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DOE OSTI2025

The meV-resolved Inelastic X-ray Scattering Beamline at NSLS-II: Design and Performance

The ultrahigh resolution inelastic X-ray scattering (IXS) beamline at NSLS-II is designed and built to achieve sub-meV resolution at a moderate energy of 9.13 keV for IXS experiments with high momentum resolution and high spectral contrast. The key instrument is a novel spectrometer featuring a new type of analyzer optics, which combines post-sample collimation with angular dispersive crystal optics. As the first user instrument of its kind, the spectrometer has demonstrated unique research capabilities in exploring low momentum transfer (Q), THz dynamics in soft material systems characterized by mesoscopic heterogeneity and complexity, such as liquid crystals and bio-membranes. Ongoing efforts to improve performance since the start of user operations have resulted in a state-of-the-art energy resolution in routine operations of less than 1.4 meV, with sharp Gaussian-like tails, making it a premier IXS spectrometer for studying the dynamics of soft materials, while also delivering competitive performance for investigating phonon dynamics in hard condensed matter systems, including a broad range of quantum materials.

43 PARTICLE ACCELERATORS↗

NASA NTRS1990

Ulysses Launch

Ulysses is a joint mission between the United States National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA) to explore the heliosphere over the full range of solar latitudes, especially in the polar regions. The goal of the Ulysses mission is to provide an accurate assessment of our total solar environment. This collaborative ESA/NASA mission will, for the first time, explore the heliosphere -- the region of space that is dominated by the Sun-- within a few astronomical units of the Sun over the full range of heliographic latitudes. The path followed by the spacecraft, using a Jupiter gravity-assist to achieve a trajectory extending to high solar latitudes, will enable the highly sophisticated scientific instruments on board to make measurements in the uncharted third dimension of the heliosphere. The Ulysses spacecraft will carry nine scientific instruments to measure the properties of the solar corona, the solar wind, the Sun/wind interface, the heliospheric magnetic field, solar radio bursts, plasma waves, solar X-rays, solar and galactic cosmic rays, and the interplanetary/interstellar neutral gas and dust. Scientists will take advantage of the enormous distance between the spacecraft and the Earth to perform astrophysical measurements and to search for gravitational waves. In conjunction with instrumentation on Earth-orbiting spacecraft, Ulysses will help to precisely locate the mysterious sources of cosmic gamma bursts. The results obtained will help to solve outstanding problems in solar and heliospheric physics, while undoubtedly revealing new and unanticipated phenomena.

Source record↗

DOE OSTI2026

Excitations across the Equilibrium and Photoinduced “Hidden” States of Magnetoresistive Manganites

“Hidden” phases, generated using ultrafast laser pulses (few hundred femtoseconds), with distinct properties than at the thermodynamic equilibrium, are appealing for technologies, as they can be long-lived, with a lifetime of hours or weeks, and reversible with temperature sweeping or extra pulses. In this regard, La 2/3 ⁢Ca 1/3⁢ MnO 3 (LCMO) stands out due to its tunability through epitaxial strain, which can drive the bulk ferromagnetic metal into an antiferromagnetic insulator (AFI), and its susceptibility to photoinduced transitions. Indeed, AFI LCMO displays a long-lived photoinduced transition into a putative hidden phase whose exact nature and excitations are still largely unknown. Here, we combine ultrafast photoexcitation in the near infrared with in situ transport, x-ray absorption, and resonant inelastic x-ray scattering (RIXS) to investigate the excitations (polarons, phonons, and orbital) of the photoexcited phase of LCMO and contrast them with the thermodynamic phases achieved through strain and temperature. In the thermodynamic regime, we establish the correlation between polarons and transport placing them in the “strong coupling” regime of the Holstein model. Upon photoexcitation of LCMO-AFI, we uncover a long-lived phase characterized by the softening of the polaron excitations, the partial suppression of the Jahn-Teller distortion, and nearly unchanged phonons, showing the emergence of a photoexcited state absent in the equilibrium phase diagram. Finally, by varying temperature, epitaxial strain, and photoexcitation fluence, we construct a polaron phase diagram and identify the key spectroscopic signatures of each phase. Our laser-RIXS approach establishes a versatile platform for exploring photoinduced hidden phases in quantum materials in nonstroboscopic conditions.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

High-Altitude ADS-B Flight Tests on a NASA ER-2 Research Airplane

Researchers at the National Aeronautics and Space Administration (NASA) Armstrong Flight Research Center (Edwards, California); the Federal Aviation Administration (FAA); and Regulus Group, LLC (Atlantic City, New Jersey) collaborated for the flight-test demonstration of an Automatic Dependent Surveillance-Broadcast (ADS-B) system equipped on a high-altitude Earth Resources-2 (ER-2) research airplane. The unique ER-2 airplane is a NASA-owned and operated airborne science version of the United States Air Force / Lockheed Martin Aeronautics (Bethesda, Maryland) U-2S airplane. The FAA has mandated that by the year 2020, aircraft operating within certain sections of the United States National Airspace system be equipped with ADS-B Out technology; the research presented in this paper is the first to show how the NASA ADS-B architecture satisfies the mandate for a unique high-altitude aircraft. An exceptional military aircraft design, security protocols, and the performance envelope of the ER-2 airplane made the avionics integration remarkably challenging. The design required the ADS-B avionics to survive the harsh flight environment of the ER-2 airplane. The most prominent challenge was the functional integration of modern civilian avionics into federated military legacy avionics. Flight-test objectives were to certify an ADS-B Out (1090ES) passive surveillance integrated with a Traffic Alert and Collision Avoidance System (TCAS) I active surveillance system on an ER-2 platform for high-altitude cruise operations. In April 2022, NASA conducted three flights at Edwards Air Force Base (Edwards, California) - each greater than one-hour flight reaching altitudes above 60,000 ft.

ADS-B↗

DOE OSTI2025

OLCF Test Harness

Acceptance and regression testing of a High Performance Computing (HPC) system requires an automated and reproducible framework and tool for running and logging results. Manually running tests across a system is labor intensive and prone to reproducibility errors. The OLCF Test Harness (OTH) provides a framework in which to document required tests for a HPC system. The OTH then provides tools to execute and log results of these tests in an automated fashion.

Dietz, Dan [Oak Ridge National Laboratory (ORNL), ↗

NASA NTRSDate not supplied

Changes in the Ozone Chemical Regime Over the Contiguous United States Inferred By the Inversion of NOx and VOC Emissions Using Satellite Observation

To investigate changes in the ozone (O3) chemical production regime over the contiguous United States (CONUS) with accurate knowledge of concentrations of its precursors, we applied an inverse modeling technique with Ozone Monitoring Instrument (OMI) tropospheric nitrogen dioxide (NO2) and total formaldehyde (HCHO) retrieval products in the summers of 2011, 2014, and 2017, years in which United States National Emission Inventory were based. The inclusion of dynamic chemical lateral boundary conditions and lightning-induced nitric oxide emissions significantly account for the contribution of background sources in the free troposphere. Satellite-constrained nitrogen oxide (NOx) and non-methane volatile organic compounds (NMVOCs) emissions mitigate the discrepancy between satellite and modeled columns: the inversion suggested 2.33-2.84 (1.07-1.34) times higher NOx over the CONUS (over urban regions) and 0.28-0.81 times fewer NMVOCs emissions over the southeastern United States. The model-derived HCHO/NO2 column ratio shows gradual spatial changes in the O3 production regime near urban cores relative to previously defined threshold values representing NOx and VOC sensitive conditions. We also found apparent shifts from the NOx-saturated regime to the transition regime (or the transition regime to the NOx-limited regime) over the major cities in the western United States. In contrast, rural areas, especially in the east-southeastern United States, exhibit a decreased HCHO/NO2 column ratio by -1.30 ± 1.71 with a reduction in HCHO column primarily driven by meteorology, becoming sensitive to VOC emissions. Results show that incorporating satellite observations into numerical modeling could help policymakers implement appropriate emission control policies for O3 pollution.

HCHO/NO2 factorInverse modelingOzone chemical regi↗

DOE OSTI2025

Topotactic Reduction‐Driven Crystal Field Excitations in Brownmillerite Manganite Thin Films

Topotactic reduction of perovskite oxides offers a powerful approach for discovering novel phenomena, such as superconducting infinite-layer nickelates and polar metallicity, and is commonly accompanied by the emergence of multiple valence states and/or complex crystal fields of transition metals. However, understanding the complex interplay between crystal chemistry, electronic structure, and physical properties at the spin- and orbital-resolved levels in these reduced systems remains elusive. Here, in this study, x-ray absorption spectroscopy, resonant inelastic x-ray scattering (RIXS), and density functional theory calculations are used to uncover topotactic metal-insulator transition and orbital-specific crystal field excitations in brownmillerite La 0.67 Ca 0.33 MnO 2.5 thin films. The Mn valence states are found to be Mn 2+ /Mn 3+ , along with their corresponding populations at octahedral and tetrahedral sites, which effectively weaken the Mn-O hybridization compared to the parent perovskite phase. As a result, La 0.67 Ca 0.33 MnO 2.5 films exhibit an antiferromagnetic insulating ground state. Moreover, by combining the RIXS measurements on selected single-valence manganites, specifically MnO, LaMnO 3 , and CaMnO 3 , with orbital- and spin-resolved density-of-states calculations, the study identifies the dd excitations of octahedrally and tetrahedrally coordinated Mn 2+ /Mn 3+ ions, directly linking the microscopic electronic structure to the macroscopic magnetic/electrical properties.

36 MATERIALS SCIENCE↗

NASA NTRS2016

Cyber-Threat Assessment for the Air Traffic Management System: A Network Controls Approach

Air transportation networks are being disrupted with increasing frequency by failures in their cyber- (computing, communication, control) systems. Whether these cyber- failures arise due to deliberate attacks or incidental errors, they can have far-reaching impact on the performance of the air traffic control and management systems. For instance, a computer failure in the Washington DC Air Route Traffic Control Center (ZDC) on August 15, 2015, caused nearly complete closure of the Centers airspace for several hours. This closure had a propagative impact across the United States National Airspace System, causing changed congestion patterns and requiring placement of a suite of traffic management initiatives to address the capacity reduction and congestion. A snapshot of traffic on that day clearly shows the closure of the ZDC airspace and the resulting congestion at its boundary, which required augmented traffic management at multiple locations. Cyber- events also have important ramifications for private stakeholders, particularly the airlines. During the last few months, computer-system issues have caused several airlines fleets to be grounded for significant periods of time: these include United Airlines (twice), LOT Polish Airlines, and American Airlines. Delays and regional stoppages due to cyber- events are even more common, and may have myriad causes (e.g., failure of the Department of Homeland Security systems needed for security check of passengers, see [3]). The growing frequency of cyber- disruptions in the air transportation system reflects a much broader trend in the modern society: cyber- failures and threats are becoming increasingly pervasive, varied, and impactful. In consequence, an intense effort is underway to develop secure and resilient cyber- systems that can protect against, detect, and remove threats, see e.g. and its many citations. The outcomes of this wide effort on cyber- security are applicable to the air transportation infrastructure, and indeed security solutions are being implemented in the current system. While these security solutions are important, they only provide a piecemeal solution. Particular computers or communication channels are protected from particular attacks, without a holistic view of the air transportation infrastructure. On the other hand, the above-listed incidents highlight that a holistic approach is needed, for several reasons. First, the air transportation infrastructure is a large scale cyber-physical system with multiple stakeholders and diverse legacy assets. It is impractical to protect every cyber- asset from known and unknown disruptions, and instead a strategic view of security is needed. Second, disruptions to the cyber- system can incur complex propagative impacts across the air transportation network, including its physical and human assets. Also, these implications of cyber- events are exacerbated or modulated by other disruptions and operational specifics, e.g. severe weather, operator fatigue or error, etc. These characteristics motivate a holistic and strategic perspective on protecting the air transportation infrastructure from cyber- events. The analysis of cyber- threats to the air traffic system is also inextricably tied to the integration of new autonomy into the airspace. The replacement of human operators with cyber functions leaves the network open to new cyber threats, which must be modeled and managed. Paradoxically, the mitigation of cyber events in the airspace will also likely require additional autonomy, given the fast time scale and myriad pathways of cyber-attacks which must be managed. The assessment of new vulnerabilities upon integration of new autonomy is also a key motivation for a holistic perspective on cyber threats.

Complex Networks↗

DOE OSTI2025

Comprehensive Measurement of the Reactor Antineutrino Spectrum and Flux at Daya Bay

This Letter reports the precise measurement of the reactor antineutrino spectrum and flux based on the full dataset of 4.7 ×10 6 inverse-beta-decay candidates collected at Daya Bay near detectors. Expressed in terms of the inverse-beta-decay yield per fission, the antineutrino spectra from all reactor fissile isotopes and the specific 235 U and 239 Pu isotopes are measured with 1.3%, 3%, and 8% uncertainties, respectively, near the 3 MeV spectrum peak in reconstructed energy, reaching the best precision in the world. The total antineutrino flux and isotopic 235 U and 239 Pu fluxes are precisely measured to be 5.84 ± 0.07, 6.16 ± 0.12, and 4.16 ± 0.21 in units of 10 −43 cm 2 /fission. These measurements are compared with the Huber-Mueller model, the reevaluated conversion model based on the Kurchatov Institute measurement, and the latest summation model (SM2023). Furthermore, the Daya Bay flux shows good consistency with the Kurchatov Institute and SM2023 models but disagrees with the Huber-Mueller model. The Daya Bay spectrum, however, disagrees with all model predictions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Mixed-precision numerics in scientific applications: survey and perspectives

The explosive demand for artificial intelligence (AI) workloads has led to a significant increase in silicon area dedicated to lower-precision computations on recent high-performance computing hardware designs. However, mixed-precision capabilities, which can achieve performance improvements of up to 8x compared to double-precision in extreme compute-intensive workloads, remain largely untapped in most scientific applications. A growing number of efforts have shown that mixed-precision algorithmic innovations can deliver superior performance without sacrificing accuracy. These developments should prompt computational scientists to seriously consider whether their scientific modeling and simulation applications could benefit from the acceleration offered by new hardware and mixed-precision algorithms. In this survey, we (1) review progress across diverse scientific domains—fluid dynamics, weather and climate, quantum chemistry, and computational genomics—that have begun adopting mixed-precision strategies; (2) examine state-of-the-art algorithmic techniques such as iterative refinement, splitting and emulation schemes, and adaptive precision solvers; (3) assess their implications for accuracy, performance, and resource utilization; and (4) survey the emerging software ecosystem that enables mixed-precision methods at scale. We conclude with perspectives and recommendations on cross-cutting opportunities, domain-specific challenges, and the role of co-design between application scientists, numerical analysts, and computer scientists. Collectively, this survey underscores that mixed-precision numerics can reshape computational science by aligning algorithms with the evolving landscape of hardware capabilities.

Graphics processing units↗

NASA NTRS2012

Design and Test Plans for a Non-Nuclear Fission Power System Technology Demonstration Unit

A joint National Aeronautics and Space Administration (NASA) and Department of Energy (DOE) team is developing concepts and technologies for affordable nuclear Fission Power Systems (FPSs) to support future exploration missions. A key deliverable is the Technology Demonstration Unit (TDU). The TDU will assemble the major elements of a notional FPS with a non-nuclear reactor simulator (Rx Sim) and demonstrate system-level performance in thermal vacuum. The Rx Sim includes an electrical resistance heat source and a liquid metal heat transport loop that simulates the reactor thermal interface and expected dynamic response. A power conversion unit (PCU) generates electric power utilizing the liquid metal heat source and rejects waste heat to a heat rejection system (HRS). The HRS includes a pumped water heat removal loop coupled to radiator panels suspended in the thermal-vacuum facility. The basic test plan is to subject the system to realistic operating conditions and gather data to evaluate performance sensitivity, control stability, and response characteristics. Upon completion of the testing, the technology is expected to satisfy the requirements for Technology Readiness Level 6 (System Demonstration in an Operational and Relevant Environment) based on the use of high-fidelity hardware and prototypic software tested under realistic conditions and correlated with analytical predictions.

Mason, Lee↗

DOE OSTI2026

Framework for X-ray mirror surface shape fitting

For accurate characterization of grazing-incidence X-ray mirrors, we present a comprehensive framework to fit measured surface shapes (either slope or height) of X-ray mirrors used in synchrotron radiation and free-electron laser facilities. We summarize the closed-form expressions of some typical surface shapes of X-ray mirrors including elliptic cylinders, hyperbolic cylinders, ellipsoids, hyperboloids, and diaboloids. This framework is composed of four layers: definition of standard shapes with closed-form expressions, generation of theoretical surface with pose parameters (six degrees of freedom defining an object's position and orientation relative to a coordinate system), parameter optimization with the ability to select which parameters are fit and which are held constant, and the development of user-friendly fitting function wrappers for particular fitting tasks. A few practical fitting examples are demonstrated to verify the effectiveness of the proposed fitting framework. We discuss the physical meanings of the fitting parameters, and provide several examples using the elliptic cylinder and ellipsoid shapes to highlight some features of the framework. Moreover, we provide the presented framework as open-source codes (MATLAB and Python codes available at https://github.com/nsls2omf/xmf) to the community to encourage academic collaboration and further improvements.

36 MATERIALS SCIENCE↗

DOE OSTI2025

CO 2 Hydrogenation on Pd(111): The Role of Subsurface Hydrogen and Surface Defects

Palladium-based catalysts are often used in carbon dioxide (CO 2 ) hydrogenation reactions with different possible reaction pathways producing methanol, methane, formic acid, or carbon monoxide. We used ambient pressure X-ray photoelectron spectroscopy (AP-XPS) to understand the surface reaction mechanism of CO 2 hydrogenation on Pd(111). AP-XPS results show that the order in which the reactants are introduced yields different initial surface species. In a CO 2 and H 2 mixture, carbonaceous species (CH x , C*, PdC x ) are formed upon heating Pd(111) at 400 K and above. In addition, a Pd(111) sample pre-exposed to an elevated pressure of H 2 followed by evacuation to ultrahigh vacuum (UHV) can store enough hydrogen atoms in the subsurface and bulk to provide a hydrogen source for the CO 2 hydrogenation reaction to occur when exposed to CO 2 gas alone. In conclusion, the formation of carbonaceous species likely occurs through the decomposition of a transient CH x O intermediate facilitated by low-coordinated sites and surface defects.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Estimating basis functions in massive fields under the spatial mixed effects model

Abstract Spatial prediction is commonly achieved under the assumption of a Gaussian random field by obtaining maximum likelihood estimates of parameters, and then using the kriging equations to arrive at predicted values. For massive datasets, fixed rank kriging using the expectation–maximization algorithm for estimation has been proposed as an alternative to the usual but computationally prohibitive kriging method. The method reduces computation cost of estimation by redefining the spatial process as a linear combination of basis functions and spatial random effects. A disadvantage of this method is that it imposes constraints on the relationship between the observed locations and the knots. We develop an alternative method that utilizes the spatial mixed effects model, but allows for additional flexibility by estimating the range of the spatial dependence between the observations and the knots via an alternating expectation conditional maximization algorithm. Experiments show that our methodology improves estimation without sacrificing prediction accuracy while also minimizing the additional computational burden of extra parameter estimation. The methodology is applied to a temperature dataset archived by the United States National Climate Data Center, with improved results over previous methodology.

Pazdernik, Karl↗

DOE OSTI2023

Integrating Reservoirs into the Dissolved Organic Matter Versus Primary Production Paradigm: How Does Chlorophyll-$a$ Change Across Dissolved Organic Carbon Concentrations in Reservoirs?

Primary production in freshwater ecosystems is largely a function of light and nutrient availability, both of which have been changing in many lakes and reservoirs in response to anthropogenic pressures. Recent studies focusing on natural lakes have found a hump-shaped response of primary production (sometimes measured as chlorophyll-$a$) to dissolved organic matter (DOM, measured as dissolved organic carbon, DOC), which has both light-absorbing chromophoric properties and DOM-bound nutrients. We used the United States National Lakes Assessment dataset to integrate reservoirs into this paradigm in comparison with natural lakes and assessed the relative differences in the predicted response’s model structure, regression parameter values, and drivers of the chlorophyll-$a$ residuals. We found that chlorophyll-$a$ in reservoirs exhibited a hump-shaped response to DOC, while natural lakes from this dataset were better fit with a linear response, differing from previous studies focused on boreal lakes. Despite this, reservoirs had a greater maximum chlorophyll-a response compared to natural lakes in this study (45.5 versus 33.8 μg L -1 ), which occurred at a lower DOC concentration threshold (18.3 versus 26.4 mg L -1 ) when compared using quadratic models. Reservoirs had lower median light:nutrient values compared to natural lakes, and greater median surface area and total phosphorus (TP), that can all influence the light environment and the peak chlorophyll-a responses. In both reservoirs and natural lakes, chlorophyll-$a$ residuals were most strongly influenced by TP, where TP < 25-30 µg L -1 suppressed chlorophyll-a residuals and higher TP amplified them. Light:nutrient values were somewhat important predictors, and patterns with chlorophyll-$a$ residuals supported previous work showing low light:nutrient values amplified chlorophyll-$a$ responses and higher values suppressed them. In conclusion, quantifying the shape of the response of primary production to DOM quantity and quality as well as the drivers of the residuals, namely TP for lakes and reservoirs in this dataset, will be important for understanding the effects that changes in water quality may have on primary production and freshwater ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Array-Based Machine Learning for Functional Group Detection in Electron Ionization Mass Spectrometry

Mass spectrometry is a ubiquitous technique capable of complex chemical analysis. The fragmentation patterns that appear in mass spectrometry are an excellent target for artificial intelligence methods to automate and expedite the analysis of data to identify targets such as functional groups. To develop this approach, we trained models on electron ionization (a reproducible hard fragmentation technique) mass spectra so that not only the final model accuracies but also the reasoning behind model assignments could be evaluated. The convolutional neural network (CNN) models were trained on 2D images of the spectra using transfer learning of Inception V3, and the logistic regression models were trained using array-based data and Scikit Learn implementation in Python. Our training dataset consisted of 21,166 mass spectra from the United States’ National Institute of Standards and Technology (NIST) Webbook. The data was used to train models to identify functional groups, both specific (e.g., amines, esters) and generalized classifications (aromatics, oxygen-containing functional groups, and nitrogen-containing functional groups). We found that the highest final accuracies on identifying new data were observed using logistic regression rather than transfer learning on CNN models. It was also determined that the mass range most beneficial for functional group analysis is 0–100 m/z. We also found success in correctly identifying functional groups of example molecules selected from both the NIST database and experimental data. Beyond functional group analysis, we also have developed a methodology to identify impactful fragments for the accurate detection of the models’ targets. The results demonstrate a potential pathway for analyzing and screening substantial amounts of mass spectral data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Doubling of U.S. Population Exposure to Climate Extremes by 2050

We quantify historical and projected trends in the population exposure to climate extremes as measured by the United States National Center for Environmental Information Climate Extremes Index (CEI). Based on the analyses of the historical observations, we find that the U.S. has already experienced a rise in the occurrence of aggregated extremes in recent decades, consistent with the climate response to historical increases in radiative forcing. Additionally, we find that exposure can be expected to intensify under the Representative Concentration Pathway 8.5, with all counties permanently exceeding the baseline variability in the occurrence of extreme hot days, warm nights, and drought conditions by 2050. As a result, every county in the U.S. is projected to permanently exceed the historical CEI variability (as measured by one standard deviation during the 1981–2005 period). Based on the current population distribution, this unprecedented change implies a yearly exposure to extreme conditions for one in every three people. We find that the increasing trend in exposure to the aggregated extremes is already detectable over much of the U.S., and particularly in the central and eastern U.S. The high correspondence between the pattern of trends in our simulations and observations increases confidence in the projected amplification of population exposure to unprecedented combinations of extreme climate conditions, should greenhouse gas concentrations continue to escalate along their current trajectory.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

The NIH Somatic Cell Genome Editing program

The move from reading to writing the human genome offers new opportunities to improve human health. The United States National Institutes of Health (NIH) Somatic Cell Genome Editing (SCGE) Consortium aims to accelerate the development of safer and more-effective methods to edit the genomes of disease-relevant somatic cells in patients, even in tissues that are difficult to reach. Here we discuss the consortium’s plans to develop and benchmark approaches to induce and measure genome modifications, and to define downstream functional consequences of genome editing within human cells. Central to this effort is a rigorous and innovative approach that requires validation of the technology through third-party testing in small and large animals. New genome editors, delivery technologies and methods for tracking edited cells in vivo, as well as newly developed animal models and human biological systems, will be assembled—along with validated datasets—into an SCGE Toolkit, which will be disseminated widely to the biomedical research community. We visualize this toolkit—and the knowledge generated by its applications—as a means to accelerate the clinical development of new therapies for a wide range of conditions.

59 BASIC BIOLOGICAL SCIENCES↗