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DOE OSTI2022

Single electrons on solid neon as a solid-state qubit platform

Progress towards the realization of quantum computers requires persistent advances in their constituent building blocks-qubits. Novel qubit platforms that simultaneously embody long coherence, fast operation and large scalability offer compelling advantages in the construction of quantum computers and many other quantum information systems 1-3 . Electrons, ubiquitous elementary particles of non-zero charge, spin and mass, have commonly been perceived as paradigmatic local quantum information carriers. Despite superior controllability and configurability, their practical performance as qubits through either motional or spin states depends critically on their material environment 3-5 . In this work, we report our experimental realization of a qubit platform based on isolated single electrons trapped on an ultraclean solid neon surface in vacuum 6-13 . By integrating an electron trap in a circuit quantum electrodynamics architecture 14-20 , we achieve strong coupling between the motional states of a single electron and a single microwave photon in an on-chip superconducting resonator. Qubit gate operations and dispersive readout are implemented to measure the energy relaxation time T 1 of 15 μs and phase coherence time T 2 over 200 ns. These results indicate that the electron-on-solid-neon qubit already performs near the state of the art for a charge qubit 21 .

36 MATERIALS SCIENCE↗

DOE OSTI2015

In pursuit of an accurate spatial and temporal model of biomolecules at the atomistic level: a perspective on computer simulation

The current computational techniques available for biomolecular simulation are described, and the successes and limitations of each with reference to the experimental biophysical methods that they complement are presented. Despite huge advances in the computational techniques available for simulating biomolecules at the quantum-mechanical, atomistic and coarse-grained levels, there is still a widespread perception amongst the experimental community that these calculations are highly specialist and are not generally applicable by researchers outside the theoretical community. In this article, the successes and limitations of biomolecular simulation and the further developments that are likely in the near future are discussed. A brief overview is also provided of the experimental biophysical methods that are commonly used to probe biomolecular structure and dynamics, and the accuracy of the information that can be obtained from each is compared with that from modelling. It is concluded that progress towards an accurate spatial and temporal model of biomacromolecules requires a combination of all of these biophysical techniques, both experimental and computational.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Quantum Computing in Next-Generation Transportation Optimization

We explore how quantum computing (QC) can advance transportation optimization, with a focus on two high-impact areas: traffic signal control and vehicle electrification with grid integration. As transportation systems grow in complexity, classical optimization methods increasingly struggle to deliver scalable and efficient solutions, particularly for real-time, data-rich environments. This work identifies key challenges within these two domains where QC may offer advantages, particularly in handling combinatorial decision spaces and dynamic constraints. We begin by outlining the limitations of classical approaches for traffic signal control optimization and electric vehicle charging coordination, highlighting where computational limitations arise. Previous quantum formulations are presented and new formulations are proposed to demonstrate how emerging quantum algorithms, including quantum annealing and the Quantum Approximation Optimization Algorithm, could be leveraged to reformulate and address these problems. We also evaluate the suitability of current quantum hardware and discuss recent trends that indicate when QC may become a viable tool for transportation applications. While acknowledging the present limitations of QC technologies, this poster emphasizes the importance of preparing quantum-compatible models today. By reviewing and establishing formulations that align with the strengths of quantum algorithms, researchers and practitioners can better position themselves to take advantage of QC advancements as they occur. This work aims to provide a practical, forward-looking perspective on the near-term potential of quantum computing in transportation optimization.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2015

Advanced Technology System Scheduling Governance Model

In the fall of 2005, the Advanced Simulation and Computing (ASC) Program appointed a team to formulate a governance model for allocating resources and scheduling the stockpile stewardship workload on ASC capability systems. This update to the original document takes into account the new technical challenges and roles for advanced technology (AT) systems and the new ASC Program workload categories that must be supported. The goal of this updated model is to effectively allocate and schedule AT computing resources among all three National Nuclear Security Administration (NNSA) laboratories for weapons deliverables that merit priority on this class of resource. The process outlined below describes how proposed work can be evaluated and approved for resource allocations while preserving high effective utilization of the systems. This approach will provide the broadest possible benefit to the Stockpile Stewardship Program (SSP).

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

A review of neutronics and thermal hydraulics–based screening methods applied to accelerated nuclear fuel qualification

This paper reviews the state-of-the-art engineering approach for using thermal hydraulic (TH) and neutronics modeling and simulation (M&S) tools to perform rapid screening studies of novel nuclear fuel concepts within the context of accelerated fuel qualification. Global research efforts have introduced nuclear fuel and material concepts that mark a significant departure from traditional reactor materials. The number of new technologies being considered for development for light water reactors and advanced reactor types has created the need for an accelerated fuel qualification procedure. A key component of this procedure is the rapid identification of the most promising fuel concepts using computational screening studies. Advanced TH and neutronic M&S tools should be leveraged to efficiently determine whether the reactor performance and safety characteristics of a given concept warrant additional studies or whether the concept requires modification or elimination. This paper reviews best practices for performing these TH and neutronics screening studies at various stages during a fuel concept's progression through the qualification procedure. The motivation behind standardizing this approach is to minimize time and resources spent on qualification activities for fuel concepts that could be quickly refined or eliminated from consideration based on their reactor physics and TH characteristics. Adoption of this screening procedure—which focuses primarily on nuclear fuels but may be applicable to other reactor materials—will also help accelerate new material qualification by generating boundary conditions crucial to fuel performance evaluations and highlighting needed areas of separate effects experimentation. This article reviews the motivation behind the introduction of novel nuclear fuel concepts, provides incentive for utilizing TH- and neutronics-based screening studies, describes the screening approach and methodology, and includes discussion on how to interpret screening results to provide recommendations for the continued development of a given concept.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

A Perspective on Sustainable Computational Chemistry Software Development and Integration

The power of quantum chemistry to predict the ground and excited state properties of complex chemical systems has driven the development of computational quantum chemistry software, integrating advances in theory, applied mathematics, and computer science. The emergence of new computational paradigms associated with exascale technologies also poses significant challenges that require a flexible forward strategy to take full advantage of existing and forthcoming computational resources. In this context, the sustainability and interoperability of computational chemistry software development are among the most pressing issues. In this perspective, we discuss software infrastructure needs and investments with an eye to fully utilize exascale resources and provide unique computational tools for next-generation science problems and scientific discoveries.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Quantum Computing and Cryptography: Analysis, Risks, and Recommendations for Decisionmakers

Some influential American policymakers, scholars, and analysts are extremely concerned with the effects that quantum computing will have on national security. Similar to the way space technology was viewed in the context of the US-Soviet rivalry in the Cold War, they view scientific advancement in quantum computing as a race with significant national security consequences and a part of the emerging US-China rivalry. It is claimed that the winner of this race will be able to thwart all the cryptographic efforts of the loser and gain unfettered access to any state secret of the losing government. Additionally, it is suggested that the winner will be able to protect their secrets with a higher level of security than contemporary cryptography guarantees at the moment. This paper argues that these three claims are considerably overstated, and that policymakers and scholars should shift focus to a different national security problem that quantum computing will create. Maintaining the long-term security of secret information secured by contemporary cryptographic protections, which will fail against an attack by a future quantum computer, is the predominant challenge needing attention. This paper takes a technically-informed approach to this issue. It first lays out the national security problems that are envisioned in much of the current discourse surrounding quantum computing. Then, it will assess the technical advantages that quantum computers will have over classical computers in the field of cryptography. Next, it will provide an explanation of the specific ways that the technical realities of quantum computing are inconsistent with the predominant areas of concern. Following, it will highlight the more pressing national security problem posed by quantum computing that the public discussion has, for the most part, missed. The piece will conclude with recommendations for how to mitigate this issue.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Report of the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science

Scientific computing is undergoing rapid transformation as advances in artificial intelligence, heterogeneous computing, automation, and data-intensive research reshape not only computational tools but also the institutions, workforce models, and collaborative practices that support scientific discovery. This report synthesizes insights from the 2026 Workshop on Next-Generation Ecosystems for Scientific Computing, the second in a three-year series focused on strengthening scientific computing ecosystems through socio-technical co-design. Workshop discussions identified four interdependent strategic themes: software ecosystems for AI-enabled scientific discovery; trust, validation, and traceability; human-AI teaming and paradigm shifts; and workforce, pedagogy, and governance. The report translates these themes into eight priorities for community action spanning shared research infrastructure, trust and traceability, user experience, human-AI teaming, workforce development, cross-sector coordination, stewardship and sustainability, and evaluation of scientific value. Together, these priorities outline directions for building scientific computing ecosystems that remain trustworthy, sustainable, innovative, and resilient as AI assumes a growing role in scientific work.

AI↗

DOE OSTI2014

Mechanical Analysis of W78/88-1 Life Extension Program Warhead Design Options

Life Extension Program (LEP) is a program to repair/replace components of nuclear weapons to ensure the ability to meet military requirements. The W78/88-1 LEP encompasses the modernization of two major nuclear weapon reentry systems into an interoperable warhead. Several design concepts exist to provide different options for robust safety and security themes, maximum non-nuclear commonality, and cost. Simulation is one capability used to evaluate the mechanical performance of the designs in various operational environments, plan for system and component qualification efforts, and provide insight into the survivability of the warhead in environments that are not currently testable. The simulation efforts use several Sandia-developed tools through the Advanced Simulation and Computing program, including Cubit for mesh generation, the DART Model Manager, SIERRA codes running on the HPC TLCC2 platforms, DAKOTA, and ParaView. Several programmatic objectives were met using the simulation capability including: (1) providing early environmental specification estimates that may be used by component designers to understand the severity of the loads their components will need to survive, (2) providing guidance for load levels and configurations for subassembly tests intended to represent operational environments, and (3) recommending design options including modified geometry and material properties. These objectives were accomplished through regular interactions with component, system, and test engineers while using the laboratory's computational infrastructure to effectively perform ensembles of simulations. Because NNSA has decided to defer the LEP program, simulation results are being documented and models are being archived for future reference. However, some advanced and exploratory efforts will continue to mature key technologies, using the results from these and ongoing simulations for design insights, test planning, and model validation.

42 ENGINEERING↗

DOE OSTI2023

Extreme-scale stochastic optimization and simulation via learning-enhanced decomposition and parallelization (Final Technical Report)

Stochastic optimization and simulation models ubiquitously arise in designing and operating complex service/engineering systems. They can be extreme in scale due to high-dimensional data and decisions, and can also involve decisions made sequentially in response to newly revealed data, both causing significant computational challenge. The objective of this research is to explore a unified framework that integrates machine learning with discrete optimization and risk-averse modeling, to improve the efficiency of decomposition paradigms for stochastic optimization and simulations at extreme scale. The models we consider represent a broad class of complex decision-making problems, where 0-1 or continuous decisions are made before and/or after knowing multiple sources of uncertainties that could be correlated. We will employ machine learning methods to dynamically decide and prioritize computational procedures, including cut generation, branching, and bounding of the optimal objective. Furthermore, the research will shed new lights on the traditional decomposition algorithms for extreme-scale computing. Deliverables of the research include new modeling and computational methods for advancing the state-of-the-art research in optimization and simulation, bringing many relevant risk-averse, data-driven optimization problems in practice within the range of tractability. Examples include distributed computing server scheduling and sensor deployment for monitoring critical infrastructures. Success in this effort will enable progress in solving multiple extreme-scale problems in the complex system design and operations arising from DoE missions in energy, environment, and national security.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Summary Report Of The FY25 Computational Fluid Dynamics Verification And Validation Exercises In The Advanced Reactor Technologies - Gas-cooled Reactor Program

Verification and Validation (V&V) of numerical tools is critical for ensuring reasonable predictions during design, safety analysis, and licensing. Recent work in the Advanced Reactor Technologies - Gas-cooled Reactor (ART-GCR) program has focused on V&V of common Computational Fluid Dynamics (CFD) tools that are used within the Untied States. This report presents an update on these CFD V&V activities. These Generation IV Forum (GIF) Very High Temperature Reactor (VHTR) Computational Methods, Validation, and Benchmarking (CMVB) is an international organization dedicated to the verification and validation of High Temperature Gas-Cooled Reactor (HTGR) simulation tools. Participation in the CMVB provides additional value to the V&V activities, as it allows for access to a wider range of data, and provides valuable benchmarking exercises. Three HTGR phenomena are targeted: Reactor Cavity Cooling System (RCCS) performance, core bypass flow, and lower plenum mixing. Simulations of the University of Wisconsin-Madison (UW-Madison) RCCS facilities are performed with Reynolds Averaged Navier-Stokes (RANS) in StarCCM+. Results are compared for both forced and natural convection conditions, with both exhibiting good agreement with experimental measurements. The Idaho National Laboratory (INL) matched index of refraction (MIR) and Korean Atomic Energy Research Institute (KAERI) bypass flow expeirments are used to validation CFD predictions of bypass flow. Simulations are performed with RANS in StarCCM+ and with Large Eddy Simulation (LES) in NekRS. Finally, preliminary simulations of the Institute of Nuclear and New Energy Technology (INET) lower plenum mixing facilities are presented. Initial work has developed models with LES, RANS, and porous media models. These preliminary models are presented and compared to each other to gauge differences in predictions with each of the three methods.

and Benchmarking (CMVB)↗

DOE OSTI2021

Advances and perspectives in discovery and functional analysis of small secreted proteins in plants

Small secreted proteins (SSPs) are less than 250 amino acids in length and are actively transported out of cells through conventional protein secretion pathways or unconventional protein secretion pathways. In plants, SSPs have been found to play important roles in various processes, including plant growth and development, plant response to abiotic and biotic stresses, and beneficial plant–microbe interactions. Over the past 10 years, substantial progress has been made in the identification and functional characterization of SSPs in several plant species relevant to agriculture, bioenergy, and horticulture. Yet, there are potentially a lot of SSPs that have not been discovered in plant genomes, which is largely due to limitations of existing computational algorithms. Recent advances in genomics, transcriptomics, and proteomics research, as well as the development of new computational algorithms based on machine learning, provide unprecedented capabilities for genome-wide discovery of novel SSPs in plants. In this review, we summarize known SSPs and their functions in various plant species. Then we provide an update on the computational and experimental approaches that can be used to discover new SSPs. Finally, we discuss strategies for elucidating the biological functions of SSPs in plants.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2012

On the Reaction Mechanism of Acetaldehyde Decomposition on Mo(110)

The strong Mo-O bond strength provides promising reactivity of Mo-based catalysts for the deoxygenation of biomass-derived oxygenates. Combining the novel dimer saddle point searching method with periodic spin-polarized density functional theory calculations, we investigated the reaction pathways of a acetaldehyde decomposition on the clean Mo(110) surface. Two reaction pathways were identified, a selective deoxygenation and a nonselective fragmentation pathways. We found that acetaldehyde preferentially adsorbs at the pseudo 3-fold hollow site in the η2(C,O) configuration on Mo(110). Among four possible bond (β-C-H, γ-C-H, C-O and C-C) cleavages, the initial decomposition of the adsorbed acetaldehyde produces either ethylidene via the C-O bond scission or acetyl via the β-C-H bond scission while the C-C and the γ-C-H bond cleavages of acetaldehyde leading to the formation of methyl (and formyl) and formylmethyl are unlikely. Further dehydrogenations of ethylidene into either ethylidyne or vinyl are competing and very facile with low activation barriers of 0.24 and 0.31 eV, respectively. Concurrently, the formed acetyl would deoxygenate into ethylidyne via the C-O cleavage rather than breaking the C-C or the C-H bonds. The selective deoxygenation of acetaldehyde forming ethylene is inhibited by relatively weaker hydrogenation capability of the Mo(110) surface. Instead, the nonselective pathway via vinyl and vinylidene dehydrogenations to ethynyl as the final hydrocarbon fragment is kinetically favorable. On the other hand, the strong interaction between ethylene and the Mo(110) surface also leads to ethylene decomposition instead of desorption into the gas phase. This work was financially supported by the National Advanced Biofuels Consortium (NABC). Computing time was granted by a user project (emsl42292) at the Molecular Science Computing Facility in the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL). This work was financially supported by the National Advanced Biofuels Consortium (NABC). Computing time was granted by a user project (emsl42292) at the Molecular Science Computing Facility in the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL). The EMSL is a U.S. Department of Energy (DOE) national scientific user facility located at Pacific Northwest National Laboratory (PNNL) and supported by the DOE Office of Biological and Environmental Research. Pacific Northwest National Laboratory is operated by Battelle for the U.S. Department of Energy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Development and Commercialization of an IDAES-Based Power Plant Performance Monitoring and Optimization System

DOE and NETL have created an advanced, open-source computational platform through the Institute for the Design of Advanced Energy Systems (IDAES). The IDAES platform is a very extensive modeling environment that can be used for a broad range of power plant and process applications. MapEx Software is developing and commercializing a software application that makes it easier to set-up and run IDAES-based analyses. The MapEx-developed software application will replace the need for custom Python language coding with a user-friendly graphical user interface where the user can construct a flowsheet diagram of the IDAES model by inserting icons representing the plant equipment onto the screen. This application will make the implementation of modeling and optimization of existing fossil-fired power plants more straight-forward and less time-consuming. The effort focuses on performance monitoring and optimization of plant operations for the existing coal-fired power plant fleet but is built on a structure that allows expansion into the broad range of applications where IDAES methods may be applied.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2024

Remote operation of the DIII-D National Fusion Facility

Abstract Full remote scientific operation of the DIII-D National Fusion Facility is now possible through significant advances in the computer science hardware and software infrastructure made over the last decade. Capabilities around information visualization, data movement, and communication have all been enhanced. The level of capability deployed to remotely operate DIII-D required an infrastructure advancement over what had previously been achieved in the fusion community. The large quantity of real-time data that is automatically displayed on DIII-D’s control room screens can now be visualized by remote participants via web-based applications. New audio/video solutions using the VoIP and instant messaging application Discord have been implemented to mimic the dynamic and ad-hoc scientific conversations that are critical in successfully operating an experimental campaign. Discord’s ability for a user to rapidly move between audio channels, text with images, and share screens is a significant enhancement over traditional videoconferencing tools. In addition, multiple combinations of broadcast audio are made available via a web-based application to allow remote participants to simultaneously listen to general announcements/sounds while conducting their own specific conversations. Secure methodologies have been put into place to allow remote control of hardware including DIII-D’s plasma control system application. Secure methods also included the ability of the on-site team to closely coordinate their work with remote team members which has been enhanced through extensions to the wireless network and the use of tablet computers for audio/video/screen sharing. However, no amount of software can fully replace the need for ‘hands on hardware.’ This infrastructure was severely stress tested during the COVID-19 pandemic where occupancy of the DIII-D control room was restricted. Operational efficiency during the pandemic, measured in discharges per hour, remained high (3.8 ± 0.8) compared to values obtained pre-pandemic (3.7 ± 0.8).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Unconventional compute methods and future challenges for superconducting digital computing

Superconducting digital computing (SDC) based on Josephson junctions (JJs) offers significant potential for enhancing compute throughput and reducing energy consumption compared to conventional room-temperature CMOS-based approaches. Current superconducting logic families exhibit diverse characteristics in clocking strategies, power management, and information encoding techniques. This paper reviews recent advancements in unconventional computing methods specifically designed for superconducting digital circuits, emphasizing temporal computing and pulse-train representations. Notable techniques include race logic (RL), temporal pulse train computing (U-SFQ), and temporal multipliers, each offering unique performance and area advantages suited to superconducting implementations. Additionally, this paper reviews innovations in superconducting coarse-grain reconfigurable architectures (CGRA), superconducting-specific on-chip communication architectures, cryogenic sensor interfaces, and quantum computing control electronics. Finally, we highlight research challenges that should be addressed to facilitate the widespread adoption of superconducting digital computing.

EDA tools↗

DOE OSTI2025

Status on Genetic Resistance to Rice Blast Disease in the Post-Genomic Era

Rice blast, caused by Magnaporthe oryzae, is a major threat to global rice production, necessitating the development of resistant cultivars through genetic improvement. Breakthroughs in rice genomics, including the complete genome sequencing of japonica and indica subspecies and the availability of various sequence-based molecular markers, have greatly advanced the genetic analysis of blast resistance. To date, approximately 122 blast-resistance genes have been identified, with 39 of these genes cloned and molecularly characterized. The application of these findings in marker-assisted selection (MAS) has significantly improved rice breeding, allowing for the efficient integration of multiple resistance genes into elite cultivars, enhancing both the durability and spectrum of resistance. Pangenomic studies, along with AI-driven tools like AlphaFold2, RoseTTAFold, and AlphaFold3, have further accelerated the identification and functional characterization of resistance genes, expediting the breeding process. Future rice blast disease management will depend on leveraging these advanced genomic and computational technologies. Emphasis should be placed on enhancing computational tools for the large-scale screening of resistance genes and utilizing gene editing technologies such as CRISPR-Cas9 for functional validation and targeted resistance enhancement and deployment. These approaches will be crucial for advancing rice blast resistance, ensuring food security, and promoting agricultural sustainability.

Pedrozo, Rodrigo↗

DOE OSTI2026

Enhanced climate reproducibility testing with false discovery rate correction

Simulating the Earth's climate is an important and complex problem, thus climate models are similarly complex, comprised of millions of lines of code. In order to appropriately utilize the latest computational and software infrastructure advancements in Earth system models running on modern hybrid computing architectures to improve their performance, precision, accuracy, or all three; it is important to ensure that model simulations are repeatable and robust. This introduces the need for establishing statistical or non-bit-for-bit reproducibility, since bit-for-bit reproducibility may not always be achievable. Here, we propose a short-simulation ensemble-based test for an atmosphere model to evaluate the null hypothesis that modified model results are statistically equivalent to that of the original model. We implement this test in version 2 of the US Department of Energy's Energy Exascale Earth System Model (E3SM). The test evaluates a standard set of output variables across the two simulation ensembles and uses a false discovery rate correction to account for multiple testing. The false positive rates of the test are examined using re-sampling techniques on large simulation ensembles and are found to be lower than the currently implemented bootstrapping-based testing approach in E3SM. We also evaluate the statistical power of the test using perturbed simulation ensemble suites, each with a progressively larger magnitude of change to a tuning parameter. The new test is generally found to exhibit more statistical power than the current approach, being able to detect smaller changes in parameter values with higher confidence.

Kelleher, Michael E. [Oak Ridge National Laborator↗