Incorporating empirical knowledge into data-driven variable selection for quantitative analysis of coal ash content by laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.

Patterning single-layer materials by electrical breakdown using atomic force microscopy

The development of nanoelectronics and nanotechnologies has been boosted significantly by the emergence of 2D materials because of their atomic thickness and peculiar properties,and developing a universal,precise patterning technology for single-layer 2D materials is critical for assembling nanodevices.Demonstrated here is a nanomachining technique using electrical breakdown by an AFM tip to fabricate nanopores,nanostrips,and other nanostructures on demand.This can be achieved by voltage scanning or applying a constant voltage while moving the tip.By measuring the electrical current,the formation process on single-layer materials was shown quantitatively.The present results provide evidence of successful pattern fabrication on single-layer MoS2,boron nitride,and graphene,although further confirmation is still needed.The proposed method holds promise as a general nanomachining technology for the future.

Research on batch multielement rapid quantitative analysis based on the standard curve-assisted calibration-free laserinduced breakdown spectroscopy method

This study proposes a batch rapid quantitative analysis method for multiple elements by combining the advantages of standard curve(SC)and calibration-free laser-induced breakdown spectroscopy(CF-LIBS)technology to achieve synchronous,rapid,and accurate measurement of elements in a large number of samples,namely,SC-assisted CF-LIBS.Al alloy standard samples,divided into calibration and test samples,were applied to validate the proposed method.SC was built based on the characteristic line of Pb and Cr in the calibration sample,and the contents of Pb and Cr in the test sample were calculated with relative errors of 6%and 4%,respectively.SC built using Cr with multiple characteristic lines yielded better calculation results.The relative contents of ten elements in the test sample were calculated using CF-LIBS.Subsequently,the SC-assisted CF-LIBS was executed,with the majority of the calculation relative errors falling within the range of 2%-5%.Finally,the Al and Na contents of the Al alloy were predicted.The results demonstrate that it effectively enables the rapid and accurate quantitative analysis of multiple elements after a single-element SC analysis of the tested samples.Furthermore,this quantitative analysis method was successfully applied to soil and Astragalus samples,realizing an accurate calculation of the contents of multiple elements.Thus,it is important to advance the LIBS quantitative analysis and its related applications.

Estimating the yield stress of soft materials via laser-induced breakdown spectroscopy

Taking three typical soft samples prepared respectively by loose packings of 77-,95-,and 109-μm copper grains as examples,we perform an experiment to investigate the energy-dependent laser-induced breakdown spectroscopy(LIBS)of soft materials.We discovered a reversal phenomenon in the trend of energy dependence of plasma emission intensity:increasing initially and then decreasing separated by a well-defined critical energy.The trend reversal is attributed to the laser-induced recoil pressure at the critical energy just matching the sample's yield strength.As a result,a one-to-one correspondence can be well established between the samples'yield stress and the critical energy that is easily obtainable from LIBS measurements.This allows us to propose an innovative method for estimating the yield stress of soft materials via LIBS with attractive advantages including in-situ remote detection,real-time data collection,and minimal destructive to sample.

Laser-induced breakdown spectroscopy as a method for millimeter-scale inspection of surface flatness

A non-contact method for millimeter-scale inspection of material surface flatness via Laser-Induced Breakdown Spectroscopy(LIBS)is investigated experimentally.The experiment is performed using a planished surface of an alloy steel sample to simulate its various flatness,ranging from 0 to 4.4 mm,by adjusting the laser focal plane to the surface distance with a step length of 0.2 mm.It is found that LIBS measurements are successful in inspecting the flatness differences among these simulated cases,implying that the method investigated here is feasible.It is also found that,for achieving the inspection of surface flatness within such a wide range,when univariate analysis is applied,a piecewise calibration model must be constructed.This is due to the complex dependence of plasma formation conditions on the surface flatness,which inevitably complicates the inspection procedure.To solve the problem,a multivariate analysis with the help of Back-Propagation Neural Network(BPNN)algorithms is applied to further construct the calibration model.By detailed analysis of the model performance,we demonstrate that a unified calibration model can be well established based on BPNN algorithms for unambiguous millimeter-scale range inspection of surface flatness with a resolution of about 0.2 mm.

Effects of improved amino acid balance diet on lysine mammary utilization, whole body protein turnover and muscle protein breakdown on lactating sows

Background The study objective was to test the hypothesis that low crude protein(CP)diet with crystalline amino acids(CAA)supplementation improves Lys utilization efficiency for milk production and reduces protein turnover and muscle protein breakdown.Eighteen lactating multiparous Yorkshire sows were allotted to 1 of 2 isocaloric diets(10.80 MJ/kg net energy):control(CON;19.24%CP)and reduced CP with“optimal”AA profile(OPT;14.00%CP).Sow body weight and backfat were recorded on d 1 and 21 of lactation and piglets were weighed on d 1,14,18,and 21 of lactation.Between d 14 and 18,a subset of 9 sows(CON=4,OPT=5)was infused with a mixed solution of 3-[methyl-2H3]histidine(bolus injection)and[13C]bicarbonate(priming dose)first,then a constant 2-h[13C]bicarbonate infusion followed by a 6-h primed constant[1-13C]lysine infusion.Serial blood and milk sampling were performed to determine plasma and milk Lys enrichment,Lys oxidation rate,whole body protein turnover,and muscle protein breakdown.Results Over the 21-d lactation period,compared to CON,sows fed OPT had greater litter growth rate(P<0.05).Compared to CON,sows fed OPT had greater efficiency of Lys(P<0.05),Lys mammary flux(P<0.01)and whole-body protein turnover efficiency(P<0.05).Compared to CON,sows fed OPT tended to have lower whole body protein breakdown rate(P=0.069).Muscle protein breakdown rate did not differ between OPT and CON(P=0.197).Conclusion Feeding an improved AA balance diet increased efficiency of Lys and reduced whole-body protein turnover and protein breakdown.These results imply that the lower maternal N retention observed in lactating sows fed improved AA balance diets in previous studies may be a result of greater partitioning of AA towards milk rather than greater body protein breakdown.

Estimating the grain size of microgranular material using laser-induced breakdown spectroscopy combined with machine learning algorithms

Recent work has validated a new method for estimating the grain size of microgranular materials in the range of tens to hundreds of micrometers using laser-induced breakdown spectroscopy(LIBS).In this situation,a piecewise univariate model must be constructed to estimate grain size due to the complex dependence of the plasma formation environment on grain size.In the present work,we tentatively construct a unified calibration model suitable for LIBS-based estimation of those grain sizes.Specifically,two unified multivariate calibration models are constructed based on back-propagation neural network(BPNN)algorithms using feature selection strategies with and without considering prior information.By detailed analysis of the performances of the two multivariate models,it was found that a unified calibration model can be successfully constructed based on BPNN algorithms for estimating the grain size in the range of tens to hundreds of micrometers.It was also found that the model constructed with a priorguided feature selection strategy had better prediction performance.This study has practical significance in developing the technology for material analysis using LIBS,especially when the LIBS signal exhibits a complex dependence on the material parameter to be estimated.

Phase field model for electric-thermal coupled discharge breakdown of polyimide nanocomposites under high frequency electrical stress

In contrast to conventional transformers, power electronic transformers, as an integral component of new energy power system, are often subjected to high-frequency and transient electrical stresses, leading to heightened concerns regarding insulation failures. Meanwhile, the underlying mechanism behind discharge breakdown failure and nanofiller enhancement under high-frequency electrical stress remains unclear. An electric-thermal coupled discharge breakdown phase field model was constructed to study the evolution of the breakdown path in polyimide nanocomposite insulation subjected to high-frequency stress. The investigation focused on analyzing the effect of various factors, including frequency, temperature, and nanofiller shape, on the breakdown path of Polyimide(PI) composites. Additionally, it elucidated the enhancement mechanism of nano-modified composite insulation at the mesoscopic scale. The results indicated that with increasing frequency and temperature, the discharge breakdown path demonstrates accelerated development, accompanied by a gradual dominance of Joule heat energy. This enhancement is attributed to the dispersed electric field distribution and the hindering effect of the nanosheets. The research findings offer a theoretical foundation and methodological framework to inform the optimal design and performance management of new insulating materials utilized in high-frequency power equipment.

Characteristics of laser-induced breakdown spectroscopy of liquid slag

Rapid online analysis of liquid slag is essential for optimizing the quality and energy efficiency of steel production. To investigate the key factors that affect the online measurement of refined slag using laser-induced breakdown spectroscopy(LIBS), this study examined the effects of slag composition and temperature on the intensity and stability of the LIBS spectra. The experimental temperature was controlled at three levels: 1350℃, 1400℃, and 1450℃. The results showed that slag composition and temperature significantly affected the intensity and stability of the LIBS spectra. Increasing the Fe content and temperature in the slag reduces its viscosity, resulting in an enhanced intensity and stability of the LIBS spectra. Additionally, 42 refined slag samples were quantitatively analyzed for Fe, Si, Ca, Mg, Al, and Mn at 1350℃, 1400℃, and 1450℃.The normalized full spectrum combined with partial least squares(PLS) quantification modeling was used, using the Ca Ⅱ 317.91 nm spectral line as an internal standard. The results show that using the internal standard normalization method can significantly reduce the influence of spectral fluctuations. Meanwhile, a temperature of 1450℃ has been found to yield superior results compared to both 1350℃ and 1400℃, and it is advantageous to conduct a quantitative analysis of the slag when it is in a “water-like” state with low viscosity.

Integrated Experimental and Simulation Investigation of Breakdown Voltage Characteristics Across Electrode Configurations in SF_(6) Circuit Breakers

This study investigates the breakdown voltage characteristics in sulfur hexafluoride(SF6)circuit breakers,employing a novel approach that integrates both experimental investigations and finite element simulations.Utilizing a sphere-sphere electrode configuration,we meticulously measured the relationship between breakdown voltage and electrode gap distances ranging from 1 cm to 4.5 cm.Subsequent simulations,conducted using COMSOL Multiphysics,mirrored the experimental setup to validate the model’s accuracy through a comparison of the breakdown voltage-electrode gap distance curves.The simulation results not only aligned closely with the experimental data but also allowed the extraction of detailed electric field strength,electric potential contours,and electric current flow curves at the breakdown voltage for gap distances extending from 1 to 4.5 cm.Extending the analysis,the study explored the electric field and potential distribution at a constant voltage of 72.5 kV for gap distances between 1 to 10 cm,identifying the maximum electric field strength.A comprehensive comparison of five different electrode configurations(sphere-sphere,sphere-rod,sphere-plane,rod-plane,rod-rod)at 72.5 kV and a gap distance of 1.84 cm underscored the significant influence of electrode geometry on the breakdown process.Moreover,the research contrasts the breakdown voltage in SF6 with that in air,emphasizing SF6’s superior insulating properties.This investigation not only elucidates the intricate dynamics of electrical breakdown in SF6 circuit breakers but also contributes valuable insights into the optimal electrode configurations and the potential for alternative insulating gases,steering future advancements in high-voltage circuit breaker technology.

Self-absorption effects of laser-induced breakdown spectroscopy under different gases and gas pressures

The self-absorption effect is one of the main factors affecting the quantitative analysis accuracy of laser-induced breakdown spectroscopy.In this paper,the self-absorption effects of laserinduced 7050 Al alloy plasma under different pressures in air,Ar,and N2have been studied.Compared with air and N2,Ar significantly enhances the spectral signal.Furthermore,the spectral self-absorption coefficient is calculated to quantify the degree of self-absorption,and the influences of gas species and gas pressure on self-absorption are analyzed.In addition,it is found that the spectral intensity fluctuates with the change of pressure of three gases.It can also be seen that the fluctuation of spectral intensity with pressure is eliminated after correcting,which indicates that the self-absorption leads to the fluctuation of spectral intensity under different pressures.The analysis shows that the evolution of optical thin spectral lines with pressure in different gases is mainly determined by the gas properties and the competition between plasma confinement and Rayleigh–Taylor instability.

A data selection method for matrix effects and uncertainty reduction for laser-induced breakdown spectroscopy

Severe matrix effects and high signal uncertainty are two key bottlenecks for the quantitative performance and wide applications of laser-induced breakdown spectroscopy(LIBS).Based on the understanding that the superposition of both matrix effects and signal uncertainty directly affects plasma parameters and further influences spectral intensity and LIBS quantification performance,a data selection method based on plasma temperature matching(DSPTM)was proposed to reduce both matrix effects and signal uncertainty.By selecting spectra with smaller plasma temperature differences for all samples,the proposed method was able to build up the quantification model to rely more on spectra with smaller matrix effects and signal uncertainty,therefore improving final quantification performance.When applied to quantitative analysis of the zinc content in brass alloys,it was found that both accuracy and precision were improved using either a univariate model or multiple linear regression(MLR).More specifically,for the univariate model,the root-mean-square error of prediction(RMSEP),the determination coefficients(R^(2))and relative standard derivation(RSD)were improved from 3.30%,0.864 and 18.8%to 1.06%,0.986 and 13.5%,respectively;while for MLR,RMSEP,R^(2)and RSD were improved from 3.22%,0.871 and 26.2%to 1.07%,0.986 and 17.4%,respectively.These results prove that DSPTM can be used as an effective method to reduce matrix effects and improve repeatability by selecting reliable data.

Influence of the electrolyte conductivity on the critical current density and the breakdown voltage

The work investigates influence of the electrolyte conductivity on the onset of partial contact glow discharge electrolysis(CGDE)in a water electrolysis.Critical current density(CCD)and breakdown voltage were measured together with in situ observation of hydrogen bubble behavior,whose influence has not been focused on.For a fixed current during normal electrolysis,hydrogen coalescence adjacent to cathode surface was invigorated at a lower conductivity.Photographic analyses elucidated the hydrogen coalescence characteristics by quantifying size and population of detached hydrogen bubbles.The CCD increased about 104% within given range of conductivity(11.50-127.48 mS·cm^(-1))due to impaired bubble coalescence,which delays hydrogen film formation on the cathode.Meanwhile,decreasing trend of breakdown voltage was measured with increased conductivity showing maximum drop of 74%.It is concluded that onset of partial CGDE is directly affected by hydrodynamic bubble behaviors,whereas the electrolyte conductivity affects the bubble formation characteristics adjacent to cathode electrode.

Matrix effect suppressing in the element analysis of soils by laser-induced breakdown spectroscopy with acoustic correction

Laser-induced breakdown spectroscopy(LIBS)has been used for soil analysis,but its measurement accuracy is often influenced by matrix effects of different kinds of soils.In this work,a method for matrix effect suppressing was developed using laser-induced plasma acoustic signals to correct the original spectrum,thereby improving the analysis accuracy of the soil elements.A good linear relationship was investigated firstly between the original spectral intensity and the acoustic signals.The relative standard deviations(RSDs)of Mg,Ca,Sr,and Ba elements were then calculated for both the original spectrum and the spectrum with the acoustic correction,and the RSDs were significantly reduced with the acoustic correction.Finally,calibration curves of MgⅠ285.213 nm,CaⅠ422.673 nm,SrⅠ460.733 nm and BaⅡ455.403 nm were established to assess the analytical performance of the proposed acoustic correction method.The values of the determination coefficient(R~2)of the calibration curves for Mg,Ca,Sr,and Ba elements,corrected by the acoustic amplitude,are improved from 0.9845,0.9588,0.6165,and 0.6490 to 0.9876,0.9677,0.8768,and 0.8209,respectively.The values of R~2 of the calibration curves corrected by the acoustic energy are further improved to 0.9917,0.9827,0.8835,and 0.8694,respectively.These results suggest that the matrix effect of LIBS on soils can be clearly improved by using acoustic correction,and acoustic energy correction works more efficiently than acoustic amplitude correction.This work provides a simple and efficient method for correcting matrix effects in the element analysis of soils by acoustic signals.

Design optimization of high breakdown voltage vertical GaN junction barrier Schottky diode with high-K/low-K compound dielectric structure

A vertical junction barrier Schottky diode with a high-K/low-K compound dielectric structure is proposed and optimized to achieve a high breakdown voltage(BV).There is a discontinuity of the electric field at the interface of high-K and low-K layers due to the different dielectric constants of high-K and low-K dielectric layers.A new electric field peak is introduced in the n-type drift region of junction barrier Schottky diode(JBS),so the distribution of electric field in JBS becomes more uniform.At the same time,the effect of electric-power line concentration at the p-n junction interface is suppressed due to the effects of the high-K dielectric layer and an enhancement of breakdown voltage can be achieved.Numerical simulations demonstrate that GaN JBS with a specific on-resistance(R_(on,sp)) of 2.07 mΩ·cm^(2) and a BV of 4171 V which is 167% higher than the breakdown voltage of the common structure,resulting in a high figure-of-merit(FOM) of 8.6 GW/cm^(2),and a low turn-on voltage of 0.6 V.

Detection and quantification of Pb and Cr in oysters using laser-induced breakdown spectroscopy

The quantitative determination of heavy metals in aquatic products is of great importance for food security issues.Laser-induced breakdown spectroscopy(LIBS)has been used in a variety of foodstuff analysis,but is still limited by its low sensitivity when targeting trace heavy metals.In this work,we compare three sample enrichment methods,namely drying,carbonization,and ashing,for increasing detection sensitivity by LIBS analysis for Pb and Cr in oyster samples.The results demonstrate that carbonization can remove a significant amount of the contributions of organic elements C,H,N and O;meanwhile,the signals of the metallic elements such as Cu,Pb,Sr,Ca,Cr and Mg are enhanced by3–6 times after carbonization,and further enhanced by 5–9 times after ashing.Such enhancement is not only due to the more concentrated metallic elements in the sample compared to the dried ones,but also the unifying of the matter in carbonized and ashed samples from which higher plasma temperature and electron density are observed.This condition favors the detection of trace elements.According to the calibration curves with univariate and multivariate analysis,the ashing method is considered to be the best choice.The limits of detection of the ashing method are 0.52 mg kg-1 for Pb and0.08 mg kg-1 for Cr,which can detect the presence of heavy metals in the oysters exceeding the maximum limits of Pb and Cr required by the Chinese national standard.This method provides a promising application for the heavy metal contamination monitoring in the aquatic product industry.

Nonlinear perturbation of a high-order exceptional point:Skin discrete breathers and the hierarchical power-law scaling

We study the nonlinear perturbation of a high-order exceptional point(EP)of the order equal to the system site number L in a Hatano-Nelson model with unidirectional hopping and Kerr nonlinearity.Notably,we find a class of discrete breathers that aggregate to one boundary,here named as skin discrete breathers(SDBs).The nonlinear spectrum of these SDBs shows a hierarchical power-law scaling near the EP.Specifically,the response of nonlinear energy to the perturbation is given by E_(m)∝Γ~(α_(m)),whereα_(m)=3^(m-1)is the power with m=1,...,L labeling the nonlinear energy bands.This is in sharp contrast to the L-th root of a linear perturbation in general.These SDBs decay in a double-exponential manner,unlike the edge states or skin modes in linear systems,which decay exponentially.Furthermore,these SDBs can survive over the full range of nonlinearity strength and are continuously connected to the self-trapped states in the limit of large nonlinearity.They are also stable,as confirmed by a defined nonlinear fidelity of an adiabatic evolution from the stability analysis.As nonreciprocal nonlinear models may be experimentally realized in various platforms,such as the classical platform of optical waveguides,where Kerr nonlinearity is naturally present,and the quantum platform of optical lattices with Bose-Einstein condensates,our analytical results may inspire further exploration of the interplay between nonlinearity and non-Hermiticity,particularly on high-order EPs,and benchmark the relevant simulations.

Microwave-Assisted Transition Metal Nanostructure Synthesis: Power-Law Signature Verification

A power-law (y = cxn) signature between process energy budget (kJ) and process energy density (kJ·ml-1) of microwave-assisted synthesis of silver and gold nanostructures has been recently described [Law and Denis. AJAC, 14(4), 149-174, (2023)]. This study explores this relation further for palladium, platinum, and zinc oxide nanostructures. Parametric cluster analysis and statistical analysis is used to test the power-law signature of over four orders of magnitude as a function of six microwave applicator-types metal precursor, non-Green Chemistry synthesis and claimed Green Chemistry. It is found that for the claimed Green Chemistry, process energy budget ranges from 0.291 to 900 kJ, with a residual error ranging between −33 to +25.9 kJ·ml-1. The non-Green Chemistry synthesis has a higher process energy budget range from 3.2 kJ to 3.3 MJ, with a residual error of −33.3 to +245.3 kJ·ml-1. It is also found that the energy profile over time produced by software controlled digestion applicators is poorly reported which leads to residual error problematic outliers that produce possible phase-transition in the power-law signature. The original Au and Ag database and new Pd, Pt and ZnO database (with and without problematic outliers) yield a global microwave-assisted synthesis power-law signature constants of c = 0.7172 ± 0.3214 kJ·ml-1 at x-axes = 0.001 kJ, and the exponent, n = 0.791 ± 0.055. The information in this study is aimed to understand variations in historical microwave-assisted synthesis processes, and develop new scale-out synthesis through process intensification.

基极触发的雪崩晶体管导通机理

为研究基极触发的雪崩晶体管导通机理,建立了雪崩晶体管(n+⁃p⁃n⁃n+掺杂结构)的准三维器件模型和实验测试电路。研究了雪崩晶体管的温度分布特征,导通结束后器件最高温度约为417 K,位于电流通道内n⁃n+边界处。当集电极电压为300 V、基极触发电压为2.4 V时,仿真和实验获得的脉冲上升时间分别为2.4 ns、2.5 ns,半高宽(FWHM)分别为6.2 ns、5.8 ns,仿真和实验结果基本一致。研究结果表明:高触发脉冲电压幅值会加速晶体管内部电场的重建过程,从而缩短延迟时间,提高晶体管响应速度;负载阻抗会影响器件导通通道尺寸,负载阻抗减小时,电流密度提升,器件通过缩窄通道来提高通道内电流密度,宏观导通电阻降低。

LIBS结合图像筛选方法提高钢铁中Cu、Cr、Mn元素检测稳定性研究

优质特种钢材和低端粗钢之间的性能差异主要受其构成元素种类及其成分含量的影响,因此,如何快速准确地对物质成分进行定性及定量分析对钢铁产品的质量评估至关重要。针对传统方法难以实现对钢铁合金成分的快速准确检测的难题,采用激光诱导击穿光谱(LIBS)结合等离子体图像信息的方法,通过快速地对不同元素的特征光谱强度与激发生成的等离子体图像进行采集,分析两者之间的相关性,并通过提取的图像特征信息的异常值剔除了部分无效光谱数据,进而实现了对钢铁成分的高精度分析。通过分析延迟时间和激光能量等不同实验条件对元素特征光谱强度及其对应等离子体图像的影响规律,不仅证明了等离子体图像与光谱之间存在相关性,还利用等离子体图像特征信息的局部最优值确定了最优延迟时间、激光能量分别为1000 ns与50 mJ,并根据图像特征的平均阈值来筛选无效光谱数据。结果表明,图像筛选优化数据后,各元素谱线校准模型的决定系数(R^(2))分别从原始数据的0.978、0.986、0.957、0.935提升至0.995、0.997、0.968、0.957,且其定标曲线对未知样品元素的预测浓度相对标准偏差(RSD)下降为原始数据预测浓度RSD的50%左右。由此可知采用LIBS结合图像筛选方法可以减少定量分析的误差,提高预测结果精确度。