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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Implementation of a High-Fidelity Interface Resolving Method in Nek5000

The development and utilization of computational fluid dynamics (CFD) models for large, high-temperature electric melters in the Waste Treatment and Immobilization Plant (WTP) in eastern Washington State have proven to be valuable for various purposes. These models allow for a better understanding of the physio-chemical processes occurring within the melter vessels and can contribute to improving operational efficiency, throughput, and addressing operational issues related to vitrification. The CFD models employed for these melter vessels incorporate multiphase fluid flow and heat transfer simulations in different regions, including the plenum, cold cap, and molten glass regions. As the tank waste and glass formers are introduced into the melter, a reacting batch layer known as the cold cap forms on top of the molten glass. To enhance the melt rate, forced convection bubblers located at the bottom of the melters generate convection currents that help homogenize the molten glass and provide heat to the cold cap. As the bubbles rise through the highly viscous glass, they adopt a spherical-cap shape [1]. Meanwhile, the conversion of the batch to glass generates significant amounts of gases (such as water vapor, carbon dioxide, sulfur dioxide, and NOx) due to thermal decomposition [2]. These gases become trapped between the cold cap and molten glass, forming a foam layer [3]. For modeling multiphase flow in CFD and heat transfer simulations of waste glass melters at different scales, efforts are underway to augment the capabilities of the Nek5000 [4] and NekRS [5] open-source codes [6]. Nek5000/NekRS is a scalable and efficient spectral element code that has been successfully applied to a wide range of fluid dynamics problems. By leveraging the Nek5000/NekRS software, it becomes possible to model the melter systems more affordably and with lower computational requirements compared to currently utilized commercial CFD software. The specific objectives of this ongoing effort include: 1. Implementation of a level set method in Nek5000/NekRS: The level set method is a numerical technique commonly employed in CFD simulations to track and represent the interface between different phases or materials accurately. By incorporating this method into Nek5000/NekRS, the ability to simulate multiphase flows in waste glass melters at a high level of fidelity can be achieved. 2. Demonstration of capability for air bubbling through molten glass: As part of the development process, a specific case of air bubbling through molten glass will be simulated using the augmented Nek5000/NekRS code. This demonstration aims to showcase the ability of the software to accurately capture and analyze the complex phenomena involved in the multiphase flow within waste glass melters. By achieving these objectives, the improved Nek5000/NekRS code will offer a powerful computational tool for simulating and analyzing waste glass melter systems, enabling better understanding, optimization, and troubleshooting of these vitrification processes. The ability to accurately model and simulate multiphase flows has broad relevance across many industries and scientific domains, and the improved functionality can contribute to advancements in various fields beyond waste glass melter simulations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Dual low vacuum-ultrahigh vacuum system for large-scale production of micro-channel plate photomultipliers

Systems and methods for the batch production of large numbers of highly uniform multichannel-plate photomultiplier tubes (MCP-PMTs) for large-scale applications are provided. The systems and methods employ dual, nested low-vacuum (LV) and UHV processing in a rapid-cycling, small-footprint, scalable, batch-production facility that is capable of fabricating many MCP-PMTs simultaneously.

Frisch, Henry J.↗
DOE OSTI2023

Adaptive, Active Learning, and Multifidelity Monte Carlo Methods in the MOOSE Stochastic Tools Module

MOOSE is an open-source computational platform for constructing multi-physics models and executing them in a massively parallel fashion. It has a stochastic tools module (STM) for forward/inverse uncertainty quantification (UQ) and surrogate modeling. This presentation details some recent developments to the STM with respect to the implementation of adaptive, active learning, and multifidelity Monte Carlo methods for forward UQ of computational models. Specifically, the adaptive Monte Carlo methods include Markov Chain Monte Carlo (MCMC)-driven algorithms like adaptive importance sampling and parallelized subset simulation for statistical QoI estimation, rare events analysis, and stochastic gradient-free optimization. The active learning methods include Gaussian Process (GP) surrogates and their training via Adam optimization, design of acquisition functions, and integration with samplers like Monte Carlo, adaptive importance, and parallelized subset simulation. These active learning methods are also designed to work in a batch mode, wherein, the required calls to the full computational model are executed in parallel whenever a user-specified batch size is met. The multifidelity methods in STM are broadly divided into two categories: hierarchical, where a defined hierarchy exists among the low-fidelity models, and peer, where all the low-fidelity models are treated equally. A GP surrogate is used to learn the differences between the low- and high-fidelity models in both multifidelity categories, and acquisition functions from the active learning classes are used to decide whether to rely on a low-fidelity model or call the expensive high-fidelity model. Alongside the software description and usage, applications are also presented to nuclear engineering computational models including a TRISO nuclear fuel particle, a reactor pressure vessel, and a heat-pipe microreactor.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Evaluating Liquid Waste Transfers and their Impacts to the SRS Tank Farm to Support Operations and Closure

The Liquid Waste (LW) contractor at the Savannah River Site, Savannah River Mission Completion (SRMC), supports the storage, processing, and safe disposition of legacy, radioactive liquid waste. The LW Tank Farms contain approximately 127 million liters (33.5 million gallons) of liquid waste within 43 active, underground waste tanks. To meet mission critical milestones for the closure of waste tanks and processing of 34 million liters (9 million gallons) of salt waste per year by the LW Salt Waste Processing Facility (SWPF), an increase in Tank Farm operations, including waste tank transfers, is required. Waste is compiled in salt and sludge batches in the Tank Farms and transferred to SWPF and the Defense Waste Processing Facility (DWPF) for treatment. All waste tank transfers, such as waste removal and batch compilation transfers, must be pre-evaluated to ensure Documented Safety Analysis (DSA) requirements are met via Evaluated Transfer Approval Forms (ETAFs). Facility conditions and configurations may change as a result of a waste transfer. These changes must be reflected in the Tank Farms Emergency Response Datasheet (ERD), which contains data utilized for operation and emergency situations.

Peterson, Shelby R.↗
DOE OSTI2025

A Managed Tokens Service for Securely Keeping and Distributing Grid Tokens

Fermilab is transitioning authentication and authorization for grid operations to using bearer tokens based on the WLCG Common JWT (JSON Web Token) Profile. One of the functionalities that Fermilab experimenters rely on is the ability to automate batch job submission, which in turn depends on the ability to securely refresh and distribute the necessary credentials to experiment job submit points. Thus, with the transition to using tokens for grid operations, we needed to create a service that would obtain, refresh, and distribute tokens for experimenters' use. This service would avoid the need for experimenters to be experts in obtaining their own tokens and would better protect the most sensitive long-lived credentials. Further, the service needed to be widely scalable, as Fermilab hosts many experiments, each of which would need their own credentials. To address these issues, we created and deployed a Managed Tokens Service. The service is written in Go, taking advantage of that language's native concurrency primitives to easily be able to scale operations as we onboard experiments. The service uses as its first credentials a set of kerberos keytabs, stored on the same secure machine that the Managed Tokens service runs on. These kerberos credentials allow the service to use htgettoken via condor_vault_storer to store vault tokens in the HTCondor credential managers (credds) that run on the batch system scheduler machines (HTCondor schedds); as well as downloading a local, shorter-lived copy of the vault token. The kerberos credentials are then also used to distribute copies of the locally-stored vault tokens to experiment submit points.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Advanced Computational Modeling of High-Level Waste Vitrification at the Hanford Site

The U.S. Department of Energy (DOE) has selected vitrification for stabilizing legacy tank waste at the Hanford site, where radioactive waste from plutonium production was historically stored in underground tanks. This waste will be separated into low-activity waste (LAW) and high-level waste (HLW) fractions and processed at the Waste Treatment and Immobilization Plant (WTP). At WTP, glass melters are used for the vitrification of radioactive tank waste, transforming it into a stable borosilicate glass form for safe long-term storage. The melter vessel is constructed from highly durable and heat-resistant materials, where the vitrification process occurs. The main regions that are modeled are the melt pool, plenum, cold cap, riser/discharge chamber, and surrounding structure with insulation layers. Forced convection induced by air bubblers at the base of the melter ensure uniform temperature distribution and provide heat to the cold cap layer. The cold cap is a region of reacting batch feed that floats on top of the molten glass and is where the batch-to-glass reactions occur. Joule heating provided by electrodes mounted along the vertical walls of the melter and immersed directly in the glass, generates the necessary heat for the net endothermic conversion processes that occur in the cold cap. The high temperatures, radioactivity, and opaque nature of the glass prevent direct observation inside the melters. Therefore, computational models are essential for providing insight into factors that affect melter throughput. Thermocouples in the plenum provide operators with plenum temperature measurements. Operational adjustments include bubbling rate, voltage supplied to the electrodes, feed adjustments, and glass removal rate. Different computational fluid dynamics (CFD) models have been developed, each serving a specific purpose. There are CFD models of different scale melters, as well as models that capture the two-phase flow interfaces of rising bubbles in the molten glass or models with a simplified molten glass region so that the surrounding structure and plenum can be feasibly incorporated. Pilot-scale melter models have been developed to serve as validation of the methods employed in the simulation of the full-scale WTP melters. Models incorporating resolved bubbling are used to develop momentum source terms to implement into a single phase, multi-region, steady-state flow model that is being validated by measured process parameters such as glass production rate, voltage, input power, plenum temperatures, etc. The resolved bubbling model uses the multiphase volume of fluid approach to model the system with a high-resolution interface capturing scheme to maintain sharp interfaces between the molten glass and the air phase. The suite of CFD models is continually being improved to incorporate more realistic physics and achieve faster turnaround time. For example, an incremental controller is implemented to automatically adjust electrode voltage within the simulation to a molten glass set point temperature of 1150°C. Newer models feature improved meshes to ensure conformal meshes between regions and eliminate unnecessary mesh refinement in areas that are not of interest (such as boundary layers in offgas ports). Instead of explicitly modeling the structural, refractory, and insulation layers of the melter, a thermal resistance approach is used with published correlations used for boundary conditions. The development of robust and efficient CFD models will be instrumental in enabling the WTP to successfully fulfill its mission of safely stabilizing legacy nuclear waste.

12 - MGMT OF RADIOACTIVE AND NON-RADIOACTIVE WASTE↗
DOE OSTI2026

Affinity and Treatment of LDR Organics in Low Activity Waste by Cementitious Materials – 26109

The physiochemical interactions between organic contaminants, minerals, and polymer additives in grout/cementitious materials are being identified. This research supports a proposed Resource Conservation and Recovery Act (RCRA) treatment variance relevant to the Land Disposal Restriction (LDR) organics present in Hanford tank waste. It provides the technical basis to address the aspects documented by the Environmental Protection Agency in a draft memo necessary to establish that organics can be immobilized/stabilized in a cementitious matrix. The organic species may interact with cementitious minerals, including slag, fly ash, cement, and other components/dopants like activated carbon. A list of 132 reasonably expected LDR organics associated with Hanford tank waste (RPP-RPT-63493, Rev 1a) was screened by functional groups, octanol-water partitioning coefficients, and detection frequency in Hanford tank waste samples. A subset of 15 compounds spanning the identified properties was tested using sorption and leachate tests. These compounds were subjected to traditional batch sorption tests and leaching tests on/from Cast Stone cementitious material with and without activated carbon (a potential organic adsorption additive). The interactions between organic compounds were observed in traditional batch sorption and modified TCLP leachate tests for surrogate Cast Stone material with and without activated carbon addition. Specifically, phthalic acid (negatively charged) and 4-chloroaniline (polar) sorbed strongly to unmodified Cast Stone, while a group of three phenolic compounds (2,4,6-Trichlorophenol, Pentachlorophenol, o-Cresol) sorbed to and were retained by Cast Stone with a 1% activated carbon amendment. Mixtures of these compounds demonstrated visible retention of the organics within the matrix with a quantifiable affinity of the organics to the cement. This novel testing supports the notion that organics within Hanford tank waste would be retained onto the cement phase with the addition of simple materials easily added to the formulation as part of the treatment process. To further provide additional support to this claim, models employing Flory-Huggins theory in conjunction with macromolecular and organic molecule solubility parameters and species activity coefficients are being utilized to better understand these interactions. Within this context, Van Krevelen (VK) and Hansen organic and polymer solubility parameters were used to inform the Flory-Huggins interaction parameter, allowing for a quantifiable method of evaluating polymer-solvent compatibility and, by extension, interactions with proposed binding additives (e.g., activated carbon). These models and measurement should test the hypothesis for our systems understanding and applicability of Flory-Huggins theory, and whether the prediction of organics in the polymer phase versus the aqueous phase can be confidently made using this strategy. The estimation of the organic molecular activity coefficient in these high salt-saturated aqueous systems is another factor that will be assessed. This project aims to predict and understand complicated organic interactions in these heterogenous systems, guiding optimal treatment and stabilization methodologies.

Jolin, Will [Savannah River National Laboratory (S↗
DOE OSTI2026

Component-Level Inverse Design of Transmon Qubits Using Neural Networks

Designing a superconducting qubit to realize specific Hamiltonian parameters typically requires iterating through a time and compute-intensive forward loop in which the designer chooses a layout geometry, simulates it, extracts circuit parameters such as capacitances, and refines the geometry. We study the inverse version of this task using a neural-network workflow that maps target Hamiltonian parameters directly to component-level layout parameters, which we subsequently demonstrate on a planar transmon layout. During training, we pair the inverse model with a frozen forward surrogate model and evaluate the loss in Hamiltonian space rather than in layout-parameter space. In validation against a conventional EM solver, 97% of generated designs produce usable geometries, and the inverse-plus-surrogate pipeline reaches mean percent errors of 0.73% for qubit frequency and 1.58% for anharmonicity, comparable to or below the fabrication and simulation-to-measurement uncertainty expected for academic-process transmon devices of this type. A single pipeline query takes ~60 ms on CPU, versus ~2 min for a conventional EM capacitance extraction on the same hardware, a speedup of approximately 2,000x. Batching minimizes the AI model inference overhead, reducing the runtime to 3.1 microseconds per sample on CPU and 2.6 microseconds per sample on GPU at a batch size of 2048, resulting in speedups of 3.9 x 10^7 and 4.6 x 10^7, respectively, relative to a single conventional CPU EM extraction. Our results indicate that component-level inverse design usefully extends and complements conventional EM simulation, including for small datasets on the order of 1,000 samples.

Seidel, Olivia [Fermilab; Texas U., Arlington]↗
DOE OSTI2026

Determining the Solubility Behavior of Kogarkoite in Simulated Nuclear Waste

Kogarkoite (Na 3 FSO 4 ) is a sparingly soluble fluoride–sulfate double salt that has been identified in high level nuclear waste sludge at the Hanford Site and, more recently, in sludge batch compilation samples at the Savannah River Site (SRS). Due to its complex dissolution behavior, which exhibits an inverse dependence on sodium ion activity, the presence of this mineral poses significant challenges to waste retrieval and processing. Incomplete dissolution during sludge washing can lead to the retention of fluoride and sulfate in the high-level waste feed, potentially causing the formation of corrosive, immiscible molten salt layers, known as "glass gall,” in vitrification melters. Current efforts to optimize flowsheet parameters and wash-water volumes are hindered by the absence of a commercially available, certified reference material, which prevents the accurate calibration of analytical methods and the verification of dissolution kinetics. To address this critical gap, this research focuses on the laboratory synthesis of pure Kogarkoite to serve as a standard for comprehensive solubility and washing performance testing. A coupled synthesis and simulant campaign was executed using an evaporative crystallization protocol designed to replicate the dynamic concentration effects observed in tank farm operations. Thirteen simulant matrices were prepared by dissolving systematically varied ratios of sodium fluoride (NaF) and sodium sulfate (Na 2 SO 4 ) in deionized water under three distinct caustic regimes: 0.0 g (control), 4.0 g (~1 M), and 12.0 g (~3 M) sodium hydroxide (NaOH). While thermodynamic equilibrium models suggest that high-caustic environments should favor the stability of the double salt7, results from this evaporative study at 25 0 C revealed a distinct kinetic divergence. Simulants with high hydroxide loading predominantly yielded large, blocky crystals of sodium sulfate decahydrate (Na 2 SO 4 .10H 2 O). Successful synthesis of pure Kogarkoite was achieved exclusively in specific NaOH-free compositional windows, where the precipitate manifested as fine, opaque granular aggregates. Ion chromatography (IC) analysis confirmed phase purity through the simultaneous stoichiometric depletion of both fluoride and sulfate from the supernatant. This successful synthesis establishes a reproducible route to generate bulk Kogarkoite, enabling the subsequent phase of quantitative dissolution testing using inhibited water to optimize sludge-batch assembly.

Sarker, Md Sharif [Florida International Univ. (FI↗
DOE OSTI2022

Dante

SAND2022-12905 O Dante is a physical security simulation package used in evaluating protective staffing and physical security elements against adversarial threats. Dante simulates force-on-force scenarios in a batch Monte Carlo process. Analysts use the included Scenario Editor to define the scenarios for their site and then execute and analyze the results using the Batch Manager tool. Dante provides insight into how well a security system performs against threats and lets analysts mine the results for key indicators of system performance. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Hart, Brian↗
DOE OSTI2025

Predicting runtime and resource utilization of jobs on integrated cloud and HPC systems

Recent advances in virtualization technologies used in cloud computing offer performance that closely approaches bare-metal levels. Combined with specialized instance types and high-speed networking services for cluster computing, cloud platforms have become a compelling option for high-performance computing (HPC). However, most current batch job schedulers in HPC systems are designed for homogeneous clusters and make decisions based on limited information about jobs and system status. Scientists typically submit computational jobs to these schedulers with a requested runtime that is often over- or under-estimated. More accurate runtime predictions can help schedulers make better decisions and reduce job turnaround times. Here, they can also support decisions about migrating jobs to the cloud to avoid long queue wait times in HPC systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Environmental Impacts of Reclaimed Asphalt Pavement on Leaching of Metals into Groundwater

To investigate the environmental impacts of reclaimed asphalt pavement (RAP) while it was freshly processed (i.e. hot mixed asphalt or HMA) and after being subjected to weathering, three RAP materials, namely north-RAP, central-RAP, south-RAP, from three plants and one fresh HMA loose mix sample (Fresh-HMA) throughout New Jersey, USA underwent four different weathering processes including: Ultraviolet (UV) and precipitation weathering on unbounded RAP, UV and precipitation weathering on compacted RAP, weathering by heat and moisture cycles, and groundwater flow-through leaching. Batch experiments were conducted to mimic releasing of trace elements in weak acidic leachate from landfills. North-RAP and central-RAP released levels of Pb greater than the United States Environmental Protection Agency (USEPA) primary drinking water maximum contaminant level (MCL) of 15 µg/L. Novel two-column experiments (a RAP column followed by a soil column) were conducted to investigate the release of trace elements from RAP and the attenuation effect of soil on potential pollutants. The results of these experiments showed that pollutants released from RAPs such as Mn and Ni were largely attenuated in the soil. The results suggest that RAP can be used as an unbound material in environments except those acidic (i.e., pH < 5 as in mines with sulfur-containing minerals and landfills with acidic environment).

batch extraction↗
DOE OSTI2025

Controlling Selective C–O and C–H Bond Scission of Methanol by Supporting Pt on TiN and Mo 2 N Model Surfaces and Powder Catalysts

Transition metal nitrides (TMNs) have been explored as effective supports for Pt due to their Pt-like electronic properties. However, there is a lack of fundamental understanding regarding the behavior of Pt on different TMNs (Pt/TMN). Herein two TMNs, Mo 2 N and TiN, were modified with Pt and compared using methanol decomposition as a probe reaction via both ultrahigh vacuum (UHV) studies on thin films and ambient-pressure batch reactor studies of powder catalysts. Temperature-programmed desorption (TPD) and high-resolution electron energy loss spectroscopy (HREELS) measurements were conducted under UHV conditions with Mo 2 N and TiN thin films. Mo 2 N was shown to favor C–H bond scission to form CO with a 56.2% selectivity, while TiN favored C–O bond scission to form CH 4 with a 74.5% selectivity. The addition of 0.9 monolayers (MLs) of Pt increased C–H bond scission selectivity to 89.7% and 49.2% for Mo 2 N and TiN respectively. Density functional theory (DFT) calculations on model surfaces revealed that the binding energy of O (BE *O ) was significantly reduced on Pt/TMNs, from −4.02 eV on Mo 2 N to −1.31 eV on Pt/Mo 2 N and −4.74 eV on TiN to −1.37 eV on Pt/TiN. As a result, C–O bond scission pathways were suppressed, leading to the preferential C–H bond scission that was observed experimentally. The C–O and C–H bond scission trends observed on thin films were then extended to powder catalysts, which demonstrated similar trends toward methanol decomposition. In conclusion, results from the current study establish that by combining UHV studies and DFT calculations over model surfaces, one can effectively predict the catalytic behavior of realistic TMN powder catalysts.

08 HYDROGEN↗
DOE OSTI2024

Continuous Polymer Synthesis and Manufacturing of Polyurethane Elastomers Enabled by Automation

Connecting polymer synthesis and processing is an important challenge for streamlining the manufacturing of polymeric materials. In this work, the automated synthesis of acrylate-capped polyurethane oligomers is integrated with vat photopolymerization 3D printing. This strategy enabled the rapid manufacturing of a library of polyurethane-based elastomeric materials with differentiated thermal and mechanical properties. The automated semi-continuous batch synthesis approach proved enabling for resins with otherwise short shelf lives because the intimate connection between synthesis, formulation, and processing. Structure-property studies demonstrated the ability to tune properties through systematic alteration of crosslink density and chemical composition.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Influence of Inorganic Carbon Sources on Low-pH Succinic Acid Production by Issatchenkia orientalis : Process Insights and Kinetic Analysis

Bio-based succinic acid (SA) production has attracted significant interest; however, the relationship between fermentation conditions and SA biosynthesis remains insufficiently understood, particularly under low-pH operation. In this study, an engineered, acid-tolerant, nonmodel yeast, Issatchenkia orientalis , was employed to investigate the role of inorganic carbon supplementation in SA production from glucose. Because regulation of gas-phase CO 2 during fermentation is challenging due to low solubility and off-gas losses, liquid-phase inorganic carbon sources, carbonic acid (H 2 CO 3 ) and sodium carbonate (Na 2 CO 3 ), were evaluated as indirect CO 2 donors. Fermentations were conducted in a corn steep liquor-based medium under acidic conditions. Shake-flask experiments demonstrated that H 2 CO 3 supplementation increased SA production, achieving a maximum titer of 8.9 g/L and a yield of 0.46 g/g glucose. Kinetic analysis of bench-scale fermentations showed that the SA formation was well described by the Luedeking–Piret model, indicating mixed growth-associated product formation with a substantial nongrowth-associated contribution under carbonic acid supplementation. Guided by these kinetic insights, a two-stage fed-batch fermentation strategy was implemented, resulting in an SA titer of 30 g/L and a yield of 0.57 g/g glucose within 115 h. Overall, this work provides process-relevant insights into integrating inorganic carbon utilization with low-pH fermentation to inform more sustainable SA biomanufacturing.

fed-batch fermentation↗
DOE OSTI2025

Geometric GNNs for charged particle tracking at GlueX

Nuclear physics experiments are aimed at uncovering the fundamental building blocks of matter. The experiments involve high-energy collisions that produce complex events with many particle trajectories. Tracking charged particles resulting from collisions in the presence of a strong magnetic field is critical to enable the reconstruction of particle trajectories and precise determination of interactions. It is traditionally achieved through combinatorial approaches that scale worse than linearly as the number of hits grows. Since particle hit data naturally form a point cloud and can be structured as graphs, graph neural networks (GNNs) emerge as an intuitive and effective choice for this task. In this study, we evaluate the GNN model for track finding on the data from the GlueX experiment at Jefferson Lab. We use simulation data to train the model and test on both simulation and real GlueX measurements. We demonstrate that GNN-based track finding outperforms the currently used traditional method at GlueX in terms of segment-based efficiency at a fixed purity while providing faster inferences. We show that the GNN model can achieve significant speedup by processing multiple events in batches, which exploits the parallel computation capability of graphical processing units (GPUs). Finally, we compare the GNN implementation on GPU and field-programmable gate array and describe the trade-off.

batched GNN pipeline↗
DOE OSTI2020

Comparing serial X-ray crystallography and microcrystal electron diffraction (MicroED) as methods for routine structure determination from small macromolecular crystals

Innovative new crystallographic methods are facilitating structural studies from ever smaller crystals of biological macromolecules. In particular, serial X-ray crystallography and microcrystal electron diffraction (MicroED) have emerged as useful methods for obtaining structural information from crystals on the nanometre to micrometre scale. Despite the utility of these methods, their implementation can often be difficult, as they present many challenges that are not encountered in traditional macromolecular crystallography experiments. Here, XFEL serial crystallography experiments and MicroED experiments using batch-grown microcrystals of the enzyme cyclophilin A are described. The results provide a roadmap for researchers hoping to design macromolecular microcrystallography experiments, and they highlight the strengths and weaknesses of the two methods. Specifically, we focus on how the different physical conditions imposed by the sample-preparation and delivery methods required for each type of experiment affect the crystal structure of the enzyme.

36 MATERIALS SCIENCE↗