Neutron reflectometry is a powerful method for probing the molecular scale structure of both hard and soft condensed matter films. Moreover, the phase-sensitive methods which have been developed make ...it possible for specular neutron reflectometry to be effectively employed as an imaging device of the composition depth profile of thin film materials with a spatial resolution approaching a fraction of a nanometer. The image of the cross-sectional distribution of matter in the film obtained in such a way can be shown to be, in most cases, unambiguous to a degree limited primarily by the range and statistical uncertainty of the reflectivity data available. The application of phase-sensitive neutron reflectometry (PSNR) to the study of several types of soft matter thin film systems are illustrated by a number of specific examples from recent studies. In addition, new software tools available to the researcher to apply PSNR methods and analysis are discussed.
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► Phase-sensitive neutron reflectometry (PSNR) is a powerful probe of film structure. ► Specular PSNR is sensitive to the compositional depth profile along the film normal. ► Specular PSNR is capable of nanometer scale resolution under ideal conditions. ► Specular PSNR is particularly applicable to soft condensed matter film systems. ► In the specular PSNR method, the retrieval of phase information minimizes ambiguity.
Neutron interferometry uniquely combines neutron imaging and scattering methods to enable characterization of multiple length scales from 1 nm to 10 µm. However, building, operating, and using such ...neutron imaging instruments poses constraints on the acquisition time and on the number of measured images per sample. Experiment time-constraints yield small quantities of measured images that are insufficient for automating image analyses using supervised artificial intelligence (AI) models. One approach alleviates this problem by supplementing annotated measured images with synthetic images. To this end, we create a data-driven simulation framework that supplements training data beyond typical data-driven augmentations by leveraging statistical intensity models, such as the Johnson family of probability density functions (PDFs). We follow the simulation framework steps for an image segmentation task including Estimate PDFs
Validate PDFs
Design Image Masks
Generate Intensities
Train AI Model for Segmentation. Our goal is to minimize the manual labor needed to execute the steps and maximize our confidence in simulations and segmentation accuracy. We report results for a set of nine known materials (calibration phantoms) that were imaged using a neutron interferometer acquiring four-dimensional images and segmented by AI models trained with synthetic and measured images and their masks.
The reference layer method allows the reconstruction of the complex neutron reflection for thin films only above the critical edge. Without the information below the critical edge, inverting the ...reflection to recover the samples scattering potential is futile. To retrieve the reflection below the critical edge, a fixed-point algorithm is presented which uses only the knowledge of the total film thickness. The convergence and uniqueness of the algorithm is proven in the Born approximation and numerical studies for both realistic and random thin films are successfully carried out in the dynamical theory.
•The reflection can be retrieved below the critical edge by an iterative algorithm.•In the Born-Approximation the fixed-point algorithm converges to the correct solution.•The algorithm shows good agreement with the exact reflection in the dynamical theory.
Thermal remediation (TR) is a broadly applicable technology that is effective at removing volatile and semi-volatile contaminants from soil. However, TR can be costly and inefficient in practice, ...with underlying removal and transformation mechanisms poorly understood. To better understand the role organic matter plays in removal, a series of experiments was performed with a humic substance, humic modified silica, and a natural soil in the presence of pyrene from 100 to 500 °C and compared to prior experiments using pure minerals. Detection of by-products confirmed that pyrene was removed by transformation in addition to volatilization. Oxidation via hydroxyl radical formation and reductive hydrogenation were both indicated as possible reaction mechanisms promoted by organic matter. Because the presence of bulk water did not impact the extent of pyrene degradation or transformation, it is hypothesized that hydroxyl radicals were produced from soil organic matter functional groups, such as carboxyl and phenol groups, and possibly bound water at elevated temperatures in dry experiments. Additionally, the average oxidation state of carbon in detected by-products increased with temperature in experiments with humic modified silica and soil but not humic substance alone, though the extent of degradation did not significantly change. This shift in oxidation state may indicate that attachment of organic matter to another surface may increase interaction between reactive species. The results of this study show that contaminant transformation in soils during TR significantly contributes to removal, even at temperatures lower than those used in traditional treatment. This information will help to guide the design and operation of TR systems, potentially reducing energy requirements and highlighting the necessity of testing for transformation by-products.
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•Organic matter impacts contaminant transformation during thermal remediation.•Fewer and less polar by-products detected at lower temperatures•Transformation occurs by hydroxyl radical formation and reductive hydrogenation.•Bulk water is not necessary to promote transformation in soil organic matter.
A framework is applied to quantify information gain from neutron or X‐ray reflectometry experiments Treece, Kienzle, Hoogerheide, Majkrzak, Lösche & Heinrich (2019). J. Appl. Cryst. 52, 47–59, in an ...in‐depth investigation into the design of scattering contrast in biological and soft‐matter surface architectures. To focus the experimental design on regions of interest, the marginalization of the information gain with respect to a subset of model parameters describing the structure is implemented. Surface architectures of increasing complexity from a simple model system to a protein–lipid membrane complex are simulated. The information gain from virtual surface scattering experiments is quantified as a function of the scattering length density of molecular components of the architecture and the surrounding aqueous bulk solvent. It is concluded that the information gain is mostly determined by the local scattering contrast of a feature of interest with its immediate molecular environment, and experimental design should primarily focus on this region. The overall signal‐to‐noise ratio of the measured reflectivity modulates the information gain globally and is a second factor to be taken into consideration.
Rules for the experimental design of scattering contrast in reflectometry experiments of biological surface architectures are derived using an information theoretical framework.
A framework based on Bayesian statistics and information theory is developed to optimize the design of surface‐sensitive reflectometry experiments. The method applies to model‐based reflectivity data ...analysis, uses simulated reflectivity data and is capable of optimizing experiments that probe a sample under more than one condition. After presentation of the underlying theory and its implementation, the framework is applied to exemplary test problems for which the information gain ΔH is determined. Reflectivity data are simulated for the current generation of neutron reflectometers at the NIST Center for Neutron Research. However, the simulation can be easily modified for X‐ray or neutron instruments at any source. With application to structural biology in mind, this work explores the dependence of ΔH on the scattering length density of aqueous solutions in which the sample structure is bathed, on the counting time and on the maximum momentum transfer of the measurement. Finally, the impact of a buried magnetic reference layer on ΔH is investigated.
A framework for the optimization of neutron reflectometry experiments based on Bayesian statistics and information theory is presented.
Abstract
Dark-field imaging probes the projected autocorrelation function at the autocorrelation length of the grating interferometer and quantitatively accesses the parameters of a microstructure ...model. The National Institute of Standards and Technology has developed a novel far-field grating interferometer to study hierarchical materials in various fields such as polymer science, geology, additive manufacturing under the INFER project. In this work, we detail the simulation of dark-field imaging which is one of the goals of INFER.
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