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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Intact mass spectrometry screening to optimize hydroxyl radical dose for protein footprinting

Hydroxyl radical protein footprinting (HRPF) using synchrotron radiation is a well-validated method to assess protein structure in the native solution state. In this method, X-ray radiolysis of water generates hydroxyl radicals that can react with solvent accessible side chains of proteins, with mass spectrometry used to detect the resulting labeled products. An ideal footprinting dose provides sufficient labeling to measure the structure but not so much as to influence the results. The optimization of hydroxyl radical dose is typically performed using an indirect Alexa488 fluorescence assay sensitive to hydroxyl radical concentration, but full evaluation of the experiment's outcome relies upon bottom-up liquid chromatography mass spectrometry (LC-MS) measurements to directly determine sites and extent of oxidative labeling at the peptide and protein level. A direct evaluation of the extent of labeling to provide direct and absolute measurements of dose and “safe” dose ranges in terms of, for example, average numbers of labels per protein, would provide immediate feedback on experimental outcomes prior to embarking on detailed LC-MS analyses. To this end, we describe an approach to integrate intact MS screening of labeled samples immediately following exposure, along with metrics to quantify the extent of observed labeling from the intact mass spectra. Intact MS results on the model protein lysozyme were evaluated in the context of Alexa488 assay results and a bottom-up LC-MS analysis of the same samples. In conclusion, this approach provides a basis for placing delivered hydroxyl radical dose metrics on firmer technical grounds for synchrotron X-ray footprinting of proteins, with explicit parameters to increase the likelihood of a productive experimental outcome. Further, the method directs approaches to provide absolute and direct dosimetry for all types of labeling for protein footprinting.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Inferring building height from footprint morphology data

As cities continue to grow globally, characterizing the built environment is essential to understanding human populations, projecting energy usage, monitoring urban heat island impacts, preventing environmental degradation, and planning for urban development. Buildings are a key component of the built environment and there is currently a lack of data on building height at the global level. Current methodologies for developing building height models that utilize remote sensing are limited in scale due to the high cost of data acquisition. Other approaches that leverage 2D features are restricted based on the volume of ancillary data necessary to infer height. Here, we find, through a series of experiments covering 74.55 million buildings from the United States, France, and Germany, it is possible, with 95% accuracy, to infer building height within 3 m of the true height using footprint morphology data. Our results show that leveraging individual building footprints can lead to accurate building height predictions while not requiring ancillary data, thus making this method applicable wherever building footprints are available. The finding that it is possible to infer building height from footprint data alone provides researchers a new method to leverage in relation to various applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Estimating the carbon footprint of computational fluid dynamics

In this study, computational resources have grown exponentially in the past few decades. These machines make possible research and design in fields as diverse as medicine, astronomy, and engineering. Despite ever-increasing computational capabilities, direct simulation of complex systems has remained challenging owing to the degrees of freedom involved. At the cusp of exascale computing, high-resolution simulation of practical problems with minimal model assumptions may soon experience a renaissance. However, growing reliance on modern computers comes at the cost of a growing carbon footprint. To illustrate this, we examine historic computations in fluid dynamics where larger computers have afforded the opportunity to simulate flows at increasingly relevant Reynolds numbers. Under a variety of flow configurations, the carbon footprint of such simulations is found to scale roughly with the fourth power of Reynolds number. This is primarily explained by the computation cost in core-hours, which is also described by similar scaling, though regional differences in renewable energy use also play a role. Using the established correlation, we examine a large database of simulations to develop estimates for the carbon footprint of computational fluid dynamics in a given year. Collectively, the analysis provides an additional benchmark for new computations where, in addition to balancing considerations of model fidelity, carbon footprint should also be considered.

42 ENGINEERING↗
DOE OSTI2023

Social Acceptance of a Reduced-Footprint Synthetic Mooring System for Floating Offshore Wind Turbines in the Gulf of Maine

Engineers are looking to reduce the size of floating offshore wind mooring footprints to minimize conflict with other ocean users. To this end, the University of Maine (UMaine) received funding from the United States Department of Energy (DOE) to design, demonstrate, and validate a novel reduced-footprint synthetic mooring system for floating offshore wind turbines (FOWTs) that reduces impacts to fisheries and the levelized cost of energy. UMaine designed two mooring systems for the New England Aqua Ventus (NEAV) I demonstration project to quantify the technical, economic, and social impacts of a reduced-footprint hybrid mooring system. Specifically, a traditional catenary chain mooring system and a novel polyester rope-chain hybrid system were designed to the front-end engineering design level for this assessment. The National Renewable Energy Laboratory (NREL) was funded by DOE to help independently quantify the social and techno-economic impacts of the rope-chain hybrid mooring system designed by UMaine. This report focuses on NREL's assessment of the social acceptance of the reduced-footprint rope-chain hybrid mooring system and the conventional all-chain mooring system by competing users in the Gulf of Maine.

ENGINEERING,WIND ENERGY↗
DOE OSTI2023

Third-Party Aggregation Rulemaking in MISO and SPP Footprints

The report highlights key considerations for retail regulators in the footprints of the Southwest Power Pool (SPP) or Midcontinent Independent System Operator (MISO) in states that previously opted out of allowing third-party aggregation participation under FERC Order 719 and that may want to explore reversing the decision due to a changing policy environment under new FERC orders (i.e., 2222) and/or tightening resource adequacy constraints. Through a document review and a series of 27 interviews with regulators, aggregators, and other industry professionals, this document provides a high-level policy overview of the retail regulator’s role in a selection of processes, rules, and regulations to better understand how states have treated and/or integrated aggregators into wholesale markets. The report summarizes findings in two sections: General Findings and Specific Policy Findings. The General Findings offer high level takeaways such as the fact that 17 of the 20 states in MISO and SPP footprints opted out of third party aggregations following Order 719. Additionally, there is only one state that is fully restructured in the MISO and SPP footprints whereas the rest are vertically integrated, and the majority of third-party aggregations in the U.S. take place in restructured states outside of these footprints. Even so, third-party aggregations do take place in MISO and SPP albeit in small numbers and in an ad hoc regulatory environment. The specific policy findings delve deeper into specific examples of state actions on the topics of jurisdiction, registration and licensing, data governance, dual participation, and dispute resolution. Tables in each category organize state actions into Tiers I-III, which roughly correspond to the possible level of involvement or possible change necessary by state regulators and/or legislators to implement these actions. The tier level does not indicate any value judgement, as each state has respective regulatory limitations and each decision comes with various tradeoffs. One main tradeoff is between simplicity and quick implementation versus comprehensive and prolonged implementation. In many cases, actions in Tier I could be implemented without significant changes by relying on the use of existing processes for an aggregator context. On the other hand, many actions in Tier III are more narrowly designed to address aggregators specifically, but often require more significant changes including the involvement of additional parties through stakeholder engagement or legislative action. In some cases, these tiers are discrete. However, state regulators may also choose to progress through these various tiers sequentially as they phase in aggregators while learning from their experience. With the ability to stack bulk system level services, distributed energy resource aggregations in MISO and SPP could provide various private benefits (e.g., increased value streams to the owner) as well as societally beneficial grid services (e.g., peaking capacity, ancillary services, and other services that increase the grid’s overall operational efficiency). In deciding how to best to enable these benefits, states and retail regulators must weigh various tradeoffs if considering reversing a previous opt out.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Improving Building Footprint Extraction Using NAIP and 3DEP Lidar Derived Features with Deep Learning

Accurate building footprint extraction is critical for applications ranging from population estimation to disaster management. Although optical imagery provides detailed spectral information, it often struggles with shadows, occlusions, and background clutter in dense urban environments. Lidar data, by contrast, offer precise elevation and structural attributes but face challenges such as variable point density and noise. This study integrates multispectral imagery from the U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) with lidar-derived feature height and intensity from the U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) to improve footprint extraction using a U-Net–based deep learning model. A six-band input stack (RGB, near-infrared, height, intensity) was developed, normalized, and tiled for training and evaluation against Microsoft Global Building Footprints (GBF). Results from the Houston, TX test site show that the six-band model achieved a precision of 0.86, recall of 0.88, F1 score of 0.87, and Intersection-over-Union (IoU) of 0.76, consistently outperforming four-band baselines by reducing false positives while maintaining sensitivity. Predictions on withheld Houston tiles confirmed strong within-region generalization, yielded a precision of 0.78, recall of 0.81, F1 score of 0.79, and IoU of 0.66. Qualitative analysis further revealed limitations stemming from both training label quality and vegetation–building confusion. These findings demonstrate the complementary value of integrating spectral and structural information for robust building footprint extraction and how domain adaptation strategies can be used to enhance cross-regional transferability.

Liu, Jung Kuan [United States Geological Survey (U↗
DOE OSTI2025

Contributions of vegetation heterogeneity within tower footprint to CO 2 flux estimations through graph neural network modeling

Net ecosystem exchange of CO 2 (Fc) measured directly by eddy covariance towers is based on various assumptions, including large, flat and homogenous land cover type. In reality, often a tower site is not large enough for flux measurements, and landscapes consist of patches of different land cover types within the flux footprint. In addition, some portions of fluxes are contributed by different cover types when a footprint exceeds the size of the target ecosystem. The contributions of non-dominant patches to Fc are often ignored. Here, in this study, we propose a novel integrated modeling framework that combines random forest (RF) and XGBoost with a residual correction module based on a deep graph convolutional network (DeeperGCN) to simulate Fc for seven flux measurement sites in southwest Michigan. High-resolution remote sensing vegetation indices, soil properties, meteorological variables, and footprint-weighted spatial features were used as model inputs at three spatial resolutions (10 m, 20 m, 30 m), and their importance in predicting Fc with DeeperGCN was assessed. We found that residual correction using DeeperGCN significantly improved prediction accuracy, with the R 2 increasing from 0.9098 to 0.9479 for RF and from 0.9235 to 0.9433 for XGBoost. At site level, the maximum improvement in R 2 reached 0.1617. Paired t-tests confirmed that these improvements were statistically significant (p < 0.05). Among all predictors, leaf area index and incoming shortwave radiation emerged as the dominant drivers of spatial residual variation, followed by precipitation, relative humidity, and selected vegetation indices. The 20 m resolution yielded the best balance between model performance and computational efficiency. In conclusion, our modeling framework effectively captures both spatial heterogeneity and nonlinear interactions, offering a robust solution for spatially explicit flux modeling in structurally diverse ecosystems beyond the study sites.

footprint model↗
DOE OSTI2022

Detecting Hot Spots of Methane Flux Using Footprint‐Weighted Flux Maps

Abstract In this study, we propose a new technique for mapping the spatial heterogeneity in gas exchange around flux towers using flux footprint modeling and focusing on detecting hot spots of methane (CH 4 ) flux. In the first part of the study, we used a CH 4 release experiment to evaluate three common flux footprint models: the Hsieh model (Hsieh et al., 2000), the Kljun model (Kljun et al., 2015), and the K & M model (Kormann and Meixner, 2001), finding that the K & M model was the most accurate under these conditions. In the second part of the study, we introduce the Footprint‐Weighted Flux Map, a new technique to map spatial heterogeneity in fluxes. Using artificial CH 4 release experiments, natural tracer approaches and flux chambers we mapped the spatial flux heterogeneity, and detected and validated a hot spot of CH 4 flux in a oligohaline restored marsh. Through chamber measurements during the months of April and May, we found that fluxes at the hot spot were on average as high as 6589 ± 7889 nmol m −2 s −1 whereas background flux from the open water were on average 15.2 ± 7.5 nmol m −2 s −1 . This study provides a novel tool to evaluate the spatial heterogeneity of fluxes around eddy‐covariance towers and creates important insights for the interpretation of hot spots of CH 4 flux, paving the way for future studies aiming to understand subsurface biogeochemical processes and the microbiological conditions that lead to the occurrence of hot spots and hot moments of CH 4 flux.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Supply Cost and Life-Cycle Greenhouse Gas Footprint of Dry and Ensiled Biomass Sorghum for Biofuel Production

Here we discuss Biomass sorghum as a promising feedstock for cellulosic biorefineries because of its high yield and drought tolerance. However, the difficulty of effectively drying sorghum in some regions means that it may require different handling than previously studied grassy feedstocks. This study compares the delivered cost and life-cycle greenhouse gas (GHG) footprint of field drying and baling, module storage (wrapped, densely packed biomass), pelletizing, and ensiling. Ensiling has not been widely considered for use in bioenergy production. For farms within 66 km of the biorefinery, ensiled biomass is of the lowest cost and GHG strategy despite additional cost and energy demand for hauling wet biomass. Field drying and baling, if feasible, is the most cost-effective option for sorghum between 66 km and 104 km, beyond which pellets are preferable. A 2000 bone-dry-metric ton (bdt)/day biorefinery can source sorghum with 18 bdt/ha yield cultivated on 5% of surrounding land at costs ranging from $\$$122 (silage) to $\$$167 (pellets)/bdt and a life-cycle GHG footprint of 111 (silage) to 179 kg CO2e/bdt (pellets). With 28 bdt/ha biomass yield, 10% cultivation of surrounding land, and low fertilizer application, costs can range from $\$$66 (silage) to $\$$85 (pellets)/ bdt and GHG footprint of 43 (silage) to 96 kg CO2e (pellets)/bdt.

09 BIOMASS FUELS↗
DOE OSTI2021

Biomechanical Comparison of Anatomic Restoration of the Ulnar Footprint vs Traditional Ulnar Tunnels in Ulnar Collateral Ligament Reconstruction

Background: Current techniques for ulnar collateral ligament (UCL) reconstruction do not reproduce the anatomic ulnar footprint of the UCL. The purpose of this study was to describe a novel UCL reconstruction technique that utilizes proximal-to-distal ulnar bone tunnels to better re-create the anatomy of the UCL and to compare the biomechanical profile at time zero among this technique, the native UCL, and the traditional docking technique. Hypothesis: The biomechanical profile of the anatomic technique is similar to the native UCL and traditional docking technique. Study Design: Controlled laboratory study. Methods: Ten matched cadaveric elbows were potted with the forearm in neutral rotation. The palmaris longus tendon graft was harvested, and bones were sectioned 14 cm proximal and distal to the elbow joint. Specimen testing included (1) native UCL testing performed at 90° of flexion with 0.5 N·m of valgus moment preload, (2) cyclic loading from 0.5 to 5 N·m of valgus moment for 1000 cycles at 1 Hz, and (3) load to failure at 0.2 mm/s. Elbows then underwent UCL reconstruction with 1 elbow of each pair receiving the classic docking technique using either anatomic (proximal to distal) or traditional (anterior to posterior) tunnel locations. Specimen testing was then repeated as described. Results: There were no differences in maximum load at failure between the anatomic and traditional tunnel location techniques (mean ± SD, 34.90 ± 10.65 vs 37.28 ± 14.26 N·m; P = .644) or when including the native UCL (45.83 ± 17.03 N·m; P = .099). Additionally, there were no differences in valgus angle after 1000 cycles across the anatomic technique (4.58°± 1.47°), traditional technique (4.08°± 1.28°), and native UCL (4.07°± 1.99°). The anatomic group and the native UCL had similar valgus angles at failure (24.13°± 5.86° vs 20.13°± 5.70°; P = .083), while the traditional group had a higher valgus angle at failure when compared with the native UCL (24.88°± 6.18° vs 19.44°± 5.86°; P = .015). Conclusion: In this cadaveric model, UCL reconstruction with the docking technique utilizing proximal-to-distal ulnar tunnels better restored the ulnar footprint while providing valgus stability comparable with reconstruction with the docking technique using traditional anterior-to-posterior ulnar tunnel locations. These results suggest that utilization of the anatomic tunnel location in UCL reconstruction has similar biomechanical properties to the traditional method at the time of initial fixation (ie, not accounting for healing after reconstruction in vivo) while keeping the ulnar tunnels farther from the ulnar nerve. Further studies are warranted to determine if an anatomically based UCL reconstruction results in differing outcomes than traditional reconstruction techniques. Clinical Relevance: Current UCL reconstruction techniques do not accurately re-create the ulnar UCL footprint. The UCL is a dynamic constraint to valgus loads at the elbow, and a more anatomic reconstruction may afford more natural joint kinematics. This more anatomic technique performs similarly to the traditional docking technique at time zero, and the results of this study may offer a starting point for future in vivo studies.

Chang, Edward S.↗
NASA NTRS1976

A Remotely Operated Multiple Array Acoustic Range (ROMAAR) and its application for the measurement of airplane flyover noise footprints

The ROMAAR now in operation at NASA will allow direct measurement and display of aircraft noise in several measurement units during takeoff, landing, and flyby operations. This information, in addition to its application in terms of ground noise footprints, will also permit determination of the statistical variation of footprints or contours due to the atmosphere or aircraft operational parameters, and a measure of the impact of various noise reduction techniques and hardware on ground noise footprints. The methods, techniques, and equipment developed for the ROMAAR concept are applicable to CTOL, STOL, General Aviation, and VTOL aircraft. ROMAAR represents a unique combination of state of the art digital and analog noise recording methods, computer-controlled digital communications methods, radar-tracking facilities, quick-look weather capabilities, and a large data handling facility complemented by a large capacity curve fitting and plotting routine. The ROMAAR is set apart from the standard airport noise monitoring system by having the unique features mentioned above plus the fact that at present as many as 38 separate (but simultaneous) noise measurements can be made for each aircraft overflight.

Hilton, D. A.↗
NASA NTRS1990

Footprint prediction of scalar fluxes - Reliability and implications for airborne flux measurements over the FIFE site

Estimates of the location and extension of the upwind ground area that affects flux observations most directly are examined to determine the reliability of airborne versus near-ground flux measurements. The theoretical issues regarding the 'footprint' are examined, and specific observations are analyzed by studying the data over a grid regarding sensible heat, latent heat, CO2, and greenness. The grid is footprint-corrected to correlate better with independently observed surface characteristics, and an optimized footprint is developed that satisfies the relationships between the observed variables. Optimized mapping of the surface flux is given which demonstrates the importance of considering local advection to correlate airborne and ground-based flux observations. The technique is particularly applicable to situations in which significant variations in the surface flux density exist.

Schuepp, P. H.↗
NASA NTRS1995

Tire footprint studies

This presentation covers the results of tire footprint studies conducted in the Landing Gear Development Facility of the USAF Wright Laboratory at the Wright Patterson Air force Base, OH. Tire footprint studies are essential in understanding tire wear mechanisms and computing tire tread wear rates. The power input into the tread is the driving force for tread wear. Variables needed for power input calculations include the footprint pressure and slip velocity distributions. Studies were performed on the effects of power input distributions due to vertical load, camber, yaw, inflation pressure, and tire construction. For the present study, two tire constructions, one radial and the other bias, were selected. These tires were for the F-16 Block 30 fighter aircraft, both of which were previously worn. The present study was limited to steady straight roll with a 14,000 lb vertical load, a 310 psi inflation pressure, and zero yaw and camber. All tests were conducted on the Tire Force Machine (TFM) with a specialized sensor plate with embedded pressure sensors (X, Y, and Z) and slip sensors (X and Y). All tests were conducted for a table speed of 1 in/s. Tests on the TFM show that the power intensity distributions and total power for both tire constructions are quite similar for straight roll. Later on, tests were also conducted on a modified dynamometer which was overlaid with a grit wear surface. The tire speed was maintained at 40 miles per hour and yaw was set to four degrees. Dynamometer tests showed that radial tires have more tread wear than the bias tire; however, in the field, radial tires have longer life.

Chawla, Mangal↗
NASA NTRS1999

Return Echoes from Medium-Large Footprint Laser Altimeters

For just over 10 years, NASA Goddard Space Flight Center has been at the forefront of developing return echo laser altimeters and analysis techniques for a variety of both space and airborne applications. In 1991, the Laser Remote Sensing Branch began investigating the use of medium-large diameter footprint return waveforms for measuring vegetation height and structure and sub-canopy topography. Over the last 8 years, using a variety of profiling and scanning laser altimeters (i.e. ATLAS, SLICER, SLA, and LVIS), we have collected return waveforms over a variety of terrestrial surface types. We describe the effects of instrument characteristics and within-footprint surface structure on the shape of the return waveform and suggest several techniques for extracting this information. Specifically for vegetation returns, we describe the effects of canopy parameters such as architecture and closure on the shape of the return waveform. Density profiles, statistics, and examples from a variety of vegetation types will be presented, as well as comparisons with small-footprint laser altimeter data.

Blair, J. Bryan↗
NASA NTRS2015

Covariance Between Arctic Sea Ice and Clouds Within Atmospheric State Regimes at the Satellite Footprint Level

Understanding the cloud response to sea ice change is necessary for modeling Arctic climate. Previous work has primarily addressed this problem from the interannual variability perspective. This paper provides a refined perspective of sea ice-cloud relationship in the Arctic using a satellite footprint-level quantification of the covariance between sea ice and Arctic low cloud properties from NASA A-Train active remote sensing data. The covariances between Arctic low cloud properties and sea ice concentration are quantified by first partitioning each footprint into four atmospheric regimes defined using thresholds of lower tropospheric stability and mid-tropospheric vertical velocity. Significant regional variability in the cloud properties is found within the atmospheric regimes indicating that the regimes do not completely account for the influence of meteorology. Regional anomalies are used to account for the remaining meteorological influence on clouds. After accounting for meteorological regime and regional influences, a statistically significant but weak covariance between cloud properties and sea ice is found in each season for at least one atmospheric regime. Smaller average cloud fraction and liquid water are found within footprints with more sea ice. The largest-magnitude cloud-sea ice covariance occurs between 500m and 1.2 km when the lower tropospheric stability is between 16 and 24 K. The covariance between low cloud properties and sea ice is found to be largest in fall and is accompanied by significant changes in boundary layer temperature structure where larger average near-surface static stability is found at larger sea ice concentrations.

Taylor, Patrick C.↗
NASA NTRS2019

A Ground Footprint Eccentricity Model For Asteroid Airbursts

Uncertainties in early observations of potentially hazardous asteroids result in preliminary impact corridors that can stretch across large portions of the Earth’s surface. At this early stage of detection, the corridor width and potential for damage are typically estimated using techniques from nuclear weapons research. These estimates often employ spherical blast assumptions resulting in a constant width impact corridor. In actuality, however, the ground damage footprint of obliquely entering asteroids is generally roughly elliptical or “butterfly” shaped, with the major axis extending in the cross range direction and the minor axis aligned with ground-track of the meteoroid. Since actual ground footprints for oblique entries may have aspect ratios greater than two or three, the assumption of a circular blast may significantly underestimate the area of the impact swath and the at-risk population. This work develops an engineering model that can be used to quickly estimate the eccentricity of the ground footprint as a function of local impact parameters. This yields vastly improved local estimates of the corridor width and can significantly enhance the accuracy of risk analysis.

Aftosmis, Michael J.↗
NASA NTRS2021

The Large Footprint of Small-scale Artisanal Gold Mining in Ghana

Gold mining has played a significant role in Ghana's economy for centuries. Regulation of this industry has varied over time and while industrial mining is prevalent in the country, the expansion of artisanal mining, or Galamsey has escalated in recent years. Many of these artisanal mines are not only harmful to human health due to the use of Mercury (Hg) in the amalgamation process, but also leave a significant footprint on terrestrial ecosystems, degrading and destroying forested ecosystems in the region. In this study, the Landsat image archive available through Google Earth Engine was used to quantify the total footprint of vegetation loss due to artisanal goldmines in Ghana from 2005 to 2019 and understand how conversion of forested regions to mining has changed over a decadal period from 2007 to 2017. A combination of machine learning and change detection algorithms were used to calculate different land cover conversions and the timing of conversion annually. Within the study area of southwestern Ghana, our results indicate that approximately 47,000 ha (⨦2218 ha) of vegetation were converted to mining at an average rate of ~2600 ha yr−1. The results indicate that a high percentage(~50%) of this mining occurred between 2014 and 2017. Around 700 ha of this mining occurred within protected areas as mapped by the World Database of Protected Areas. In addition to deforestation, increased artisanal mining activity in recent years has the potential to affect human health, access to drinking water resources and food security. This work expands upon limited research into the spatial footprint of Galamseyin Ghana, complements mapping efforts by local geographers, and will support efforts by the government of Ghana to monitor deforestation caused by artisanal mining.

Abigail Barenblitt↗
DOE OSTI2021

New high-throughput endstation to accelerate the experimental optimization pipeline for synchrotron X-ray footprinting

Synchrotron X-ray footprinting (XF) is a growing structural biology technique that leverages radiation-induced chemical modifications via X-ray radiolysis of water to produce hydroxyl radicals that probe changes in macromolecular structure and dynamics in solution states of interest. The X-ray Footprinting of Biological Materials (XFP) beamline at the National Synchrotron Light Source II provides the structural biology community with access to instrumentation and expert support in the XF method, and is also a platform for development of new technological capabilities in this field. Hee, the design and implementation of a new high-throughput endstation device based around use of a 96-well PCR plate form factor and supporting diagnostic instrumentation for synchrotron XF is described. This development enables a pipeline for rapid comprehensive screening of the influence of sample chemistry on hydroxyl radical dose using a convenient fluorescent assay, illustrated here with a study of 26 organic compounds. The new high-throughput endstation device and sample evaluation pipeline now available at the XFP beamline provide the worldwide structural biology community with a robust resource for carrying out well optimized synchrotron XF studies of challenging biological systems with complex sample compositions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗