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• Non-invasive composition determination from six different measurements experimentally verified. • Composition determination from density data most accurate and robust. • Data from system level heat pump testing sufficient for rapid mixture model evaluation. • REFPROP mixture models for R-1234yf/1233zd(E), R-1234yf /1336mzz(Z), R32/1224yd(Z) and several ternary mixtures thereof proven useful for system level design. Refrigerant mixtures are frequently used in air-conditioners and heat pumps. However, mixtures with high glides of 30 K and more during evaporation are rare, partially because there is an increased concern about composition shifts within the system. An easy and reliable inline composition measurement could alleviate these concerns and simplify the handling of systems with high-glide mixtures. This study investigates six composition determination methods, which are all non-invasive, five of which can be conducted during system operation. All methods were applied to all available mixtures in a dataset of 380 data points. The binary and ternary mixtures tested consist of the refrigerants R-1233zd(E), R-1336mzz(Z), R-1234yf, R-1224yd(Z), and R-32. Each method was applied to all datapoints collected with a certain refrigerant mixture at varying operating conditions. The average of the calculated mass fraction was then compared to the manually charged mass fraction. For the density method, this difference of the calculated and measured mass fraction was always less than 0.03 and usually smaller than 0.01 across all tested mixtures. Most other methods performed well with deviations typically less than 0.05. Some of the methods require only low-cost sensors like thermocouples and pressure transducers. Property data of ternary mixtures is also discussed in the study but a composition determination, theoretically possible combining any two of the six methods, is not attempted in this study. [ABSTRACT FROM AUTHOR]

By selecting extraction method and determining the content of polysaccharide of S. lonicericola, the polysaccharide extraction method with high extraction rate and the optimal conditions were selected. The results showed that ultrasonic assisted enzymatic method had a higher yield than water bath assisted solvent extraction method and microwave-assisted extraction method. The optimal extraction conditions were solid-liquid ratio of 1: 20 (g: mL), ultrasonic extraction time of 40 min, ultrasonic power of 300 W, the enzyme dosage of 0.15%. Under these conditions, the yield of polysaccharide from mycelial of S. lonicericola was (6.58±0.01) %. By HPLC external standard method, the main monosaccharide components of S. lonicericola mycelial polysaccharide were mannose, glucosamine, ribose, rhamnose, glucuronic acid, galacturonic acid, amino galactose, glucose, galactose, xylose, arabinose and fucose. Through oxidation-reduction analysis of S. lonicericola mycelial polysaccharide, it was found that S. lonicericola mycelial polysaccharide had certain antioxidant capacity, but compared to VC, the antioxidant effect of S. lonicericola mycelial polysaccharide was slightly weaker. [ABSTRACT FROM AUTHOR]

A great research effort is involved in polyhydroxyalkanoates (PHAs) production and characterization since they are an attractive degradable polyester family that potentially could substitute oil-based polymers. This is due to two main key factors: their production is sustainable, being that they are produced by microorganisms possibly fed by organic waste-derived products, and they are degradable. Moreover, PHAs' thermal and mechanical properties could be tuned by varying their monomeric composition through the proper selection of microorganism feedstock and bioreactor operative conditions. Hence, a rapid and facile determination of the PHA chemical structure by widely available instrumentation is useful. As an alternative to the standard gas-chromatographic method, a new procedure for the composition determination of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (P3HBV), the most common PHA copolymer, by attenuated total reflection FTIR (ATR-FTIR) is presented. It is based on the linear dependence of selected and normalized absorption band intensity with the molar fraction of repeating units. To break free from the crystallinity variability, which affects the result reproducibility and data scattering, the polymer sample was rapidly quenched from the melt directly on the surface of the ATR internal reflection element and analyzed. The data obtained from 14 samples with a molar fraction of 3-hydroxybutyrate repeating units (X3HB) ranging from 0.15 to 1 were analyzed. According to preliminary analyses, the normalized intensity of two absorption bands was selected to develop a calibration method able to predict X3HB of unknown samples and to evaluate the related uncertainty through prediction intervals of inverse regression. The proposed method proves to be useful for an easy and rapid estimation of P3HBV composition. [ABSTRACT FROM AUTHOR]

This paper mainly introduces the experiment implementation process, results and extension issues in the synthesis and composition determination part of the inorganic and analytical chemistry laboratory project, the synthesis of the complex [Ni(Me3en)(acac)]BPh4 and its solvato/thermochromic behavior research experiment, designed by Nanjing University for the 10th National Undergraduate Chemistry Laboratory Tournament. Based on the detailed and intuitive synthetic experimental process shown, we focus on the two major goals of synthesis, the "quality" and the "quantity", i.e., guided by how to obtain both "good" and "more" [Ni(Me3en)(acac)]BPh4 complex. By asking questions and discussing, we instruct students to understand the experimental process. Through the above process, the students are guided to understand the significance of the control of experimental conditions, the analysis of experimental phenomena and the separation, analysis and identification of intermediate products and impurities in the process of synthesis. As a result, students can develop the ability of analysis, judgment, induction, summarizing and critical thinking. [ABSTRACT FROM AUTHOR]

Abstract Background Bioassessment and biomonitoring of meat products are aimed at identifying and quantifying adulterants and contaminants, such as meat from unexpected sources and microbes. Several methods for determining the biological composition of mixed samples have been used, including metabarcoding, metagenomics and mitochondrial metagenomics. In this study, we aimed to develop a method based on next-generation DNA sequencing to estimate samples that might contain meat from 15 mammalian and avian species that are commonly related to meat bioassessment and biomonitoring. Results In this project, we found the meat composition from 15 species could not be identified with the metabarcoding approach because of the lack of universal primers or insufficient discrimination power. Consequently, we developed and evaluated a meat mitochondrial metagenomics (3MG) method. The 3MG method has four steps: (1) extraction of sequencing reads from mitochondrial genomes (mitogenomes); (2) assembly of mitogenomes; (3) mapping of mitochondrial reads to the assembled mitogenomes; and (4) biomass estimation based on the number of uniquely mapped reads. The method was implemented in a python script called 3MG. The analysis of simulated datasets showed that the method can determine contaminant composition at a proportion of 2% and the relative error was

Polyethylene (PE) and polypropylene (PP) are among the most recycled polymers. However, these polymers present similar physicochemical characteristics and cross-contamination between them is commonly observed, affecting the quality of the recyclates. With the increasing demand for recycled plastics, understanding the composition of these materials is crucial. Numerous techniques have been introduced in the literature to determine the composition of recycled plastics. An ideal technique should be accessible, cost-efficient, fast, and accurate. Differential Scanning Calorimetry (DSC) emerges as a suitable technique since it analyzes the thermal behavior of compounds under controlled time and temperature conditions, entitling the quantitative determination of each component, e.g., in PE/PP blends. Nevertheless, the existing predictive methods lack accuracy in estimating the composition of PE/PP blends from DSC analysis since the composition of this blend affects its overall crystallinity. This study advances the state-of-the-art regarding this quantification using DSC by implementing a non-linear calibration curve correlating the evolutions of crystallinity with blend composition. Additionally, a machine-learned (ML) model is introduced and validated, achieving high accuracy for the composition determination, presenting an overall mean absolute error as low as 1.0 wt%. Notably, this ML-assisted approach can also quantify the content of subcategory polymers, enhancing its utility. • Composition of PE/PP blends can be quantified with high accuracy via DSC. • Crystallinity of constituents changes nonlinearly with composition in PE/PP blends. • Machine-learned models improve the accuracy of composition determination via DSC. • Content of subcategory polymers also can be quantified via machine-learned models. [ABSTRACT FROM AUTHOR]

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Arc plasmas have been extensively studied, experimentally and by means of modeling, due to their wide range of applications. In this article, a calibration-free Boltzmann plot method was applied to measure the species composition and pressure in the arc plasmas based on the assumption of local thermodynamic equilibrium and only single ionization of atoms. Experiments were performed on the argon free-burning arcs at two different pressures. Firstly, several Ar I and Ar II spectral lines were utilized to draw the Boltzmann plot. Then, the plasma temperatures were obtained by three different methods, the Boltzmann plot method, two-line Saha–Boltzmann plot method, and the Fowler–Milne method. The species concentration was calculated using the intercepts with ordinate in the Boltzmann plot. Combined with the electron number density determined from the Stark broadening of Ar I 696.54 nm, arc pressures are calculated based on the equation of state. The measured species concentration and pressures are in good agreement with the theoretical results, indicating that the used method is reliable for further arc plasma applications. [ABSTRACT FROM AUTHOR]

The aim is development of a single model of various processes for the thermal processing of organic substances. The possibility of determining the composition of substances in the process of their processing in real time is taken into account. It is possible to take into account the different phase state of the feedstock. The model is based on the method of calculating the processes of fuel combustion in liquid rocket engines. In the earlier studies, a comparison was made of the results of calculations based on it with the available data for the case of methane and ethyl alcohol burning in air. The proposed model is distinguished by the possibility of taking into account the composition of the reaction products in the condensed phase in the form of a carbonaceous residue. Its presence accompanies the pyrolysis process. The composition of the products of the process of slow pyrolysis of pine wood is calculated. The results are compared with the available data. To determine the unknown composition of the feedstock, the previously developed model for the case of gaseous presentation is used. As a result, the gross formula of the gaseous fuel is determined. The peculiarity of the process under consideration is the need to ensure isoenthalpy of the combustion process. Such a condition can be provided in a rocket type combustion chamber with regenerative cooling. It is noted that the results obtained in this way can be extended to the case of various types of combustible substances in a condensed state. The developed model of thermal conversion and, on its basis, a method for determining the unknown composition of heterophasic organic combustible substances can be used in the processing of various alternative types of combustible, industrial, and household waste. The real-time determination of their variable composition may allow the organization of a controlled process of burning them. As a result of the work: a single model is selected and adapted to solve the problems of combustion, gasification and slow pyrolysis with a known composition of the initial hydrocarbon substances; results of calculations based on it are given; A method for determining the real-time composition of the hydrocarbon component of combustible substances in various states of aggregation is proposed. [ABSTRACT FROM AUTHOR]

• Local determination of thickness and composition for ternary III-V semiconductors. • Method requires one STEM image and complementary image simulations only. • Feasibility of method is proven by application to simulated STEM image. • Influence of detector angle and specimen thickness on results is investigated. • Good agreement of experimentally derived concentration of Ga(AsBi) with XRD results. Scanning transmission electron microscopy (STEM) is a suitable method for the quantitative characterization of nanomaterials. For an absolute composition determination on an atomic scale, the thickness of the specimen has to be known locally with high accuracy. Here, we propose a method to determine both thickness and composition of ternary III-V semiconductors locally from one STEM image as shown for the example material systems Ga(AsBi) and (GaIn)As. In a simulation study, the feasibility of the method is proven and the influence of specimen thickness and detector angles used is investigated. An application to an experimental STEM image of a Ga(AsBi) quantum well grown by metal organic vapour phase epitaxy yields an excellent agreement with composition results from high resolution X-ray diffraction. [ABSTRACT FROM AUTHOR]

• An extension of the established procedure that is used to determine compositions of materials by comparing STEM multislice simulations to experimental images is presented. • A comprehensive investigation of the capabilities and limitations of the extended method is presented. • The question whether single-atom accuracy is achievable is addressed. • Three technologically important semiconductor samples were used to prove the applicability of the method. This paper presents a comprehensive investigation of an extended method to determine composition of materials by scanning transmission electron microscopy (STEM) high angle annular darkfield (HAADF) images and using complementary multislice simulations. The main point is to understand the theoretical capabilities of the algorithm and address the intrinsic limitations of using STEM HAADF intensities for composition determination. A special focus is the potential of the method regarding single-atom accuracy. All-important experimental parameters are included into the multislice simulations to ensure the best possible fit between simulation and experiment. To demonstrate the capabilities of the extended method, results for three different technical important semiconductor samples are presented. Overall the method shows a high lateral resolution combined with a high accuracy towards single-atom accuracy. [ABSTRACT FROM AUTHOR]

Technological control of nitration of organic compounds needs data about a composition of acid nitrating mixture before and after nitration. Content of water is a crucial factor for efficiency and safety of the nitration process. The industrial laboratories demands for fast, accurate, precise, low cost and easy to maintain analytical methods. This paper presents the development of a protocol for determination of composition of acid nitrating mixture. The determination of nitric acid is based on redox back titration. Determination of sulfuric acid is based on direct precipitation titration. Water content is determined by calculation. The proposed method showed good accuracy, precision and selectivity, with recoveries (99.80±0.06)% H2SO4 and (98.91±0,80)% HNO3,and total analysis time 20 min..

Standard high resolution 13C NMR spectra of PA10T, PA6T, PA106, and PA66 were obtained by a nonacidic solvent mixture of HFIP and CDCl3. Several chemical shifts were found extremely sensitive to the polyamide type. According to the standard spectra, semi-aromatic copolyamides comprising PA10T, PA6T, PA106, and PA66 units could be distinguished. The ratio of each polyamide component in the copolyamide was determined through the integration of the methylene carbon peak associated with the amine group. 13C NMR analysis results were consistent with the theoretical values and copolyamide hydrolysis test results, making 13C NMR analysis quite reliable on the quick composition analysis of semi-aromatic copolyamides. Based on this technique, several commercial semi-aromatic copolyamides were further examined and their compositions were easily determined. [ABSTRACT FROM AUTHOR]

This paper demonstrates two different pretreatment protocols for oil palm trunks (OPT); steam-alkali-chemical (SAC) and microwave-alkali (Mw-A) method. The composition, morphology, structure and crystallinity of OPT before and after pretreatment were analyzed. The effectiveness of the pretreated methods was investigated by performing enzymatic saccharification on the OPT. The physiochemical factors namely: enzyme ratio (cellulase to β-glucosidase), pH, temperature and substrate loading (w/v) on enzymatic saccharification were also investigated. The pre-determined optimal conditions were then used for further enzymatic hydrolysis of raw and pretreated OPT substrates. The results revealed a huge degree of reduction in lignin, up to 89% for SAC treated OPT and at least 15% for Mw-A treated OPT sample as compared to untreated ones. High glucose accumulation (79.4%) was obtained after 72 h saccharification for both pretreated OPT samples. [ABSTRACT FROM AUTHOR]

Nitride-based three-dimensional core-shell nanorods (NRs) are promising candidates for the achievement of highly efficient optoelectronic devices. For a detailed understanding of the complex core-shell layer structure of InGaN/GaN NRs, a systematic determination and correlation of the structural, compositional, and optical properties on a nanometer-scale is essential. In particular, the combination of low-temperature cathodoluminescence (CL) spectroscopy directly performed in a scanning transmission electron microscope (STEM), and quantitative high-angle annular dark field imaging enables a comprehensive study of the nanoscopic attributes of the individual shell layers. The investigated InGaN/GaN core-shell NRs, which were grown by metal-organic vapor-phase epitaxy using selective-area growth exhibit an exceptionally low density of extended defects. Using highly spatially resolved CL mapping of single NRs performed in cross-section, we give a direct insight into the optical properties of the individual core-shell layers. Most interesting, we observe a red shift of the InGaN single quantum well from 410 to 471 nm along the nonpolar side wall. Quantitative STEM analysis of the active region reveals an increasing thickness of the single quantum well (SQW) from 6 to 13 nm, accompanied by a slight increase of the indium concentration along the nonpolar side wall from 11% to 13%. Both effects, the increased quantum-well thickness and the higher indium incorporation, are responsible for the observed energetic shift of the InGaN SQW luminescence. Furthermore, compositional mappings of the InGaN quantum well reveal the formation of locally indium rich regions with several nanometers in size, leading to potential fluctuations in the InGaN SQW energy landscape. This is directly evidenced by nanometer-scale resolved CL mappings that show strong localization effects of the excitonic SQW emission. [ABSTRACT FROM AUTHOR]

In the present paper, a reliable and rugged thermogravimetry-gas chromatography-mass spectrometry (TGA-GC-MS) method was developed to determine the composition of ultrathin films consisting of binary blends of functional polystyrene (PS) and polymethylmethacrylate (PMMA) grafted to a silicon wafer. A general methodology will be given to address the composition determination problem for binary or even multicomponent polymer brush systems using the PS/PMMA-based samples as a paradigmatic example. In this respect, several distinct tailor-made materials were developed to ensure reliable calibration and validation stages. The analytical method was tested on unknown samples to follow the composition evolution in PS/PMMA brushes during the grafting reaction. A preferential grafting of the PMMA was revealed in full agreement with its preferential interaction with the SiO polar surface. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

Natural rubber/Poly(methyl methacrylate) or NR/PMMA blends were prepared by polymerization of the methyl methacrylate monomer and natural rubber latex. Their PMMA content before and after Soxhlet extraction was determined by H-NMR spectrometry. In this work, the thermal properties of the same NR/PMMA blends were determined using simultaneous thermogravimetry/differential scanning calorimetry (TG/DSC). The composition of the samples was determined on the basis of the derivative thermogravimetric (DTG) data. As the decomposition of the samples took place by simultaneous processes, by varying the heating rates the shape of the DTG curves was optimized for the deconvolution into two individual peaks of the two-component polymer system. Assuming the compensation of the errors, from the deconvoluted curves the amounts of the components in the blends were calculated. TG/MS data showed that the deconvolution was justified as the first part of the DTG curve could be related mainly to the decomposition of NR, while at higher temperatures, the decomposition of PMMA took place. The thermogravimetric method of composition determination of the polymer is simple and rapid, and in addition, is cheap compared with the costs of other instrumental techniques. The results were acceptable when compared with the corresponding data of H-NMR studies, too. [ABSTRACT FROM AUTHOR]

High-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) is a valuable method for composition determination of nanomaterials. However, light elements do not scatter efficiently into the scattering angles employed for HAADF-STEM which hinders the composition determination of material systems containing light elements by HAADF-STEM. This makes the usage of lower scattering angles favourable. Moreover, static atomic displacements (SADs) caused by the small covalent radius of the substituting light elements in semiconductor alloys increase the scattering intensity at low angles. Nevertheless, at low angles, a quantitative match between complementary image simulations and experiments is not straight forward, since e.g. inelastic scattering and correlated phonon movement is often neglected in simulations. In this study, we establish a method to quantify material systems containing light elements at low angles by resolving the remaining sources of discrepancy. An outstanding agreement between simulations and experiments is achieved by using a combination of an in-column energy filter and a fast pixelated detector. By applying this method to GaN x As 1-x quantum wells, a good agreement of the TEM results with results from high-resolution x-ray diffraction is obtained. The method developed enables the nanoscale analysis of functional materials containing light elements, especially in the presence of SADs. [ABSTRACT FROM AUTHOR]

GaInNAs alloys are mostly used as an active part of light sources for long wavelength telecom applications. Beside this, these materials are used as thin quantum wells (QWs), and a need is to grow thick layers of such semiconductor alloys for photodetectors and photovoltaic cells applications. However, structural characterization of the GaInNAs layers is hindered by non-homogeneity of the In and N distributions along the layer. In this work the challenges of the structural characterization of doped thick GaInNAs layers grown by atmospheric pressure metalorganic vapour phase epitaxy (APMOVPE) will be presented [ABSTRACT FROM AUTHOR]

Abstract: High angle annular dark field scanning transmission electron microscopy (HAADF STEM) images provide sample information which is sensitive to the chemical composition. The image intensities indeed scale with the mean atomic number Z. To some extent, chemically different atomic column types can therefore be visually distinguished. However, in order to quantify the atomic column composition with high accuracy and precision, model-based methods are necessary. Therefore, an empirical incoherent parametric imaging model can be used of which the unknown parameters are determined using statistical parameter estimation theory (Van Aert et al., 2009, [1]). In this paper, it will be shown how this method can be combined with frozen lattice multislice simulations in order to evolve from a relative toward an absolute quantification of the composition of single atomic columns with mixed atom types. Furthermore, the validity of the model assumptions are explored and discussed. [Copyright &y& Elsevier]

Determination of indium and nitrogen content in InGaAsN quantum wells (QWs) is often based on the analysis of high-resolution X-ray diffraction (HRXRD) measurements. The comparison of diffraction curves of two similar samples, with and without nitrogen, together with an assumption of constant indium incorporation efficiency during the growth of layers with and without nitrogen, may lead to a large deviation in the determined In and N content. The HRXRD curve simulations supported by bandgap determination and calculations seem to be a solution of this problem. Comparison of the results achieved from simulated HRXRD curves with the calculations of all QWs transitions measured by contactless electro-reflectance (CER) can lead to reduction of deviations in composition determination of InGaAsN quantum wells. The proposed algorithm was applied for investigation of InGaAsN QWs grown by atmospheric pressure metalorganic vapor phase epitaxy (APMOVPE). [ABSTRACT FROM AUTHOR]

Abstract: We suggest a method for chemical mapping that is based on scanning transmission electron microscopy (STEM) imaging with a high-angle annular dark field (HAADF) detector. The analysis method uses a comparison of intensity normalized with respect to the incident electron beam with intensity calculated employing the frozen lattice approximation. This procedure is validated with an In0.07Ga0.93N layer with homogeneous In concentration, where the STEM results were compared with energy filtered imaging, strain state analysis and energy dispersive X-ray analysis. Good agreement was obtained, if the frozen lattice simulations took into account static atomic displacements, caused by the different covalent radii of In and Ga atoms. Using a sample with higher In concentration and series of 32 images taken within 42min scan time, we did not find any indication for formation of In rich regions due to electron beam irradiation, which is reported in literature to occur for the parallel illumination mode. Image simulation of an In0.15Ga0.85N layer that was elastically relaxed with empirical Stillinger–Weber potentials did not reveal significant impact of lattice plane bending on STEM images as well as on the evaluated In concentration profiles for specimen thicknesses of 5, 15 and 50nm. Image simulation of an abrupt interface between GaN and In0.15Ga0.85N for specimen thicknesses up to 200nm showed that artificial blurring of interfaces is significantly smaller than expected from a simple geometrical model that is based on the beam convergence only. As an application of the method, we give evidence for the existence of In rich regions in an InGaN layer which shows signatures of quantum dot emission in microphotoluminescence spectroscopy experiments. [Copyright &y& Elsevier]

Abstract: In the vapour compression plants possible leaks can vary the composition of a zeotropic refrigerant mixture. The main aim of this paper is to verify experimentally if the plant performances are restored with a proper recharge, when leaks are imposed. As for the R407C mixture the percentage of the less volatile component (R134a) increases, while the percentage of the more volatile components (R32 and R125) decreases when leaks occur. The experimental tests have been realized determining refrigerant leaks from the liquid receiver placed at the condenser outlet and measuring the properties in steady state condition. The recharge is realized in different ways: with R407C, with R134a and R410A or with R32 R125 and R134a. The different solutions are then compared from the economical point of view, in terms of COP, refrigeration power and air temperature at the evaporator outlet, adopting an iteration method. This method determines the real composition of a zeotropic mixture working in a compression plant, when only the temperature and pressure values at the expansion valve inlet and outlet are known. [Copyright &y& Elsevier]

Abstract: In scanning transmission electron microscopy using a high-angle annular dark field detector, image intensity strongly depends on specimen thickness and composition. In this paper we show that measurement of image intensities relative to the intensity of the incoming electron beam allows direct comparison with simulated image intensities, and thus quantitative measurement of specimen thickness and composition. Simulations were carried out with the frozen lattice and absorptive potential multislice methods. The radial inhomogeneity of the detector was measured and taken into account. Using a focused ion beam (FIB) prepared specimen we first demonstrate that specimen thicknesses obtained in this way are in very good agreement with a direct measurement of the thickness of the lamella by scanning electron microscopy in the FIB. In the second step we apply this method to evaluate the composition of layers. We measured ratios of image intensities obtained in regions with unknown and with known Al-concentration x, respectively. We show that estimation of the specimen thickness combined with evaluation of intensity ratios allows quantitative measurement of the composition x. In high-resolution images we find that the image intensity is well described by simulation if the simulated image is convoluted with a Gaussian with a half-width at half-maximum of 0.07nm. [Copyright &y& Elsevier]

A technique for the determination of the partial pressures of Cd and Te2 vapors in equilibrium with cadmium zinc telluride (CdZnTe) crystals has been developed. The technique has shown a large range of applicability. First of all, the technique can be used for the in-situ monitoring of the partial vapor pressures in the case of technological relevant processes, such as material purification and crystal growth. Moreover, the technique is applied to the characterization of the composition of CdZnTe crystals with a sensitivity of at least two orders of magnitude more than previously reported techniques [ABSTRACT FROM PUBLISHER]

The determination of large sample composition via prompt gamma measurements is examined as a non-linear inverse problem. We show that this non-linear problem can be formulated as a fixed point problem that always has a physically meaningful solution, even in the presence of significant contributions to photopeak area from gammas emitted by the surroundings. The formulation involves only ratios of measured photopeak areas, and, separately, ratios of modeled photopeak areas. It therefore does not require the absolute comparison of measured or modeled quantities. The proof of the existence of meaningful solutions relies on very simple and natural hypotheses of positivity and continuity. The natural fixed point iteration is examined, and certain physical limits where its global convergence can be guaranteed are examined. Several computational examples are presented. [Copyright &y& Elsevier]

We present composition estimation results using fixed point iteration compared to the true composition of sample for prompt gamma measurements. The analysis showed that the fixed point iteration algorithm converges very rapidly to true composition of the sample independent of the initial guess when there is no significant background contribution. Even in the presence of significant background contribution, the true composition of the sample was estimated with high precision but with slower convergence. Although approximate data for neutron source spectrum and relative efficiency of the detector was used for analysis, the results showed that the method is not very sensitive to the details of the model since it is based on ratios. Despite the approximate data used for computations, the composition estimation results are in excellent agreement with chemical analysis. [Copyright &y& Elsevier]

• Imaging parameters are optimized for composition determination in a simulation study. • Optimum detector angle and semi-convergence angle depend on specimen thickness. • Both a minimum sampling of the image and a minimum electron dose are required. • Optimized condition is applied experimentally using a free choice of angle by 4DSTEM. • Good agreement of experimentally derived composition with XRD results. Quantitative scanning transmission electron microscopy (STEM) allows composition determination for nanomaterials at an atomic scale. To improve the accuracy of the results obtained, optimized imaging parameters should be chosen for annular dark field imaging. In a simulation study, we investigate the influence of imaging parameters on the accuracy of the composition determination with the example of ternary III-V semiconductors. It is shown that inner and outer detector angles and semi-convergence angle can be optimized, also in dependence on specimen thickness. Both, a minimum sampling of the image and a minimum electron dose are required. These findings are applied experimentally by using a fast pixelated detector to allow free choice of detector angles. [ABSTRACT FROM AUTHOR]

SiGe heterostructures have been grown by molecular beam epitaxy, with nominal compositions of 10 and 15 at %. Analytical electron microscopy, Rutherford backscattering spectrometry and ion channeling have been used in order to determine film thickness, Ge molar fraction and tetragonal distortion. The actual Ge concentrations were found to be smaller than the nominal ones. For all the SiGe films a coherent growth was found, with a small deviation from the perfect tetragonal distortion. The good agreement found between the results obtained by each analytical technique demonstrate that these methods of characterization are powerful tools for the control of the epitaxial layer parameters. [ABSTRACT FROM AUTHOR]

• Diffractions are used to determine local thickness and composition. • Electron diffractions ranging from 0 to 130 mrad were obtained by 4D-STEM. • Experiment and simulated diffractions are compared. • This method reduces the electron dose to 1/10 or less compared with EELS. The nanometer-scale spatial distributions of local thickness or composition of noncrystalline materials are generally measured by spectroscopy with scanning transmission electron microscopy (STEM). Since spectroscopy requires a high electron dose and causes irradiation damage, alternative non-spectroscopic methods are required to measure the local thickness or composition of electron-sensitive noncrystalline materials. Here, we focus on the radial distribution function (RDF) of the electron diffraction of non-crystalline materials. We confirm that the RDF of the electron diffraction obtained by simulation contains information on the thickness and composition. Next, we demonstrate the determination of both thickness and composition from experimentally obtained RDFs. Although some constraints are required, we determine the local thickness and composition of a BaO-SiO2 glass sample by comparing the RDFs of diffraction measured by a high-speed pixelated detector with those of the simulated diffractions. Collaterally, this determination method can improve the quality of STEM images. [ABSTRACT FROM AUTHOR]

• Composition determination for quaternary III–V semiconductors with two elements on each sub lattice. • Single STEM image and complementary image simulations are used. • Capability of proposed method is explored in simulation study. • Good agreement of experimentally determined concentrations for (GaIn)(AsBi) with XRD results. Quantitative scanning transmission electron microscopy (STEM) is a powerful tool for the characterization of nano-materials. Absolute composition determination for ternary III–V semiconductors by direct comparison of experiment and simulation is well established. Here, we show a method to determine the composition of quaternary III–V semiconductors with two elements on each sub lattice from the intensities of one STEM image. As an example, this is applied to (GaIn)(AsBi). The feasibility of the method is shown in a simulation study that also explores the influence of detector angles and specimen thickness. Additionally, the method is applied to an experimental STEM image of a (GaIn)(AsBi) quantum well grown by metal organic vapour phase epitaxy. The obtained concentrations are in good agreement with X-ray diffraction and photoluminescence results. [ABSTRACT FROM AUTHOR]