Analysis of gamma-ray spectra by using fast Fourier transform (author's transl)]

In order to simplify the mass data processing in a response matrix method for gamma-ray spectral analysis, a method using a Fast Fourier Transform devised. The validity of the method was confirmed by a computer simulation for spectra of a NaI detector. The method uses the fact that spectral data can be represented by Fourier series with reduced number of terms. The estimation of intensities of gamma-ray components is performed by a matrix operation using the compressed data of an observation spectrum and standard spectra in Fourier coefficients. The identification of gamma-ray energies is also easy. Several features in the method and a general problem to be solved in a response matrix method are described.     

Performance evaluation of spectral deconvolution analysis tool (SDAT) software used for nuclear explosion radionuclide measurements

The Spectral Deconvolution Analysis Tool (SDAT) software was developed to improve counting statistics and detection limits for nuclear explosion radionuclide measurements. SDAT utilizes spectral deconvolution spectroscopy techniques and can analyze both β-γ coincidence spectra for radioxenon isotopes and high-resolution HPGe spectra from aerosol monitors. Spectral deconvolution spectroscopy is an analysis method that utilizes the entire signal deposited in a gamma-ray detector rather than the small portion of the signal that is present in one gamma-ray peak. This method shows promise to improve detection limits over classical gamma-ray spectroscopy analytical techniques; however, this hypothesis has not been tested. To address this issue, we performed three tests to compare the detection ability and variance of SDAT results to those of commercial-off-the-shelf (COTS) software which utilizes a standard peak search algorithm.     

Precise determination of macro contents of nitrogen in titanium carbonitride by instrumental photon activation analysis

SYNTH, a Windows^TM based software package developed for generating synthetic gamma-ray spectra, has been updated and extended to include the ability to generate gamma-ray spectra resulting from neutron activation. Along with a new gamma-ray library (based on the NNDC PCNuDat compilation), and the best available neutron cross-sections, it is now possible to simply, and quickly predict the interference effects of different bulk and trace element compositions by generating a synthetic gamma-ray spectrum that will be representative of a specific set of input parameters. The parameters include, but are not limited to: elemental composition (bulk, and trace) of the sample; irradiation, decay, and count times; thermal, and resonance neutron flux; sample to detector distance; detector specifications; and electronics configuration. Using existing data reduction codes, it is then possible to generate Minimum Detectable Activities (MDA's) for other trace elements that you may wish to detect in this type of matrix.     

Ground‐State and Excitation Spectra of a Strongly Correlated Lattice by the Coupled Cluster Method

The coupled cluster method is applied to a strongly correlated lattice Hamiltonian, and the coupled cluster linear response method is extended to the calculation of electronic spectra by finding an approximation to a resolvent operator which describes the spectral response of the coupled cluster solution to excitation operators. In this spectral coupled cluster method, the ground and excited states appear as resonances in the spectra, and the resolvent can be iteratively improved in selected spectral regions. The method is applied to a MnO₂ plane model which corresponds to previous experimental works.     

A new approach to near-infrared spectral data analysis using independent component analysis

This paper presents a new approach to near-infrared spectral (NIR) data analysis that is based on independent component analysis (ICA). The main advantage of the new method is that it is able to separate the spectra of the constituent components from the spectra of their mixtures. The separation is a blind operation, since the constituent components of mixtures can be unknown. The ICA based method is therefore particularly useful in identifying the unknown components in a mixture as well as in estimating their concentrations. The approach is introduced by reference to case studies and compared to other techniques for NIR analysis including principal component regression (PCR), multiple linear regression (MLR), and partial least squares (PLS) as well as Fourier and wavelet transforms.     

New Lutetium Silicate Scintillators

Cerium-doped lutecium orthosilicate (LSO) is the most promising scintillator discovered in almost five decades. It exhibits a unique combination of important properties for x and gamma-ray spectroscopy: high density, fast decay, and large light yield. However, the practical use of LSO is hindered by difficulties related to its fabrication as a single crystal by the Czochralski method. We report on the usefulness of the sol-gel process in obtaining lutecium silicate scintillators. Upon appropriate drying and firing, lutetium silicate crystals can be grown in a silica matrix. The bulk, polycrystalline transparent scintillators are characterized by XRD, optical absorption, light decay measurement and gamma-ray spectral response. Their properties are comparable to that of traditional LSO single crystals.     

Curve-fitting of Fourier manipulated spectra comprising apodization, smoothing, derivation and deconvolution

We present a general method for curve-fitting Fourier manipulated spectra, comprising apodized, smoothed, derivatised and deconvoluted spectra. The analytical expressions of Fourier manipulated bands in the spectral domain, needed for the curve-fitting, are usually very complex or do not even exist; hence an accurate curve-fit of Fourier manipulated spectra becomes unfeasible. Our strategy is to construct both the model and their derivatives in the Fourier domain, where they have simple and general expressions, and then Fourier transform them back to the spectral domain. The first benefit of this approach is the accurate curve-fitting of Fourier deconvoluted spectra, a main step in the secondary structure estimation of proteins by FTIR spectroscopy.     

Analysis of gamma-ray spectra from an aircraft-mounted array of high-resolution sensors

Gamma-ray spectra have been collected using the Environmental Radionuclide Sensor System.². Twenty aircraft-mounted, high-purity germanium sensors are utilized to collect high-resolution environmental spectra. Since time-over-target is limited for aerial surveys, one must often attempt to glean the maximum quantity of information from low-count spectra. The spectral data are collected in a time-stamped-list-mode, which time tags every gamma-ray. This allows a gamma-ray spectrum to be built without dilution for only the time-over-target. The analysis package utilizes photopeaks from natural background isotopes to autocalibrate and gain shift the individual spectra into a composite spectrum. The analysis software utilizes several unique techniques to robustly analyze low-count spectra. It carefully determines the spectral baseline, finds all the peaks which differ from the baseline by more than 4-standard deviations, uses a binary-search technique to fit Gaussian peaks, and utilizes a large library to identify peaks (including minor and escape peaks). Although in an aerial survey, the source geometry is often unknown or difficult to model, the software attempts to assign consistent source strengths to radionuclides. *** DIRECT SUPPORT *** A00E1009 00008     

A dual purpose Compton suppression spectrometer

A gamma-ray spectrometer with a passive and an active shield is described. It consists of a HPGe coaxial detector of 42% efficiency and 4 NaI(Tl) detectors. The energy output pulses of the Ge detector are delivered into the 3 spectrometry chains giving the normal, anti- and coincidence spectra. From the spectra of a number of ¹³⁷Cs and ⁶⁰Co sources a Compton suppression factor, SF and a Compton reduction factor, RF, as the parameters characterizing the system performance, were calculated as a function of energy and source activity and compared with those given in literature. The natural background is reduced about 8 times in the anticoincidence mode of operation, compared to the normal spectrum which results in decreasing the detection limits for non-coincident gamma-rays up to a factor of 3. In the presence of other gamma-ray activities, in the range from 5 to 11 kBq, non- and coincident, the detection limits can be decreased for some nuclides by a factor of 3 to 5.7.     

Automated mass analysis of low-molecular-mass bacterial proteome by liquid chromatography-electrospray ionization mass spectrometry

Due to the presence of a large number of proteins in cell extracts, ion chromatograms of cell extracts obtained by electrospray ionization mass spectrometry (ESI-MS) can be quite complicated. It is found that the elevated baseline in an ion chromatogram contains many protein signals. One deficiency of current commercially available LC-ESI-MS data interpretation software is found to be the lack of functional operation that allows automated mass spectral integration and interpretation over signals hidden in the baseline. This current limitation can be overcome by a technique that involves the introduction of artificial pulses to an ion chromatogram by removing the solvent mixer in the HPLC pump. These artificial pulses are treated as chromatographic peaks by the software, thereby allowing automated spectral integration over the duration of a pulse. The reliability of mass analysis from the integrated spectra is shown to be dependent on spectral interpretation parameters such as mass spectral baseline threshold. The application of this method is demonstrated for rapid detection and mass analysis of low-molecular-mass proteins from cell extracts of Escherichia coli or Bacillus globigii.     

Dechaos — A program for automatic or interactive analysis of gamma-ray spectra

DECHAOS is a gamma-ray spectral analysis program for personal computers. The program offers two modes of operation, automatic or interactive. The spectra to be analyzed can be acquired using any pulse height analyzer. The program includes routines for energy calibration, peak shape and efficiency calibration. Complex multiplets can be resolved automatically with the peak areas being determined using least-squares fitting techniques. Output tables include all data used in the calculation and peak information. The program is public domain software.     

Estimation of component spectra by the principal components method

The principal components method enables component spectra from pigment mixtures to be estimated by evaluating the eigenvectors of the second moment matrix. The components are linear combinations of these eivenvectors, but cannot be identified unambiguously. With the conditions of non-negativity of spectral values and of concentrations, this ambiguity can be limited; components spectra for 2 and 3 components were calculated earlier. In the present work, maximal dissimilarity of component spectra is assumed as a further condition. An algorithm based on linear programming is described; it enables any number of components to be estimated from eigenvectors of the second moment matrix with better reliability than previously.     

Automated parameter optimization in modeling absorption spectra and resonance Raman excitation profiles

An automated method is described for optimizing the molecular parameters in simultaneous modeling of optical absorption spectra and resonance Raman excitation profiles. The method utilizes a previously developed Fortran routine that calculates absorption spectra and Raman excitation profiles for polyatomic molecules in solution from a model for the potential energy surfaces and spectral broadening mechanisms. It is combined here with an optimization routine from the commercial MATLAB package that iteratively adjusts the parameters of the molecular model to minimize the least-squared error between calculated and experimental spectra. Optimizations that typically require days to weeks of human time when performed interactively can be accomplished automatically in less than an hour of computer time. The method can handle large molecules (we show results for as many as 23 Raman-active modes) and mixtures of spectral broadening mechanisms (lifetime, Brownian oscillator, and inhomogeneous), and is robust toward noise or missing data points.     

Status of the Monte Carlo library least-squares (MCLLS) approach for non-linear radiation analyzer problems

The Center for Engineering Applications of Radioisotopes (CEAR) has been working for over a decade on the Monte Carlo library least-squares (MCLLS) approach for treating non-linear radiation analyzer problems including: (1) prompt gamma-ray neutron activation analysis (PGNAA) for bulk analysis, (2) energy-dispersive X-ray fluorescence (EDXRF) analyzers, and (3) carbon/oxygen tool analysis in oil well logging. This approach essentially consists of using Monte Carlo simulation to generate the libraries of all the elements to be analyzed plus any other required background libraries. These libraries are then used in the linear library least-squares (LLS) approach with unknown sample spectra to analyze for all elements in the sample. Iterations of this are used until the LLS values agree with the composition used to generate the libraries. The current status of the methods (and topics) necessary to implement the MCLLS approach is reported. This includes: (1) the Monte Carlo codes such as CEARXRF, CEARCPG, and CEARCO for forward generation of the necessary elemental library spectra for the LLS calculation for X-ray fluorescence, neutron capture prompt gamma-ray analyzers, and carbon/oxygen tools; (2) the correction of spectral pulse pile-up (PPU) distortion by Monte Carlo simulation with the code CEARIPPU; (3) generation of detector response functions (DRF) for detectors with linear and non-linear responses for Monte Carlo simulation of pulse-height spectra; and (4) the use of the differential operator (DO) technique to make the necessary iterations for non-linear responses practical. In addition to commonly analyzed single spectra, coincidence spectra or even two-dimensional (2-D) coincidence spectra can also be used in the MCLLS approach and may provide more accurate results.     

傅利叶变换光谱技术中的"折叠假线"研究

根据奈奎斯特(Nyquist)采样定理,解释了傅利叶变换光谱采集过程中由于折叠而出现的假线现象,并且对假线的特点进行了预测,进而总结出实验过程中利用光学滤波器和电子学滤波器来防止假线,同时兼顾信噪比的实验参数设置方法.经实验证实,这套方法是行之有效的.     

A Geant4 Monte Carlo method for synthesizing radioxenon beta-gamma coincidence spectra

This paper describes a Monte Carlo (MC) simulation method for calculating radioxenon beta-gamma coincidence spectral information. These spectral components include detector response simulations by Geant4 modeling, detector energy and resolution calibrations using the histograms of detector response, beta-gamma coincidence efficiency values and spectral interference ratios. The work presented in this paper demonstrates the feasibility of using the spectral information to create beta-gamma coincidence spectra at various radioxenon activity concentrations. The analysis of these synthetic spectra by XECON software shows an excellent correlation between the analysed radioxenon activity concentration and number of MC samplings.     

一种面向多组分定量的通用谱图解析方法

在一个多组分系统中各组分的定量分析是非常重要的。现代光谱如拉曼光谱(RS)、傅里叶变换红外(FT-IR)光谱、紫外-可见(UV-Vis)光谱、核磁共振(NMR)、质谱(MS)等,可通过获取丰富峰信号的谱图对样品进行各角度的详尽描述。然而,由于谱图的复杂性及其解析工作的繁重,使得仅通过样品谱图来同时量化混合物中的每个组分成为很具挑战性的工作。在这项研究中,我们首次介绍了一个名为定量主成分分析(q PCA)的可靠策略,快速计算混合物中每个成分的比例,而不需要任何手动解谱。通过使用纯组分的谱图作为参考,多组分系统的谱图可以通过PCA自动分辨并解析,然后就可以使用我们的计算方法来计算每个组分的比例。计算机建模实验和RS、FT-IR、UV-Vis、NMR、MS实验都证明了这一策略胜任多组分系统的快速定量工作。     

Generation of response functions of a NaI detector by using an interpolation technic

A computer method is developed for generating response functions of a NaI detector to monoenergetic gamma-rays. The method is based on an interpolation between measured response curves by a detector. The computer programs are constructed for Heath's response spectral library. The principle of the basic mathematics used for interpolation, which was reported previously by the author, et al., is that response curves can be decomposed into a linear combination of intrinsic-component patterns, and thereby the interpolation of curves is reduced to a simple interpolation of weighting coefficients needed to combine the component patterns. This technique has some advantages of data compression, reduction in computation time, and stability of the solution, in comparison with the usual functional fitting method. The processing method of segmentation of a spectrum is devised to generate useful and precise response curves. A spectral curve, obtained for each gamma-ray source, is divided into some regions defined by the physical processes, such as the photopeak area, the Compton continuum area, the backscatter peak area, and so on. Each segment curve then is processed separately for interpolation. Lastly the estimated curves to the respective areas are connected on one channel scale. The generation programs are explained briefly. It is shown that the generated curve represents the overall shape of a response spectrum including not only its photopeak but also the corresponding Compton area, with a sufficient accuracy.     

Performance and robustness of a multi-user, multi-spectrometer system for INAA

The laboratory for instrumental neutron activation analysis at the Reactor Institute Delft, Delft University of Technology uses a network of 3 gamma-ray spectrometers with well-type detectors and 2 gamma-ray spectrometers with coaxial detectors, all equipped with modern sample changers, as well as 2 spectrometers with coaxial detectors at the two fast rabbit systems. A wide variety of samples is processed through the system, all at specific optimized (and thus different) analytical protocols, and using different combination of the spectrometer systems. The gamma-ray spectra are analyzed by several qualified operators. The laboratory therefore needs to anticipate on the occurrence of random and systematic inconsistencies in the results (such as bias, non-linearity or wrong assignments due to spectral interferences) resulting from differences in operator performance, selection of analytical protocol and experimental conditions. This has been accomplished by taking advantage of the systematic processing of internal quality control samples such as certified reference materials and blanks in each test run. The data from these internal quality control analyses have been stored in a databank since 1991, and are now used to assess the various method performance indicators as indicators for the method’s robustness.