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At least 559 records · Page 31

2024 roadmap on magnetic microscopy techniques and their applications in materials science

Considering the growing interest in magnetic materials for unconventional computing, data storage, and sensor applications, there is active research not only on material synthesis but also characterisation of their properties. In addition to structural and integral magnetic characterisations, imaging of magnetisation patterns, current distributions and magnetic fields at nano- and microscale is of major importance to understand the material responses and qualify them for specific applications. In this roadmap, we aim to cover a broad portfolio of techniques to perform nano- and microscale magnetic imaging using superconducting quantum interference devices, spin centre and Hall effect magnetometries, scanning probe microscopies, x-ray- and electron-based methods as well as magnetooptics and nanoscale magnetic resonance imaging. The roadmap is aimed as a single access point of information for experts in the field as well as the young generation of students outlining prospects of the development of magnetic imaging technologies for the upcoming decade with a focus on physics, materials science, and chemistry of planar, three-dimensional and geometrically curved objects of different material classes including two-dimensional materials, complex oxides, semi-metals, multiferroics, skyrmions, antiferromagnets, frustrated magnets, magnetic molecules/nanoparticles, ionic conductors, superconductors, spintronic and spinorbitronic materials.

2D materials↗

Transient local secondary structure in the intrinsically disordered C‐term of the Albino3 insertase

Albino3 (Alb3) is an integral membrane protein fundamental to the targeting and insertion of light‐harvesting complex (LHC) proteins into the thylakoid membrane. Alb3 contains a stroma‐exposed C‐terminus (Alb3‐Cterm) that is responsible for binding the LHC‐loaded transit complex before LHC membrane insertion. Alb3‐Cterm has been reported to be intrinsically disordered, but precise mechanistic details underlying how it recognizes and binds to the transit complex are lacking, and the functional roles of its four different motifs have been debated. Using a novel combination of experimental and computational techniques such as single‐molecule fluorescence resonance energy transfer, circular dichroism with deconvolution analysis, site‐directed mutagenesis, trypsin digestion assays, and all‐atom molecular dynamics simulations in conjunction with enhanced sampling techniques, we show that Alb3‐Cterm contains transient secondary structure in motifs I and II. The excellent agreement between the experimental and computational data provides a quantitatively consistent picture and allows us to identify a heterogeneous structural ensemble that highlights the local and transient nature of the secondary structure. This structural ensemble was used to predict both the inter‐residue distance distributions of single molecules and the apparent unfolding free energy of the transient secondary structure, which were both in excellent agreement with those determined experimentally. We hypothesize that this transient local secondary structure may play an important role in the recognition of Alb3‐Cterm for the LHC‐loaded transit complex, and these results should provide a framework to better understand protein targeting by the Alb3‐Oxa1‐YidC family of insertases.

Okoto, Patience S.↗

Dynamics of antiferroelectric phase transition in PbZrO 3

The dynamics of the phase transition in antiferroelectric PbZrO 3 which is a subject of a decades long debate, is examined using first-principles-based simulations. This is achieved through development of a computational approach that allows calculations of generalized complex susceptibilities at an arbitrary point of the Brillouin zone. Application of this approach to the case of PbZrO 3 predicts the temperature evolution of many of its lattice modes, some of which remain elusive or even ``invisible'' in experiments. Here, the computational data suggest that two lattice modes are primarily responsible for the antiferroelectric phase transition in this material: the one associated with oxygen octahedra tilts dynamics and the other due to lead ions antipolar vibrations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Intrinsic dynamics of the electric-field-induced phase switching in antiferroelectric PbZrO 3 ultrathin films

Antiferroelectric ultrathin PbZrO3 films can exhibit both ferroelectric and antiferroelectric behavior depending on the thickness. We use first-principles-based nanoscopic simulations to investigate the intrinsic high-frequency dynamics of the electric-field-induced phase switching in such films which so far remains unknown. Here in this comprehensive study we report (i) the size and frequency evolution of the polarization response to the electric field;(ii)the intrinsic time for the phase switching; (iii) detailed comparison between the polarization reversal in the films with ferroelectric and antiferroelectric behavior; (iv) dynamics of the antiferroelectric and antiferrodistortive order parameters; (v) nanoscopic mechanism responsible for the phase switching. The nanoscopic insight leads to the prediction of the existence of two possible scenarios for the antipolar-polar phase switching depending on the mutual orientation of the antiferroelectric order parameter and the electric field. The two scenarios have different dynamical fingerprints. The polar-antipolar phase switching is found to be assisted by the formation of a nonpolar phase. Computational data indicate that the phase switching time is only fractions of nanoseconds for the polar-polar phase switching in ferroelectric films and polar-antipolar phase switching in antiferroelectric films. The antipolar-polar phase switching in antiferroelectric films is just a bit slower and takes the order of nanosecond. Under nonequilibrium conditions we find formation of antiferroelectric and antiferrodistortive nanodomains and coexistence of polar and antipolar order parameters.

25 ENERGY STORAGE↗

Quantum-accurate spectral neighbor analysis potential models for Ni-Mo binary alloys and fcc metals

In recent years, efficient interatomic potentials approaching the accuracy of density functional theory (DFT) calculations have been developed using rigorous atomic descriptors satisfying strict invariances, for example, for translation, rotation, permutation of homonuclear atoms, among others. In this work, we generalize the spectral neighbor analysis potential (SNAP) model to bcc-fcc binary alloy systems. We demonstrate that machine-learned SNAP models can yield significant improvements even over the well-established high-performing embedded atom method (EAM) and modified EAM potentials for fcc Cu and Ni. We also report on the development of a SNAP model for the fcc Ni-bcc Mo binary system by machine learning a carefully constructed large computed data set of elemental and intermetallic compounds. We demonstrate that this binary Ni-Mo SNAP model can achieve excellent agreement with experiments in the prediction of a Ni-Mo phase diagram as well as near-DFT accuracy in the prediction of many key properties, such as elastic constants, formation energies, melting points, etc., across the entire binary composition range. In contrast, the existing Ni-Mo EAM has significant errors in the prediction of the phase diagram and completely fails in binary compounds. Lastly, this paper provides a systematic model development process for multicomponent alloy systems, including an efficient procedure to optimize the hyperparameters in the model fitting, and paves the way for long-time large-scale simulations of such systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Wide-area lustre file system using LNet routers

Scientific and big data computations are increasingly being distributed across wide-area networks, and they often require access to remote files. The file systems that are directly mounted over wide-area networks transparently support such computations, and also obviate the need for special purpose file transfer tools. In typical distributed file systems, the access is limited to local sites, and in particular, the reach of Lustre file system implemented over InfiniBand (IB) is limited to at most tens of miles due to 2.5ms latency bound. We describe LNet router methods that connect IB Lustre file system to remote Ethernet clients over wide-area networks. We collect extensive Lustre throughput measurements over 10Gbps connections with 0-366ms round-trip times. They demonstrate that Gbps throughput can be sustained over connections spanning the globe. We present Lustre throughput profiles over local and wide-area connections, which show the effects of various buffers and credits; in particular, they highlight the throughput limits for large transfers over wide-area connections. Furthermore, the measurements show the positive effects of pipelining in achieving higher throughput for successively file transfers compared to rates indicated by IOzone benchmark rates.

Rao, Nageswara↗

Experimental and Computational Investigation of Shaped Film Cooling Holes Designed to Minimize Inlet Separation

Abstract Film cooling is used to protect turbine components from the extreme temperatures by ejecting coolant through arrays of holes to create an air buffer from the hot combustion gases. Limitations in traditional machining meant film cooling holes universally have sharp inlets, which create separation regions at the hole entrance. The present study uses experimental and computational data to show that these inlet separation are a major cause of performance variation in crossflow fed film cooling holes. Three-hole designs were experimentally tested by independently varying the coolant velocity ratio (VR) and the coolant channel velocity ratio (VRc) to isolate the effects of crossflow on hole performance. Leveraging additive manufacturing (AM) technologies, the addition of a 0.25D radius fillet to the inlet of a 7-7-7 shaped hole is shown to significantly improve diffuser usage and significantly reduce variation in performance with VRc. A second AM design used a very large radius of curvature inlet to reduce biasing caused by the inlet crossflow. Experiments showed that this “swept” hole design did minimize biasing of the coolant flow to one side of the shaped hole, and it significantly reduced variations due to varying VRc. RANS simulations at six VR and three VRc conditions were made for each geometry to better understand how the new geometries changed the velocity field within the hole. The sharp and rounded inlets were seen to have very similar tangential velocity fields and jet biasing. Both AM inlets created more uniform, slower velocity fields entering the diffuser. The results of this article indicate that large improvements in film cooling performance can be found by leveraging AM technology.

Engineering↗

Cross-Cutting Software Solutions in Support of Experimental Analysis Challenges at National Scattering Facilities

Rapid improvements in instrumentation at neutron and light source combined with new capabilities in computing, data analytics, and machine learning offer unprecedented scientific capabilities to address fundamental and applied science questions in a wide area of subjects from quantum materials to biological systems. In order to make these capabilities accessible to the broader scientific community, significant developments are needed related to workflow spanning from experimental control to advanced materials simulations as well as the underpinning scientific software. In this chapter, we explore these needs and recent developments at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory. A central part of the workflow at the SNS is the data reduction framework Mantid which is developed as a partnership between European and US neutron-scattering facilities.

Proffen, Thomas↗

Synthesis and functionalization of electron-deficient perfluoroalkyl porphyrin building blocks for supermolecular systems

Synthetic strategies for electron-deficient meso-perfluoroalkylporphyrins bearing diverse functional groups are described. Scalable and efficient syntheses for 5-triisopropylsilylethynyl-10,15,20-tris(heptafluoropropyl)porphyrin and 5-triisopropylsilylethynyl-10,20-bis(heptafluoropropyl)porphyrin that equip meso-ethynyl functional groups via the bilane route have been established, along with a refined route to [5,15-bis(heptafluoropropyl)porphinato]zinc(II). meso-Position halogenation of [5,15-bis(heptafluoropropyl)porphinato]zinc(II) was achieved by selective meso-nitration and subsequent reduction, diazonium salt formation, and iodination reactions. Computational data describe the low energy excited states of these chromophores and the electronic structural factors that control reactivity of these meso-perfluoroalkyl substituted porphyrin complexes. meso-Functionalized [5-triisopropylsilylethynyl-10,20-bis(heptafluoropropyl)porphinato]zinc(II) and [5-iodo-10,20-bis(heptafluoropropyl)porphinato]zinc(II) building blocks lay the foundation for the construction of highly conjugated multiporphyrin arrays that feature electronic structural properties important for the development of n-type materials and high potential photooxidants.

Chemistry↗

Dynamic Facade Dashboard v0.1.0

The dashboard is a useful tool for early-stage building design decision-making and communication, as it can help users quickly compare the energy and non-energy related performance of various automated, integrated facade systems using a library of pre-computed data. Users can explore the impacts of various design choices by selecting different facade glazing and shading systems, facade control strategies, and lighting control strategies across multiple climate zones. The dashboard instantly visualizes key metrics, including energy usage in HVAC and lighting, peak cooling and heating load, and daylight availability, allowing immediate trade-off analysis to optimize building efficiency and comfort.

Yu, Tammie [Lawrence Berkeley National Laboratory ↗

Co-design Center for Exascale Machine Learning Technologies (ExaLearn)

We report rapid growth in data, computational methods, and computing power is driving a remarkable revolution in what variously is termed machine learning (ML), statistical learning, computational learning, and artificial intelligence. In addition to highly visible successes in machine-based natural language translation, playing the game Go, and self-driving cars, these new technologies also have profound implications for computational and experimental science and engineering, as well as for the exascale computing systems that the Department of Energy (DOE) is developing to support those disciplines. Not only do these learning technologies open up exciting opportunities for scientific discovery on exascale systems, they also appear poised to have important implications for the design and use of exascale computers themselves, including high-performance computing (HPC) for ML and ML for HPC. The overarching goal of the ExaLearn co-design project is to provide exascale ML software for use by Exascale Computing Project (ECP) applications, other ECP co-design centers, and DOE experimental facilities and leadership class computing facilities.

97 MATHEMATICS AND COMPUTING↗

Thermodynamic Modeling of Intrinsic Defects in MnBi₂Te₄

This repository contains the computational data supporting the manuscript titled “The critical role of intrinsic defects and many-body interactions on the stability of MnBi₂Te₄.” It includes: 1. DFT data generated using VASP, used for training and benchmarking electronic structure models. 2. Quantum Monte Carlo (QMC) data produced with QMCPACK, used to apply many-body corrections and validate the electronic and magnetic properties of MnBi₂Te₄. 3. Relevant scripts used to run, analyze, and process the calculations, enabling reproducibility and transparency of the workflows.

36 MATERIALS SCIENCE↗

X-ray diffraction reveals two structural transitions in szomolnokite

Hydrated sulfates have been identified and studied in a wide variety of environments on Earth, Mars, and the icy satellites of the solar system. The subsurface presence of hydrous sulfur-bearing phases to any extent necessitates a better understanding of their thermodynamic and elastic properties at pressure. End-member experimental and computational data are lacking and are needed to accurately model hydrous, sulfur-bearing planetary interiors. In this work, high-pressure X-ray diffraction (XRD) and synchrotron Fourier-transform infrared (FTIR) measurements were conducted on szomolnokite (FeSO 4 ·H 2 O) up to ~83 and 24 GPa, respectively. This study finds a monoclinic-triclinic (C2/c to P1¯) structural phase transition occurring in szomolnokite between 5.0(1) and 6.6(1) GPa and a previously unknown triclinic-monoclinic (P1¯ to P2 1 ) structural transition occurring between 12.7(3) and 16.8(3) GPa. The high-pressure transition was identified by the appearance of distinct reflections in the XRD patterns that cannot be attributed to a second phase related to the dissociation of the P1¯ phase, and it is further characterized by increased H 2 O bonding within the structure. We fit third-order Birch-Murnaghan equations of state for each of the three phases identified in our data and refit published data to compare the elastic parameters of szomolnokite, kieserite (MgSO 4 ·H 2 O), and blödite (Na 2 Mg(SO 4 ) 2 ·4H 2 O). At ambient pressure, szomolnokite is less compressible than blödite and more than kieserite, but by 7 GPa both szomolnokite and kieserite have approximately the same bulk modulus, while blödite’s remains lower than both phases up to 20 GPa. Furthermore, these results indicate the stability of szomolnokite’s high-pressure monoclinic phase and the retention of water within the structure up to pressures found in planetary deep interiors.

58 GEOSCIENCES↗

ASC FY17 Implementation Plan, Rev. 1

The Stockpile Stewardship Program (SSP) is an integrated technical program for maintaining the safety, surety, and reliability of the U.S. nuclear stockpile. The SSP uses nuclear test data, computational modeling and simulation, and experimental facilities to advance understanding of nuclear weapons. It includes stockpile surveillance, experimental research, development and engineering programs, and an appropriately scaled production capability to support stockpile requirements. This integrated national program requires the continued use of experimental facilities and programs, and the computational capabilities to support these programs. The Advanced Simulation and Computing Program (ASC) is a cornerstone of the SSP, providing simulation capabilities and computational resources that support annual stockpile assessment and certification, study advanced nuclear weapons design and manufacturing processes, analyze accident scenarios and weapons aging, and provide the tools to enable stockpile Life Extension Programs (LEPs) and the resolution of Significant Finding Investigations (SFIs). This requires a balance of resources, including technical staff, hardware, simulation software, and computer science solutions.

97 MATHEMATICS AND COMPUTING↗

Topology Optimization for Nonlinear Transient Applications Using a Minimally Invasive Approach (LDRD Final Report)

The purpose of this project was to devise, implement, and demonstrate a method that can use Sandia's existing analysis codes (e.g., Sierra, Alegra, the CTH hydro code) with minimal modification to generate objective function gradients for optimization-based design in transient, non-linear, coupled-physics applications. The approach uses a Moving Least Squares representation of the geometry to substantially reduce the number of geometric degrees of freedom. A Multiple-Program Multiple-Data computing model is then used to compute objective gradients via finite differencing. Details of the formulation and implementation are provided, and example applications are presented that show effectiveness and scalability of the approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Blockchain for High Performance Data Integrity and Provenance

Describes the development of a test bed to evaluate the the feasibility of different Blockchain mechanisms for determining the integrity of data computed on a high performance computer while limiting the degradation of performance.

99 GENERAL AND MISCELLANEOUS↗

Atomically Defined Edge-Doping of Graphene Nanoribbons for Mesoscale Electronics

The outstanding transformative potential of graphene, an infinite two-dimensional sheet of carbon atoms tightly packed into a honeycomb lattice, has been recognized mostly due to its exceptionally high electric conductivity, thermal conductivity, and tensile strength. These undeniably very desirable properties, however, represent only a very small facet of the true potential of all-sp2 carbon materials and its promise to revolutionize the field of molecular electronics. Graphene's most unusual characteristics emerge when the infinite macroscopic sheet is scaled down to nanometer dimensions. The exploration, realization, and implementation of these truly exotic magnetic and electronic properties rely on the development of innovative synthetic strategies that provide atomically precise control over the self-assembly of mesoscale objects. While traditional device architectures based on inorganic semiconductors have been fabricated using a top-down approach, we pursued a diametrically opposite strategy. Our design of a new generation of high-performance electronic materials relies on a modular bottom-up strategy. This highly multidisciplinary research program has been rooted in the synthesis of functional organic materials with precisely defined properties, their controlled assembly into hierarchical structures, and the evaluation of their performance at the molecular and the macroscopic scale. A part of this research program we have developed the chemical tools required to synthesize and to fine-tune the physical properties of graphene nanoribbons (GNR) with atomic precision. We further demonstrated that the innovative techniques and the expanded knowledge can be used to rationally tailor desired physical properties and function into nanometer-scale carbon-based electronic devices; e.g. transistors as logic gates in computing, data storage media based on electrically gated spin valves, or molecular amplifiers, all functionally integrated in atomically defined GNRs. We demonstrated the design and experimental realization of a rationally engineered graphene nanoribbon superlattice that hosts a 1D array of symmetry-protected topological states. We developed a hierarchical bottom-up fabrication strategy for graphene nanoribbons that preferentially exhibit a single heterojunction interface rather than a random statistical sequence of junctions along the ribbon. We reported the bottom-up synthesis of a series of atomically precise graphene nanoribbons featuring trigonal planar heteroatom dopants (nitrogen, oxygen, and sulfur) along the edges that induce a narrowing of the intrinsic band gap by ~0.2–0.3 eV per dopant atom. We reported the bottom-up synthesis of a graphene nanoribbon heterostructure featuring a highly tunable porphyrin quantum dot embedded at the center of a solution processable graphene nanoribbon. We reported a new technique for fabricating bottom-up graphene nanoribbon heterojunctions through a late-stage chemical transformation that results in atomically sharp heterojunction structures from a single precursor. We demonstrated the intrinsic performance enhancement of a composite material comprised of gold nanoparticles (AuNPs) embedded in a bottom-up synthesized graphene nanoribbon matrix for the electrocatalytic reduction of CO 2 . We developed a scalable, solution-based approach toward the synthesis of an exotic class of polycyclic aromatic hydrocarbons that exhibit unusual electronic and magnetic properties in the ground state. We reported the bottom-up synthesis and characterization of atomically-defined graphene nanoribbons featuring a regioregular pattern of group III dopant atoms (boron) along the backbone of the ribbon.

36 MATERIALS SCIENCE↗

Summer Proceedings 2019

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researchers to learn about problems in computer and computational science at DOE laboratories. Participants conduct leading-edge research, interact with scientists and engineers at the laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, adaptivity and mesh refinement, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers and heterogeneous computers, data-intensive computing, environments for scalable computing, parallel input/output, advanced architectures, and theoretical computer science. The CSRI Summer Program includes the organization of a weekly seminar series and the publication of this summer proceedings.

97 MATHEMATICS AND COMPUTING↗