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At least 1,369 records · Page 76

Engineering mechanical and thermomechanical performance in additive manufacturing–Compression molded composites through multiplexed extrusion

Traditional extrusion-based additive manufacturing is limited to single material systems, restricting the multifunctional properties of composites. For this work to overcome this limitation, multiplexed additive manufacturing–compression molding (AM-CM) was employed to fabricate multi-material thermoplastic composites with spatially tailored architectures. Neat acrylonitrile butadiene styrene (ABS) and 20 wt% carbon-fiber reinforced ABS (CF-ABS) were co-extruded through a core–sheath nozzle to produce hybrid composites with neat ABS as sheath (30-50 wt%) and CF-ABS as core (50 – 70 wt%). The results show that the hybrid composites have balance of mechanical and thermomechanical performance. The tensile strength and modulus of hybrid composites exhibited a 61–95% and 173–473% increase compared to neat ABS with increases in CF-ABS content whereas the impact resistance improved by 41% compared to CF-ABS at 50 wt% ABS. Additionally, hybrid composites showed significant reduction (54 - 70%) in creep strain at 100 °C compared to neat ABS. These findings demonstrate that multiplexed AM-CM enables tunable structure–property relationships, reducing CF-ABS usage up to 50 wt% while maintaining balanced stiffness, toughness, and creep resistance.

Additive manufacturing↗

Discovery and construction of surface kagome electronic states induced by p-d electronic hybridization in Co3Sn2S2

Abstract Kagome-lattice materials possess attractive properties for quantum computing applications, but their synthesis remains challenging. Herein, based on the compelling identification of the two cleavable surfaces of Co 3 Sn 2 S 2 , we show surface kagome electronic states (SKESs) on a Sn-terminated triangular Co 3 Sn 2 S 2 surface. Such SKESs are imprinted by vertical p-d electronic hybridization between the surface Sn (subsurface S) atoms and the buried Co kagome-lattice network in the Co 3 Sn layer under the surface. Owing to the subsequent lateral hybridization of the Sn and S atoms in a corner-sharing manner, the kagome symmetry and topological electronic properties of the Co 3 Sn layer is proximate to the Sn surface. The SKESs and both hybridizations were verified via qPlus non-contact atomic force microscopy (nc-AFM) and density functional theory calculations. The construction of SKESs with tunable properties can be achieved by the atomic substitution of surface Sn (subsurface S) with other group III-V elements (Se or Te), which was demonstrated theoretically. This work exhibits the powerful capacity of nc-AFM in characterizing localized topological states and reveals the strategy for synthesis of large-area transition-metal-based kagome-lattice materials using conventional surface deposition techniques.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Numerical study of pure rotational fs/ps CARS coherence beating at high pressure and for multi-species rotation-vibration non-equilibrium thermometry

Coherent anti-Stokes Raman scattering (CARS) has long been the gold standard for non-intrusively measuring gas temperature in reacting flows such as flames and plasmas. Recently, the development of ultrafast hybrid fs/ps CARS has enabled the exploitation of coherence beating between neighboring spectral lines to simultaneously measure rotational and vibrational temperatures from a single pure rotational spectrum. However, the influence of non-Boltzmann vibrational state distributions and limitations due to collisional dephasing at pressures greater than 1 atm remains unclear. In this work, we use spectral simulations to investigate the effects of non-Boltzmann vibrational state distributions and the applicability of coherence beating at pressures up to 10 atm. We show that short probe pulses can be leveraged to quantify non-Boltzmann vibrational state distributions of N2. Furthermore, we demonstrate that fs/ps CARS coherence beating can simultaneously provide sensitive measurements of rotational and vibrational temperatures of both O2 and N2 in air. A sensitivity analysis was conducted to qualitatively explain the accuracy and precision comparisons between probe delays.

Chen, Timothy Y. (ORCID:0000000330269767)↗

Improved band gaps and structural properties from Wannier–Fermi–Löwdin self-interaction corrections for periodic systems

The accurate prediction of band gaps and structural properties in periodic systems continues to be one of the central goals of electronic structure theory. However, band gaps obtained from popular exchange–correlation (XC) functionals (such as LDA and PBE) are severely underestimated partly due to the spurious self-interaction error (SIE) inherent to these functionals. In this work, we present a new formulation and implementation of Wannier function-derived Fermi–Löwdin (WFL) orbitals for correcting the SIE in periodic systems. Since our approach utilizes a variational minimization of the self-interaction energy with respect to the Wannier charge centers (WCC), it is computationally more efficient than the HSE hybrid functional and other self-interaction corrections that require a large number of transformation matrix elements. Here, calculations on several (17 in total) prototypical molecular solids, semiconductors, and wide-bandgap materials show that our WFL self-interaction correction approach gives better band gaps and bulk moduli compared to semilocal functionals, largely due to the partial removal of self-interaction errors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Noise resilience of variational quantum compiling

Variational hybrid quantum-classical algorithms (VHQCAs) are near-term algorithms that leverage classical optimization to minimize a cost function, which is efficiently evaluated on a quantum computer. Recently VHQCAs have been proposed for quantum compiling, where a target unitary U is compiled into a short-depth gate sequence V. In this work, we report on a surprising form of noise resilience for these algorithms. Namely, we find one often learns the correct gate sequence V (i.e. the correct variational parameters) despite various sources of incoherent noise acting during the cost-evaluation circuit. Our main results are rigorous theorems stating that the optimal variational parameters are unaffected by a broad class of noise models, such as measurement noise, gate noise, and Pauli channel noise. Furthermore, our numerical implementations on IBM's noisy simulator demonstrate resilience when compiling the quantum Fourier transform, Toffoli gate, and W-state preparation. Hence, variational quantum compiling, due to its robustness, could be practically useful for noisy intermediate-scale quantum devices. Finally, we speculate that this noise resilience may be a general phenomenon that applies to other VHQCAs such as the variational quantum eigensolver.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Enhancing Power Grid Resilience with Causal Loops Diagram and Bayesian Networks

Enhancing power grid resilience through improved analysis and planning of Distributed Energy Resources is a key for power system planner. This paper explores the integration of Causal Loop Diagrams (CLDs) and Bayesian Networks (BNs) for enhancing resilience in power systems, focusing on Distributed Energy Resources (DER) planning. By automating CLD analysis in Python's matplotlib, we present a tool for rapid model validation and structural accuracy, crucial for power system planners. This hybrid approach utilizes BNs for inferential depth and CLDs for dynamic system modeling, offering a comprehensive framework for policy formulation and collaborative strategy development against disruptions. Here, we highlight the tool's capability to identify and analyze interconnected feedback loops, facilitating a deeper understanding of DER integration's impact on network resilience. This work aims to bridge quantitative analysis and qualitative insights, addressing the limitations of each method while providing a robust model for power system resilience assessment.

14 SOLAR ENERGY↗

Atomic-resolution lithography with an on-chip scanning tunneling microscope

In this work, atomic-resolution lithography with a Microelectromechanical-System (MEMS) based Scanning Tunneling Microscope (STM) is demonstrated for the first time. The microscope consists of a commercial UltraHigh-Vacuum (UHV) STM whose regular tip is replaced with a 1-Degree-of-Freedom (1-DOF) MEMS nanopositioner. This results in a hybrid STM system where XY-plane motions are provided by the piezotube of the original system and Z-axis motion by the MEMS with a higher bandwidth. Sharp tips made of Pt or W are added to the MEMS devices with postfabrication techniques. With this hybrid system, STM-based lithography is demonstrated on an H-passivated Si (100)-2×1 sample under UHV condition. Results prove the capability of the hybrid STM system for atomic-scale lithography. This capability, paired with the small footprint of the MEMS device, makes this approach a candidate for building a high-throughput parallel STM lithography platform by incorporating an array of 1-DOF MEMS devices that perform lithography in parallel.

Alipour, Afshin (ORCID:0000000263252067)↗

Designing and prototyping extensions to the Message Passing Interface in MPICH

As HPC system architectures and the applications running on them continue to evolve, the MPI standard itself must evolve. The trend in current and future HPC systems toward powerful nodes with multiple CPU cores and multiple GPU accelerators makes efficient support for hybrid programming critical for applications to achieve high performance. However, the support for hybrid programming in the MPI standard has not kept up with recent trends. The MPICH implementation of MPI provides a platform for implementing and experimenting with new proposals and extensions to fill this gap and to gain valuable experience and feedback before the MPI Forum can consider them for standardization. Here, in this work, we detail six extensions implemented in MPICH to increase MPI interoperability with other runtimes, with a specific focus on heterogeneous architectures. First, the extension to MPI generalized requests lets applications integrate asynchronous tasks into MPI’s progress engine. Second, the iovec extension to datatypes lets applications use MPI datatypes as a general-purpose data layout API beyond just MPI communications. Third, a new MPI object, MPIX_Stream, can be used by applications to identify execution contexts beyond MPI processes, including threads and GPU streams. MPIX stream communicators can be created to make existing MPI functions thread-aware and GPU-aware, thus providing applications with explicit ways to achieve higher performance. Fourth, MPIX Streams are extended to support the enqueue semantics for offloading MPI communications onto a GPU stream context. Fifth, thread communicators allow MPI communicators to be constructed with individual threads, thus providing a new level of interoperability between MPI and on-node runtimes such as OpenMP. Lastly, we present an extension to invoke MPI progress, which lets users spawn progress threads with fine-grained control to adapt the communication performance to their application designs. We describe the design and implementation of these extensions, provide usage examples, and highlight their expected benefits with performance results.

97 MATHEMATICS AND COMPUTING↗

Towards a more general understanding of the algorithmic utility of recurrent connections

Lateral and recurrent connections are ubiquitous in biological neural circuits. Yet while the strong computational abilities of feedforward networks have been extensively studied, our understanding of the role and advantages of recurrent computations that might explain their prevalence remains an important open challenge. Foundational studies by Minsky and Roelfsema argued that computations that require propagation of global information for local computation to take place would particularly benefit from the sequential, parallel nature of processing in recurrent networks. Such “tag propagation” algorithms perform repeated, local propagation of information and were originally introduced in the context of detecting connectedness, a task that is challenging for feedforward networks. Here, we advance the understanding of the utility of lateral and recurrent computation by first performing a large-scale empirical study of neural architectures for the computation of connectedness to explore feedforward solutions more fully and establish robustly the importance of recurrent architectures. In addition, we highlight a tradeoff between computation time and performance and construct hybrid feedforward/recurrent models that perform well even in the presence of varying computational time limitations. We then generalize tag propagation architectures to propagating multiple interacting tags and demonstrate that these are efficient computational substrates for more general computations of connectedness by introducing and solving an abstracted biologically inspired decision-making task. Our work thus clarifies and expands the set of computational tasks that can be solved efficiently by recurrent computation, yielding hypotheses for structure in population activity that may be present in such tasks.

59 BASIC BIOLOGICAL SCIENCES↗

Atomistic Assessment of Solute-Solute Interactions during Grain Boundary Segregation

Grain boundary solute segregation is becoming increasingly common as a means of stabilizing nanocrystalline alloys. Thermodynamic models for grain boundary segregation have recently revealed the need for spectral information, i.e., the full distribution of environments available at the grain boundary during segregation, in order to capture the essential physics of the problem for complex systems like nanocrystalline materials. However, there has been only one proposed method of extending spectral segregation models beyond the dilute limit, and it is based on simple, fitted parameters that are not atomistically informed. In this work, we present a physically motived atomistic method to measure the full distribution of solute-solute interaction energies at the grain boundaries in a polycrystalline environment. We then cast the results into a simple thermodynamic model, analyze the Al(Mg) system as a case study, and demonstrate strong agreement with physically rigorous hybrid Monte Carlo/molecular statics simulations. This approach provides a means of rapidly measuring key interactions for non-dilute grain boundary segregation for any system with an interatomic potential.

36 MATERIALS SCIENCE↗

Field Science Ethnography: Methods For Systematic Observation on an Expedition

The Haughton-Mars expedition is a multidisciplinary project, exploring an impact crater in an extreme environment to determine how people might live and work on Mars. The expedition seeks to understand and field test Mars facilities, crew roles, operations, and computer tools. I combine an ethnographic approach to establish a baseline understanding of how scientists prefer to live and work when relatively unemcumbered, with a participatory design approach of experimenting with procedures and tools in the context of use. This paper focuses on field methods for systematically recording and analyzing the expedition's activities. Systematic photography and time-lapse video are combined with concept mapping to organize and present information. This hybrid approach is generally applicable to the study of modern field expeditions having a dozen or more multidisciplinary participants, spread over a large terrain during multiple field seasons.

Clancey, William J.↗

Micro-Slit Collimators for X-Ray/Gamma-Ray Imaging

A hybrid photochemical-machining process is coupled with precision stack lamination to allow for the fabrication of multiple ultra-high-resolution grids on a single array substrate. In addition, special fixturing and etching techniques have been developed that allow higher-resolution multi-grid collimators to be fabricated. Building on past work of developing a manufacturing technique for fabricating multi-grid, high-resolution coating modulation collimators for arcsecond and subarcsecond x-ray and gamma-ray imaging, the current work reduces the grid pitch by almost a factor of two, down to 22 microns. Additionally, a process was developed for reducing thin, high-Z (tungsten or molybdenum) from the thinnest commercially available foil (25 microns thick) down to approximately equal to 10 microns thick using precisely controlled chemical etching

Appleby, Michael↗

Mission Oriented Support and Theory (MOST) for MMS -- The Goddard Space Flight Center/University of California Los Angeles Interdisciplinary Science Program

The MOST IDS team was tasked with focusing on two general areas: The first was to participate with the Fast Plasma Investigation (FPI) team in the development of virtual detectors that model the instrument responses of the MMS FPI sensors. The virtual instruments can be 'flown through' both simulation data (from magnetohydrodynamic, hybrid, and kinetic simulations) and Cluster and THEMIS spacecraft data. The goal is to determine signatures of magnetic reconnection expected during the MMS mission. Such signatures can serve as triggers for selection of burst mode downloads. The chapter contributed by the FPI team covers that effort in detail and, therefore, most of that work has not been included here. The second area of emphasis, and the one detailed in this chapter, was to build on past and present knowledge of magnetic reconnection and its physical signatures. Below we describe intensive analyses of Cluster and THEMIS data together with theoretical models and simulations that delineate the plasma signatures that surround sites of reconnection, including the effects of turbulence as well as the detailed kinetic signatures that indicate proximity to reconnection sites. In particular, we point out that particles are energized in several regions, not only at the actual site of reconnection.

Goldstein, Melvyn L.↗

Aeroheating Predictions for a Hypersonic, Turbulent Near-Wake

The accuracy of heating predictions using various turbulence models is examined for an axisymmetric near-wake at Mach 6. The CFD predictions are compared with experimental data collected under AGARD Working Group 18 on the wake of a 70-degree sphere-cone. The impact of grid resolution and discretization error is estimated, which allows a comparison of stacked-block and conventional structured meshes. The accuracy of steady Reynolds-averaged Navier-Stokes (RANS) models is contrasted with that of a hybrid RANS/Large-Eddy Simulation model. The predictions are made with three different CFD codes (LAURA, FUN3D, and HyperSolve), to demonstrate the code-to-code variation in the results. Steady SST models capture the qualitative nature of the heating in the wake, including the increasing peak heating with increasing Reynolds number. Spalart-Allmaras models, including SA-Catris, under-predicted the peak heating in the wake. Hybrid RANS/LES models improve upon the SA results but have their own modeling difficulties near the shear layer impingement. These results are generally consistent across solvers and grid topologies.

RANS↗

Aeroheating Predictions for a Hypersonic, Turbulent Near-Wake

The accuracy of heating predictions using various turbulence models is examined for an axisymmetric near-wake at Mach 6. The CFD predictions are compared with experimental data collected under AGARD Working Group 18 on the wake of a 70-degree sphere-cone. The impact of grid resolution and discretization error is estimated, which allows a comparison of stacked-block and conventional structured meshes. The accuracy of steady Reynolds-averaged Navier-Stokes (RANS) models is contrasted with that of a hybrid RANS/Large-Eddy Simulation model. The predictions are made with three different CFD codes (LAURA, FUN3D, and HyperSolve), to demonstrate the code-to-code variation in the results. Steady SST models capture the qualitative nature of the heating in the wake, including the increasing peak heating with increasing Reynolds number. Spalart-Allmaras models, including SA-Catris, under-predicted the peak heating in the wake. Hybrid RANS/LES models improve upon the SA results but have their own modeling difficulties near the shear layer impingement. These results are generally consistent across solvers and grid topologies.

RANS↗

Reduced Surface Recombination Velocity in Mixed-Cation Mixed-Halide Hybrid Perovskite Devices Leads to Improved Open-Circuit Voltage

Surface recombination plays an important role in perovskite solar cell performance.Despite rapid progress, the record power conversion efficiency (PCE, ~ 25.7%) for perovskite single-junction solar cells still lags behind its theoretical limit (~ 32%), largely due to the open circuit voltage (VOC) deficit that results from non-radiative recombination at the bulk of perovskite films and the interfaces between perovskite and transport layers. In this work, we show that (3-aminopropyl)trimethoxysilane (APTMS) surface passivation can reduce the surface recombination velocities (SRVs) of perovskite solar cells, thus improving device VOC and PCE.

perovskite solar cell, surface recombination, surf↗

Thermal Energy Storage Model Development within the Integrated Energy Systems Hybrid Repository

This publication details newly created energy storage models developed within the HYBRID Modelica repository as part of the Department of Energy Office of Nuclear Energy (DOE-NE) Integrated Energy Systems (IES) program, led by Idaho National Laboratory (INL). Model development to-date includes creation of dynamic systems-level models of concrete, latent heat, and packed-bed thermocline energy storage technologies for deployment in the IES-based HYBRID repository. Models are developed using the latest publicly available data and incorporate the possibility of control strategy inclusion for use with the existing IES modeling, analysis, and optimization toolset. Simulations showcase the abilities of each technology to cyclically charge and discharge when exposed to time-varying boundary conditions. In addition, low-level surrogate models for some of the thermal energy storage technologies were created using Python. These lower order Python files are much cheaper to run (i.e., computationally faster) and thus operate well when incorporated within the stochastic optimization problems run for the IES program. Moreover, economic data was collected for use within the INL-developed Framework for Optimization of ResourCes and Economics (FORCE). This information is incorporated within the FORCE platform. This work has resulted in creation of systems-level models for concrete, latent heat, and thermocline thermal energy storage systems with associated control systems. Now that these models are available, they can be utilized within different integrated energy park concepts to understand optimal system operation, control, and dispatching. Moreover, given the generic nature of the models, industrial partner technologies (e.g., Storworks Power, EnergyNest) can be quickly added to the repository using the existing models as a basis. Additional dynamic models for thermal energy storage concepts can be developed and added to the HYBRID repository as needed.

25 ENERGY STORAGE↗

Singleplex, multiplex and pooled sample real-time RT-PCR assays for detection of SARS-CoV-2 in an occupational medicine setting

Abstract For workplaces which cannot operate as telework or remotely, there is a critical need for routine occupational SARS-CoV-2 diagnostic testing. Although diagnostic tests including the CDC 2019-Novel Coronavirus (2019-nCoV) Real-Time RT-PCR Diagnostic Panel (CDC Diagnostic Panel) (EUA200001) were made available early in the pandemic, resource scarcity and high demand for reagents and equipment necessitated priority of symptomatic patients. There is a clearly defined need for flexible testing methodologies and strategies with rapid turnaround of results for (1) symptomatic, (2) asymptomatic with high-risk exposures and (3) asymptomatic populations without preexisting conditions for routine screening to address the needs of an on-site work force. We developed a distinct SARS-CoV-2 diagnostic assay based on the original CDC Diagnostic Panel (EUA200001), yet, with minimum overlap for currently employed reagents to eliminate direct competition for limited resources. As the pandemic progressed with testing loads increasing, we modified the assay to include 5-sample pooling and amplicon target multiplexing. Analytical sensitivity of the pooled and multiplexed assays was rigorously tested with contrived positive samples in realistic patient backgrounds. Assay performance was determined with clinical samples previously assessed with an FDA authorized assay. Throughout the pandemic we successfully tested symptomatic, known contact and travelers within our occupational population with a ~ 24–48-h turnaround time to limit the spread of COVID-19 in the workplace. Our singleplex assay had a detection limit of 31.25 copies per reaction. The three-color multiplexed assay maintained similar sensitivity to the singleplex assay, while tripling the throughput. The pooling assay further increased the throughput to five-fold the singleplex assay, albeit with a subtle loss of sensitivity. We subsequently developed a hybrid ‘multiplex-pooled’ strategy to testing to address the need for both rapid analysis of samples from personnel at high risk of COVID infection and routine screening. Herein, our SARS-CoV-2 assays specifically address the needs of occupational healthcare for both rapid analysis of personnel at high-risk of infection and routine screening that is essential for controlling COVID-19 disease transmission. In addition to SARS-CoV-2 and COVID-19, this work demonstrates successful flexible assays developments and deployments with implications for emerging highly transmissible diseases and future pandemics.

60 APPLIED LIFE SCIENCES↗