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Powering the Future: Fusion & Plasmas

This report provides a decade-long vision for the field of fusion energy and plasma science and presents a path to a promising future of new scientific discoveries, industrial applications, and, ultimately, the delivery of fusion energy. We identify critical areas for research and development and prioritize investments to maximize impact. The research community worked for more than a year to develop a wealth of creative ideas designed to accelerate fusion energy and advance plasma science. The effort culminated in the consensus Community Planning Process report. Our work is based heavily on that report, and we extend our sincere gratitude to our colleagues for their efforts. Following the research community’s lead, we worked through consensus to generate this report. Many ideas were heard and were thoughtfully deliberated until a shared view on each issue emerged. This process allowed us to discuss and appreciate our different points of view and come to consensus language. Ultimately, we speak with one voice in conveying a vision for a vibrant program that will bring significant benefit to society.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Integration Of PanDA Workload Management System With Supercomputers for ATLAS and Data Intensive Science

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS, one of the largest collaborations ever assembled in the sciences, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Management System for managing the workflow for all data processing on over 150 data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. While PanDA currently uses more than 250,000 cores with a peak performance of 0.3 petaFLOPS, LHC data taking runs require more resources than Grid computing can possibly provide. To alleviate these challenges, LHC experiments are engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with supercomputers in United States, Europe and Russia (in particular with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF), MIRA supercomputer at Argonne Leadership Computing Facilities (ALCF), Supercomputer at the National Research Center Kurchatov Institute , IT4 in Ostrava and others). Current approach utilizes modified PanDA pilot framework for job submission to the supercomputers batch queues and local data management, with light-weight MPI wrappers to run single threaded workloads in parallel on LCFs multi-core worker nodes. This implementation was tested with a variety of Monte-Carlo workloads on several supercomputing platforms for ALICE and ATLAS experiments and it is in full production for the ATLAS experiment since September 2015. We will present our current accomplishments with running PanDA WMS at supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications, such as bioinformatics and astro-particle physics.

Data-intensive science↗

Next Generation Workload Management System For Big Data on Heterogeneous Distributed Computing

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS and ALICE are the largest collaborations ever assembled in the sciences and are at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, both experiments rely on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Management System (WMS) for managing the workflow for all data processing on hundreds of data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. The scale is demonstrated by the following numbers: PanDA manages O(10 2 ) sites, O(10 5 ) cores, O(10 8 ) jobs per year, O(10 3 ) users, and ATLAS data volume is O(10 17 ) bytes. In 2013 we started an ambitious program to expand PanDA to all available computing resources, including opportunistic use of commercial and academic clouds and Leadership Computing Facilities (LCF). The project titled 'Next Generation Workload Management and Analysis System for Big Data' (BigPanDA) is funded by DOE ASCR and HEP. Extending PanDA to clouds and LCF presents new challenges in managing heterogeneity and supporting workflow. The BigPanDA project is underway to setup and tailor PanDA at the Oak Ridge Leadership Computing Facility (OLCF) and at the National Research Center "Kurchatov Institute" together with ALICE distributed computing and ORNL computing professionals. Our approach to integration of HPC platforms at the OLCF and elsewhere is to reuse, as much as possible, existing components of the PanDA system. Finally, we will present our current accomplishments with running the PanDA WMS at OLCF and other supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications.

97 MATHEMATICS AND COMPUTING↗

Sustaining and Extending the Open Science Grid: Science Innovation on a PetaScale Nationwide Facility (DE-FC02-06ER41436) SciDAC-2 Closeout Report

Under this SciDAC-2 grant the project’s goal w a s t o stimulate new discoveries by providing scientists with effective and dependable access to an unprecedented national distributed computational facility: the Open Science Grid (OSG). We proposed to achieve this through the work of the Open Science Grid Consortium: a unique hands-on multi-disciplinary collaboration of scientists, software developers and providers of computing resources. Together the stakeholders in this consortium sustain and use a shared distributed computing environment that transforms simulation and experimental science in the US. The OSG consortium is an open collaboration that actively engages new research communities. We operate an open facility that brings together a broad spectrum of compute, storage, and networking resources and interfaces to other cyberinfrastructures, including the US XSEDE (previously TeraGrid), the European Grids for ESciencE (EGEE), as well as campus and regional grids. We leverage middleware provided by computer science groups, facility IT support organizations, and computing programs of application communities for the benefit of consortium members and the US national CI.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Beam Dump Experiments with Photon and Electron Beams

Programs are underway to search for light dark matter (DM) with masses between 1 and 1000~MeV produced by photon and electron interactions in a beam dump. We summarize various strategies being pursued. Details are given on the Beam-Dump eXperiment (BDX) at Jefferson Lab, which will use a $\sim$1 m$^3$ segmented CsI(Tl) scintillator detector placed downstream of Hall A and accumulate 10$^{22}$ electrons-on-target (EOT) in 285 days. The dark matter signal is an electromagnetic shower of few hundreds of MeV, together with a reduced activity in the surrounding active veto counters. This experiment would be sensitive to elastic DM-electron and to inelastic DM scattering at the level of 10 counts per year, reaching the limit of the neutrino irreducible background.The proposed experiment will be sensitive to large regions of DM parameter space, exceeding the discovery potential of existing and planned experiments in the MeV-GeV DM mass range by up to two orders of magnitude.

Smith, Elton↗

Investigating Deformation and Failure Mechanisms in Nanoscale Multilayer Metallic Composites

Over the history of materials science there are many examples of materials discoveries that have made superlative materials; the strongest, lightest, or toughest material is almost always a goal when we invent new materials. However, often these have been a result of enormous trial and error approaches. A new methodology, one in which researchers design, from the atoms up, new ultra-strong materials for use in energy applications, is taking hold within the science and engineering community. This project focused on one particular new classification of materials; nanolaminate metallic composites. These materials, where two metallic materials are intimately bonded and layered over and over to form sheets or coatings, have been shown over the past decade to reach strengths over 10 times that of their constituents. However, they are not yet widely used in part because while extremely strong (they don’t permanently bend), they are also not particularly tough (they break relatively easily when notched). Our program took a coupled approach to investigating new materials systems within the laminate field. We used computational materials science to explore ways to institute new deformation mechanisms that occurred when a tri-layer, rather than the more common bi-layer system was created. Our predictions suggested that copper-nickel or copper-niobium composites (two very common bi-layer systems) with layer thicknesses on the order of 20 nm and then layered 100’s of times, would be less tough than a copper-nickel-niobium metallic composite of similar thicknesses. In particular, a particular mode of permanent deformation, cross-slip, could be activated only in the tri-layer system; the crystal structure of the other bi-layers would prohibit this particular mode of deformation. We then experimentally validated this predication using a wide range of tools. We utilized a DOE user facility, the Center for Integrated Nanotechnology (CINT), to fabricate, for the first time, these tri-layer composites. CINT formed nanolaminate composites were tested in tension, with bulge testing, using nanoindentation, and using micro-compression testing to demonstrate that the tri-layer films were indeed tougher and hardened more during deformation (they got stronger as we deformed them) than equivalent bi-layers. The seven graduate students, 4 post-docs and research faculty, and the two faculty co-PI’s were able to create a collaborated computational prediction and experimental validation team to demonstrate the benefits of this class of materials to the community. The computational work crossed from atomistic to bulk simulations, and the experiments coupled form nm-scale to the mm scale; closely matching the simulations. The simulations provided viable mechanisms that explained the observed results, and new experimental results were used to push the boundaries of the simulation tools. Over the life of the 7 years of this program we proved that tri-layer nanolaminate metallic composite systems exceeded the mechanical performance of bi-layer systems if the right materials were chosen, and that the mechanism responsible for this was tied to the cross slip of dislocations. With 30 journal publications resulting from this work we have broadly disseminated this family of results to the scientific community.

36 MATERIALS SCIENCE↗

Proposal to support the 4th international conference on nitrification and related processes (ICoN4)

The 4th International Conference on Nitrification and Related Processes (ICoN4) commencing between June 27 and July 1, 2015, at the University of Alberta in Edmonton, Alberta, Canada brings together an international collection of academic, government, and private sector researchers of the global biogeochemical nitrogen cycle to share their scientific discoveries, innovations and pertinent societal impacts. The classical understanding of “nitrification” describes the two-step transformation of ammonium to nitrite and nitrite to nitrate; however, we now know from the analysis genome sequences, the application of ‘omics technologies, microbial ecology, biogeochemistry, and microbial physiology that the transformation of ammonium is not performed by a few particular groups of microorganisms nor is it confined to oxic environments. Past ICoN meetings have explored the interconnections between ammonium- and nitrite-consuming processes in all ecosystems, the emission of greenhouse gases by these processes and their control, and the intersection between intermediates of the nitrification process and other elemental cycles; this has generated tremendous progress in our understanding of the global nitrogen cycle and it has generated excitement in the next generation of N cycle researchers. Nitrification research has a long-standing connection to the Community Science Program of the DOE. Between 1999 and 2001, the JGI generated the first genome sequence of an ammonia-oxidizing bacterium, Nitrosomonas europaea ATCC 19718, and it has subsequently sequenced, or is in the process of sequencing over 50 additional genomes from ammonia-oxidizing bacteria, nitrite-oxidizing bacteria, and ammonia-oxidizing archaea. Autotrophic ammonia- and nitrite-transforming microorganisms play also a critical role in carbon cycling and sequestration in nearly all ecosystems. Not only do they control the concentration and speciation of biologically available N to plants and other microorganisms, nitrification is also the source of the various forms of nitrogen pollution. Nitrate pollution from over-fertilization of managed soils causes eutrophication and the reduction of nitrate and nitrate also results in emission of N2O, a denitrification process that leads to the accumulation of this major greenhouse gas in the atmosphere. Anaerobic ammonia oxidation (anammox) and nitrite-driven anaerobic methane oxidation (n-DAMO) are involved in the transformation of ammonium, nitrite, and nitrate to dinitrogen without N2O as an intermediate, acting as mitigating processes to nitrification. Along with the vast international participation in the ICoN conferences, encouragement and inclusion of early career investigators and graduate students is viewed as critical to the continued success of our discipline.

42 ENGINEERING↗

DEVELOPMENT OF INEXPENSIVE HIGH TEMPERATURE NITI-BASED SHAPE MEMORY ALLOYS FOR POWDER BED ADDITIVE MANUFACTURING

NiTi and NiTi-based Shape Memory Alloys (SMA) exhibit a reversible solid-state phase transformation from martensite to austenite driven by thermal energy. High temperature (Mf>100°C) SMAs are martensite at room temperature and can be fabricated into solid-state actuators that return to a pre-programmed shape against a designed load after heating to transformation threshold. Reactive as-fabricated additively manufactured parts (4-D printing) is the current state of the art in manufacturing of SMAs but requires compositions compliant to rapid solidification. Existing actuator designs are developed from commercially available, highly investigated material compositions. However, existing high temperature high performance (high actuation strain, low thermal hysteresis) shape memory alloys contain significant (>10% at.) portions of high-cost Platinum Group Metals (PGMs). It is of significant scientific interest to investigate material compositions that are peer performing or superior to PGMs whose constituent elements represent a significant cost savings. Shape memory alloy properties vary significantly with small (0.1% at.) compositional changes making robust investigative sample sets very large. Computational material design can be deployed to shrink the compositional space of possible alloy combinations and reduce the experimental load in material discovery. Investigating shape memory effect (SME) and validating process additive process parameters for a single novel composition is cost intensive in both time and consumed materials. Additionally, sub-optimal processing, oxygen, or solidification rate sensitivity could render additively manufacturing specimens without micro, macro cracks, or significant chemical variance impossible. Unfortunately, such failure susceptibility cannot be simulated. Therefore, a research pathway to validate novel shape memory alloy compositions for powder bed fusion additive manufacturing without the need for powdered feedstock is also proposed. This research investigates novel high temperature shape memory alloys for actuators without platinum group alloying elements to discover one that could be commercially viable as an additive manufacturing feedstock.

Sundermann, Tayler↗

Realizing the scientific program with polarized ion beams at the future BNL Electron Ion Collider

Polarized ion beams at the Electron Ion Collider (EIC) are essential to address some of the most important open questions at the twenty-first century frontiers of understanding of the fundamental structure of matter. Here, in this work, we summarize the science case and identify polarized 2 H, 3 He, 6 Li, and 7 Li ion beams as critical technology that will enable experiments which address the most important science. Furthermore, we discuss the required ion polarimetry and spin manipulation at the EIC. The current EIC accelerator design is presented. We identify a significant research and development effort across national and international laboratories and universities that is required over about a decade to realize the polarized ion beams and estimate (based on previous experience) that it will require about 20 full-time equivalent (FTE) over 10 years (or a total of about 200 FTE-years) of personnel, including graduate students, postdoctoral researchers, technicians, and engineers. Attracting, educating, and training a new generation of physicists in experimental spin techniques will be essential for the successful realization. Artificial intelligence and machine learning are seen as having significant potential for both acceleration of research and development and amplification of discovery in the optimal realization of this unique quantum technology on a cutting-edge collider. The research and development effort is synergistic with research in atomic physics and fusion energy science.

43 PARTICLE ACCELERATORS↗

The Present and Future of QCD: QCD Town Meeting White Paper – An Input to the 2023 NSAC Long Range Plan

It is currently understood that there are four fundamental forces in nature: gravitational, electromagnetic, weak and strong forces. The strong force governs the interactions between quarks and gluons, elementary particles whose interactions give rise to the vast majority of visible mass in the universe. The mathematical description of the strong force is provided by the non-Abelian gauge theory Quantum Chromodynamics (QCD). While QCD is an exquisite theory, constructing the nucleons and nuclei from quarks, and furthermore explaining the behavior of quarks and gluons at all energies, remain to be complex and challenging problems. Such challenges, along with the desire to understand all visible matter at the most fundamental level, position the study of QCD as a central thrust of research in nuclear science. Experimental insight into the strong force can be gained using large particle accelerator facilities, which are necessary to probe the very short distance scales over which quarks and gluons interact. The Long Range Plans (LRPs) exercise of 1989 and 1996 led directly to the construction of two world-class facilities: the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab (JLab) that is focused on studying how the structure of hadrons emerges from QCD (cold QCD research), and the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Lab (BNL) that aims at the discovery and study of a new state of matter, the quark-gluon plasma (QGP), at extremely high temperatures (hot QCD research). These past investments have produced major advances. Nucleons and nuclei are being studied with increasing precision with a unified description of the partonic structure utilizing multi-dimensional imaging. Significant progress has been made, paving the way towards a complete picture of how quarks and gluons give rise to the mass, spin, and momentum of the nucleon. In hot QCD, the QGP is created in the collisions of nuclei at RHIC and the Large Hadron Collider (LHC) and is observed to behave like a fluid with very low specific shear viscosity; the current goals are to understand how the fluid behavior emerges from QCD and to characterize the temperature (and chemical potential) dependence of the properties of the QGP. As this White Paper is written, current experimental programs at CEBAF, RHIC and the LHC continue to provide exciting near term opportunities to capitalize on the investments in experimental equipment and accelerator operations. Most importantly, the QCD community looks forward to the construction of the Electron Ion Collider (EIC) as a major new facility to push forward QCD research in the next decades, with significant focus on exploring the properties of gluons, the mediators of the strong force.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

PNNL DataHub NIAID Program Project: Modeling Host Responses to Understand Severe Human Virus Infections, Multi-Omic Viral Dataset Catalog Collection

The National Institute of Allergy and Infectious Diseases (NIAID) "Modeling Host Responses to Understand Severe Human Virus Infections" program project was a highly integrated and comprehensive systems biology research core, funded by the National Institute of Health (U19AI106772) from 2013-06-01 to 2018-05-31, investigating the complex host response to category A, B, and C priority pathogen infections. Resulting project deliverables include an extensive comprehensive collections of linked primary and secondary transformation viral experimental infection data. Here we provide a never before released comprehensive infectious disease collection of primary and secondary transformation multi-Omics data profiling a series of priority pathogen primary experimental studies for enhanced open access to viral Omics lifecycle datasets and project metadata. Using a highly integrated and multidisciplinary approach, linked primary data and metadata supporting secondary normalization datasets, provide critical information necessary for research reproducibility and long-term preservation. Enabling on-demand data access for research community consumption and developer reuse, serves to support new mechanistic insights and discoveries into host-pathogen interactions for aiding future biohazard data preparedness efforts in emergency response to global health crises involving viral infection.

59 BASIC BIOLOGICAL SCIENCES↗

Projected Cosmological Constraints from Strongly Lensed Supernovae with the Roman Space Telescope

One of the primary mission objectives of the Roman Space Telescope is to investigate the nature of dark energy with a variety of methods. Observations of Type I supernovae (SNe Ia) will be one of the principal anchors of the Roman cosmology program through traditional luminosity distance measurements. This SNe Ia cosmology program can provide another valuable cosmological probe, without altering the strategy of the mission: time delay cosmography with gravitationally lensed supernova (SN). In this work, we forecast lensed SN cosmology constraints with the Roman Space Telescope, while providing useful tools for future work. Using the anticipated characteristics of the Roman SNe Ia survey, we have constructed mock catalogs of expected resolved lensing systems, as well as strongly lensed Type Ia and core-collapse (CC) SN light curves, including microlensing effects. We predict Roman will find ~11 lensed SNe Ia and ~20 CCSNe, depending on the survey strategy. Next, we estimate the time delay precision obtainable with Roman (Ia: ~2 days, CC: ~3 days), and use a Fisher matrix analysis to derive projected constraints on H 0 ,Ω m , and the dark energy equation of state, w, for each SNe Ia survey strategy. Here, a strategy optimized for the discovery of high-redshift SNe Ia is preferred when considering the constraints possible from both SNe Ia and lensed SN cosmology, also delivering ~1.5 times more lensed SNe than other proposed survey strategies.

79 ASTRONOMY AND ASTROPHYSICS↗

Probing Naturalness with Searches for Supersymmetric Higgs Partners at the Large Hadron Collider

The discovery of the Higgs boson at the Large Hadron Collider completed the standard model of particle physics and led to the 2013 Nobel Prize. While it has been extremely successful in describing a wide variety of phenomena, the standard model cannot be the final theory of nature because it is unable to explain why the Higgs boson mass lies at the electroweak scale rather than 16 orders of magnitude larger at the Planck scale, a theoretical flaw known as the ``hierarchy problem.'' Supersymmetry is a standard model extension that could provide a natural solution to the hierarchy problem by introducing light supersymmetric Higgs partners. This proposal focused on searches that are sensitive to supersymmetric Higgs partners in data collected by the ATLAS experiment, which were carried out by the University of Illinois high-energy physics group led by PI Ben Hooberman as part of his Department of Energy Early Career Research Program award from 2017-2023. The searches were complemented by improvements to particle identification algorithms and the ATLAS trigger system that extend the sensitivity of future supersymmetry searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Discovery of a selective catalytic p300/CBP inhibitor that targets lineage-specific tumours

The dynamic and reversible acetylation of proteins, catalysed by histone acetyltransferases (HATs) and histone deacetylases (HDACs), is a major epigenetic regulatory mechanism of gene transcription1 and is associated with multiple diseases. Histone deacetylase inhibitors are currently approved to treat certain cancers, but progress on the development of drug-like histone actyltransferase inhibitors has lagged behind2. The histone acetyltransferase paralogues p300 and CREB-binding protein (CBP) are key transcriptional co-activators that are essential for a multitude of cellular processes, and have also been implicated in human pathological conditions (including cancer3). Current inhibitors of the p300 and CBP histone acetyltransferase domains, including natural products4, bi-substrate analogues5 and the widely used small molecule C6466,7, lack potency or selectivity. Here, we describe A-485, a potent, selective and drug-like catalytic inhibitor of p300 and CBP. We present a high resolution (1.95 Å) co-crystal structure of a small molecule bound to the catalytic active site of p300 and demonstrate that A-485 competes with acetyl coenzyme A (acetyl-CoA). A-485 selectively inhibited proliferation in lineage-specific tumour types, including several haematological malignancies and androgen receptor-positive prostate cancer. A-485 inhibited the androgen receptor transcriptional program in both androgen-sensitive and castration-resistant prostate cancer and inhibited tumour growth in a castration-resistant xenograft model. These results demonstrate the feasibility of using small molecule inhibitors to selectively target the catalytic activity of histone acetyltransferases, which may provide effective treatments for transcriptional activator-driven malignancies and diseases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Results of a search for γ Dor and δ SCT stars with the Kepler spacecraft

The light curves of 2768 stars with effective temperatures and surface gravities placing them near the gamma Doradus (γ Dor)/delta Scuti (δ Sct) instability region were observed as part of the Kepler Guest Observer program from Cycles 1 through 5. The light curves were analyzed in a uniform manner to search for γ Dor, δ Sct, and hybrid star pulsations. The γ Dor, δ Sct, and hybrid star pulsations extend asteroseismology to stars slightly more massive (1.4–2.5 M{sub ⊙}) than our Sun. We find 207 γ Dor, 84 δ Sct, and 32 hybrid candidate stars. Many of these stars are cooler than the red edge of the γ Dor instability strip as determined from ground-based observations made before Kepler. A few of our γ Dor candidate stars lie on the hot side of the ground-based γ Dor instability strip. The hybrid candidate stars cover the entire region between 6200 K and the blue edge of the ground-based δ Sct instability strip. None of our candidate stars are hotter than the hot edge of the ground-based δ Sct instability strip. Our discoveries, coupled with the work of others, show that Kepler has discovered over 2000 γ Dor, δ Sct, and hybrid star candidates in the 116 square degree Kepler field of view. We found relatively few variable stars fainter than magnitude 15, which may be because they are far enough away to lie between spiral arms in our Galaxy, where there would be fewer stars.

79 ASTRONOMY AND ASTROPHYSICS↗

Dealing with Historical Discrepancies: The Recovery of National Research Experiment (NRX) Reactor Fuel Rods at Chalk River Laboratories (CRL) - 13324

Following the 1952 National Research Experiment (NRX) Reactor accident, fuel rods which had short irradiation histories were 'temporarily' buried in wooden boxes at the 'disposal grounds' during the cleanup effort. The Nuclear Legacy Liabilities Program (NLLP), funded by Natural Resources Canada (NRCan), strategically retrieves legacy waste and restores lands affected by Atomic Energy of Canada Limited (AECL) early operations. Thus under this program the recovery of still buried NRX reactor fuel rods and their relocation to modern fuel storage was identified as a priority. A suspect inventory of NRX fuels was compiled from historical records and various research activities. Site characterization in 2005 verified the physical location of the fuel rods and determined the wooden boxes they were buried in had degraded such that the fuel rods were in direct contact with the soil. The fuel rods were recovered and transferred to a modern fuel storage facility in 2007. Recovered identification tags and measured radiation fields were used to identify the inventory of these fuels. During the retrieval activity, a discrepancy was discovered between the anticipated number of fuel rods and the number found during the retrieval. A total of 32 fuel rods and cans of cut end pieces were recovered from the specified site, which was greater than the anticipated 19 fuel rods and cans. This discovery delayed the completion of the project, increased the associated costs, and required more than anticipated storage space in the modern fuel storage facility. A number of lessons learned were identified following completion of this project, the most significant of which was the potential for discrepancies within the historical records. Historical discrepancies are more likely to be resolved by comprehensive historical record searches and site characterizations. It was also recommended that a complete review of the wastes generated, and the total affected lands as a result of this historic 1952 NRX accident be undertaken. These lessons and recommendations have lead to changes in how the NLLP is executed in the CRL waste management areas. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Fabrication and test of a 6-tesla-class high-temperature superconducting dipole magnet at 4.2 K

Superconducting magnets enable energy-frontier accelerators by generating strong magnetic fields to steer and focus the particles. Although high-temperature superconductors such as REBa 2 Cu 3 O x (, RE = rare earth) hold a strong potential for generating a higher magnetic field than Nb-Ti and Nb 3 Sn , the associated magnet and conductor technology for accelerator applications is still in its infancy. The U.S. Magnet Development Program is developing magnet technology in collaboration with industry. Here we report an experiment of making a dipole magnet called C3 using commercial high-temperature superconducting wires. The magnet, following a canted cos θ design, generated a dipole field of 5.99 T at 4.2 K in its clear aperture of 65 mm at 6.795 kA when a resistive voltage of 105 μ V appeared across one of the coils in the magnet. The stored energy was 53 kJ at the peak field. The magnet showed no degradation in the current-carrying capability at 4.2 K after the thermal cycle. We report on the detailed design, fabrication, and performance of the C3 magnet that can be of interest to potential users of this emerging technology. We also discuss issues and research needs to inform future magnet development. The experiment represented another step to addressing if the high-temperature superconducting accelerator magnet technology can increase the discovery capability of future particle accelerators.

Abraimov, Dmytro [National High Magnetic Field Lab↗

Basic Research Needs for Inverse Methods for Complex Systems under Uncertainty

Inverse problems, which aim to infer unknown properties of a system using experimental and observational data, are central to addressing many of the U.S. Department of Energy’s (DOE) most critical scientific and engineering challenges. Accurate, computationally efficient, and data-efficient solutions to inverse problems are essential for advancing DOE mission-critical science drivers, including analyzing data from large-scale experimental facilities, optimizing fusion reactor performance, accelerating materials discovery, enhancing geophysical imaging, improving wildfire predictions, and enabling autonomous systems and digital twins. However, these problems are becoming increasingly complex, often involving nonlinear, highdimensional, and interconnected systems and models that span multiple physics and scales, while relying on data with varying quantity, quality, and information content. Compounding these challenges is the uncertainty inherent in DOE-relevant systems, where errors in inputs, noise in data, incompleteness of data, and discrepancies between models and reality constrain the accuracy and precision of solutions. At the same time, the convergence of recent scientific computing trends—scientific machine learning, artificial intelligence, and computing advances such as exascale computing—is creating unprecedented opportunities for tackling these challenges. The cross-cutting nature of inverse problems, combined with their growing complexity and rapidly evolving data and algorithmic demands, strongly motivates the formulation of a prioritized research agenda to maximize their capabilities and impact. In response to this need, DOE’s Advanced Scientific Computing Research (ASCR) program in the Office of Science convened the Workshop on Basic Research Needs for Inverse Problems for Complex Systems Under Uncertainty in June 2025. This workshop brought together experts across disciplines to identify grand challenges and major opportunities in the field. Through collaborative discussions, the workshop defined transformative research directions aimed at addressing the mathematical, statistical, and computational challenges posed by inverse problems under uncertainty. As a result of these efforts, four priority research directions (PRDs) were identified to guide future research and development in this area. These PRDs, summarized below, represent a roadmap for advancing the foundational science and mathematics of inverse problems, enabling robust, scalable, and uncertainty-aware solutions that are critical for DOE applications.

97 MATHEMATICS AND COMPUTING↗