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At least 451 records · Page 25

Few-shot Learning for Post-disaster Structure Damage Assessment

Automating post-disaster damage assessment with remote sensing data is critical for faster surveys of structures impacted by natural disasters. One significant obstacle to training state-of-the-art deep neural networks to support this automation is that large quantities of labelled data are often required. However, obtaining those labels is particularly unrealistic to support post-disaster damage assessment in a timely manner. Few-shot learning methods could help to mitigate this by reducing the amount of labelled data required to successfully train a model while achieving satisfactory results. To this end, we explore a feature reweighting method to the YOLOv3 object detection architecture to achieve few-shot learning of damage assessment models on the xBD dataset. Our results show that the feature reweighting approach yield improved mAP over the baseline with significantly fewer labelled samples. In addition, we use t-SNE to analyze the class-specific reweighting vectors generated by the reweighting module in order to evaluate their inter-class and intra-class similarity. We find that the vectors form clusters based on class, and that these clusters overlap with visually similar classes. Those results show the potential to employ this few-shot learning strategy for rapid damage assessment with post-event remote sensing images.

Bowman, Jordan↗

Situational awareness-enhancing community-level load mapping with opportunistic machine learning

Motivated by present and forthcoming challenges in the adoption and integration of distributed renewable energy, we develop a machine learning (ML) approach that builds short-fuse mappings connecting the occasionally-unobservable true load in one target community with information-rich signals collected from relatively more instrumented reference communities. Our setting is inspired by and tailored to target communities with significant unobservable behind-the-meter solar generation, where true load (a relatively well-behaved quantity of interest to grid operators) is hard to discern during daytime due to insufficient instrumentation and/or privacy reasons, but that can be related to reference communities with low unobservable distributed variable generation or with sufficient instrumentation. The developed mapping, herein realized with Support Vector Machine regression, is built using nighttime data from all communities, when their distributed generation is low or zero. Our ML algorithm opportunistically learns to correlate signals of interest and then is operationally used the next day to shed light into target community load evolution. The mapping is subsequently rebuilt, rolling its short-fuse scope perpetually forward in time. Here, we demonstrate the efficacy of our approach on nine synthetically generated topologies and associated timeseries stemming from real-world data, on which we observe cumulative error performance that yields lower than 10% and 15% daily-averaged mean absolute percentage errors in target community load estimation on more than about 75% and 90% of days, respectively, in multiple yearly evaluations that shed light on long-term performance also under seasonal and one-off effects. The proposed ML-powered methodology can offer grid operators much-improved visibility into a previously obscure space and can also serve as an additional source of information in broader, multi-modal solar disaggregation solutions.

14 SOLAR ENERGY↗

Laboratory and pilot-scale studies of membrane distillation for desalination of produced water from Permian Basin

Substantial quantities of produced water generated during the extraction of oil and gas from unconventional reservoirs present significant environmental concern and increase the operating cost for this industry. Membrane Distillation (MD) can serve as a potential solution for beneficial reuse of produced water by generating high-quality permeate and reducing the volume of produced water requiring disposal. This study investigated treatment of produced water from Permian Basin in both laboratory and pilot-scale studies. Laboratory tests revealed the potential to successfully recover 50% of produced water although some increase in permeate conductivity was observed due to the passage of ammonia from the feed side. Initial pilot-scale test with filtration of raw produced water as the only pre-treatment step led to precipitation of SrSO 4 , NaCl, and Fe in the system once the solubility limits for these salts were exceeded. However, chemical pretreatment that included pH adjustment, aeration, and barite precipitation, allowed successful steady-state operation of the AGMD pilot system for 5 days where the produced water was concentrated from 127 g/L to 255 g/L (~50% water recovery) while recovering high quality permeate. Overall, greater than 99.7 % salt rejection was achieved with the average permeate flux of 1.86 LMH. Finally, mass balance analysis suggested potential Ba and Ca precipitation in the system but there was no impact on AGMD performance and permeate quality during 5 days of continuous operation in the field.

42 ENGINEERING↗

Quasi-Classical Trajectory Calculation of Rate Constants Using an Ab Initio Trained Machine Learning Model (aML-MD) with Multifidelity Data

Machine learning (ML) provides a great opportunity for the construction of models with improved accuracy in classical molecular dynamics (MD). However, the accuracy of a ML trained model is limited by the quality and quantity of the training data. Generating large sets of accurate ab initio training data can require significant computational resources. Furthermore, inconsistent or incompatible data with different accuracies obtained using different methods may lead to biased or unreliable ML models that do not accurately represent the underlying physics. Recently, transfer learning showed its potential for avoiding these problems as well as for improving the accuracy, efficiency, and generalization of ML models using multifidelity data. In this work, ab initio trained ML-based MD (aML-MD) models are developed through transfer learning using DFT and multireference data from multiple sources with varying accuracy within the Deep Potential MD framework. Further, the accuracy of the force field is demonstrated by calculating rate constants for the H + HO 2 → H 2 + 3 O 2 reaction using quasi-classical trajectories. We show that the aML-MD model with transfer learning can accurately predict the rate constants while reducing the computational cost by more than five times compared to the use of more expensive quantum chemistry training data sets. Hence, the aML-MD model with transfer learning shows great potential in using multifidelity data to reduce the computational cost involved in generating the training set for these potentials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Numerical simulation of a relativistic magnetron using a fluid electron model

An approach to numerically modeling relativistic magnetrons, in which the electrons are represented with a relativistic fluid, is described. A principal effect in the operation of a magnetron is space-charge-limited (SCL) emission of electrons from the cathode. We have developed an approximate SCL emission boundary condition for the fluid electron model. This boundary condition prescribes the flux of electrons as a function of the normal component of the electric field on the boundary. Here we show the results of a benchmarking activity that applies the fluid SCL boundary condition to the one-dimensional Child–Langmuir diode problem and a canonical two-dimensional diode problem. Simulation results for a two-dimensional A6 magnetron are then presented. Computed bunching of the electron cloud occurs and coincides with significant microwave power generation. Numerical convergence of the solution is considered. Sharp gradients in the solution quantities at the diocotron resonance, spanning an interval of three to four grid cells in the most well-resolved case, are present and likely affect convergence.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Global energy balance simulations of shattered pellet injection

The dynamics of shattered pellet injection (SPI) shutdowns are simulated using a time-dependent global energy balance model, based on a modification of the KPRAD framework. The new SPI particle source in the model calculates the ablation of individual pellet fragments that enter the plasma as a temporally resolved plume, thus capturing the effects of earlier fragments on the ablation of those that follow, which has a significant impact on the overall assimilation. Despite the reduced physics and the global averaging of all quantities, results from a large number of DIII-D, KSTAR, and JET experiments are well reproduced, including the plasma cooling timescales, particle assimilation, and current quench (CQ) rates. Cooling timescales and CQ rates are in good agreement for pellets containing as little as ∼1% neon, while particle assimilations are most accurate for neon fractions above ∼15% by number of atoms. Below this, the assimilation tends to be overestimated due to the lack of radial transport in the particle balance, which becomes important in the low-Z limit. Predictive simulations of mixed-composition dual-SPI shutdowns in ITER are compared against those with the 3D non-linear magnetohydrodynamic code JOREK and are found to reproduce overall trends observed in the higher-fidelity modeling across a range of injection scenarios. The general success of the model points to the critical role of energy balance in determining SPI particle assimilation and the subsequent disruption dynamics and highlights the value of these simulations for experimental interpretation and for optimizing the deployment of computationally expensive, higher-fidelity models.

energy balance model↗

A Stochastic Calculus Approach to Boltzmann Transport

Traditional Monte Carlo methods for particle transport utilize source iteration to express the solution, the flux density, of the transport equation as a Neumann series. Our contribution is to show that the particle paths simulated within source iteration are associated with the adjoint flux density and the adjoint particle paths are associated with the flux density. Here, we make our assertion rigorous through the use of stochastic calculus by representing the particle path used in source iteration as a solution to a stochastic differential equation (SDE). The solution to the adjoint Boltzmann equation is then expressed in terms of the same SDE, and the solution to the Boltzmann equation is expressed in terms of the SDE associated with the adjoint particle process. An important consequence is that the particle paths used within source iteration simultaneously provide Monte Carlo samples of the flux density and adjoint flux density in the detector and source regions, respectively. The significant practical implication is that particle trajectories can be reused to obtain both forward and adjoint quantities of interest. To the best our knowledge, the reuse of entire particles paths has not appeared in the literature. Monte Carlo simulations are presented to support the reuse of the particle paths.

Boltzmann transport↗

To the problem about the origin of lunar maria and continents (Moessbauer investigations)

A comparative study of Mossbauer spectra of regolith returned by the Luna 16 and Luna 20 spacecraft is presented. The Mossbauer spectra of the mare regolith differs significantly for all fractions from the spectra for the same fractions of continental regolith. The total quantity of iron is 1.85 times greater in the mare regolith. There is 2.4 times less olivine in the mare region than in the continental region. The pyroxene component of the mare regolith is less homogeneous in composition (contains more augite and glass) and is present in larger quantities. Ilmenite was found only in the mare regolith. In the continental region, the predominant titanium-containing phase is ulvospinel. The mare regolith contains more metallic iron, which is more finely dispersed and contains less nickel. Troilite is found in the maria region. Based on these differences, it is concluded that the formation of continental rocks occurred at an earlier stage of crystallization from the melt and at higher temperatures and higher partial pressures of oxygen. The mare basalts crystallized from a more reduced magma, apparently in a later process.

Malysheva, T. V.↗

Cryogenic Fluid Management Technology Development for Nuclear Thermal Propulsion

The purpose of this paper is to investigate, facilitate a discussion and determine a path forward for technology development of cryogenic fluid management technology that is necessary for long duration deep space missions utilizing nuclear thermal propulsion systems. There are a number of challenges in managing cryogenic liquids that must be addressed before long durations missions into deep space, such as a trip to Mars can be successful. The leakage rate of hydrogen from pressure vessels, seals, lines and valves is a critical factor that must be controlled and minimized. For long duration missions, hydrogen leakage amounts to large increases in hydrogen and therefore vehicle mass. The size of a deep space vehicle, such as a mars transfer vehicle, must be kept small to control cost and the logistics of a multi launch, assembled in orbit vehicle. The boil off control of the cryogenic fluid is an additional obstacle to long duration missions. The boil off caused by heat absorption results in the growth of the propellant needs of the vehicle and therefore vehicle mass. This is a significant problem for a vehicle using nuclear (fission) propulsion systems. Radiation from the engines deposits large quantities of heat into the cryogenic fluid, greatly increasing boil off beyond that caused by environmental heat leakage. Addressing and resolving these challenges is critical to successful long duration space exploration. This paper discusses the state of the technology needed to address these challenges and discuss the path forward needed in technology development.

Taylor, Brian↗

Understanding Oceanic Heavy Precipitation Using Scatterometer, Satellite Precipitation, and Reanalysis Products

The primary aim of this study is to understand the heavy precipitation events over Oceanic regions using vector wind retrievals from space based scatterometers in combination with precipitation products from satellite and model reanalysis products. Heavy precipitation over oceans is a less understood phenomenon and this study tries to fill in the gaps which may lead us to a better understanding of heavy precipitation over oceans. Various phenomenon may lead to intense precipitation viz. MJO (Madden-Julian Oscillation), Extratropical cyclones, MCSs (Mesoscale Convective Systems), that occur inside or outside the tropics and if we can decipher the physical mechanisms behind occurrence of heavy precipitation, then it may lead us to a better understanding of such events which further may help us in building more robust weather and climate models. During a heavy precipitation event, scatterometer wind observations may lead us to understand the governing dynamics behind that event near the surface. We hypothesize that scatterometer winds can observe significant changes in the near-surface circulation and that there are global relationships among these quantities. To the degree to which this hypothesis fails, we will learn about the regional behavior of heavy precipitation-producing systems over the ocean. We use a "precipitation feature" (PF) approach to enable statistical analysis of a large database of raining features.

Winds↗

Magnetic Mapping in the Inner Magnetosphere using Kamodo

Many models require specialized access and interpolation schemes to effectively extract and interpolate their outputs. In particular, the Block-Adaptive Tree Solarwind Roe Upwind Scheme (BATSRUS) component of the Space Weather Modeling Framework (SWMF) requires Kamodo to take advantage of its block-based adaptive grid structure, and the Lyon-Fedder Mobarry magnetosphere model (or its successor GAMERA) needs a scheme that appreciates the distorted spherical arrangement of grid vertices on a non-orthogonal grid. With the flythrough layer developed by Ringuette et al. (SH42E-2337), the underlying model readers have been adapted to use multiple time steps in a single Python session to perform 4- dimensional interpolations in time and space. Kamodo now utilizes lazy interpolation that loads data only when needed. We present the successful integration of SWMF/BATSRUS magnetosphere access and interpolation into the new 4D Kamodo framework utilizing an external library of C code. Through function composition, Kamodo facilitates the calculation of derived quantities and the transformation of positions and vectors into different coordinate systems. This work is a significant step towards performing field line tracing in Kamodo with SWMF magnetosphere outputs.

Lutz Rastaetter↗

Overview: Small Aircraft Transportation System Airborne Remote Sensing Fuel Droplet Evaporation

The NASA Nebraska Preparation Grant was designed to solidify relationships, intensify communication, and launch collaborative initiatives among Nebraska researchers and key contacts at NASA research centers and enterprises. In doing so, Nebraska was successful in laying the groundwork for the foundation for numerous long-term, mutually beneficial collaborations that were subsequently proposed and awarded in the NASA EPSCoR 2000 competition. The NASA Nebraska EPSCoR Preparation Grant was managed by the same administrative team that oversees Nebraska's NASA Space Grant and EPSCoR programs. An advisory board (later Technical Advisory Committee) made up of voting representatives from all affiliate and partner organizations regularly reviewed grant progress and direction. The University of Nebraska at Omaha's Aviation Institute, the host institution for all three programs, provided additional administrative oversight and program evaluation through established review mechanisms. This structure has served NASA well and has been cited as a model program. The second year of preparation grant funding served as a significant opportunity for Nebraska to lay the groundwork for the continued elevation and success of its NASA EPSCoR program. In anticipation of the NASA EPSCoR 2000 grant competition, Year 2 funding enabled funded researchers to further broaden and enhance the quality and quantity of collaborations with NASA Field Centers, Codes, and Enterprises. The plan set the stage for long-term research and outreach endeavors that have contributed significantly to the achievement of NASA's strategic objectives; the state of Nebraska's economic and aerospace development efforts; and have advanced Nebraska s aeronautics research efforts to a national leadership level. The overarching goal of the NASA Nebraska EPSCoR Preparation grant was met by facilitating research endeavors among Nebraska faculty that addressed research and technology priorities of the NASA Field Centers, Codes, and Strategic Enterprises. During the first year of funding, Nebraska established open and frequent lines of communication with university affairs officers and other key personnel at all NASA Centers and Enterprises, and facilitated the development of collaborations between and among junior faculty in the state and NASA researchers. As a result, Nebraska initiated a major research cluster, the Small Aircraft Transportation System Nebraska Implementation Template.

Bowen, Brent↗

Transit Habitat Government-Reference Conceptual Design Reaction Control System Propulsion Concept Design Data Book

The function of Transit Habitat (TH) Reaction Control System (RCS) propulsion is to provide free-flying spacecraft capabilities and to augment Gateway stack control when docked on Gateway. The requirements of multiple propellant replenishments and extensive life operation have significant impacts on selection of the propulsion system concept and components for the RCS. The intent of this document is to provide insight into the government-reference conceptual design of a propulsion system for TH element. A pressure-fed hypergolic bi-propellant system is the assumed propulsion approach for the RCS. Its architectural concept is being traded within the NASA Moon to Mars architecture. A pressure-regulated system is examined. The propellants under consideration are Monomethyl Hydrazine (MMH) and Mixed Oxides of Nitrogen with 3% Nitric Oxide (MON3). A peer review was conducted to assess the flow schematic design and propulsion component selection, compliant with a set of assumed requirements. Redundant components to satisfy one-fault tolerance for function and two-fault tolerance against catastrophic events are incorporated in the propulsion concept design. Instrumentation laid out on the schematic would be used to gather data to monitor the health of the propulsion system and to support quantity gauging of the propulsion system fluids. Venting propellant ullage gas overboard during the refilling operations poses a significant concern to the external surfaces of the TH. A liquid/gas separator would be required to eliminate, or at least reduce, the amount of liquid propellant expelled in the vent gas mixture. The technology readiness level of the phase separator for the TH must be advanced. Metal diaphragm and non-positive-expulsion PMD propellant tank systems were traded against each other, with the PMD architecture being selected. A blowdown concept is also considered for the TH RCS propulsion. Its fluid schematic is derived from the pressure-regulated schematic with removal of assemblies involving the helium pressurization and ullage venting. Its system wet mass is 10% heavier than the pressure-regulated due to thruster performance loss and larger propellant tanks. There is no firm constraint on the propulsion system mass at this phase of the design. The blowdown concept can offer reduction in component count and operation, that would lead to a more reliable propulsion system. The blowdown concept would also benefit avionics, thermal, power, and structures on the TH. Assessing these benefits will be carried as a future work. Drawbacks of thrust and minimum impulse bit (MIB) variations due to the blowdown operation would be acceptable to Guidance, Navigation, and Control (GNC). Although the blowdown concept has been selected as a current baseline, further evaluation of the concept will be the subject of future work to ensure that the blowdown propulsion operation is appropriate for the HT RCS propulsion. This document also highlights key trade studies and design decisions, including pros and cons of the selected concept. Other appropriate options for components are pointed out for future assessments. Additional background information and documents for further review are referenced in this report.

spacecraft propulsion↗

Errors introduced in fission neutron spectrum measurements using a single reference

Measurements of physical quantities are often made relative to a reference quantity, simplifying the interpretation of the measurement and its uncertainties. However, if applied without careful considerations, this technique can carry with it a significant and complex systematic error that is usually ignored. For example, measurements of continuous neutron spectra relative to a reference spectrum yield a result that does not properly include the important effects of neutron scattering in the experimental environment. These effects act to distort the measured spectrum shape and create notable errors in spectrum-integrated quantities. While this effect is one of a series of known potential sources of systematic error including, but not limited to target impurities, angular distributions, incident beam flux, and others, the error introduced from differences in environmental scattering effects between the reference and desired spectra are frequently overlooked. In this work, we demonstrate the origin of this error using simulated data corresponding to measurements of the neutron-induced prompt fission neutron spectra of 233 U, 235 U, 238 U, and 239 Pu as well as the spontaneous fission neutron spectrum of 252 Cf. Errors in the spectrum shape can be as high as 10%–15% depending on the combination of incident and outgoing neutron energy. The spectrum integral and average spectrum energy also contain errors that change with incident neutron energy and can be as high as ~2%. Although this study is based on simulated data, we also show a method for proving that this error exists in an experimental data set and we show a correction that can be applied to results of this type to obtain a more accurate result, thereby largely removing systematic errors from environmental scattering effects. The potential for these kinds of errors should be considered in measurements producing continuous neutron spectra.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Effects of antibacterial peptide-producing Bacillus subtilis, gallic acid, and cellulase on fermentation quality and bacterial community of whole-plant corn silage

In the current study, we assessed the effects of antibacterial peptide-producing Bacillus subtilis (BS), gallic acid (GA) and cellulase (CL) on the fermentation quality and bacterial community of various varieties of whole-plant corn silage. Three different varieties of whole-plant corn (Yuqing386, Enxiai298, and Nonghe35) were treated with 0.02% BS (fresh material basis), 0.2% GA (fresh material basis) and 0.02% CL (fresh material basis), after which 45 days of anaerobic fermentation were conducted. With the exception of its low dry matter content, the results showed that Yuqing386’s crude protein, water-soluble carbohydrate, and lactic acid contents were significantly higher than those of the other two corn varieties. However, its acid detergent fiber and cellulose contents were significantly lower than those of the other two corn varieties. Among the three corn variety silages, Yuqing386 had the highest relative abundance of Lactobacillus at the genus level and the biggest relative abundance of Firmicutes at the phylum level. In addition, the three additives markedly enhanced the quantity of dry matter and crude protein as compared to the control group. The application of GA considerably decreased the level of neutral detergent fiber while significantly increasing the content of lactic acid and water-soluble carbohydrates. Even though all additives enhanced the structure of the bacterial community following silage, the GA group experienced the greatest enhancement. On a phylum and genus level, the GA group contains the highest relative abundance of Firmicutes and Lactobacillus , respectively. Overall, of the three corn varieties, Yuqing386 provides the best silage qualities. GA has the biggest impact among the additions employed in this experiment to enhance the nutritional preservation and fermentation quality of whole-plant corn silage.

Zhang, Zhiheng↗

Interdisciplinary Interactions During R&D and Early Design of Large Engineered Systems

Designing Large-Scale Complex Engineered Systems (LaCES) such as aircraft and submarines requires the input of thousands of engineers and scientists whose work is proximate in neither time nor space. Comprehensive knowledge of the system is dispersed among specialists whose expertise is in typically one system component or discipline. This study examined the interactive work practices among such specialists seeking to improve engineering practice through a rigorous and theoretical understanding of current practice. This research explored current interdisciplinary practices and perspectives during R&D and early LaCES design and identified why these practices and perspectives prevail and persist. The research design consisted of a three-fold, integrative approach that combined an open-ended survey, semi-structured interviews, and ethnography. Significant empirical data from experienced engineers and scientists in a large engineering organization were obtained and integrated with theories from organization science and engineering. Qualitative analysis was used to obtain a holistic, contextualized understanding. The over-arching finding is that issues related to cognition, organization, and social interrelations mostly dominate interactions across disciplines. Engineering issues, such as the integration of hardware or physics-based models, are not as significant. For example, organization culture is an important underlying factor that guided researchers more toward individual sovereignty over cross-disciplinarity. The organization structure and the engineered system architecture also serve as constraints to the engineering work. Many differences in work practices were observed, including frequency and depth of interactions, definition or co-construction of requirements, clarity or creation of the system architecture, work group proximity, and cognitive challenges. Practitioners are often unaware of these differences resulting in confusion and incorrect assumptions regarding work expectations. Cognitively, the enactment and coconstruction of knowledge are the fundamental tasks of the interdisciplinary interactions. Distributed and collective cognition represent most of the efforts. Argument, ignorance, learning, and creativity are interrelated aspects of the interactions that cause discomfort but yield benefits such as problem mitigation, broader understanding, and improved system design and performance. The quality and quantity of social interrelations are central to all work across disciplines with reciprocity, respectful engagement, and heedful interrelations being significant to the effectiveness of the engineering and scientific work.

McGowan, Anna-Maria Rivas↗

Activation Analysis for the Inboard Region of FNSF Using SERPENT

This study describes an application of the SERPENT 2 code with the TENDL-2017 nuclear data library and the latest available model features of the Fusion Energy System Studies–Fusion Nuclear Science Facility (FNSF), to evaluate the activation of components after shutdown at 1, 10, and 100 years, assuming a plant lifetime of 8.5 full-power years. The primary parameters evaluated include the specific activity, decay heat, and waste disposal rating (WDR). The specific activity and decay heat are calculated with SERPENT 2 using a 360-deg model of the FNSF, while the WDR is calculated and classified based on the waste disposal limits established by the U.S. Nuclear Regulatory Commission under 10 CFR 61.55 as well as by using the Fetter approach. A python-based script developed for a previous high-level waste classification and analysis study was implemented and adapted to this research to calculate the WDR by comparing nuclide concentrations to the values established in 10 CFR 61.55 to generate a waste classification for each component surveyed. As only three short-lived isotopes have limitations for classifications beyond Class A, of which only 63Ni is present in appreciable quantities, there is a limit to the amount that short-lived isotopes contribute to the most significant waste analyzed here. In most cases, a handful of long-lived isotopes can be problematic, such as 59Ni and 94Nb, for example, which are solely responsible for multiple Class C classifications. The results herein reported heavily depend on the specific materials and mass/volume fractions in the specific model used in this study, which has changed and evolved since the inception of the FNSF concept and past studies. Furthermore, the more significant contributions of this study may be the development of a modeling and simulation toolkit and a strategy to perform these calculations, so to help evaluate and optimize future fusion facilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Serial crystallography using automated drop dispensing

Automated, pulsed liquid-phase sample delivery has the potential to greatly improve the efficiency of both sample and photon use at pulsed X-ray facilities. In this work, an automated drop on demand (DOD) system that accelerates sample exchange for serial femtosecond crystallography (SFX) is demonstrated. Four different protein crystal slurries were tested, and this technique is further improved here with an automatic sample-cycling system whose effectiveness was verified by the indexing results. Here, high-throughput SFX screening is shown to be possible at free-electron laser facilities with very low risk of cross contamination and minimal downtime. The development of this technique will significantly reduce sample consumption and enable structure determination of proteins that are difficult to crystallize in large quantities. This work also lays the foundation for automating sample delivery.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗