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Results for “THROUGHPUT”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15

All sources NASA NTRS DOE OSTI

DOE OSTI2014

Solion ion source for high-efficiency, high-throughput solar cell manufacturing

In this paper, we introduce the Solion ion source for high-throughput solar cell doping. As the source power is increased to enable higher throughput, negative effects degrade the lifetime of the plasma chamber and the extraction electrodes. In order to improve efficiency, we have explored a wide range of electron energies and determined the conditions which best suit production. To extend the lifetime of the source we have developed an in situ cleaning method using only existing hardware. With these combinations, source life-times of >200 h for phosphorous and >100 h for boron ion beams have been achieved while maintaining 1100 cell-per-hour production.

14 SOLAR ENERGY↗

DOE OSTI2016

High-throughput and automated SAXS/USAXS experiment for industrial use at BL19B2 in SPring-8

A highly automated system combining a sample transfer robot with focused SR beam has been established for small-angle and ultra small-angle X-ray scattering (SAXS/USAXS) measurement at BL19B2 for industrial use of SPring-8. High-throughput data collection system can be realized by means of X-ray beam of high photon flux density concentrated by a cylindrical mirror, and a two-dimensional pixel detector PILATUS-2M. For SAXS measurement, we can obtain high-quality data within 1 minute for one exposure using this system. The sample transfer robot has a capacity of 90 samples with a large variety of shapes. The fusion of high-throughput and robotic system has enhanced the usability of SAXS/USAXS capability for industrial application.

43 PARTICLE ACCELERATORS↗

DOE OSTI2016

A pulse-front-tilt–compensated streaked optical spectrometer with high throughput and picosecond time resolution

A high-throughput, broadband optical spectrometer coupled to the Rochester optical streak system equipped with a Photonis P820 streak tube was designed to record time-resolved spectra with 1-ps time resolution. Spectral resolution of 0.8 nm is achieved over a wavelength coverage range of 480 to 580 nm, using a 300-groove/mm diffraction grating in conjunction with a pair of 225-mm-focal-length doublets operating at an f/2.9 aperture. Overall pulse-front tilt across the beam diameter generated by the diffraction grating is reduced by preferentially delaying discrete segments of the collimated input beam using a 34-element reflective echelon optic. The introduced delay temporally aligns the beam segments and the net pulse-front tilt is limited to the accumulation across an individual sub-element. The resulting spectrometer design balances resolving power and pulse-front tilt while maintaining high throughput.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Message-passing neural networks for high-throughput polymer screening

Machine learning methods have shown promise in predicting molecular properties, and given sufficient training data, machine learning approaches can enable rapid high-throughput virtual screening of large libraries of compounds. Graph-based neural network architectures have emerged in recent years as the most successful approach for predictions based on molecular structure and have consistently achieved the best performance on benchmark quantum chemical datasets. However, these models have typically required optimized 3D structural information for the molecule to achieve the highest accuracy. These 3D geometries are costly to compute for high levels of theory, limiting the applicability and practicality of machine learning methods in high-throughput screening applications. In this study, we present a new database of candidate molecules for organic photovoltaic applications, comprising approximately 91,000 unique chemical structures. Compared to existing datasets, this dataset contains substantially larger molecules (up to 200 atoms) as well as extrapolated properties for long polymer chains. We show that message-passing neural networks trained with and without 3D structural information for these molecules achieve similar accuracy, comparable to state-of-the-art methods on existing benchmark datasets. Furthermore, these results therefore emphasize that for larger molecules with practical applications, near-optimal prediction results can be obtained without using optimized 3D geometry as an input. We further show that learned molecular representations can be leveraged to reduce the training data required to transfer predictions to a new density functional theory functional.

14 SOLAR ENERGY↗

DOE OSTI2023

VIPIR: A High-Throughput Drop-Weight Impact Instrument for Imaging the Initiation and Propagation of Reactions in Energetic Materials

Characterizing the handling safety and sensitivity of explosives has been a challenging area of study for over 60 years. Historically one of the most accessible and widely utilized experiments has been the drop-weight impact test, which involves dropping a weight on a small sample sandwiched between two anvils. Because this experiment generally only utilizes sound thresholds to determine whether or not a sample reacted, the physical and chemical properties governing sensitivity remain convolved. Better understanding of chemical and material characteristics is needed to give the chemistry and engineering communities a predictive tool to determine the handling sensitivity of explosives prior to pursuing expensive and potentially hazardous synthesis and formulation operations. Here, we are developing a high throughput drop tower instrument capable of imaging the deformation and flow of energetic materials during impact and the resulting thermal ignition and propagation events. This instrument is based on previous designs but has been modified for higher throughput and tailorable modifications in the future. Herein, we present key design features that enable high-speed visible and thermal imaging of explosive initiation by sub-shock impacts, as well as preliminary results in which ignition sites were observed in an erythritol tetranitrate sample.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Absolute throughput calibration of multiple spherical crystals for the Orion High-REsolution X-ray spectrometer (OHREX)

We present absolute throughput analysis of several crystals for the Orion High-REsolution X-ray (OHREX) imaging crystal spectrometer using ray tracing and experimental measurements. The OHREX spectrometer is a high-resolution x-ray spectrometer designed to measure spectral line shapes at the Orion laser facility. The spectrometer is fielded with up to two spherical crystals simultaneously covering two independent spectral ranges. Each crystal has a nominal radius of curvature of R = 67.2 cm and is fielded at a nominal Bragg angle of 51.3°. To cover different bands of interest, several different crystals are available, including Ge (111), KAP, and several cuts of quartz, whose resolving power λ/Δλ exceeds 10 000. The calibrated response of the available crystals has previously been reported from measurements at the EBIT-I electron beam ion trap at Lawrence Livermore National Laboratory. Here, we model the absolute throughput of each crystal using ray tracing and verify the results using experimental data for the quartz $(10\bar{1}1)$ crystal.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

High-throughput, in situ imaging of multi-layer powder-blown directed energy deposition with angled nozzle

Laser metal additive manufacturing (AM) has become an increasingly popular technology due to its flexibility in geometry and materials. As one of the commercialized additive processes, powder-blown directed energy deposition (DED) has been used in multiple industries such as aerospace, automotive, medical device, etc. However, a lack of fundamental understanding remains for this process, and many opportunities for alloy development and implementation can be identified. A high-throughput, in situ DED system capable of multi-layer builds that can address these issues is presented here. In this work, implications of layer heights and energy density are investigated through an extensive process parameter sweep, showcasing the power of a high-throughput setup while also discussing multi-layer interactions.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

High throughput, spatially resolved thermal properties measurement using attachable and reusable 3ω sensors

The 3ω method is a well-established thermal technique used to measure the thermal conductivity of materials and the thermal resistance of interfaces. It has significant advantages over other steady state and transient thermal techniques in its ability to provide spatially resolved thermal property measurements over a wide range of thermal conductivity. Despite its advantages, it has been restricted to lab-scale use because of the difficulty involved in sample preparation and sensor fabrication and is limited to non-metallic substrates. High-throughput 3ω measurements with reusable sensors have not been realized yet. In this work, we demonstrate a method of applying reusable 3ω sensors fabricated on flexible polyimide films to measure bulk and spatially resolved thermal properties. Here, we establish the limits of thermal conductivity measurement with the method to be 1 to 200 W/mK, and within the measurement limit, we verify the method by comparing the measured thermal conductivities of standard samples with established values. From the 3ω measurements, we also determine the thermal resistance of an interlayer of thermal grease as a function of pressure and compare it against the resistance calculated from direct thickness measurements to demonstrate the ability of this method to provide spatially resolved subsurface information. The technique presented is general and applicable to both metallic and non-metallic substrates, providing a method for high-throughput 3ω measurements with reusable sensors and without considerable sample preparation.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

High-throughput approach for investigating interdiffusion in medium- and high-entropy alloys

Interdiffusion experiments are usually time-consuming and tedious since diffusion couples must be annealed at several temperatures for a long time. The efforts required to study interdiffusion in multicomponent alloys increase dramatically as multiple diffusion couples are required to cover broad composition ranges and determine the diffusivities of individual elements in different chemical environments. To circumvent this challenge, we present a high-throughput approach applicable to single-phase and compositionally complex alloys, which are assumed to approximate ideal solid solutions. Here, a simple diffusion-multiple experiment combined with a physically based kinetic model is proposed to efficiently determine the diffusion coefficients of the constituent elements in quaternary CrFeCoNi alloys. Compared with tracer diffusivities reported in the literature, the results, thus, obtained do not differ by more than a factor of 2 and were obtained from a single interdiffusion experiment. In contrast, the diffusivities simulated with commercial mobility and thermodynamic databases are strongly overestimated by a factor ranging from 1 to 16. Therefore, our approach enables high-throughput determination of diffusivities and can help in the design of alloys for high-temperature applications where diffusion plays a key role.

36 MATERIALS SCIENCE↗

DOE OSTI2026

pyRMG: A framework for high-throughput, large-cell DFT calculations on supercomputers

Exascale computing delivers the raw power to simulate ever larger and more chemically realistic systems, but realizing this potential requires codes that can efficiently use thousands of processors. Our real-space multigrid (RMG) density functional theory (DFT) code’s grid-decomposition approach scales nearly linearly with the number of graphics processing units (GPUs), even for simulations exceeding thousands of atoms. This scalability makes RMG a compelling tool for high-throughput DFT studies of materials that would otherwise be bottlenecked in other codes (for example, by global fast Fourier transforms in plane-wave DFT). However, the limited workflow infrastructure for RMG has thus far constrained its adoption to a small user community. In this work, we present pyRMG, a Python package designed to streamline the setup and execution of RMG DFT calculations. Built on the pymatgen and ASE (Atomic Simulation Environment) computational materials science Python packages, pyRMG automates input generation and convergence checking, and it integrates with modern job schedulers (e.g., Flux) on leadership-class platforms such as Frontier and Perlmutter. Here, we demonstrate pyRMG for a high-throughput study of strain effects in 2D 2L-Bi 2 Se 3 /2L-NbSe 2 heterostructures, which offers chemical insights into this system and shows that RMG-based workflows can converge with limited user intervention.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

High-throughput, combinatorial synthesis of multimetallic nanoclusters

Significance Multielement nanomaterials hold great promise for various applications due to their widely tunable surface chemistry, yet it remains challenging to efficiently study this multidimensional space. Conventional approaches are typically slow and depend on serendipity, while a robust and general synthesis is still lacking among increasingly complex compositions. We report a high-throughput technique for combinatorial compositional design (formulation in solution phases) and rapid synthesis (within seconds) of ultrafine multimetallic nanoclusters with a homogeneous alloy structure. We synthesized and screened the PtPdRhRuIrFeCoNi compositional space using scanning droplet cell electrochemistry, with two promising catalysts quickly identified and further verified in a rotating disk setup. The reported high-throughput approach establishes a facile and reliable pipeline to significantly accelerate material discovery in multimetallic nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Automated segmentation of soft X-ray tomography: Native cellular structure with submicron resolution at high-throughput for whole-cell quantitative imaging in yeast

Soft X-ray tomography (SXT) is an invaluable tool for quantitatively analyzing cellular structures at suboptical isotropic resolution. However, it has traditionally depended on manual segmentation, limiting its scalability for large datasets. Here, we leverage a deep learning-based autosegmentation pipeline to segment and label cellular structures in hundreds of cells across three Saccharomyces cerevisiae strains. This task-based pipeline uses manual iterative refinement to improve segmentation accuracy for key structures, including the cell body, nucleus, vacuole, and lipid droplets, enabling high-throughput and precise phenotypic analysis. Using this approach, we quantitatively compared the three-dimensional (3D) whole-cell morphometric characteristics of wild-type, VPH1-GFP, and vac14 strains, uncovering detailed strain-specific cell and organelle size and shape variations. We show the utility of SXT data for precise 3D curvature analysis of entire organelles and cells and detection of fine morphological features using surface meshes. Our approach facilitates comparative analyses with high spatial precision and statistical throughput, uncovering subtle morphological features at the single-cell and population level. This workflow significantly enhances our ability to characterize cell anatomy and supports scalable studies on the mesoscale, with applications in investigating cellular architecture, organelle biology, and genetic research across diverse biological contexts.

Chen, Jianhua [Lawrence Berkeley National Laborato↗

DOE OSTI2013

GROMACS 4.5: A high-throughput and highly parallel open source molecular simulation toolkit

In this study, molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources. As a result, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

High-throughput quantification of quasistatic, dynamic and spall strength of materials across 10 orders of strain rates

Abstract The response of metals and their microstructures under extreme dynamic conditions can be markedly different from that under quasistatic conditions. Traditionally, high strain rates and shock stresses are achieved using cumbersome and expensive methods such as the Kolsky bar or large spall experiments. These methods are low throughput and do not facilitate high-fidelity microstructure–property linkages. In this work, we combine two powerful small-scale testing methods, custom nanoindentation, and laser-driven microflyer (LDMF) shock, to measure the dynamic and spall strength of metals. The nanoindentation system is configured to test samples from quasistatic to dynamic strain-rate regimes. The LDMF shock system can test samples through impact loading, triggering spall failure. The model material used for testing is magnesium alloys, which are lightweight, possess high-specific strengths, and have historically been challenging to design and strengthen due to their mechanical anisotropy. We adopt two distinct microstructures, solutionized (no precipitates) and peak-aged (with precipitates) to demonstrate interesting upticks in strain-rate sensitivity and evolution of dynamic strength. At high shock-loading rates, we unravel an interesting paradigm where the spall strength vs. strain rate of these materials converges, but the failure mechanisms are markedly different. Peak aging, considered to be a standard method to strengthen metallic alloys, causes catastrophic failure, faring much worse than solutionized alloys. Our high-throughput testing framework not only quantifies strength but also teases out unexplored failure mechanisms at extreme strain rates, providing valuable insights for the rapid design and improvement of materials for extreme environments.

Eswarappa Prameela, Suhas (ORCID:0000000334530184)↗

DOE OSTI2025

High-throughput spin-bath characterization of spin defects in semiconductors

Detailed knowledge of the local environments of spin defects in semiconductors, such as nitrogenvacancy (NV) centers in diamond or divacancies in silicon carbide, is crucial for optimizing control and entanglement protocols in quantum sensing and information applications. However, at present a direct experimental characterization of individual defect environments is not scalable, as conventional spin-bath measurements are time consuming and difficult to automate. Achieving high-throughput characterization requires short experiments to probe the spin bath. However, with fewer and noisier measurements, the inverse problem of recovering spin-bath properties from measured data becomes ill posed, with multiple spin baths having a high likelihood of yielding the same data. In this work, we present a set of computational tools to resolve the ill-posed inverse problem of recovering the atomic positions and hyperfine couplings of random nuclei surrounding spin defects from sparse, noisy experimental coherence data, which can be obtained in hours. Here, we use a trans-dimensional Bayesian approach that incorporates ab initio data to yield full posterior distributions over nuclear spin environments, enabling robust recovery from limited data. We also provide practical tools and guidelines to determine the limits of detectability for hyperfine couplings under specific dynamical decoupling sequences and sampling conditions. In addition, we demonstrate how the tools developed here, in combination with ab initio simulations of spin baths, can guide the design of efficient experimental protocols for application-specific high-throughput screening. To showcase the utility of our approach, we apply it to design fast dynamical decoupling experiments to characterize the spin baths often individual NV centers in diamond. While the primary focus is on accelerating spin-bath characterization of spin defects, this Bayesian approach also lays the foundation for digital-twin studies of spin defects, where a virtual model of the spin-defect system evolves in real time with ongoing experimental measurements. Together, the set of tools we designed and applied paves the way for scalable deployment of spin defects in semiconductors for quantum sensing and information applications.

Bayesian methods↗

DOE OSTI2010

Quantum throughput: Quantifying quantum-communication devices with homodyne measurements

Quantum communication relies on optical implementations of channels, memories, and repeaters. In the absence of perfect devices, a minimum requirement on real-world devices is that they preserve quantum correlations, meaning that they have some throughput of a quantum-mechanical nature. Previous work has verified throughput in optical devices while using minimal resources. We extend this approach to the quantitative regime. Our method is illustrated in a setting where the input consists of two coherent states while the output is measured by two homodyne measurement settings.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2011

High-energy-throughput pulse compression by off-axis group-delay compensation in a laser-induced filament

Off-axial beam dynamics of ultrashort laser pulses in a filament enable a radical energy-throughput improvement for filamentation-assisted pulse compression. We identify regimes where a weakly diverging wave, produced on the trailing edge of the pulse, catches up with a strongly diverging component, arising in the central part of the pulse, allowing sub-100-fs millijoule infrared laser pulses to be compressed to 20-25-fs pulse widths with energy throughputs in excess of 70%. Theoretical predictions have been verified by experimental results on filamentation-assisted compression of 70-fs, 1.5-{mu}m laser pulses in high-pressure argon.

42 ENGINEERING↗

DOE OSTI2016

Benchmarking density functional perturbation theory to enable high-throughput screening of materials for dielectric constant and refractive index

We demonstrate a high-throughput density functional perturbation theory (DFPT) methodology capable of screening compounds for their dielectric properties. The electronic and ionic dielectric tensors are calculated for 88 compounds, where the eigenvalues of the total dielectric tensors are compared with single crystal and polycrystalline experimental values reported in the literature. We find that GGA/PBE has a smaller mean average deviation from experiments (MARD=16.2%) when compared to LDA. The prediction accuracy of DFPT is lowest for compounds that exhibit complex structural relaxation effects (e.g., octahedra rotation in perovskites) and/or strong anharmonicity. Despite some discrepancies between DFPT results and reported experimental values, the high-throughput methodology is found to be useful in identifying interesting compounds by ranking. This is demonstrated by the high Spearman correlation factor (ρ=0.92). Finally, we demonstrate that DFPT provides a good estimate for the refractive index of a compound without calculating the frequency dependence of the dielectric matrix (MARD=5.7%).

36 MATERIALS SCIENCE↗