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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Design of an Out-Of-Pile Experimental Facility to Demonstrate the Feasibility of In Situ Thermal Conductivity Measurements of Nuclear Fuels Under Irradiation

There is substantial merit in quantifying nuclear fuel performance under irradiation. At Oak Ridge National Laboratory (ORNL), the MiniFuel irradiation platform has become the primary test vehicle for conducting separate-effects fuel performance irradiation experiments. The MiniFuel experiment is a passively controlled capsule design deployed in the High Flux Isotope Reactor (HFIR) through which fuel performance data is collected post-irradiation. Separate effects fuels irradiation capabilities are being expanded at ORNL by developing instrumented capsule designs that aim to capture fuel performance phenomena in-situ. One such capsule will specifically target fuel specimen thermal conductivity changes as a function of fuel burnup. Due to the complexity of making this measurement on nuclear fuel in-pile, this paper describes the necessary out-of-pile testing conducted on the thermal conductivity capsule (TCC) design. The measurement is ascertained via a thermopile system with heat transferred unidirectionally through a surrogate fuel specimen sandwiched between two conductive materials. The capsules investigated in this study are representative of the in-pile design, with the primary departure from irradiation conditions being the distribution of heat generation within the capsule. In the out-of-pile experiment, an external heater was used to drive heat through the conductive slug materials and into the specimen. This paper expounds the design of the out-of-pile experimental system and the thermal conductivity measurement technique. Predictive models used to determine the sensitivity of the measurement to variables governing thermal contact conductance between the specimen and slug materials and to predict experimental results are also described. Data from the out-of-pile experiment will be used to validate the readiness of the design for insertion into HFIR for irradiation.

Parker, Trevor [ORNL]↗
DOE OSTI2025

Characterization of MC&A for the Molten Salt Fuel Cycle

Advanced reactor developers are exploring diverse reactor designs, including molten salt reactors (MSRs). These advanced reactors are considered for wider applications and a range of deployment locations, including supporting the integration of renewable energy sources in the grid. There are three main types of MSRs: (1) reactors in which the fuel salt freely circulates within the core; (2) reactors with the fuel salt contained within vented fuel tubes; and (3) reactors that use molten salt solely as a coolant, with the fuel in a separate, solid form. In this document, the term MSR refers specifically to the first two types, which use fuel salt—special nuclear material (enriched uranium, plutonium, and 233 U) in chloride or fluoride form mixed with chloride- or fluoride-based carrier salt in a peritectic mixture—as the primary medium for fission. The composition of fuel salt, both at startup and for makeup or refueling, varies depending on the MSR design and the chosen fuel cycle approach, which can be either once-through or closed. For MSRs, a variety of fuel cycle approaches (e.g., U, U–Pu, U–Pu–TRU, U–Th, U–Pu–Th) are being considered. Fuel in MSRs is much different than traditional solid fuel, including its preparation. The uniqueness warrants investigation into characterizing fuel preparation processes, known as fuel salt synthesis . This effort characterized major fuel preparation and synthesis processes, identifying temperature, equipment, and environmental requirements for uranium-, plutonium-, and thorium-based fuel preparation and synthesis. Because MSR fuel salt synthesis facilities handle special nuclear material in loose, bulk form, a material control and accounting plan will be required for licensing from the US Nuclear Regulatory Commission or under the US Department of Energy authorization. This effort serves as a foundation to investigate material control and accounting approaches for synthesis facilities, including determining measurement points and techniques. Because several MSR developers are planning demonstration facilities in the coming years, this effort will support stakeholders with preparing or reviewing material control and accounting plans for providing assurance that all special nuclear material is accounted for at fuel salt synthesis facilities. This report was produced for Materials Protection, Accounting, and Control Technologies (MPACT) program under the US Department of Energy (DOE), Office of Nuclear Energy, Nuclear Fuel Cycle and Supply Chain.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Inference as a Service for HEP & NP experiments

This work presents how American Science Cloud resources and services can accelerate scientific discovery across large-scale HEP & NP experiments. Our demonstrators include use cases from intensity and energy frontiers. This is a first end-to-end multi-experiment, multi-facility demonstration of AmSC platforms.

Bhattacharya, M. [Fermilab]↗
DOE OSTI2026

Cost Competitive Process of Battery Grade Oxides Preparation from Aged LIBs

The increasing demand for lithium-ion batteries (LIBs) is driving development of advanced recycling and refining methods. In this project, new cathode active materials are prepared from recycled lithium battery materials and subsequently electrochemically evaluated in coin cells. In detail, scrap LIBs were mechanically processed into a metal rich black mass, then reductive acid leached into an aqueous metal solution, and finally high-purity metal hydroxide precursor materials were prepared by selective electrochemical flow precipitation. Closed-loop LIB recycling into active electrode materials will enable US manufacturers to break their reliance on foreign sources of critical materials. For example, electroextraction process used here has potential to significantly reduce chemical & water use as well as waste production as compared to traditional metallurgic techniques. To this end, electroextracted materials refined from used batteries were collected and processed to be tested as precursor cathode active material (pCAM). For this project, two samples of high purity recycled NMC hydroxide (~1 kg each) were received from N th Cycle’s Ohio demonstration facility. The NMC compositions of the two materials are similar, and the levels of impurities have been confirmed. Indeed, impurities like copper, boron and sodium are present in quantities that could negatively impact battery performance. However, some studies have demonstrated that the control of the quantity of elements like copper or boron may improve the electrochemistry properties of Lithium-NMC batteries. The principal objective is to determine the electrochemical performance of these 2 NMC hydroxide batches and clearly determine the effect of the impurities on the performance.

25 ENERGY STORAGE↗
DOE OSTI2025

The Staged, Pressurized Oxy-Combustion Technology: Status and Application to Boiler Retrofits to Yield Carbon-Negative Power via Biomass

Recognizing the benefits of pressurization and fuel staging on the efficiency of oxy-combustion, the staged, pressurized oxy-combustion (SPOC) process was introduced in 2012. The combination of fuel staging and pressurized oxy-combustion results in a more compact plant, a higher plant efficiency and reduced costs for pollutant and greenhouse gas removal compared with plants equipped with conventional carbon capture. This approach to power generation enables a modular boiler design and optimizes the plant for flexible operation, which is essential to meet the demands of the modern grid when it contains intermittent power sources. Originally designed to burn coal, the SPOC process is well-suited for biomass because the combustion of biomass leads to a high moisture content in the flue gas and the SPOC process is able to recover the latent heat of this moisture, enhancing system performance over that of traditional biomass combustion at atmospheric pressure. The present work is focused on evaluating the potential for utilizing the SPOC process in retrofit applications wherein the boilers of an existing plant are replaced with the SPOC process, and woody biomass is used as the fuel to yield carbon-negative power. Two applications are considered: power generation and cogeneration (heat and power). Modeling these systems in Aspen Plus demonstrates that the SPOC process surpasses the performance of baseline plants with post-combustion capture (PCC) for both power generation and cogeneration. Specifically, compared to a PCC equipped plant, the SPOC power plant has 33% higher efficiency, and the SPOC cogeneration plant reaches 42% higher net energy. Experimentally, the existing SPOC facility was fired for the first time with 100% biomass and after minor improvements were made to the feeding system, the facility demonstrated excellent performance during startup, steady-state operation and turndown.

Carbon capture and storage↗
DOE OSTI2025

New physics at the Muon (Synchrotron) Ion Collider: MuSIC for several scales

A Muon (Synchrotron) Ion Collider (MuSIC) can be the successor to the Electron-Ion Collider at Brookhaven National Laboratory, as well as the ideal demonstrator facility for a future multi-TeV Muon Collider. Besides its rich nuclear physics and Standard Model particle physics programs, in this work we show that the MuSIC with a TeV-scale muon beam offers also a unique opportunity to probe New Physics. In particular, the relevant searches have the potential to surpass current experimental limits and explore new regimes of the parameter space for a variety of Beyond the Standard Model scenarios including: lepton-flavor violating leptoquarks, muonphilic vector boson interactions, axion-like particles coupling to photons, and heavy sterile neutrinos. Depending on the particular case, the sensitivity of the searches in the MuSIC may span a wide range of energy scales, namely from sub-GeV particles to the few TeV New Physics mediators. Our analysis demonstrates that the MuSIC can strike a powerful chord in the search for New Physics, thanks to unique combination of features that amplify its capabilities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Myna: Connecting powder bed fusion build data to simulation tools for digital twin applications

Additive manufacturing (AM), as a digital process, can generate a detailed digital thread linking a part’s design and manufacturing to its operational performance. As AM systems advance, an increasing amount of process data is stored in manufacturing databases. In principle, this data can be utilized by simulation-based digital twin approaches, such as real-time process control and asynchronous post-processing guidance. However, few tools currently exist for systematically integrating digital thread data with computational tools. Here, in this study, we propose a software package, called Myna, for connecting data from powder bed fusion processes to simulation tools. The utility of such a platform is demonstrated using build data from the Oak Ridge National Laboratory Manufacturing Demonstration Facility “Peregrine v2023-10” public dataset to automatically configure and run 54 semi-analytical 3DThesis melt pool simulations, 78 numerical Additive FOAM melt pool simulations, and 3 ExaCA microstructure simulations. The simulated, spatially registered microstructures are then compared directly with electron backscatter diffraction characterization of the corresponding as-built part locations. The resulting simulated microstructure showed variation as a function of process parameters, particularly stripe width; however, the experimental data had little variation between the microstructure texture and grain size resulting from different processing conditions. Analysis of the discrepancies suggest that it is possible a two-phase ferritic-austenitic solidification model is needed to accurately predict grain size and texture for certain stainless steel 316L feedstock compositions under powder bed fusion conditions, providing direction for future research. As illustrated here, due to the number and complexity of the simulations involved in AM process-structure–property predictions, automated methods to connect process data and simulations will remain necessary tools for testing hypotheses and implementing digital twin applications.

Knapp, Gerald L. [Oak Ridge National Laboratory (O↗
DOE OSTI2026

A 24-channel ultra-low-noise preamplifier for dN/dx measurements with drift tube detectors

Cluster counting $(dN/dx)$ is a promising method to enhance particle identification for gaseous detectors, especially in next-generation collider experiments like the FCC-ee, where good $π/K$ separation over a broad momentum range is essential. However, its implementation in large-scale systems has been limited by the challenging requirements for high-resolution signal amplification and readout. This paper presents a 24-channel ultra-low-noise preamplifier board designed for drift tube detectors to enable $dN/dx$ measurements. The three-stage amplification topology employs SiGe transistors and integrates dedicated noise-minimization techniques, achieving a charge gain of 21.11 mV/fC from 0.3 fC to 50 fC, a bandwidth of 542 MHz, and a voltage gain of 47.8 dB. The measured voltage noise density is 0.35 nV/$\sqrt{\textrm{Hz}}$ , surpassing most of the state-of-the-art preamplifiers for gaseous and silicon detectors. Validation tests conducted on the sMDT chambers at the CERN Proton Synchrotron test beam facility demonstrate that the proposed design meets the stringent preamplifier requirements for implementing the $dN/dx$ method in drift-tube detector systems, achieving an equivalent noise charge of 0.14 fC and a signal-to-noise ratio of 73 when operated with a He:iC 4 H 10 (90:10) gas mixture. The design also shows promise for broader application in other gaseous or semiconductor detectors.

Drift tube detector↗
DOE OSTI2026

Electro-chemo-mechanically Driven Ni Exsolution from (Pr,Ce,Ni)O 2−δ : Controlled Nucleation Density and Enhanced Electrode Kinetics

In situ exsolution of metal nanoparticles is a promising strategy to prepare electrocatalysts with enhanced activity and resistance to agglomeration for efficient chemical transformations and energy conversion. Achieving a high nucleation density of nanoparticles under mild conditions and understanding how to tailor the process is important for performance of these electrodes in electrochemical cells. In this work, we demonstrate facile exsolution of Ni nanoparticles using fluorite-structured (Pr,Ce)O 2−δ as the support oxide, driven by electrochemical potential and aided by the metastability of Ni in the solid solution (elastic driving force). We prepare single-phase oriented thin films of (Pr,Ce,Ni)O 2−δ (NPCO) on (Zr,Y)O 2−δ (YSZ) substrates by pulsed laser deposition. With the aid of a high-throughput electrochemical cell that provides a lateral gradient in Nernst voltage, we apply in situ near-ambient pressure synchrotron X-ray photoelectron spectroscopy and ex situ atomic force microscopy to investigate the impact of electrochemical potential on Ni nucleation density. We find that metallic Ni can be successfully exsolved at 550 °C upon cathodic biasing in 20 mTorr O 2 , and its nucleation density increases with increasing electrochemical driving force/decreasing oxygen chemical potential. We further evaluate the electrochemical performance under highly reducing (fuel electrode) conditions by electrochemical impedance spectroscopy. With the exsolved Ni nanoparticles, the surface exchange coefficient of the NPCO is found to be ∼4× higher than for PCO without exsolution. This work confirms mixed conducting fluorites as beneficial host lattices for facile transition-metal exsolution and suggests the possibility for constructing an all ceria-based electrochemical cell with PCO serving as both the cathode and the anode.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Rotation of electrothermal-instability-driven overheating structure due to helically oriented surface magnetic field on a high-current-density aluminum rod

Experiments on the 1-MA, 100-ns-rise-time Mykonos Facility demonstrate rotation of electrothermal instability (ETI)-driven overheating structure on 1.00-mm-diameter, 10-nm-surface roughness, 99.999%-pure aluminum rods, which are pulsed with helically polarized surface magnetic field. Rods are machined to include pairs of 10-micron-scale quasi-hemispherical voids or “engineered defects (ED)” which provide the dominant current density perturbation from which ETI grows most rapidly. Experiments include an axial magnetic field component through the addition of a helically wound return-current electrode or “helical return can (HRC).” For a given HRC design, azimuthal field (B ɵ ) and axial field (B z ) components rise at a prescribed and fixed ratio, driving an increasing magnetic field of constant polarization at the rod's surface; most experiments generated surface magnetic field at a 15-degree field polarization angle (from horizontal) defined as ɸ B = arctan(B z /B ɵ ). ETI-driven emission patterns from individual ED are observed to rotate along ɸ B , while emission patterns from dielectric-coated ED pairs are shown to elongate and preferentially merge along ɸ B , in qualitative agreement with 3D-magnetohydrodynamic simulations. These data strongly support that for a randomized distribution of current density perturbations on a high-current density conductor, nearby perturbations will favorably merge about ɸ B , with the degree of merging increasing with current. Such observations offer fundamental new understanding of the seeding mechanisms of the helical magneto-Rayleigh Taylor (MRT) instabilities observed from axially magnetized magnetically driven imploding liners.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

A New 1D Model for Thermal Mixing and Stratification in Advanced Reactor Transients

Thermal mixing and stratification in large pools and enclosures play a critical role in the safety and performance of pool-type nuclear reactors, particularly during transient scenarios involving significant temperature differences between incoming and bulk coolant. Accurate modeling of these phenomena is essential for predicting system behavior and supporting passive safety features such as natural circulation. Here, this paper presents a new 1D model for thermal mixing and stratification, developed and implemented in the SAM code. The model represents a large pool as 1D coolant jet channels and zero-dimensional bulk pool volumes, enabling the simulation of a wide range of flow configurations, including hot and cold jet interactions, stratified layers, and the influence of complex geometries such as ceilings, free surfaces, and internal obstacles. Heat exchange between jet and pool regions is governed by closure relations calibrated against 3D computational fluid dynamics (CFD) simulations. The model improves upon earlier approaches by incorporating time-dependent jet characteristics and capturing the associated delay effects more accurately. Code-to-code comparisons and validation against experimental data from the Thermal Stratification Test Facility demonstrate the model’s accuracy and flexibility. This work offers two key contributions: (1) an efficient and robust method for simulating thermal mixing and stratification at the system level, eliminating the need for external coupling between system analysis codes and CFD, and (2) a significant enhancement of SAM’s capabilities to analyze thermal stratification phenomena in advanced reactor systems.

SAM↗
DOE OSTI2025

Computational Modeling of a 3D Printed Recuperator and Subsequent Experimental Loop for Supercritical Carbon Dioxide Cycles

Oak Ridge National Laboratory (ORNL), in collaboration with mechanical-thermal energy storage (mTES) provider EarthEn, a US Department of Energy (DOE) Lab-Embedded Entrepreneurship Program (LEEP) recipient at ORNL’s Innovation Crossroads 2023, is utilizing a state-of-the-art patented 3D printing technique to design an additively manufactured (AM) supercritical CO2 (sCO2) recuperator (REC) for EarthEn’s charge/discharge cycle. The AM REC will be printed at ORNL’s Manufacturing Demonstration Facility using Inconel Alloy 718 and tested on a closed-loop, ∼100 kW scale experimental facility that is under construction. The testing will compare the printed design against a commercial-off-the-shelf Printed Circuit Heat Exchanger (PCHE) REC. The design of the sCO2 facility is guided by a Modelica-based system model which is primarily dependent on the open-source TRANSFORM library developed at ORNL and uses the open-source CoolProp library for thermophysical properties of sCO2 via the External Media library. It is envisioned that an iterative process will be followed between the physical loop and the system model wherein the initial experimental data will be used to tune the model, which in turn will be used to guide future loop operation. Simultaneously, the AM REC is being designed using computer-aided design models, and it is also being analyzed for hydraulic and thermomechanical response using commercial computational fluid dynamics software, Simcenter STAR-CCM+, on highperformance computing resources.1

See, Nate [ORNL] (ORCID:0000000178581202)↗
DOE OSTI2025

X-ray Computed Tomography Data of Dense Metallic Components

The data shared in here are X-ray computed tomography (XCT) scans of a hexagonal fuel nozzle in 3 sections with the Metrotom 800 system at the Manufacturing Demonstration Facility (MDF) at Oak Ridge National Laboratory. The data are used in the paper "Tomographic Sparse View Selection using the View Covariance Loss, by Lin et al. (doi:10.1109/TPAMI.2025.36000720), accepted to the international conference on computational imaging (ICCP 2025). Figures 4-7 in the paper describe the part/XCT scan. File name Descriptions: Bottom section: TCR- Single Channeled SRC L 2019-3-18 12-26-41.hdf5 Medium section: TCR- Single Channeled SRC M 2019-3-18 13-8-9.hdf5 Top section: TCR- Single Channeled SRC T 2019-3-18 13-45-39.hdf5 Each hdf5 file contains projection data, and all the relevant X-ray CT scan setting. The full list of included attributes: distance_unit: Units of all distances specified angle_unit : Units of the angles angles: Array of all angles used voxel_size_xy: Baseline recon (if any) has this voxel size in the in-plane direction voxel_size_z: Baseline recon (if any) has this voxel size in the cross-plane direction det_pixel_size_col: Size of the detector pixels in the column dimension det_pixel_size_row: Size of the detector pixels in the row dimension src_iso_dist: Source to iso-center distance iso_det_dist: Iso-center to detector distance det_angle: If the detector is rotated/tilted, this angle corresponds to that value det_row_offset: Center of rotation offset in the vertical direction det_col_offset: Center of rotation offset in the horizontal direction reconstruction: A baseline reconstruction stored as 3D array BHC params: Beam-hardening parameters - Van De Casteel Model - if it has been used to pre-process the projections We also provided a python script (hdf_io.py) that allows the user to read the relevant data from each hdf5 file.

Ziabari, Amir [Oak Ridge National Laboratory]↗
DOE OSTI2025

In-Situ Process Monitoring Evaluation and Demonstration using Advanced Characterization with Laser Powder Bed Systems

Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with EOS Group to evaluate the current in-situ sensor capabilities of an EOS M290 Laser Powder Bed Fusion machine. The M290 was fitted with a 1 Mega-Pixel (MP) grayscale visible-light camera and a 5 MP temporally integrated (TI) near-infrared (NIR) camera. One print from stainless steel (SS) 316 and two from Inconel 625 (IN625) were performed where data including in-situ imaging and a machine log file were captured. These data were subsequently analyzed using a Dynamic Multi-Scale Segmentation Convolutional Neural Network (DMSCNN) trained on user defined classes and correlated to as-printed flaws, in the form of porosity, discovered in X-Ray Computed Tomography (XCT). In Phase I, two indications were detected in-situ and spatially correlated to stochastic lack-of-fusion flaws discovered using XCT. In Phase II, using these links from in-situ signatures to XCT flaw populations, a second neural network (NN) was trained to create a Voxelized Property Prediction Model (VPPM) to predict porosity percentages within the part using only features garnered from the in-situ data from two IN625 complex geometries. The VPPM was able to accurately predict porosity values for IN625 parts with an R 2 value of 0.764.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Additive Manufacturing of Leak-Free Metal Components with Thin Walls and Sealing Surfaces

Laser-powder bed fusion (L-PBF) offers the ability to print free form design components which often do not require post-processing. However, challenges arise when printing small geometries with mating surfaces. Using an AddUp FormUp 350 L-PBF machine installed at the Manufacturing Demonstration Facility (MDF) of Oak Ridge National Laboratory (ORNL), a User Agreement project was formed with intent to manufacture metal leak-free cylindrical sealing surfaces. One print of twelve 12.7mm outer diameter (OD) cylinders was designed varying wall thickness in the computer-aided design (CAD) model. A build plate was successfully printed but included two build pauses each adding about five minutes per layer. The build plate of 12 cylinders was removed from the chamber and shipped to the partner.

36 MATERIALS SCIENCE↗
DOE OSTI2025

In-Situ Process Monitoring Evaluation and Demonstration using Advanced Characterization with Laser Powder Bed Systems

Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with EOS Group to evaluate the current in-situ sensor capabilities of an EOS M290 Laser Powder Bed Fusion machine. The M290 was fitted with a 1 Mega-Pixel (MP) grayscale visible-light camera and a 5 MP temporally integrated (TI) near-infrared (NIR) camera. One print from stainless steel (SS) 316 and two from Inconel 625 (IN625) were performed where data including in-situ imaging and a machine log file were captured. These data were subsequently analyzed using a Dynamic Multi-Scale Segmentation Convolutional Neural Network (DMSCNN) trained on user defined classes and correlated to as-printed flaws, in the form of porosity, discovered in X-Ray Computed Tomography (XCT). In Phase I, two indications were detected in-situ and spatially correlated to stochastic lack-of-fusion flaws discovered using XCT. In Phase II, using these links from in-situ signatures to XCT flaw populations, a second neural network (NN) was trained to create a Voxelized Property Prediction Model (VPPM) to predict porosity percentages within the part using only features garnered from the in-situ data from two IN625 complex geometries. The VPPM was able to accurately predict porosity values for IN625 parts with an R 2 value of 0.764.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Quantum Computing Strategy 2026

Quantum computing (QC) is a rapidly maturing technology with the potential for revolutionary impacts on stockpile stewardship science and national security. Recent developments in fault-tolerant architectures have compressed vendor roadmaps, and predictions of a production-ready quantum computer by the mid-2030s are becoming increasingly credible. This strategy provides a roadmap for integrating QC into the Advanced Simulation and Computing (ASC) program by investing in four strategic focus areas: 1. Develop Capabilities in Mission-Relevant Quantum Applications: ASC will prioritize developing quantum-ready applications in mission areas that have shown significant promise for quantum advantage, including simulations of materials in extreme environments, nuclear dynamics, solving linear and nonlinear partial differential equations, and uncertainty quantification. These applications directly support stockpile stewardship science and modernization objectives. 2. Conduct R&D in Algorithms, Software, and Hardware: Sustained research into quantum algorithms, robust software tools, and quantum hardware is essential. ASC will develop efficient quantum algorithms; invest in quantum compilers, debuggers, and performance tools; and explore specialized quantum hardware tailored to NNSA’s unique requirements. 3. Engage with Vendors and Partners: Early and active collaboration with commercial quantum hardware vendors and academic partners is critical. Through testbeds, co-design agreements, and quantum demonstration facilities, ASC will influence hardware design, gain early access to emerging technologies, and ensure that quantum platforms evolve to meet mission needs. 4. Build Knowledge, Experience, and Workforce: Expanding and upskilling the quantum-trained workforce is essential to long-term success. This includes hiring, internal training, university outreach, and postdoctoral support to ensure ASC maintains the expertise required to operate, program, and integrate quantum systems as they become available. While quantum computing will never replace classical computing, it has the potential to solve certain problems with speed and accuracy that would be unachievable using any conceivable classical high-performance computing (HPC) system. By investing strategically in QC, ASC will help propel the emergent QC industry, maintain U.S. technological leadership, ensure mission readiness, and position itself to rapidly adopt quantum technologies as they mature.

97 MATHEMATICS AND COMPUTING↗