BYU Represents at DPS

Coherent x-ray imaging and scattering from accelerator based sources such as synchrotrons continue to impact biology, medicine, technology, and materials science. Many synchrotrons around the world are currently undergoing major upgrades to increase their available coherent x-ray flux by approximately two orders of magnitude. The improvement of synchrotrons may enable imaging of materials in operando at the atomic scale which may revolutionize battery and catalysis technologies. Current algorithms used for phase retrieval in coherent x-ray imaging are based on the projection onto sets method. These traditional iterative phase retrieval methods will become more computationally expensive as they push towards atomic resolution and may struggle to converge. Additionally, these methods do not incorporate physical information that may additionally constrain the solution. In this work, we present an algorithm which incorporates molecular dynamics into Bragg coherent diffraction imaging (BCDI). This algorithm, which we call PRAMMol (Phase Retrieval with Atomic Modeling and Molecular Dynamics) combines statistical techniques with molecular dynamics to solve the phase retrieval problem. We present several examples where our algorithm is applied to simulated coherent diffraction from 3D crystals and show convergence to the correct solution at the atomic scale.

As part of our variable star follow-up program, we have examined a number of stars from the Asteroid Terrestrial-impact Last Alert System (ATLAS) survey. Using a combination of our own data, ATLAS data, and other archival data, we confirmed the published periods and established a baseline ephemeris for each star. This initial sample of six stars are from the PUL or mono-periodic set from the ATLAS survey. Our determined periods agreed well with the published values. Five targets were found to be high amplitude δ Scuti variables (HADS), and one a low-amplitude δ Scuti (LADS). Beyond the primary period we examined the frequency content, Q value, position in the PL relation, and position within the instability strip of each object. We found ATO J070.9950+37.4038 to be the most complex target. The frequency content is likely a set of nonradial pulsations. ATO J328.8034+58.0406 is a multiperiodic HADS variable that is pulsating in the first and second overtones. ATO 345.4240+42.0479 was found to be a simple HADS monoperiodic fundamental pulsator. In the case of ATO J086.0780+30.3287, we found a strong fundamental pulsation with many harmonics and a weaker first overtone pulsation. We classify ATO J086.0780+30.3287 as a HADS. ATO J077.6090+36.5619 was found to be an interesting case of a monoperiodic star that appears to be pulsating in the third overtone. The lower amplitude for this target would put it in the LADS group. ATO J045.8159+46.0090 was found to be a multiperiodic HADS pulsating in the first and second overtones.

Many material properties can be traced back to properties of their grain boundaries. Grain boundary energy (GBE), as a result, is a key quantity of interest in the analysis and modeling of microstructure. A standard method for calculating grain boundary energy is molecular dynamics (MD); however, on-the-fly MD calculations are not tenable due to the extensive computational time required. Lattice matching (LM) is a reduced-order method for estimating GBE quickly; however, it has only been tested against a relatively limited set of data, and does not have a suitable means for assessing error. In this work, we use the recently published dataset of Homer et al. (2022) to assess the performance of LM over the full range of GB space, and to equip LM with a metric for error estimation. LM is used to generate energy estimates, along with predictions of facet morphology, for each of the 7,304 boundaries in the Homer dataset. The relative and absolute error of LM, based on the reported MD data, is found to be 5%-8%. An essential part of the LM method is the faceting relaxation, which corrects the expected energy by convexification across the compact space (S2) S 2) of boundary plane orientations. The original Homer dataset did not promote faceting, but upon extended annealing, it is shown that facet patterns similar to those predicted by LM emerge.

Due to the difficulty and expense of underwater field trials, a high-fidelity underwater simulator is a necessity for testing and developing algorithms. To fill this need, we present HoloOcean, an open-source underwater simulator, built upon Unreal Engine 4 (UE4). HoloOcean comes equipped with multiagent support, various sensor implementations of common underwater sensors, and simulated communications support. Due to being built upon UE4, new environments are straightforward to add, enabling easy extensions to be built. HoloOcean is controlled via a simple Python interface, allowing simple installation via pip, and requiring few lines of code to execute simulations. Each agent is equipped with various control schemes and dynamics that can be customized via the Python interface. Also included is a novel sonar sensor framework that leverages an octree representation of the environment for efficient and realistic sonar imagery generation. In addition, to improve the authenticity of the imaging sonar simulation, we use a novel cluster-based multipath ray-tracing algorithm, various probabilistic noise models, and properties of reflecting surfaces. We also leverage the sonar simulation framework to simulate sidescan, single-beam, and multibeam profiling sonars.

Bronin et al. [Phys. Rev. E 108, 045209 (2023)] recently reported molecular-dynamics simulations of ultracold neutral plasmas expanding in a quadrupole magnetic field. While the main results are in agreement with prior experimental measurements, we present data showing oscillations not captured in the simulations of Bronin et al. Plasmas formed using pulsed or continuous-wave ionization processes have similar confinement times.

The past few decades have made clear that the properties and performances of emerging functional and quantum materials can depend strongly on their local atomic and/or magnetic structure, particularly when details of the local structure deviate from the long-range structure averaged over space and time. Traditional methods of structural refinement (e.g., Rietveld) are typically sensitive only to the average structure, creating a need for more advanced structural probes suitable for extracting information about structural correlations on short length- and time-scales. In this Perspective, we describe the importance of local magnetic structure in several classes of emerging materials and present the magnetic pair distribution function (mPDF) technique as a powerful tool for studying short-range magnetism from neutron total-scattering data. We then provide a selection of examples of mPDF analysis applied to magnetic materials of recent technological and fundamental interest, including the antiferromagnetic semiconductor MnTe, geometrically frustrated magnets, and iron-oxide magnetic nanoparticles. The rapid development of mPDF analysis since its formalization a decade ago puts this technique in a strong position for making continued impact in the study of local magnetism in emerging materials.