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At least 1,189 records · Page 66

EXPERIMENTAL DEMONSTRATION OF A STRAIGHT-MERGER BEAMLINE

Beamlines capable of merging beams with different energies are critical to many applications related to advanced accelerator concepts and energy recovery linacs (ERLs). A straight merger system composed of a transverse deflecting cavity with a superimposed dipole magnet was proposed and recently tested at the Argonne Wakefield Accelerator. This paper reports on the experimental demonstration of the concept along with detailed beam dynamics investigations of the merger concept and its ability to conserve the beam brightness associated with the fresh bunch. Possible applications to ERL and beam-driven wakefield accelerators are also discussed.

Phillips, C.↗

Preliminary Tests and Beam Dynamics Simulations of a Straight-Merger Beamline

Beamlines capable of merging beams with different energies are critical to many applications related to advanced accelerator concepts and energy-recovery linacs (ERLs). In an ERL, a low-energy "fresh" bright bunch is generally injected into a superconducting linac for acceleration using the fields established by a decelerated "spent" beam traveling on the same axis. A straight-merger system composed of a selecting cavity with a superimposed dipole magnet was proposed and recently test at AWA. This paper reports on the experimental results obtained so far along with detailed beam dynamics investigations of the merger concept and its ability to conserve the beam brightness associated with the fresh bunch.

Al Marzouk, A. A.↗

FAIRmaterials: Ontology Tools with Data FAIRification in Development

The bilingual FAIRmaterials package simplifies the creation and visualization of materials and data science ontologies. FAIRmaterials, available in the Python and R languages, addresses the complexities associated with traditional ontology editors based on manual user input such as Protege with an intuitive workflow and easy-to-use templates, making it accessible to users both experienced and inexperienced with ontologies. The FAIRmaterials package is its ability to programatically convert simple and structured CSV inputs into rich, well-defined ontologies. This capability is designed to support the findability, accessibility, interoperability, and reusability (FAIR) of research data and serve as a tool in the process of data FAIRification. Its additional features, such as automated ontology merging, static visualizations, and comprehensive documentation for outputs extend its utility, making it a valuable tool for any researcher engaged in knowledge management.

Bradley, Alexander Harding [Case Western Reserve U↗

Single-molecule 3D imaging of HIV cellular entry by liquid-phase electron tomography

Enveloped viruses, including human immunodeficiency virus (HIV) and SARS-CoV-2, target cells through membrane fusion process. The detailed understanding of the process is sought after for vaccine development but remains elusive due to current technique limitations for direct three-dimensional (3D) imaging of an individual virus during its viral entry. Recently, we developed a simple specimen preparation method for real-time imaging of metal dynamic liquid-vaper interface at nanometer resolution by transmission electron microscopy (TEM). Here, we extended this method to study biology sample through snapshot 3D structure of a single HIV (pseudo-typed with the envelope glycoprotein of vesicular stomatitis virus, VSV-G) at its intermediate stage of viral entry to HeLa cells in a liquid-phase environment. By individual-particle electron tomography (IPET), we found the viral surface release excess lipids with unbound viral spike proteins forming ~50-nm nanoparticles instead of merging cell membrane. Moreover, the spherical-shape shell formed by matrix proteins underneath the viral envelope does not disassemble into a cone shape right after fusion. Further, the snapshot 3D imaging of a single virus provides us a direct structure-based understanding of the viral entry mechanism, which can be used to examine other viruses to support the development of vaccines combatting the current ongoing pandemic.

Kong, Lingli↗

A Study of QCD Radiation in VBF Higgs Production with Vincia and Pythia

We discuss and illustrate the properties of several parton-shower algorithms available in Pythia and Vincia, in the context of Higgs production via vector boson fusion (VBF). In particular, the distinctive colour topology of VBF processes allows to define observables sensitive to the coherent radiation pattern of additional jets. We study a set of such observables, using the Vincia sector-antenna shower as our main reference, and contrast it to Pythia's transverse-momentum-ordered DGLAP shower as well as Pythia's dipole-improved shower. We then investigate the robustness of these predictions as successive levels of higher-order perturbative matrix elements are incorporated, including next-to-leading-order matched and tree-level merged calculations, using Powheg Box and Sherpa respectively to generate the hard events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Interpolated Sounding and Gridded Sounding Value-Added Products

Standard Atmospheric Radiation Measurement (ARM) Climate Research Facility sounding files provide atmospheric state data in one dimension of increasing time and height per sonde launch. Many applications require a quick estimate of the atmospheric state at higher time resolution. The INTERPOLATEDSONDE (i.e., Interpolated Sounding) Value-Added Product (VAP) transforms sounding data into continuous daily files on a fixed time-height grid, at 1-minute time resolution, on 332 levels, from the surface up to a limit of approximately 40 km. The grid extends that high so the full height of soundings can be captured; however, most soundings terminate at an altitude between 25 and 30 km, above which no data is provided. Between soundings, the VAP linearly interpolates atmospheric state variables in time for each height level. In addition, INTERPOLATEDSONDE provides relative humidity scaled to microwave radiometer (MWR) observations.The INTERPOLATEDSONDE VAP, a continuous time-height grid of relative humidity-corrected sounding data, is intended to provide input to higher-order products, such as the Merged Soundings (MERGESONDE; Troyan 2012) VAP, which extends INTERPOLATEDSONDE by incorporating model data. The INTERPOLATEDSONDE VAP also is used to correct gaseous attenuation of radar reflectivity in products such as the KAZRCOR VAP.

54 ENVIRONMENTAL SCIENCES↗

Mitigation of Beam Losses in LANSCE Linear Accelerator

Suppression of beam losses is essential for successful operation of high-intensity accelerator facility. The LANSCE accelerator started routine operation in 1972 as a 0.8 MW average proton beam power facility for meson physics research, and delivered highpower beam for a quarter century. The accelerator currently delivers 100 MeV proton beam to Isotope Production Facility (IPF) and 800 MeV H- beams to various experimental areas. The accelerator is equipped with two independent injectors for H + and H - beams, merging at the entrance of a 201.25 MHz Drift Tube Linac (DTL). The DTL performs acceleration up to the energy of 100 MeV. After the DTL, the Transition Region beamline directs a 100 MeV proton beam to the Isotope Production Facility, while the H - beam is accelerated up to the final energy of 800 MeV in an 805- MHz Coupled Cavity Linac. The H - beams, created with different time structure by a lowenergy chopper, are distributed in the Switch Yard (SY) to four experimental areas: the Lujan Neutron Scattering Center equipped with a Proton Storage Ring (PSR), the Weapons Neutron Research facility (WNR), the Proton Radiography facility (pRad), and the Ultra-Cold Neutron facility (UCN). Multi-beam operation requires careful control of accelerator tune to minimize beam losses. In this paper we review main effects affecting beam losses in LANSCE linear accelerator and discuss methods to reduce them.

43 PARTICLE ACCELERATORS↗

Thermophotovoltaic Heat Engine

This project was aimed at developing a thermophotovoltaic device that efficiently converts thermal radiation to electrical power. Historically, TPV devices have been plagued by poor robustness; this project sought to overcome this by merging innovations in nanophotonics, photovoltaics, and robust thermal engineering. Efforts were focused on developing high efficiency TPV devices which may drastically alter the electricity sector by enabling efficient (> 20%), fuel-flexible (any combustion fuel), distributed (< 10 kW) power generation. The project research identified the technical performance limits, technology differentiator, and customer value proposition for TPV devices and established technical performance requirements for a minimum viable product.

30 DIRECT ENERGY CONVERSION↗

Imaging of Calibrated Defects in Additively Manufactured Materials: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Known material flaws in AM include low-density regions consisting of non-sintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. Currently, limited options are available for nondestructive evaluation (NDE), either during or post manufacturing. As a solution to NDE of AM, we are developing pulsed thermal imaging which is non-contact, one-sided, and scalable to arbitrary size and shape of the AM parts. Pulsed thermography (PT) system utilizes a high intensity flash lamp to rapidly heat surface of sample, and a high sensitivity fast-frame megapixel infrared (IR) camera to capture data of surface temperature variations. The acquired data cube consists of a stack of surface temperature images taken at different times. Information about material internal defects is extracted by analyzing the data cube. This report provides results of preliminary performance evaluation of pulsed thermal imaging capability in detection of imprinted flaws in AM metallic structures. The flaws were introduced into AM parts as imprinted hemispherical low density regions, consisting of trapped un-sintered metallic powder. Specimens for developed for this study consisted of AM stainless steel 316 and Inconel 718 plates. The diameters of imprinted defects varied from 1mm to 8mm, and their depths below the plate flat surface varied between 1mm and 6mm. Pulsed thermal tomography (PTT) processes the measured data cube to obtain 3D reconstructions of material effusivity using a unique inversion algorithm developed at Argonne. PTT has been previously used in imaging of similar size flat bottom hole (FBH) simulated defects in stainless steel 316 and Inconel 718 specimens. In the study involving AM specimens, PTT imaging results have shown that 1mm-diameter defects located 1mm and 2mm below the surface of specimens were detectable. Larger size defects were detectable at greater depth. We also explored an alternative approach to detection of material flaws in PT data cube, which is using neural learning-based approach to blind source separation. Detection of small material defects requires finding features in the data cube which have signal contrast levels approaching sensitivity limit of IR camera. In this study, an optimized Neural Learning based Blind Source Separation (NLBSS) algorithm, including Principal Component Analysis (PCA), and Independent Component Analysis (ICA) is demonstrated to automatically extract principal temporal and spatial features of thermography frames to enhance flaw detection. By using the NLBSS algorithm, material internal defects can be automatically detected. Furthermore, this processing approach compensates for experimental thermal imaging artifacts, such as noise and uneven heating. By merging artificial intelligence with phtotothermics, the NDE system detects internal calibrated defects of various sizes and depths in AM nuclear-grade metallic alloys.

36 MATERIALS SCIENCE↗

WNR Facility FP90L Visual Inspection Report

An external and internal visual inspection of FP90L was performed March 2020. This report presents the results from this visual inspection, detailing individual components and their relative location along FP90L within the WNR facility bulk shield. This report will present the data gathered from this visual inspection. Then, utilizing available facility drawings as well as LIDAR data from surveys performed in the spring/summer of 2019, this inspection data will be merged with previous efforts and studies regarding the WNR facility to document a more complete representation of the current state of WNR FP90L.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Compare linear-system solver and preconditioner stacks with emphasis on GPU performance and propose phase-2 NGP solver development pathway

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind project are Nalu-Wind, which is an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, and OpenFAST, which is a whole-turbine simulation code. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and a momentum equation for the velocity. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. In this report we evaluated GPU-performance baselines for the linear solvers in the Trilinos and hypre solver stacks using two representative Nalu-Wind simulations: an atmospheric boundary layer precursor simulation on a structured mesh, and a fixed-wing simulation using unstructured overset meshes. Both strong-scaling and weak-scaling experiments were conducted on the OLCF supercomputer Summit and similar proxy clusters. We focused on the performance of multi-threaded Gauss-Seidel and two-stage Gauss-Seidel that are extensions of classical Gauss-Seidel; of one-reduce GMRES, a communication-reducing variant of the Krylov GMRES; and algebraic multigrid methods that incorporate the afore-mentioned methods. The team has established that AMG methods are capable of solving linear systems arising from the fixed-wing overset meshes on CPU, a critical intermediate result for ExaWind FY20 Q3 and Q4 milestones. For the fixed-wing strong-scaling study (model with 3M grid-points), the team identified that Nalu-Wind simulations with the new Trilinos and hypre solvers scale to modest GPU counts, maintaining above 70% efficiency up to 6 GPUs. However, there still remain significant bottlenecks to performance: matrix assembly (hypre), AMG setup (hypre and Trilinos) In the weak-scaling experiments (going from 0.4M to 211M gridpoints), it's shown that the solver apply phases are faster on GPUs, but that Nalu-Wind simulation times grow, primarily due to the multigrid-setup process. Finally, based on the report outcomes, we propose a linear solver path-forward for the remainder of the ExaWind project. Near term, the NREL team will continue their work on GPU-based linear-system assembly. They will also investigate how the use of alternatives to the NVIDIA UVM (unified virtual memory) paradigm affects performance. Longer term, the NREL team will evaluate algorithmic performance on other types of accelerators and merge their improvements back to the main hypre repository branch. Near term, the Trilinos team will address performance bottlenecks identified in this milestone, such as implementing a GPU-based segregated momentum solve and reusing matrix graphs across linear-system assembly phases. Longer term, the Trilinos team will do detailed analysis and optimization of multigrid setup.

17 WIND ENERGY↗

Neuromorphic Processing and Sensing for Interception

Interception of a moving and potentially evading target can be a challenging problem, in particular for conditions in which the target may be moving at high speeds and difficult to detect. We have proposed to merge two Sandia LDRD efforts, the SPARR Spiking/Processing Array (neuromorphic event-driven sensing) and the Dragonfly-Inspired Algorithms for Intercept- Trajectory Planning (neural-inspired algorithms for interception) toward a unified system with direct application to national security. Neuromorphic systems demonstrate the most potential for speed and efficiency gains when communication is event-driven and computations are simple but parallelizable. Accordingly, we anticipate fully realizing potential benefits from a neuromorphic interception system if event-driven sensing is combined with processing and acting also implemented on event-driven (spiking) systems. We have successfully translated a neural-inspired interception algorithm to a neural network architecture for evaluation on neuromorphic hardware. Preliminary implementations of the neural network designed for implementation on the Loihi chip are still too immature for conclusive evaluation, but the results of this effort have demonstrated a viable path for a previously developed dragonfly-inspired interception algorithm to be implemented on neuromorphic hardware.

97 MATHEMATICS AND COMPUTING↗

Macro-physical Properties of Shallow Cumulus from Integrated ARM Observations (Final Report)

Fair-weather shallow cumuli (ShCu) play an important role in many climate-related processes. Irregular geometry of ShCu and their strong temporal and spatial variability make it challenging to observe ShCu holistically and to represent them correctly in climate models. To improve ShCu parameterizations, information on both vertically and horizontally resolved cloud properties is required. Commonly, the vertically resolved cloud properties are provided by zenith pointing lidar-radar observations with a very narrow field of view (FOV). Thus, these “pencil-beam” properties may not be representative of a larger surrounding area. Limited number of areal-averaged cloud properties, such as fractional sky cover (FSC), are offered typically by wide-FOV observations. The main goal of our project was to integrate advantages of the narrow-FOV (vertical structure of clouds) and wide-FOV (spatial arrangement of clouds) observations for an improved characterization of single-layer ShCu observed at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for an 18-yr period (2000-2017). There are four major accomplishments of our project, First, an updated operational cloud classification for days with ShCu has been suggested and evaluated through a detailed comparison with the manually curated records. Our classification extends successfully the latest ARM cloud type Value Added Product (VAP) based on the Active Remote Sensing of Clouds (ARSCL) cloud product by incorporating both cloud fraction (CF) provided by narrow-FOV ceilometer data and FSC from wide-FOV images offered by a Total Sky Imager (TSI). Moreover, our classification allows one to identify impact of instrumentation changes at the SGP site, namely the transition to KAZRARSCL with the updated cloud radar, on the identification of periods with single-layer ShCu. Second, a new approach that resolves cloud area distributions for a given region (up to 4x4 km 2 ) has been suggested and cloud equivalent diameters (CEDs) have been estimated for the first time. These estimations have been performed over a wide range of cloud sizes (about 0.01–3.5 km) with high temporal resolution (30s) using wide-FOV TSI images and cloud base height (CBH) provided by complementary narrow-FOV lidar measurements. Our simple and computationally inexpensive approach offers a previously unavailable dataset for process studies in the convective boundary layer and evaluation of ShCu parameterizations in cloud-resolving models. Third, a long-term integrated record of ShCu macrophysical properties has been developed. The developed record represents the longest available compilation of events with ShCu and includes (i) a novel visualization of the spatial variability in cloud cover both along- and across-wind directions, (ii) updated estimates of narrow-FOV CF and wide-FOV FSC, (iii) updated narrow-FOV CBH, and (iv) complementary data, such as wind speed and direction from the 915-MHz Radar Wind Profiler (RWP) data. The developed record has been used successfully to assess conventional observational estimates of cloud cover and their sensitivity to the following two factors: (i) instrument-dependent cloud detection and data merging criteria and (ii) FOV configuration. Fourth, co-variability of the ShCu macrophysical properties and environmental parameters has been analyzed for a 3-yr period (2016-2018). Our initial analysis includes diurnal changes of FSCs obtained for clouds with small, moderate and large CEDs and several environmental parameters, such as lifted condensation level (LCL) and mixed layer height (zi). Preliminary results of our analysis suggest that the horizontal extent of ShCu is controlled substantially by the sign and magnitude of difference between these two parameters (zi-LCL): the CED tends to grow with increase of this difference (zi exceeds LCL). We have initiated relationships between the ShCu and key atmospheric parameters that control both the development and evolution of ShCu using our new data product, which combines effectively the advantages of narrow-FOV data offered by zenith pointing cloud radars and lidars and wide-FOV TSI images. While the latest instrumentation at the ARM sites may address these challenging relationships in the future, we believe that the historical ARM data at the SGP site has not yet been fully utilized. Overall, our data product can be used by researchers working on a wide range of climate-related projects. These projects may include (i) a comprehensive evaluation of outputs from the Large-Eddy Simulation (LES) and single-column models for their future improvement, (ii) the representativeness of “short-period” results obtained from the previous model and observational studies and (iii) the planning of future field campaigns with focus on improved understanding of the diurnal cycle of cumulus convection.

54 ENVIRONMENTAL SCIENCES↗

Use of Remote Sensing and In-Situ Observations to Develop and Evaluate Improved Representations of Convection and Clouds for the ACME Model

The overachieving goal of the whole CMDV-MCS project is to improve understanding of warm season continental convection and to develop treatments of convection and microphysics capable of representing mesoscale convective systems (MCSs) features in large-scale models. Our tasks for this project contributing to the overachieving goal include: (1) Improve the ice nucleation formulation for MG2 and P3 cloud microphysics schemes; (2) Improve the treatment of subgrid dynamics and thermodynamics driving the ice nucleation in E3SM; and (3) Test the performance of improved ice microphysics in E3SM with observation data. In this project, we have (1) Improved the ice nucleation parameterization for MG2 and P3 in E3SM by implementing two advanced empirical parameterizations with connection to aerosols. The two deterministic heterogeneous ice nucleation parameterizations (i.e., DeMott et al., 2015; Niemand et al., 2012) were merged with the MG2 and P3 cloud microphysics schemes in E3SM. Long-term simulations were conducted to examine the impacts of these new parameterizations on simulated cloud properties; (2) Improved the treatment of subgrid dynamics and thermodynamics driving the ice nucleation in E3SM. We evaluated the double Gaussian PDF of vertical velocity simulated by the Cloud Layers Unified By Binormals (CLUBB) and the sub-column vertical velocity sampled from the Subgrid Importance Latin Hypercube Sampler (SILHS) in E3SM. We introduced the vertical velocity variance induced by topographic gravity waves for ice nucleation and droplet activation; and (3) Tested the performance of improved ice microphysics in E3SM with observation data. We tested the new treatments of ice nucleation in the single column model (SCM) mode for the stratiform mixed-phase clouds observed during 9-10 October 2004 in the DOE ARM Mixed-Phase Arctic Cloud Experiment (M-PACE) and for the convective clouds observed on 20 May 2011 in the Midlatitude Continental Convective Clouds Experiment (MC3E). Modeled ice nucleating particles (INPs) concentrations were compared against observations collected around the globe.

54 ENVIRONMENTAL SCIENCES↗

End-to-End Differentiable Modeling and Management of the Environment

Focal Area: (2) Data acquisition and assimilation enabled by machine learning, AI, and advanced methods including experimental/network design/optimization. We emphasize the importance of leveraging optimization techniques from AI/machine learning (ML) to solve challenging problems in Earth system modeling. Science Challenge: Automatic differentiation has had a transformative effect on ML by allowing the calculation of gradients of arbitrary functions in an incredibly large class of models. We can potentially realize similar improvements in parameter estimation and control for Earth system models (ESMs) by reimplementing them in computational frameworks from ML. Practitioners working with large (>10 7 parameters) models in ML and AI can obtain good predictive performance in a range of spatiotemporal tasks by making use of optimization via stochastic gradient descent and incorporating prior knowledge at multiple levels. We propose writing ESMs in open-source computational frameworks such as Torch, Tensorflow, and JAX to greatly expand the scope of environmental forecasting and management challenges, which can be addressed by leveraging automatic differentiation and gradient descent-like algorithms. We do not call for a wholesale replacement of physical models with data-driven surrogates, but rather advocate for interleaving physical and empirical equations in a manner that is most faithful to the extent of our scientific knowledge and observational data. Central to this topic is the merging of differentiable physical simulations with differentiable optimization layers, which are now both beginning to come to the forefront.

54 ENVIRONMENTAL SCIENCES↗

Google/Makani Energy Kite Modeling (CRADA CRD-18-00569 Final Report)

In support of Makani’s energy kite development program, Makani engaged with NREL to develop, verify, and document a multiphysics engineering model of a megawatt-scale tethered energy kite (named KiteFAST). After the original development of KiteFAST was completed, Makani further engaged NREL to develop a software enhancement of KiteFAST to enable the dynamics modeling of an energy kite tethered to a floating offshore platform (named KiteFAST-OS). Before this project, the capability to model the aero-hydro-servo-elastic dynamics of an airborne wind energy (AWE) system with electricity generation on the flying device (fly gen) and crosswind flight operation did not exist. Such physics-based modeling capability is needed for loads analysis, structural design, and certification of energy kites. Throughout the project, an exclusive license kept KiteFAST and KiteFAST-OS available only to Makani, NREL, and its counterparts. With the ending of Makani, the KiteFAST and KiteFAST-OS software were merged into a single code base (named KiteFAST), the exclusive license was terminated, and the source code, documentation, and example models were released publicly.

17 WIND ENERGY↗

Summary Report of the Reactive CO 2 Capture: Process Integration for the New Carbon Economy Workshop, February 18-19, 2020

This report provides a summary of feedback from the “Reactive CO 2 Capture: Process Integration for the New Carbon Economy” workshop held February 18-19, 2020. The focus of this workshop was to discuss approaches for merging carbon dioxide (CO 2 ) capture and CO 2 conversion/utilization systems into an integrated "reactive capture" strategy. By the workshop’s definition, reactive capture (RC) of CO 2 is the coupled process of capturing CO 2 from a mixed gas stream and converting it into a valuable product without going through a purified CO 2 intermediate. Participants were able to identify four key themes and associated calls to action for the reactive capture community: (1) essential role of partnerships; (2) critical challenges; (3) defining the value proposition; and (4) approach to support technological advancement.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Summary Report of the Reactive CO 2 Capture: Process Integration for the New Carbon Economy Workshop

Decarbonization of our global economy is required to limit planetary warming to +1.5⁰C above pre-industrial levels, an ambitious goal set into motion by the Paris agreement. Given the scale and urgency, the solution demands international, cross-sector advancements spanning policy, social responsibility, and technology, with emphasis on step changes over incremental changes. To that end, technological revolutions that disrupt the status quo need to be envisioned and enacted. One potential technological revolution is the production of fuels, chemicals, and materials from carbon dioxide (CO 2 ) as the starting feedstock, leveraging renewable energy as the driving force. Over the past decades, significant research, development, and deployment has occurred on technologies for capturing CO 2 from point sources or the air and utilizing this CO 2 as a working fluid or as a chemical reactant; however, most of this work has been siloed in these two categories. Recently, an emerging field has started to explore the direct integration of CO 2 capture and conversion technologies as a means to reduce overall energy demand (i.e., avoid energy penalty of CO 2 desorption/regeneration of capture media) and capital expense through process intensification. This strategy represents an opportunity to leapfrog forward this technological revolution. However, the field is in its infancy and the technologies are at an early stage of development, thus it is critically important to define and assess the value proposition of this strategy relative to alternatives (e.g., separated capture and conversion technologies, fuels and chemicals derived from renewable feedstocks like biomass, and industrial electrification) to chart a path forward. To identify next steps, we organized a workshop titled “Reactive CO 2 Capture: Process Integration for the New Carbon Economy” which was held in Golden, Colorado, February 18–19, 2020. The focus of this workshop was to discuss approaches for merging CO 2 capture and CO 2 conversion/utilization systems into what we denoted as an integrated "reactive capture" strategy. By our definition, reactive capture of CO 2 is the coupled process of capturing CO 2 from a mixed gas stream and converting it into a valuable product without going through a purified CO 2 intermediate (see full definition in the Introduction section). This report seeks to summarize feedback from the approximately 125 participants and subject matter experts in attendance from academia, industry, U.S. Department of Energy (DOE), and DOE national laboratories. The workshop agenda is included in Appendix A and the full list of attendees can be found in Appendix B. To elucidate a path forward, we first asked the attendees to define what success would look like for reactive capture in the short term (0–5 years), midterm (5–10 years), and long term (10+ years) and then asked them to answer four questions related to how we could achieve that success: (1) What are the key barriers and challenges to success? (2) What are needed activities to overcome barriers and challenges? (3) What opportunities will arise from these activities? (4) What is a target outcome and what metrics need to be met?

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗