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DOE OSTI2024

Carbonate Management to Enable Energy- and Carbon-Efficient CO 2 Electrolysis (Final Technical Report)

The rapid growth and plummeting cost of solar energy have spurred growing interest in using CO 2 electrolysis to produce chemicals and fuels as an alternative to conventional petrochemical processes. High-temperature (>800 °C) solid oxide electrolyzers that convert CO 2 into CO and O 2 have recently become commercially available. Low-temperature electrolysis cells offer the prospect of more convenient and flexible operation, which is critical for utilizing intermittent solar energy, and provide access to more valuable C 2+ products such as ethylene, ethanol, and propanol. Over the past 10 years, research in this area has yielded substantial progress in both fundamental understanding of the requisite electrocatalytic reactions and design of prototype devices. Leveraging insights from fuel cells and membrane water electrolyzers, researchers have developed electrolysis cells with gas diffusion electrodes (GDE) that have demonstrated high CO 2 electrolysis current densities (>100 mA cm –2 ) as well as promising selectivity and stability. Despite these advances, the energy efficiency (electrical energy-to-product) and carbon efficiency (CO 2 -to-product) of low-temperature CO 2 electrolysis remain far too low for large-scale deployment. A preponderance of evidence indicates that the principal source of efficiency losses is the rapid and thermodynamically favorable reaction of CO 2 with hydroxide (OH – ) to form carbonate (CO 3 2– ). Carbonate formation imposes steady-state electrolysis conditions that result in large voltage and CO 2 losses for all known (photo)electrochemical CO 2 cells. While much current research remains focused on CO 2 reduction catalyst design, this largely overlooked CO 3 2– problem presents a fundamental scientific barrier to creating a viable electrochemical option for converting solar energy into chemicals and fuels. The project pursues an integrated, multi-PI research effort that establishes a fundamental science of CO 3 2– management. PI Kanan and Co-PI Mani’s contribution to the project is to evaluate strategies to mitigate the CO 3 2– problem by changing the properties of the electrolyte and the environment in which CO 2 reduction catalysis takes place. Experimental studies showed that electrolytes composed of a high concentration of both CO 3 2– and HCO 3 – , which serve as moderately alkaline buffers, improved the cell voltage by compared to all-HCO 3 – electrolytes, but these buffered systems still show substantial CO 2 uptake that reduces pH over time. Computational studies developed a homogenized model of a CO 2 reduction catalyst layer that permits a low-cost exploration of the high-dimensional parameter space associated with catalyst layers on gas diffusion electrodes. The model was validated by accurately reproducing experimental data for the related but simpler reaction of CO reduction and then used to probe the effects of catalyst layer architecture on CO 2 reduction. Minimizing the size of catalyst and hydrophobic domains in the catalyst layer is predicted to mitigate CO 3 2– formation and thereby enable prolonged operation at elevated pH. In support of the CO 2 electrolysis studies, a new method for rapidly prototyping electrochemical cells was developed and validated. The method uses a combination of 3D printing and electroless plating to generate conductive cell components for evaluating new cell designs. The carbonate problem encompasses mass transport processes and acid-base reactions that are relevant to many other electrochemical systems. Investigation of strategies to address the carbonate problem led to an additional line of inquiry into the physicochemical phenomena that determine the efficiency of electrochemical acid-base production, which has numerous applications in the broader field of carbon management. New strategies for using the supporting electrolyte to inhibit H + /OH – recombination in electrochemical acid-base production were evaluated, leading to the development of a novel acid-base producing system that eliminates the need for ion exchange membranes and exhibits promising efficiency and current densities for scalable applications.

25 ENERGY STORAGE↗

DOE OSTI2025

Entrapment Behavior of Solid Surrogate Fission Products at Engineered UN Nano‐Hetero‐Interfaces Within Metallic Nuclear Fuels

Nanometric hetero-interfaces provide a wealth of scientific and engineering opportunities due to their complex and often misunderstood properties that can differ from their respective bulk constituents. In this work, the ability for engineered nanostructures within a bulk U─Mo alloy to arrest simulant fission products is investigated experimentally and computationally. Nanostructured 90 wt% U/ 10 wt% Mo (U-10Mo) with 7.1 at% Nd is consolidated using spark-plasma- sintering (SPS) techniques and is heat-treated at 500 °C under vacuum for 24, 100, 500, and 1000 h. Analysis on the sintered and heat-treated U-10Mo reveals rapid kinetics in Nd diffusion to nanocluster sites, with evidence of Nd diffusion occurring during sintering and during the following heat-treatment. The segregation behavior of Nd at two different U─Mo/UN interfaces is computationally verified using density functional theory (DFT) to reinforce experimental data.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

DFT-based insight into finite-temperature properties of ferroelectric perovskites with lone-pair: the case of CsGeX 3 (X = Cl, Br, I)

Ferroelectrics remain in the focus of scientific attention for decades owing to their fundamental and practical appeal. Recently, ferroelectricity has been demonstrated in semiconducting halide perovskites (Zhang et al 2022 Sci. Adv. 8 eabj5881), offering both a rare combination of ferroelectricity and semiconductivity in the same material and a possible alternative to the prevailing perovskite oxide ferroelectrics. We propose a route to simulating such materials at finite temperatures capable of reproducing key experimental and first-principle data, such as Curie temperature, phase transition sequence, spontaneous polarization, and soft mode frequencies. The key methodological finding is the superior performance of hybrid exchange correlation functionals in parametrization of effective Hamiltonians for ferroelectrics with lone pair. The parametrization for effective Hamiltonians for CsGeX 3 (X = Cl, Br, I) is reported. The application of methodology to study polarization reversal in CsGeX 3 allows for the development of a ‘minimalistic’ model for polarization reversal in ferroelectrics that provides an insight into the mechanisms of polarization reversal and its key features, such as the relationship between the coercive field, temperature, and AC field frequency. Importantly, the model reveals the origin of the well-known and ever-puzzling overestimation of coercive fields in computations. Furthermore, we report a variety of finite-temperature properties of CsGeX 3 ferroelectrics, such as dielectric susceptibility, pyroelectric coefficients, and energy storage density, which reveal that these halide perovskites possess properties comparable to their oxide counterparts. Here, we believe that our work provides significant methodological advancements, deepens fundamental understanding of ferroelectrics, and reveals the potential of halide perovskite ferroelectrics.

effective Hamiltonian↗

DOE OSTI2026

Kramers nodal line in the charge density wave state of YTe 3 and the influence of twin domains

Recent studies have focused on the relationship between charge density wave (CDW) collective electronic ground states and nontrivial topological states. YTe 3 , a nonmagnetic quasi-two-dimensional chalcogenide, has been reported to exhibit a CDW state below 334 K. Using angle-resolved photoemission spectroscopy (ARPES) and density functional theory (DFT), we establish that YTe 3 is a CDW-induced Kramers nodal line (KNL) metal, a recently proposed topological state of matter. Scanning tunneling microscopy and low energy electron diffraction reveal two orthogonal domains, each with a unidirectional CDW and a similar wave vector (𝐪 CDW ). When the influence of twin domains is considered, the effective band structure (EBS) computations that utilize DFT-calculated bands using a noncentrosymmetric structure determined by x-ray crystallography, show excellent agreement with ARPES. The noncentrosymmetry of YTe 3 is established by Raman spectroscopy. The Fermi surface and ARPES intensity plots show weak shadow bands displaced by 𝐪 CDW from the main bands. Furthermore, these are linked to CDW modulation, as the EBS calculation confirms. Bilayer split main and shadow bands suggest the existence of crossings, according to theory and experiment. DFT bands, including spin-orbit coupling, indicate existence of a KNL along the Σ direction from multiple crossings of bands dispersing perpendicular to it. Additionally, doubly degenerate bands are only found along the KNL at all energies, with some bands dispersing through the Fermi level.

Angle-resolved photoemission spectroscopy↗

DOE OSTI2020

Nanostructures for Electrical Energy Storage (NEES) (2020 Final Technical Report)

Nanostructures for Electrical Energy Storage (NEES, www.efrc.umd.edu) was an Energy Frontier Research Center supported by the DOE Office of Science, Basic Energy Sciences, from 8/1/2009 to 7/31/2020. Led by the University of Maryland, NEES enjoyed extensive collaborations with its funded partners, including two DOE Laboratories and six universities. The NEES vision has been to reveal a set of scientific insights and design principles that can underpin a next-generation electrical energy storage approach, building on advances in nanoscale science and technology to achieve simultaneous high power and high energy over extended charge/discharge cycling. The vision is motivated by the recognition that scaling into the nano regime opens the door to new physical phenomena and that the tools enlisted in nanoscale research provide major new opportunities for the synthesis not only of materials at molecular scale but for structures at nano scale and above. NEES has translated this vision into its research program based on two observations. First, while the behavior of ions and electrons in electrolytes and in electrode materials is crucial to electrical energy storage (or more appropriately electrochemical energy storage), it is the transport of ion and electron charge between different structural components of a storage device that ultimately determine its performance. With it well recognized that the choice of electrode materials typically constrain ion transport kinetics as well as maximum ion concentration, the search for better electrode materials has been a primary driver of battery research. At the same time the synthesis of electrodes is typically based on aggregation of particles with varying size, shape, and orientation in the electrode. Together with the presence of additional materials to impart electrical conductivity and cohesion to the composite electrode, change in electrode materials is necessarily accompanied by structural changes at the nano/micro scale that are difficult to categorize and manage. From the beginning, NEES’ vision has been to create and study simpler, highly controlled spatial arrangements of known materials as battery components (electrodes, current collectors, and electrolyte) and to understand how design and structure above the molecular scale determines the energy storage performance available from known materials. Second, advances in nanoscience dramatically expanded the portfolio of synthesis methods, structural motifs, and new phenomena available for research. Some of these gave rapid access to new building blocks at the deep nanoscale (e.g., carbon nanotubes grown by self-assembly, nanoscale arrays formed by electrochemical self-alignment, monolayer films controlled by self-limiting reaction). Such advances served as the enabler for the NEES vision to be pursued experimentally through study of 3D structures created and controlled at the nano, micro, and meso scales. Here, we use meso as in the BES MESO Report, implying not only intermediate or varying length scales, but very much the way behavior is influenced by other factors including aggregation of nanocomponents at different densities and spatial configurations, statistical variations in the aggregates, hierarchical architectures in which they can be assembled, or local 3D configurations that result from the architectures. Over its life cycle, NEES has pursued two overarching goals: (1) to understand the scientific fundamentals of electrochemical storage from the nanoscale to the mesoscale; and (2) to create and learn from innovative, controlled, heterogeneous nanostructures, where such nanostructures can enable the first goal and serve as models for future paradigms in energy storage. Specific goals have included: Synthesize heterogeneous nanostructures comprised of multiple materials arranged in controlled fashion and characterize their behavior; Demonstrate and elucidate design principles for achieving simultaneous high power and high energy; Develop materials processes which enable precision control of thin layers and 3D structures; Investigate the impact of artificial interphases on electrode stability during ion insertion/deinsertion; Create dense arrays of nanostructures to understand how the architecture of these assemblies, along with nanostructure design, influences energy storage behavior at the mesoscale; Identify and understand the consequences of nanoconfinement and local inhomogeneities in 3D mesoscale arrays; Develop and apply computational models to stimulate, guide and interpret experiments.

25 ENERGY STORAGE↗

DOE OSTI2023

Visual Style Elements in Human–System Interface Design for Nuclear Power Operations: Does Style Affect Performance and Preference?

As the world increasingly adopts renewable and sustainable energy systems, transitionary solutions include nuclear power, which currently provides 20% of the United States’ electricity and is the largest single source of carbon-free electricity generation. Advanced reactors are a critical component of a carbon-free mixed energy portfolio that require careful design of first-of-a-kind control rooms. The application of Human Factors Engineering (HFE) is essential for scientific and iterative testing of novel human–system interface (HSI) concepts to ensure effective, efficient, and safe plant operations. Microworlds are simulators that use simplified physics models and control systems to distill nuclear power operations into essential functions. HFE scientists used the Rancor Microworld Simulator to obtain preference and performance metrics for novel and traditional static HSI design styles. Participants comprised advanced reactor company employees and nuclear industry consultants. A mixture of quantitative and qualitative data was captured. There was a preference for the basic graphical style that included high contrast and traditional color scheme elements. No single HSI design outperformed the others, and the participants did not perform better using their preferred HSI style. We report this experiment is the first in a series of HFE testing for HSIs in advanced reactor control room development. Clear user preferences emerged for elements within static displays. The cutting-edge neumorphic style was the least preferred. Future directions include tests of dynamic displays. HFE is used in evaluating and designing HSI devices that will improve the efficiency and safety of advanced nuclear power operations.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Characterizing the Impact of GPU Power Management on an Exascale System

As GPU-accelerated high-performance computing (HPC) systems approach exascale performance, controlling energy consumption without compromising throughput is essential. Architectures such as the AMD MI250X-based Frontier supercomputer provide runtime mechanisms like frequency and power capping, enabling energy tuning without modifying application code. Although both target energy reduction, they operate via distinct hardware control paths and influence workloads differently. We present a comprehensive evaluation of these strategies on a leadership-class system using diverse HPC proxy applications representative of production workloads. Our study analyzes performance–energy trade-offs across multiple capping levels, node counts (1 and 32), and application profiles. Results show that frequency capping generally achieves higher energy efficiency and scalability, with gains of up to 13.2% without performance loss, while power capping is more effective for single-node runs or bursty GPU utilization. We also provide practical guidelines to help system administrators and users balance energy efficiency and performance in large-scale scientific workloads.

Costa, Mariana [Universidade Federal do Rio Grande↗

DOE OSTI2016

Nevada National Security Site: Site-Directed Research and Development (SDRD) Fiscal Year 2015 Annual Report

This report presents results of multiple research projects, new and ongoing, funded under the Site-Directed Research and Development Program for the Nevada National Security Site during federal fiscal year 2015. The Site's legacy capabilities in remote sensing combined with new paradigms for emergency response and consequence management help drive the need to develop advanced aerial sensor platforms. Likewise, dynamic materials science is a critical area of scientific research for which basic physics issues are still unresolved. New methods of characterizing materials in extreme states are vitally needed, and these efforts are paving the way with new knowledge. Projects selected in FY 2015 for the Exploratory Research portfolio exhibit a strong balance of NNSS mission relevance. Geoscience, seismology, and techniques for detecting underground nuclear events are still essential focus areas. Many of the project reports in the second major section of this annual report are ongoing continuations in multi-year lifecycles. Diagnostic techniques for stockpile and nuclear security science figured prominently as well, with a few key efforts coming to fruition, such as phase transition detection. In other areas, modeling efforts toward better understanding plasma focus physics has also started to pay dividends for major program needs.

42 ENGINEERING↗

DOE OSTI2019

Building Towards Discovery: Preparing for New Physics at the LHC [Final papers]

Particle physics today is at a crossroads. The Standard Model (SM) has survived four decades of experimental scrutiny and spurred multiple landmark discoveries, culminating with the 2012 discovery of the Higgs boson at the Large Hadron Collider (LHC). Yet we know that this model is incomplete. We live in a universe dominated by matter and energy unaccounted for by the SM– and the Higgs boson itself is improbably light. It falls to the current generation of high-energy physicists to go beyond the model and enter a new era of discovery. Andeen is leading a new research group at the University of Texas at Austin (UT-Austin) that is endeavoring to reveal novel physical phenomena through the discovery of new particles with the ATLAS detector at the LHC. A key element of our experience thus far has been collaborating closely with theorists to identify both interesting new physics models. In addition we work closely with electrical engineers in detector development. Our approach is therefore unique in its integration of theory, analysis and instrumentation, and is encapsulated in a three-pronged strategy. First is the essential task of analyzing our rapidly expanding dataset. I am directing my group in searches for vector-like quarks (VLQs). Should they exist, these hypothetical particles would indicate physics scenarios beyond the SM. Experimental constraints suggest VLQs decay preferentially to a third generation quark and a Higgs, W or Z boson. Today at 13 TeV, both multi-lepton (electron and muon) and jet substructure signatures are sensitive to identifying the VLQ decay products. The large Run 2 dataset (collected through 2018) of up to 150 fb -1 will allow us to simultaneously use multi-lepton signatures with jet-substructure in searches for new physics. UT-Austin is well positioned to be a leader in this area. Prof. P. Onyisi’s postdoctoral researchers and graduate students are searching for ttH signatures in three- and four-lepton channels and we benefit from their experience. We are also aided by the availability of the Texas Advanced Computing Center, which provides us with easy access to several high performance computing (HPC) systems. My previous experience in VLQ searches propels the work today. I have published both the first investigation into the single production of top partners (signatures of composite Higgs Models) of any LHC experiment 1 as well as one of the first analyses utilizing jet-substructure techniques to search for the single production of vector-like quarks. 2 Adding to this is my group’s work with the Liquid Argon (LAr) calorimeter, the primary instrument we use in detecting electrons. Second, my group is contributing to the operations of the LAr calorimeter while preparing to install and commission new electronic hardware (the Phase 1 upgrade) to this crucial component of the ATLAS detector. I have played a leading role in the development of a critical, radiation-hard, high-speed Analog-to-Digital Convertor (ADC) that is essential inselecting data collected by the LAr calorimeter. 3 This upgrade will improve the e!ciency with which we can select events in our detector. Postdoctoral researcher N. Nikiforou (based at CERN May 2016 onward) and graduate students (one based at CERN from the start of 2018 onward, with one additional graduate students from summer 2018) are growing our already deep experience in the operation of the LAr calorimeter to prepare for installation and commissioning of the new trigger readout in 2018-2019. My group will then be positioned to be the first to exploit the potential of the improved triggers in our multi-lepton searches for new physics. Third, a suite of preparations for a major detector upgrade, scheduled to be completed in 2024, are underway. My group is building hardware that will improve the electronic readout of the ATLAS detector. I am partnering with a group in the Electrical and Computer Engineering (ECE) Department at UT-Austin (Prof. N. Sun) to employ his work at the cutting edge of ADC research. We will support an ECE grad student for the layout of this design, and collaborate with engineering groups at Nevis Laboratory and the Electrical Engineering Department (Prof. P. Kinget) at Columbia University to integrate our ADC with gain selection circuits. We will provide this critical component of the ASIC at the challenging boundary of the analog and digital signals in the LAr calorimeter readout chain. Furthermore UT-Austin will lead the testing of this device during development and production (approximately 55,000 four-channel chips). This effort compliments my work as the deliverables manager for the LAr front-end ASICs for the US ATLAS HL-LHC project and strengthens the US commitment to that upgrade.In so doing, my group at the UT-Austin will be at the forefront of efforts to probe the structure of the universe to an unmatched degree both at the current LHC and with its future upgrades. Through both the ongoing analysis of data at the ATLAS detector and improvements to the detector itself, an answer to what lies beyond the SM may come within our grasp. My background in instrumentation and analysis allows my group to establish a singular research effort on the ATLAS experiment. In addition to answering fundamental questions about the subatomic world, the technologies developed could advance the broader scientific community and result in valuable spin-offs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2006

High Efficiency Power Combining of Ka-Band TWTs for High Data Rate Communications

Future NASA deep space exploration missions are expected in some cases to require telecommunication systems capable of operating at very high data rates (potentially 1 Gbps or more) for the transmission back to Earth of large volumes of scientific data, which means high frequency transmitters with large bandwidth. Among the Ka band frequencies of interest are the present 500 MHz Deep Space Network (DSN) band of 31.8 to 32.3 GHz and a broader band at 37-38 GHz allocated for space science [1]. The large distances and use of practical antenna sizes dictate the need for high transmitter power of up to 1 kW or more. High electrical efficiency is also a requirement. The approach investigated by NASA GRC is a novel wave guide power combiner architecture based on a hybrid magic-T junction for combining the power output from multiple TWTs [1,2]. This architecture was successfully demonstrated and is capable of both high efficiency (90-95%, depending on frequency) and high data rate transmission (up to 622 Mbps) in a two-way power combiner circuit for two different pairs of Ka band TWTs at two different frequency bands. One pair of TWTs, tested over a frequency range of 29.1 to 29.6 GHz, consisted of two 110-115W TWTs previously used in uplink data transmission evaluation terminals in the NASA Advanced Communications Technology Satellite (ACTS) program [1,2]. The second pair was two 100W TWTs (Boeing 999H) designed for high efficiency operation (greater than 55%) over the DSN frequency band of 31.8 to 32.3 GHz [3]. The presentation will provide a qualitative description of the wave guide circuit, results for power combining and data transmission measurements, and results of computer modeling of the magic-T and alternative hybrid junctions for improvements in efficiency and power handling capability. The power combiner results presented here are relevant not only to NASA deep space exploration missions, but also to other U.S. Government agency programs.

Wintucky, E. G.↗

DOE OSTI2023

CommAwareNet: Towards Communication‐Aware Smart Facilities: Designing an Energy‐Efficient High‐Data‐Rate and Reliable Hybrid THz/VLC Comm. Arch. Reinforced with Intelligent Surfaces for Future Network

This project will develop foundations for energy-efficient, high-data-rate, and reliable communication links for next-generation advanced wireless technologies. The Internet of Everything is emerging as a major technology that can establish a massively connected network among both human-type users and machine-type devices. Particularly, massive machine-type communication is becoming the dominant communication paradigm for numerous emerging areas, including data center networking and wireless backhaul, healthcare (e-health), manufacturing (industry 4.0), utilities, transportation (connected cars and public safety), and virtual or augmented reality for human-machine interaction applications. The rising demand for high data rates, especially in indoor scenarios and densely populated outdoor environments, will eventually overload conventional RF-based technologies. This project aims to conduct fundamental research to design, optimize, and validate a communication-aware, energy-efficient, and reliable network (CommAwareNet) architecture for future smart facilities and environments that require unprecedented high throughput needs for massive numbers of the machine- and human-type users. The scientific and technical merit of this work lies in the research required to bring the proposed transformative CommAwareNet solution into fully functional and practical architecture.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

MO-DE-209-00: DBT Physics Basic to Advanced

Digital Breast Tomosynthesis (DBT) is rapidly replacing mammography as the standard of care in breast cancer screening and diagnosis. DBT is a form of computed tomography, in which a limited set of projection images are acquired over a small angular range and reconstructed into tomographic data. The angular range varies from 15° to 50° and the number of projections varies between 9 and 25 projections, as determined by the equipment manufacturer. It is equally valid to treat DBT as the digital analog of classical tomography – that is, linear tomography. In fact, the name “tomosynthesis” stands for “synthetic tomography.” DBT shares many common features with classical tomography, including the radiographic appearance, dose, and image quality considerations. As such, both the science and practical physics of DBT systems is a hybrid between computed tomography and classical tomographic methods. In this lecture, we will explore the continuum from radiography to computed tomography to illustrate the characteristics of DBT. This lecture will consist of four presentations that will provide a complete overview of DBT, including a review of the fundamentals of DBT acquisition, a discussion of DBT reconstruction methods, an overview of dosimetry for DBT systems, and summary of the underlying image theory of DBT thereby relating image quality and dose. Learning Objectives: To understand the fundamental principles behind tomosynthesis image acquisition. To understand the fundamentals of tomosynthesis image reconstruction. To learn the determinants of image quality and dose in DBT, including measurement techniques. To learn the image theory underlying tomosynthesis, and the relationship between dose and image quality. ADM is a consultant to, and holds stock in, Real Time Tomography, LLC. ADM receives research support from Hologic Inc., Analogic Inc., and Barco NV.; ADM is a member of the Scientific Advisory Board for Gamma Medica Inc.; A. Maidment, Research Support, Hologic, Inc.; Research Support, Barco, Inc.; Scientific Advisory Board, Gamma Medica, Inc.; Scientific Advisory Board, Real-Time Tomography, LLC.; Shareholder, Real-Time Tomography, LLC; J. Mainprize, Our lab has a research agreement with GE Healthcare on various topics in digital mammography and digital tomosynthesis; W. Zhao, Research grant from Siemens Health Care.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Modeling Impacts of Resilience Architectures for Extreme-Scale Storage Systems

The Scientific Modeling and Simulation of Storage project focused on improving our ability to store information reliably. The project, done jointly at the University of Wisconsin-Madison, Los Alamos National Laboratories, and Sandia National Laboratories, had the main goal of transforming the art of reliable storage system construction into a more precise science. Along those lines, the project developed numerous tools to expose problems in existing systems; these tools, when applied to the state of the art, uncovered numerous flaws in existing approaches, showing that they both are error prone and in some cases contain serious design flaws. The project also led to the creation of new approaches in reliable system construction. One such approach shows how a storage system can adapt its behavior on the fly to deliver higher performance when there are few underlying failures, but then act more conservatively when more failures are occurring to ensure the safe storage of user data. Another approach develops a storage system consistency model which both delivers high performance but high levels of reliability, a significant advance over previous approaches. Overall, the tools developed within the project advanced the science of reliable storage design, and the new approaches that resulted advanced the science of storage system construction.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

The Artificial Scientist: in-Transit Machine Learning of Plasma Simulations

Large-scale simulations or scientific experiments produce petabytes of data per run. This poses massive challenges for I/O and storage when scientific analysis workflows are run manually offline. Unsupervised deep learning-based techniques to extract patterns and non-linear relations from these large amounts of data provide a way to build scientific understanding from raw data, reducing the need for manual pre-selection of analysis steps, but require exascale compute and memory to process the full dataset available. In this paper, we demonstrate a heterogeneous streaming workflow in which plasma simulation data is streamed directly to a Machine Learning (ML) application training a model on the simulation data in-transit, completely circumventing the capacity-constrained filesystem bottleneck. This workflow employs openPMD to provide a high level interface to describe scientific data and also uses ADIOS2, to transfer volumes of data that exceed the capabilities of the filesystem. We employ experience replay to avoid catastrophic forgetting in learning from this non-steady state process in a continual manner and adapt it to improve model convergence while learning in-transit. As a proof-of-concept, we approach the ill-posed inverse problem of predicting particle dynamics from radiation in a particle-incell (PIConGPU) simulation of the Kelvin-Helmholtz instability (KHI). We detail hardware-software co-design challenges as we scale PIConGPU to full Frontier, the Top-1 system as of June 2024 Top500 list.

Kelling, Jeffrey [Helmholtz-Zentrum Dresden Rossen↗

DOE OSTI2019

Interrelationship between Lab, Space, Astrophysical, Magnetic Fusion, and Inertial Fusion Plasma Experiments (Graduate support for DIII-D Frontier Science Experiments)

The project, to explore the use of the DIII-D facility to investigate questions of value to discovery plasma science and provide a deepened scientific understanding behind basic plasma processes that are outside of the fusion-energy-science research line, began in September 2016 when five discovery-plasma physicists were contacted by General Atomics to form a Frontier Science Experiments (FSE) panel for brainstorming and for implementing the FSE campaign at the DIII-D National Fusion Facility. After advertising the FSE opportunity at the annual plasma physics conference, the panel grew to include six others. By January 2017, the panel for reviewing and ranking proposals was established. Evaluation of FY2017 proposals took place in February 2017. Evaluation of FY2018 proposals took place in January 2018. This proposal began 15 August 2017 and funded two research assistantships for three students who interacted, gained expertise in experimental and computational physics, and shared responsibilities on the following projects within the DIII-D (non-fusion) Frontier Science Experiments (FSE) campaign: (1) "Impact of Magnetic Perturbations on Turbulence - Zonal Flow Interactions and Saturation", (2) "Nonlinear Processes during Toroidal Alfvén Mode-Mode Interaction", (3) "Self-Consistent Chaos in Magnetic Field Dynamics", (4) “Nonmodal Decomposition of Turbulence”, and (5) “Multi-harmonic EMIC Emission -- Species mix and distribution function dependence of instabilities near the ion-cyclotron frequency”. The outcome was a fraction of one doctoral dissertation and the entirety of one master of science thesis. The work took advantage of the unique capabilities of the DIII-D National Fusion Facility to serve as the first phase of the Frontier Science Experiment (FSE) campaign, an innovative concept aiming to advance fundamental understanding in 3 key general plasma science areas - particle acceleration and energetic particles in plasmas, turbulence and transport in plasmas, and nonlinear waves and processes – all at discovery’s cutting edge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

A New Era of Discovery: The 2023 Long-Range Plan for Nuclear Science (V.1.2)

Nuclear science is the investigation of how protons and neutrons are formed from elementary particles and how the forces between those particles produce both nuclei and the vast variety of nuclear phenomena that occur in the universe. It has evolved into a broad field that addresses profound scientific questions: Where does the mass of visible matter come from? How do stars ignite, live, and die? How do nuclei illuminate the search for new laws of nature? This science points the way to using nuclei to build new technologies that benefit society. The 2015 Nobel Prize in physics was shared by nuclear physicists Art McDonald and Takaaki Kajita for the discovery of neutrino oscillations, which confirmed that neutrinos have mass. Our progress on big questions like this one since 2015 has been remarkable owing to new experimental tools, theoretical breakthroughs, powerful computational techniques, and the talented people who make these innovations possible. Focusing on these new tools, the Facility for Rare Isotope Beams (FRIB) at Michigan State University is already producing exciting results on decays of never-before-produced isotopes a year after it was completed on time and on budget. The energy upgrade of the Continuous Electron Beam Accelerator Facility (CEBAF) at the Thomas Jefferson National Accelerator Facility (Jefferson Lab) was also completed on schedule and on budget—new data from this facility are revealing the spectrum, structure, and dynamics of protons, neutrons, nuclei, and mesons. On the theory front, we can now calculate the distribution of quarks inside the proton from first principles. The implementation of artificial intelligence (AI) and machine learning (ML) techniques has led to improved data analysis and increased efficiency in running experiments and theoretical calculations. The impact of nuclear science goes beyond expanding the frontiers of knowledge about matter in the universe. We simultaneously develop a STEM work force that advances the security, technology, health, and wealth of our nation. Some connections are obvious. Expert scientists trained to work with radioactive nuclei are in demand in nuclear security arenas and are highly sought after by various government agencies and private industries. Graduate students and postdoctoral fellows (postdocs) obtain extensive computational, modeling, and data science skills that are similarly in high demand. Less obvious but equally important is the connection between these trained scientists and success in other professions, including medicine, energy, and entrepreneurial pursuits. The workforce that enables discovery in nuclear science also makes breakthroughs in technologies with tremendous impact on the nation’s economic advancement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Workshop on Addressing Rigor and Reproducibility in Thermal, Heterogeneous Catalysis

Heterogeneous catalysis has long served as the bedrock of the manufacturing of energy carriers, fuels and chemicals, and various technologies for pollution abatement. The significant complexity and variability spanning the entire breadth of catalyst material properties, synthesis methods, characterization techniques, and evaluation procedures, has focused attention on the need to establish community-accepted best practices for ensuring high-quality, benchmarked, and reproducible data. In addition, increased societal urgency to transition to clean energy and reduce greenhouse gas concentrations has incentivized interdisciplinary, convergent, and translational approaches to catalysis research in recent years. Research engineers and scientists with expertise cutting broadly across materials science, chemical synthesis, interfacial science, spectroscopy, and methods of data science and computational simulation, all bring diverse and important perspectives to catalysis research, but often with little awareness of the complexity of catalytic systems, especially in their working environment. As has already occurred in other scientific fields, there has been growing recognition and consensus in the heterogeneous catalysis research community that mechanisms are needed to improve the rigor and reproducibility (R&R) of experimental measurements, to ensure alignment of the broader research community with a common core of best practices specific to the realization of high-quality catalysis research. Similarly, the field is moving rapidly toward computationally informed and data science-driven catalyst design, but the success of implementing such predictive tools hinges on model training and validation rooted in rigorously obtained and reproducible experimental data that are benchmarked to common specifications. As such, this workshop was convened to prepare a report summarizing best practices for reporting data and performing experiments that researchers can use to benchmark, validate, and reproduce data in specific sub-fields of thermal, heterogeneous catalysis. Additionally, we discussed recommendations for future actions that may improve R&R in this field. The workshop organizers and participants include a diverse range of catalysis researchers from various employment sectors (e.g., academia, industry, national laboratory), institutional mission and resources (e.g., PhD-granting research universities, non-PhD-granting teaching universities), career stage (e.g., early, mid and late-career), technical expertise, and demographic background. This diverse group was involved in the discussion of workshop agenda items, writing this report, and discussing possible future action items for the community to consider, which helped ensure that a broad range of perspectives were captured in the description of the problems at hand and the creation of actionable solutions that may be effectively adopted by the diverse practitioners in catalysis research. Importantly, this group of workshop participants also included very early career researchers (e.g., senior PhD students, postdoctoral scholars) who will become the next generation of scientific leaders in various sectors, thus capturing emerging perspectives of newcomers to the field to shape its future while positively impacting the development of its future workforce. We envision that this effort will help advance the field of catalysis science by improving the rigor and reproducibility of experimental data collected by current researchers and future newcomers to the field, which is of broad importance to health and vitality of any scientific discipline. Therefore, best practices identified in this endeavor for thermal heterogeneous catalysis can be translated to such efforts in other areas of catalysis and other scientific fields involving the study of materials, and vice versa. We also envision this to be an ongoing effort, with future workshops that are convened to discuss issues of rigor and reproducibility on technical topics that were unable to be covered in this workshop due to its scope limitations, and as emerging methods and materials become more prevalent in the research community.

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DOE OSTI2022

The Geothermal Data Repository: Ten Years of Supporting the Geothermal Industry with Open Access to Geothermal Data

The Department of Energy's (DOE) Geothermal Data Repository (GDR) is celebrating its tenth anniversary! Over the last decade it has grown from the simple idea of storing public data in a centralized location to a valuable tool at the center of the US geothermal scientific community and an integral part of the DOE Geothermal Technologies Office (DOE GTO) project management strategy. Researchers funded by the DOE GTO have contributed over 1,300 data submissions to the GDR. These data have been used to further advancements in geothermal science, economic analysis, exploration, research, development, and operational efficiency. The adoption of open data methodologies and a data management strategy that prioritizes universal open access and standardized, interoperable data have further increased the value of GDR data, making them available across a distributed network of data sharing partners and improving their utility to other industries and related fields, including material science and space exploration. Incorporating feedback from users has been critical to the GDR's success, allowing it to grow over the years to meet the evolving needs of the geothermal community. This paper will explore some of many changes that occurred throughout the GDRs tenure and the lessons learned along the way, as well as highlight some of the new features and recent improvements that been implemented to support innovation, reduce duplication of effort, and advance the geothermal industry as a whole.

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