of the developed framework.The results prove that the proposed framework provides a scientific,feasible,and effective tool to characterize the properties and physical mechanism of geomaterials under uncertainty in geotechnical engineering problems.

ICP-OES电感耦合等离子体发射光谱法测定粉条中铝含量的不确定度评定

本文对ICP-OES电感耦合等离子体光谱法测定粉条中铝含量不确定度进行评定,分析了整个检测过程产生的不确定度,得出扩展不确定度。结果表明ICP-OES法线性关系、重现性和稳定性均良好,其线性相关系数为0.9999。最终结果表示:X=(220±6.3184)mg/kg。ICP-OES法测定粉条中的铝测量不确定度主要来源于标准溶液的配制和检测仪器产生的误差。

High-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer based on probability density evolution method

This paper proposed an efficient research method for high-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer.Firstly,the dynamic model of projectile motion is established considering the flexible deformation of the barrel and the interaction between the projectile and the barrel.Subsequently,the accuracy of the dynamic model is verified based on the external ballistic projectile attitude test platform.Furthermore,the probability density evolution method(PDEM)is developed to high-dimensional uncertainty quantification of projectile motion.The engineering example highlights the results of the proposed method are consistent with the results obtained by the Monte Carlo Simulation(MCS).Finally,the influence of parameter uncertainty on the projectile disturbance at muzzle under different working conditions is analyzed.The results show that the disturbance of the pitch angular,pitch angular velocity and pitch angular of velocity decreases with the increase of launching angle,and the random parameter ranges of both the projectile and coupling model have similar influence on the disturbance of projectile angular motion at muzzle.

Uncertainty quantification of mechanism motion based on coupled mechanism—motor dynamic model for ammunition delivery system

In this paper,a dynamic modeling method of motor driven electromechanical system is presented,and the uncertainty quantification of mechanism motion is investigated based on this method.The main contribution is to propose a novel mechanism-motor coupling dynamic modeling method,in which the relationship between mechanism motion and motor rotation is established according to the geometric coordination of the system.The advantages of this include establishing intuitive coupling between the mechanism and motor,facilitating the discussion for the influence of both mechanical and electrical parameters on the mechanism,and enabling dynamic simulation with controller to take the randomness of the electric load into account.Dynamic simulation considering feedback control of ammunition delivery system is carried out,and the feasibility of the model is verified experimentally.Based on probability density evolution theory,we comprehensively discuss the effects of system parameters on mechanism motion from the perspective of uncertainty quantization.Our work can not only provide guidance for engineering design of ammunition delivery mechanism,but also provide theoretical support for modeling and uncertainty quantification research of mechatronics system.

Quantification of the concrete freeze–thaw environment across the Qinghai–Tibet Plateau based on machine learning algorithms

The reasonable quantification of the concrete freezing environment on the Qinghai–Tibet Plateau(QTP) is the primary issue in frost resistant concrete design, which is one of the challenges that the QTP engineering managers should take into account. In this paper, we propose a more realistic method to calculate the number of concrete freeze–thaw cycles(NFTCs) on the QTP. The calculated results show that the NFTCs increase as the altitude of the meteorological station increases with the average NFTCs being 208.7. Four machine learning methods, i.e., the random forest(RF) model, generalized boosting method(GBM), generalized linear model(GLM), and generalized additive model(GAM), are used to fit the NFTCs. The root mean square error(RMSE) values of the RF, GBM, GLM, and GAM are 32.3, 4.3, 247.9, and 161.3, respectively. The R^(2) values of the RF, GBM, GLM, and GAM are 0.93, 0.99, 0.48, and 0.66, respectively. The GBM method performs the best compared to the other three methods, which was shown by the results of RMSE and R^(2) values. The quantitative results from the GBM method indicate that the lowest, medium, and highest NFTC values are distributed in the northern, central, and southern parts of the QTP, respectively. The annual NFTCs in the QTP region are mainly concentrated at 160 and above, and the average NFTCs is 200 across the QTP. Our results can provide scientific guidance and a theoretical basis for the freezing resistance design of concrete in various projects on the QTP.

Revolutionizing disease diagnosis and management:Open-access magnetic resonance imaging datasets a challenge for artificial intelligence driven liver iron quantification

Artificial intelligence(AI),particularly machine learning(ML)and deep learning(DL)techniques,such as convolutional neural networks(CNNs),have emerged as transformative technologies with vast potential in healthcare.Body iron load is usually assessed using slightly invasive blood tests(serum ferritin,serum iron,and serum transferrin).Serum ferritin is widely used to assess body iron and drive medical management;however,it is an acute phase reactant protein offering wrong interpretation in the setting of inflammation and distressed patients.Magnetic resonance imaging is a non-invasive technique that can be used to assess liver iron.The ML and DL algorithms can be used to enhance the detection of minor changes.However,a lack of open-access datasets may delay the advancement of medical research in this field.In this letter,we highlight the importance of standardized datasets for advancing AI and CNNs in medical imaging.Despite the current limitations,embracing AI and CNNs holds promise in revolutionizing disease diagnosis and treatment.

应用ICP-OES法测定矿区土壤中有价稀土元素含量

传统测定稀土矿区土壤中稀有元素含量的方法主要采用化学分析法,该方法污染性强,接触过程也容易对结果造成干扰,故本文应用ICP-OES法测定矿区土壤中有价稀土元素含量。测定结果表明:应用所提测试技术测定标准土壤样本,稀土元素回收率均在97%以上,并且当硫酸铵浓度为0.1 g/mL、振荡时间为2 h、波长为414 nm时测定效果更好,能准确完成有价稀土元素含量测量。通过对研究区域各剖面土壤样本进行测定可知,该地区的母质层显示出较好的稀土元素富集趋势。尽管淋溶层和淀积层中稀土元素的含量相对较低,但仍保持在一定水平。这进一步表明该地区具有轻稀土元素富集的特点,具有较好地开采价值。

ICP-OES法测定高镍合金铸铁中锰铬镍铜

高镍合金铸铁已广泛用于制造耐高温的反应器、换热器等设备和构件以及高强度、高韧性的机械零件,先行国家标准方法对铸铁中高含量元素的测定都有局限性。本实验建立了电感耦合等离子体原子发射光谱法(ICPOES)同时测定高镍铸铁中锰、铬、镍、铜元素的方法。试验探讨了不同溶解方法对分析结果的影响,优选出最佳溶样方法:先加(1+1)硝酸溶解样品至剧烈反应后滴加浓盐酸和氢氟酸,最后加入高氯酸加热至冒烟,定容后测定。将该法应用于实际样品测定,测定结果锰的质量分数在0.05%~4%,镍的质量分数在0.05%~40%,铬的质量分数在0.05%~5%,铜的质量分数在0.05%~10%范围内。在选定的仪器工作条件下,各元素的校准曲线线性相关系数均大于0.999,方法中各元素的回收率为98.0%~105.6%,实际样品分析相对标准偏差RSD≤2.00%(n=11),将本方法应用于高镍铸铁标准物质中锰、铬、镍、铜元素的测定,结果与证书标称值吻合。

ICP-OES测定地下水中锰含量的不确定度评定

为提高地下水监测数据的准确性,采用电感耦合等离子体发射光谱(ICP-OES)法测定地下水中锰含量的不确定度进行评定,找出影响地下水锰元素含量测定的主要影响因素。依据JJF1059.1-2012评定理论和CNAS-GL006-2019对测定不确定度的有关规定,建立相关数学模型,分析不确定度的主要来源,并将各分量因子进行计算与合成,得到地下水中锰含量扩展不确定度。结果表明,当样品锰含量为0.0396 mg/L时,其扩展不确定度为0.002 mg/L(k=2),结果表示为0.0396±0.002 mg/L。影响样品测定误差的主要来源是仪器、样品重复测定、标准溶液不确定度、标准曲线配制、标准曲线拟合,其中标准溶液配制和标准溶液自身影响最大,需要在监测过程重点控制。该研究可为ICP-OES测定地下水中锰含量的不确定度评定提供参考。

ICP-OES检测盾构机在用润滑油中磷元素含量

盾构机在用润滑中含有磷、硅、锌、铜、铁等多种元素。对盾构机在用润滑油的监控需要对其多种元素含量同时进行检测。目前多使用电感耦合等离子体发射光谱仪(ICP-OES)方法实现,既可保证测量精准度,又可保证灵敏度。其中对于磷元素,检测方法标准推荐了多个波长的选择,而盾构机在用润滑油实际使用状况比较复杂,本文重点研究用ICP-OES检测盾构机在用润滑中磷元素含量的方法,优化仪器设备工作条件,选用Conostan S21标准油制备标准曲线,采用不同稀释剂对润滑油中的磷元素含量进行检测。结果显示,溶剂油和煤油都可以作为检测稀释剂使用。测试结果还发现,优选177.434nm作为磷元素检测波长,可取得最佳准确度和稳定性。

ICP-OES有机直接进样法测定食品添加剂中铁、钙、铝、铅、锌、砷

建立了ICP-OES(电感耦合等离子体发射光谱仪)有机直接进样测定复配食品添加剂中铁、钙、铝、铅、锌、砷共6种元素含量的方法。采用乙醇溶液为稀释剂,按一定比例稀释后直接进仪器检测。结果表明,这6种元素在0.05~5.00 mg/L线性关系良好,相关系数均大于0.9999,检出限为0.0001~0.0016 mg/L,加标回收率为91.4%~108.4%,相对标准偏差为0.53%~3.65%。该方法操作简单,准确度高,安全快捷,可用于复配食品添加剂中的杂质元素检测。

ICP-OES法同时测定固体废物中碲、钯、铂、锡的含量

对固体废物中碲(Te)、钯(Pd)、铂(Pt)和锡(Sn)的定量分析有助于识别固体废物和危险废物。本文使用9 mL硝酸、2 mL盐酸、3 mL氢氟酸和1 mL过氧化氢对样品进行微波消解,然后进行赶酸和定容,最后,用电感耦合等离子体发射光谱仪(ICP-OES)测定溶液中Te、Pd、Pt和Sn的含量。本文探讨了预处理的最佳消化温度,分析了仪器不同波长测量结果的差异,并进行检出限测定。结果表明,当消解最高温度为180℃,选择仪器推荐的检测波长时,Te、Pd、Pt、Sn曲线的相关系数在0.9996~0.9999,其检出限为0.1~0.6 mg·kg^(-1);精密度为1.2%~3.3%,回收率为94.1%~102%。该方法检测效率高,精密度、准确度良好,可满足检测和鉴别需求。