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At least 91 records · Page 5

Improved joint X-ray and neutron refinement procedure in Phenix

Neutron diffraction is one of the three crystallographic techniques (X-ray, neutron and electron diffraction) used to determine the atomic structures of molecules. Its particular strengths derive from the fact that H (and D) atoms are strong neutron scatterers, meaning that their positions, and thus protonation states, can be derived from crystallographic maps. However, because of technical limitations and experimental obstacles, the quality of neutron diffraction data is typically much poorer (completeness, resolution and signal to noise) than that of X-ray diffraction data for the same sample. Further, refinement is more complex as it usually requires additional parameters to describe the H (and D) atoms. The increase in the number of parameters may be mitigated by using the `riding hydrogen' refinement strategy, in which the positions of H atoms without a rotational degree of freedom are inferred from their neighboring heavy atoms. However, this does not address the issues related to poor data quality. Therefore, neutron structure determination often relies on the presence of an X-ray data set for joint X-ray and neutron (XN) refinement. In this approach, the X-ray data serve to compensate for the deficiencies of the neutron diffraction data by refining one model simultaneously against the X-ray and neutron data sets. To be applicable, it is assumed that both data sets are highly isomorphous, and preferably collected from the same crystals and at the same temperature. However, the approach has a number of limitations that are discussed in this work by comparing four separately re-refined neutron models. To address the limitations, a new method for joint XN refinement is introduced that optimizes two different models against the different data sets. This approach is tested using neutron models and data deposited in the Protein Data Bank. The efficacy of refining models with H atoms as riding or as individual atoms is also investigated.

36 MATERIALS SCIENCE↗

A conformation-dependent stereochemical library improves crystallographic refinement even at atomic resolution

A script was created to allow SHELXL to use the new CDL v.1.2 stereochemical library which defines the target values for main-chain bond lengths and angles as a function of the residue’s ϕ/ψ angles. Test refinements using this script show that the refinement behavior of structures at resolutions even better than 1 Å is substantially enhanced by the use of the new conformation-dependent ideal geometry paradigm. To utilize a new conformation-dependent backbone-geometry library (CDL) in protein refinements at atomic resolution, a script was written that creates a restraint file for the SHELXL refinement program. It was found that the use of this library allows models to be created that have a substantially better fit to main-chain bond angles and lengths without degrading their fit to the X-ray data even at resolutions near 1 Å. For models at much higher resolution (∼0.7 Å), the refined model for parts adopting single well occupied positions is largely independent of the restraints used, but these structures still showed much smaller r.m.s.d. residuals when assessed with the CDL. Examination of the refinement tests across a wide resolution range from 2.4 to 0.65 Å revealed consistent behavior supporting the use of the CDL as a next-generation restraint library to improve refinement. CDL restraints can be generated using the service at http://pgd.science.oregonstate.edu/cdl{sub s}helxl/.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Deformable elastic network refinement for low-resolution macromolecular crystallography

An overview of applications of the deformable elastic network (DEN) refinement method is presented together with recommendations for its optimal usage. Crystals of membrane proteins and protein complexes often diffract to low resolution owing to their intrinsic molecular flexibility, heterogeneity or the mosaic spread of micro-domains. At low resolution, the building and refinement of atomic models is a more challenging task. The deformable elastic network (DEN) refinement method developed previously has been instrumental in the determinion of several structures at low resolution. Here, DEN refinement is reviewed, recommendations for its optimal usage are provided and its limitations are discussed. Representative examples of the application of DEN refinement to challenging cases of refinement at low resolution are presented. These cases include soluble as well as membrane proteins determined at limiting resolutions ranging from 3 to 7 Å. Potential extensions of the DEN refinement technique and future perspectives for the interpretation of low-resolution crystal structures are also discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Strengthening and Improving Yield Asymmetry of Magnesium Alloys by Second Phase Particle Refinement Under the Guidance of Integrated Computational Materials Engineering

Improving yield strength and asymmetry is critical to expand applications of magnesium alloys in industry for higher fuel efficiency and lower CO 2 production. Grain refinement is an efficient method for strengthening low symmetry magnesium alloys, achievable by precipitate refinement. This study provides guidance on how precipitate engineering will improve mechanical properties through grain refinement. Precipitate refinement for improving yield strengths and asymmetry is simulated quantitatively by coupling a stochastic second phase grain refinement model and a modified polycrystalline crystal viscoplasticity φ-model. Using the stochastic second phase grain refinement model, grain size is quantitatively determined from the precipitate size and volume fraction. Yield strengths, yield asymmetry, and deformation behavior are calculated from the modified φ-model. If the precipitate shape and size remain constant, grain size decreases with increasing precipitate volume fraction. If the precipitate volume fraction is kept constant, grain size decreases with decreasing precipitate size during precipitate refinement. Yield strengths increase and asymmetry approves to one with decreasing grain size, contributed by increasing precipitate volume fraction or decreasing precipitate size.

36 MATERIALS SCIENCE↗

Empirical Refinement of the GADRAS Detector Response Function

The Gamma Detector Response and Analysis Software (GADRAS) was augmented to enable empirical refinement of the Detector Response Function (DRF) for gamma-ray detectors. This capability is included in GADRAS starting with Version 18.8.2, which was released in February 2019 Empirical refinement enables improved computational accuracy for gamma-ray spectra when detectors exhibit characteristics that are essentially unique to a particular sensor. This report discusses how to perform the empirical refinement, and examples are presented for the following scenarios where empirical refinement is appropriate: Large plastic scintillators, which are generally composed of polyvinyl toluene (PVT), often exhibit low-energy peaks that are not associated with incident gamma rays. Regardless of whether they are artifacts produced by poor light collection or pulse processing methods, accurate spectral synthesis requires replication of these features; Some detectors, particularly those using Silicon Photomultipliers (SiPM), exhibit energy shifts of Compton edges and escape peaks relative to the same scintillator material attached to a photomultiplier tube. Empirical refinement compensates for these effects, which derive from nonlinearities in the detector response; The change in the DRF as a function of displacement of the source relative to the detector axis cannot always be replicated adequately using only the few shielding parameters that are used by the response function. Empirical refinement enables improved accuracy for computation of spectra during linear transits or when the detector is close to a large radiation source. This is a particularly important consideration for collimated detectors; and, Gamma-ray imagers exhibit complex relationships between spectral response and spatial locations. Empirical refinement enables substantial improvement of the DRF accuracy for imagers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Comparison Study of Conventional and Adaptive Mesh Refinement in Organic Material Decomposition Models

This study compares conventional mesh refinement techniques, specifically Uniform Mesh Refinement (UMR), with a new Adaptive Mesh Refinement (AMR) method, applied to Organic Material Decomposition (OMD) models. The proposed benefit of AMR is that only areas that require refinement, based on minimizing a specific field gradient, are refined thus decreasing model wall time compared to conventional UMR methods. This work specifically focuses on comparing UMR and AMR methods on decomposing (both No-Flow and Porous-Flow material models) Polymeric Methylene Diisocyanate (PMDI) polyurethane foam. Throughout the work, the geometry increased in complexity to assess the refinement methods performance at varying levels geometric intricacy. While AMR has been shown to work well in a variety of applications, the UMR approach proved to be computationally faster, for many of the geometries and foam decomposition models, than AMR. However, it was observed that at higher levels of refinement, greater than 3 UMR, AMR begins to be computationally better. Additionally, the settings used to perform AMR greatly impact its performance, and lessons learned, in terms of OMD models, are shared. Due to physics involved in material decomposition, specifically the evolution of state variables, these problems don’t fully benefit from the advantages of AMR.

36 MATERIALS SCIENCE↗

An object-oriented approach for parallel self adaptive mesh refinement on block structured grids

Self-adaptive mesh refinement dynamically matches the computational demands of a solver for partial differential equations to the activity in the application's domain. In this paper we present two C++ class libraries, P++ and AMR++, which significantly simplify the development of sophisticated adaptive mesh refinement codes on (massively) parallel distributed memory architectures. The development is based on our previous research in this area. The C++ class libraries provide abstractions to separate the issues of developing parallel adaptive mesh refinement applications into those of parallelism, abstracted by P++, and adaptive mesh refinement, abstracted by AMR++. P++ is a parallel array class library to permit efficient development of architecture independent codes for structured grid applications, and AMR++ provides support for self-adaptive mesh refinement on block-structured grids of rectangular non-overlapping blocks. Using these libraries, the application programmers' work is greatly simplified to primarily specifying the serial single grid application and obtaining the parallel and self-adaptive mesh refinement code with minimal effort. Initial results for simple singular perturbation problems solved by self-adaptive multilevel techniques (FAC, AFAC), being implemented on the basis of prototypes of the P++/AMR++ environment, are presented. Singular perturbation problems frequently arise in large applications, e.g. in the area of computational fluid dynamics. They usually have solutions with layers which require adaptive mesh refinement and fast basic solvers in order to be resolved efficiently.

Lemke, Max↗

An adaptive mesh-moving and refinement procedure for one-dimensional conservation laws

We examine the performance of an adaptive mesh-moving and /or local mesh refinement procedure for the finite difference solution of one-dimensional hyperbolic systems of conservation laws. Adaptive motion of a base mesh is designed to isolate spatially distinct phenomena, and recursive local refinement of the time step and cells of the stationary or moving base mesh is performed in regions where a refinement indicator exceeds a prescribed tolerance. These adaptive procedures are incorporated into a computer code that includes a MacCormack finite difference scheme wih Davis' artificial viscosity model and a discretization error estimate based on Richardson's extrapolation. Experiments are conducted on three problems in order to qualify the advantages of adaptive techniques relative to uniform mesh computations and the relative benefits of mesh moving and refinement. Key results indicate that local mesh refinement, with and without mesh moving, can provide reliable solutions at much lower computational cost than possible on uniform meshes; that mesh motion can be used to improve the results of uniform mesh solutions for a modest computational effort; that the cost of managing the tree data structure associated with refinement is small; and that a combination of mesh motion and refinement reliably produces solutions for the least cost per unit accuracy.

Biswas, Rupak↗

FINITE ELEMENT MODEL MESH REFINEMENT EFFECTS ON QUALIFICATION OF NUCLEAR GRADE GRAPHITE COMPONENTS

The American Society of Mechanical Engineers (ASME) provides the full and simplified design-by-analysis probabilistic assessments for determining acceptance of nuclear grade graphite core components. The assessments can be characterized by three parts: (1) a component stress distribution, often determined by a finite element (FE) model; (2) a Weibull probability density function (pdf) that characterizes the experimental tensile strength distribution; and (3) the post-processor, which combines the FE model and the Weibull strength distribution in accordance with the full and simplified assessments to determine component acceptance. It is known that the level of mesh refinement in FE models can affect the modeled component’s calculated stress distribution. Depending on the component geometry, the stress distribution may converge with sufficient refinement. It was previously unknown whether the acceptance decision resulting from the full and simplified assessments might change even with sufficient mesh refinement. This study explores that question using experimental strength results for a dog-bone geometry for two graphite grades, IG-110 and PCEA. The simplified assessment has two criteria that must be met, the first limits the combined membrane stress by the allowable stress and the second limits the peak equivalent stress by the allowable stress scaled by the ratio of flexural to tensile strength. In the application of the simplified assessment, convergence of the peak equivalent stress required extreme mesh refinement, however, the acceptance decision was not affected. It is hypothesized that more complex geometries with stress concentrations may present mesh refinement effects on the simplified assessment acceptance decision. Mesh refinement did affect the acceptance decision in the full assessment for the applied pressure loadings in this study. This work suggests component stress distribution convergence is not a sufficient criteria for POF convergence in the full assessment and that mesh refinement should continue until the POF has converged, especially where the resulting POF is bordering the SRC acceptable POF limit.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Application of Al-2La-1B Grain Refiner to Al-10Si-0.3Mg Casting Alloy

This paper reports the application and microstructure refining effect of an Al-2La-1B grain refiner in Al-10Si-0.3Mg casting alloy. Compared with the traditional Al-5Ti-1B refiner, Al-2La-1B refiner shows better performances on the grain refinement of Al-10Si-0.3Mg alloy. Transmission electron microscopy analysis suggests that the crystallite structure features of LaB6 are beneficial to the heterogeneous nucleation of α-Al grains. Regarding the mechanical performances, tensile properties of Al-10Si-0.3Mg casting alloy are prominently improved, due to the refined microstructures.

36 MATERIALS SCIENCE↗

Improved chemistry restraints for crystallographic refinement by integrating the Amber force field into Phenix

The refinement of biomolecular crystallographic models relies on geometric restraints to help to address the paucity of experimental data typical in these experiments. Limitations in these restraints can degrade the quality of the resulting atomic models. Here, an integration of the full all-atom Amber molecular-dynamics force field into Phenix crystallographic refinement is presented, which enables more complete modeling of biomolecular chemistry. The advantages of the force field include a carefully derived set of torsion-angle potentials, an extensive and flexible set of atom types, Lennard–Jones treatment of nonbonded interactions and a full treatment of crystalline electrostatics. The new combined method was tested against conventional geometry restraints for over 22 000 protein structures. Structures refined with the new method show substantially improved model quality. On average, Ramachandran and rotamer scores are somewhat better, clashscores and MolProbity scores are significantly improved, and the modeling of electrostatics leads to structures that exhibit more, and more correct, hydrogen bonds than those refined using traditional geometry restraints. In general it is found that model improvements are greatest at lower resolutions, prompting plans to add the Amber target function to real-space refinement for use in electron cryo-microscopy. This work opens the door to the future development of more advanced applications such as Amber -based ensemble refinement, quantum-mechanical representation of active sites and improved geometric restraints for simulated annealing.

59 BASIC BIOLOGICAL SCIENCES↗

Influence of Alloy and Solidification Parameters on Grain Refinement in Aluminum Weld Metal due to Inoculation

The goals are: (1) Establish how much Ti/B grain refiner is need to completely refine aluminum weld metal for different alloys and different welding conditions; (2) Characterize how alloy composition and solidification parameters affect weld metal grain refinement; and (3) Apply relevant theory to understand observed behavior. Conclusions are: (1) additions of Ti/B grain refiner to weld metal in Alloys 1050, 5083, and 6082 resulted in significant grain refinement; (2) grain refinement was more effective in GTAW than LBW, resulting in finer grains at lower Ti content - reason is limited time available for equiaxed grain growth in LBW (inability to occlude columnar grain growth); (3) welding travel speed did not markedly affect grain size within GTAW and LBW clusters; and (4) application of Hunt CET analysis showed experimental G to be on the order of the critical G{sub CET}; G{sub CET} was consistently higher for GTAW than for LBW.

36 MATERIALS SCIENCE↗

Investigation on temporal evolution of the grain refinement in copper under high strain rate loading via in-situ synchrotron measurement and predictive modeling

Synchrotron X-rays are integrated with a modified Kolsky tension bar to conduct in situ tracking of the grain refinement mechanism operating during the dynamic deformation of metals. Copper with an initial average grain size of 36 μm is refined to 6.3 μm when loaded at a constant high strain rate of 1200 s -1 . The synchrotron measurements revealed the temporal evolution of the grain refinement mechanism in terms of the initiation and rate of refinement throughout the loading test. A multiscale coupled probabilistic cellular automata based recrystallization model has been developed to predict the microstructural evolution occurring during dynamic deformation processes. The model accurately predicts the initiation of the grain refinement mechanism with a predicted final average grain size of 2.4 μm. As a result, the model also accurately predicts the temporal evolution in terms of the initiation and extent of refinement when compared with the experimental results.

36 MATERIALS SCIENCE↗

Thickness-based adaptive mesh refinement methods for multi-phase flow simulations with thin regions

In numerical simulations of multi-scale, multi-phase flows, grid refinement is required to resolve regions with small scales. A notable example is liquid-jet atomization and subsequent droplet dynamics. It is essential to characterize the detailed flow physics with variable length scales with high fidelity, in order to elucidate the underlying mechanisms. In this paper, two thickness-based mesh refinement schemes are developed based on distance- and topology-oriented criteria for thin regions with confining wall/plane of symmetry and in any situation, respectively. Both techniques are implemented in a general framework with a volume-of-fluid formulation and an adaptive-mesh-refinement capability. The distance-oriented technique compares against a critical value, the ratio of an interfacial cell size to the distance between the mass center of the cell and a reference plane. The topology-oriented technique is developed from digital topology theories to handle more general conditions. The requirement for interfacial mesh refinement can be detected swiftly, without the need of thickness information, equation solving, variable averaging or mesh repairing. The mesh refinement level increases smoothly on demand in thin regions. The schemes have been verified and validated against several benchmark cases to demonstrate their effectiveness and robustness. These include the dynamics of colliding droplets, droplet motions in a microchannel, and atomization of liquid impinging jets. Overall, the thickness-based refinement technique provides highly adaptive meshes for problems with thin regions in an efficient and fully automatic manner.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Fe-24 wt.%Cr-4.1 wt.%C hardfacing alloy: Microstructure and carbide refinement mechanisms with ceria additive

The microstructure and carbide refinement mechanisms of Fe-24 wt.%Cr-4.1 wt.%C hardfacing alloys with 0 wt.%, 0.5 wt.%, 1.0 wt.%, 2 wt.%, and 4 wt.% ceria additives have been systematically investigated in this work. Optical microscopy, field emission scanning electron microscopy with energy dispersive spectrometer, and X-ray diffraction were collectively used to study the microstructure, the phase components, and the chemical formation of inclusion formed in the welding process. Wear-resistance of the alloys was comparatively studied using an abrasive wear testing machine. The structure analysis results show that the Fe-Cr-C hardfacing alloy mainly consists of martensite, retained austenite, MC carbide and M{sub 7}C{sub 3} carbide. With increasing ceria additive contents, the average size of the primary M{sub 7}C{sub 3} carbide decreases and reaches a most refined state in the alloy with 2 wt.% ceria additives. Comparative wear tests data shows that the wear resistance of the hardfacing alloys with ceria additives is better than that without ceria additive. In a good agreement with the carbide refinement results, the wear resistance of the alloy reaches an optimum level in the sample with 2 wt.% ceria additive. The main RE inclusion type identified with in-situ XRD analysis is RE inclusion Ce{sub 2}O{sub 2}S. Thermodynamics calculation confirms that this type of RE inclusion could precipitate prior to M{sub 7}C{sub 3} carbides, and act as a heterogeneous nucleus for M{sub 7}C{sub 3} in the welding process, which effectively provides a mechanism for significant refinement of the M{sub 7}C{sub 3} carbide and improves its wear resistance. - Graphical Abstract: Rare Earth inclusion (Ce{sub 2}O{sub 2}S) distributes in the primary M{sub 7}C{sub 3} carbide. Moreover, Ce{sub 2}O{sub 2}S, which acts as heterogeneous nuclei of the primary M{sub 7}C{sub 3} carbide, is medium effective. Therefore, the primary M{sub 7}C{sub 3} carbide has been refined. Highlights: Black-Right-Pointing-Pointer Micro-hardness of primary M{sub 7}C{sub 3} carbide in Fe-Cr-C hardfacing alloy is 1594 HV. Black-Right-Pointing-Pointer RE inclusion Ce{sub 2}O{sub 2}S can be observed in the primary M{sub 7}C{sub 3} carbide. Black-Right-Pointing-Pointer Ce{sub 2}O{sub 2}S as heterogeneous nuclei of the Cr{sub 7}C{sub 3} is medium effective. Black-Right-Pointing-Pointer Primary carbide is most refined with 2 wt.% ceria additive.

36 MATERIALS SCIENCE↗

Atomic protein structure refinement using all-atom graph representations and SE(3)-equivariant graph transformer

Abstract Motivation The state-of-art protein structure prediction methods such as AlphaFold are being widely used to predict structures of uncharacterized proteins in biomedical research. There is a significant need to further improve the quality and nativeness of the predicted structures to enhance their usability. In this work, we develop ATOMRefine, a deep learning-based, end-to-end, all-atom protein structural model refinement method. It uses a SE(3)-equivariant graph transformer network to directly refine protein atomic coordinates in a predicted tertiary structure represented as a molecular graph. Results The method is first trained and tested on the structural models in AlphaFoldDB whose experimental structures are known, and then blindly tested on 69 CASP14 regular targets and 7 CASP14 refinement targets. ATOMRefine improves the quality of both backbone atoms and all-atom conformation of the initial structural models generated by AlphaFold. It also performs better than two state-of-the-art refinement methods in multiple evaluation metrics including an all-atom model quality score—the MolProbity score based on the analysis of all-atom contacts, bond length, atom clashes, torsion angles, and side-chain rotamers. As ATOMRefine can refine a protein structure quickly, it provides a viable, fast solution for improving protein geometry and fixing structural errors of predicted structures through direct coordinate refinement. Availability and implementation The source code of ATOMRefine is available in the GitHub repository (https://github.com/BioinfoMachineLearning/ATOMRefine). All the required data for training and testing are available at https://doi.org/10.5281/zenodo.6944368.

59 BASIC BIOLOGICAL SCIENCES↗

Free kick instead of cross-validation in maximum-likelihood refinement of macromolecular crystal structures

The maximum-likelihood free-kick target, which calculates model error estimates from the work set and a randomly displaced model, proved superior in the accuracy and consistency of refinement of crystal structures compared with the maximum-likelihood cross-validation target, which calculates error estimates from the test set and the unperturbed model. The refinement of a molecular model is a computational procedure by which the atomic model is fitted to the diffraction data. The commonly used target in the refinement of macromolecular structures is the maximum-likelihood (ML) function, which relies on the assessment of model errors. The current ML functions rely on cross-validation. They utilize phase-error estimates that are calculated from a small fraction of diffraction data, called the test set, that are not used to fit the model. An approach has been developed that uses the work set to calculate the phase-error estimates in the ML refinement from simulating the model errors via the random displacement of atomic coordinates. It is called ML free-kick refinement as it uses the ML formulation of the target function and is based on the idea of freeing the model from the model bias imposed by the chemical energy restraints used in refinement. This approach for the calculation of error estimates is superior to the cross-validation approach: it reduces the phase error and increases the accuracy of molecular models, is more robust, provides clearer maps and may use a smaller portion of data for the test set for the calculation of R{sub free} or may leave it out completely.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Deformable complex network for refining low-resolution X-ray structures

A new refinement algorithm called the deformable complex network that combines a novel angular network-based restraint with a deformable elastic network model in the target function has been developed to aid in structural refinement in macromolecular X-ray crystallography. In macromolecular X-ray crystallography, building more accurate atomic models based on lower resolution experimental diffraction data remains a great challenge. Previous studies have used a deformable elastic network (DEN) model to aid in low-resolution structural refinement. In this study, the development of a new refinement algorithm called the deformable complex network (DCN) is reported that combines a novel angular network-based restraint with the DEN model in the target function. Testing of DCN on a wide range of low-resolution structures demonstrated that it constantly leads to significantly improved structural models as judged by multiple refinement criteria, thus representing a new effective refinement tool for low-resolution structural determination.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗