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At least 505 records · Page 28

Observation of Antiferroelectric Domain Walls in a Uniaxial Hyperferroelectric

Abstract Ferroelectric domain walls are a rich source of emergent electronic properties and unusual polar order. Recent studies show that the configuration of ferroelectric walls can go well beyond the conventional Ising‐type structure. Néel‐, Bloch‐, and vortex‐like polar patterns have been observed, displaying strong similarities with the spin textures at magnetic domain walls. Here, the discovery of antiferroelectric domain walls in the uniaxial ferroelectric Pb 5 Ge 3 O 11 is reported. Highly mobile domain walls with an alternating displacement of Pb atoms are resolved, resulting in a cyclic 180° flip of dipole direction within the wall. Density functional theory calculations show that Pb 5 Ge 3 O 11 is hyperferroelectric, allowing the system to overcome the depolarization fields that usually suppress the antiparallel ordering of dipoles along the longitudinal direction. Interestingly, the antiferroelectric walls observed under the electron beam are energetically more costly than basic head‐to‐head or tail‐to‐tail walls. The results suggest a new type of excited domain‐wall state, expanding previous studies on ferroelectric domain walls into the realm of antiferroic phenomena.

36 MATERIALS SCIENCE↗

Development of a 300 MWe Utility Scale Oxy-Fuel sCO2 Turbine

A 300 MWe direct-fired supercritical carbon dioxide (sCO2) oxy-fuel turbine is being developed that will burn natural gas-fired, coal syngas and even hydrogen mixtures capable of 1,150ºC turbine inlet temperature at 300 bar. This design will significantly improve the state-of-the-art for thermal efficiency and results in a high-pressure stream of CO2 with 98%+ carbon capture, making the power plant near emission-free and more efficient than Natural Gas Combined Cycle (NGCC) plants with carbon capture. This power plant will be capable of burning coal through gasification and cleanup of the synthesis gas (syngas). sCO2 power cycles are a transformational technology for the energy industry, providing higher efficiency heat source energy conversion for conventional and alternative energy sources. This novel cycle significantly reduces capital costs because of smaller equipment footprints, design modularity, and allows for rapid cyclic load and source following to balance solar and wind energy power swings. Oxy-fuel sCO2 cycles take these advantages even further, utilizing higher firing temperatures, improved efficiency, and simpler carbon capture strategies. This turbine will require cooled turbine nozzles and blades as well as advanced thermal management systems to accommodate these high temperatures. The cooled blade heat transfer correlations required new test programs at higher Reynolds number than air-breathing gas turbines for impingement, serpentine, and pin-fin regions. Novel blade optimization was performed to maximize aerodynamic efficiency, while minimizing cooling flows. A turbine layout was generated utilizing individual combustor cans with cooled liners feeding into a 6-stage axial flow turbine with cooled stator nozzles and turbine blades. The case design and thermal management preliminary design will be described.

Moore, Jeffrey↗

Multispectral UAV imagery of experimental freshwater wetlands under 5 ppt saltwater intrusion, Louisiana, 2023 and 2024

Multispectral imagery was collected using an unmanned aerial vehicle (UAV) to evaluate how freshwater vegetation responds to short-term simulated saltwater intrusion events. The purpose of this data collection was to understand how plant health changes in response to acute salinity exposure, which is increasingly relevant in coastal wetland ecosystems facing sea level rise and storm surge events, such as in coastal Louisiana. Three experimental saltwater intrusions were conducted at a salinity of approximately 5 parts per thousand (ppt) for durations of 6-days, 10-days, and 17-days. UAV flights occurred both before and after each treatment. The resulting imagery was processed using Pix4DMapper software to georeference the images and generate orthomosaics. The multispectral sensor used in this study captures reflectance in five bands: blue, green, red, red-edge, and near-infrared. The uploaded data consist of georeferenced .tif orthomosaics for each spectral band, which are compatible with GIS software for vegetation analysis. This imagery can be utilized in investigations into vegetation stress, remote sensing of freshwater wetland ecosystems, and modeling of plant response to environmental changes.

EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS↗

5G integrated edge computing platform for efficient component monitoring in coal-fired power plants

This project developed a cutting-edge 5G-integrated edge computing framework to enhance operational efficiency and reliability in coal-fired power plants through real-time component monitoring and anomaly detection. The initiative focused on leveraging distributed machine learning, federated learning, and 5G-based dynamic network slicing to support scalable, fault-tolerant monitoring environments to meet the operational requirements in industrial control systems. With a Distributed Edge Computing Service (DECS) orchestration, this project enabled federated learning at edge for condition monitoring and introduced adaptive client selection strategies to minimize communication overhead. Scalable distributed training was achieved using the Horovod framework, thus enhancing performance across edge nodes. In the realm of 5G networking, the project designed and deployed reconfigurable, QoS-aware network slicing tailored for operational technology (OT) environments, integrating software-defined networks to bolster cyber-resilience and enabling dynamic slicing for federated learning workloads. A significant milestone was the development of a virtualized ICS environment with 5G core integration—which allowed elastic and fault tolerant distributed training on real-world datasets such as NASA Bearings, Hydraulic Systems, and TEP. To broaden the impact of the project, a TRL-3 virtualized ICS testbed for research and education was designed. This project engaged several graduate and undergraduate students to conduct research on the cutting-edge technology, and it resulted in one PhD dissertation, one MS thesis, and over 14 peer-reviewed publications. With the support of this project students also participated in national cybersecurity competitions to improve their professional development skills.

20 FOSSIL-FUELED POWER PLANTS↗

Testing and Expertise for Marine Energy (TEAMER) Program Support (CRADA Final Report)

Virginia Tech (VT) had previously developed a 50 kW AC to DC power converter that is specifically designed to improve the performance and efficiency of wave energy converters (WECs). Through this CRADA, NLR will test the VT power converter via a coupled dynamometer and power electronics test platform. The NLR test platform will be comprised of (1) a rotary dynamometer that will drive a VT provided gearbox and generator, (2) one or more DC regenerative power supplies that provide input power to and take power from the VT supplied power electronics, and (3) a data acquisition system for measurement. NLR will work with VT to develop a test plan, set up the test platform and integrate the test article, perform the testing, and assist in the data analysis.

16 TIDAL AND WAVE POWER↗

Analysis of the Beaufort Gyre Freshwater Content in 2003–2018

Abstract Hydrographic data collected from research cruises, bottom‐anchored moorings, drifting Ice‐Tethered Profilers, and satellite altimetry in the Beaufort Gyre region of the Arctic Ocean document an increase of more than 6,400 km 3 of liquid freshwater content from 2003 to 2018: a 40% growth relative to the climatology of the 1970s. This fresh water accumulation is shown to result from persistent anticyclonic atmospheric wind forcing (1997–2018) accompanied by sea ice melt, a wind‐forced redirection of Mackenzie River discharge from predominantly eastward to westward flow, and a contribution of low salinity waters of Pacific Ocean origin via Bering Strait. Despite significant uncertainties in the different observations, this study has demonstrated the synergistic value of having multiple diverse datasets to obtain a more comprehensive understanding of Beaufort Gyre freshwater content variability. For example, Beaufort Gyre Observational System (BGOS) surveys clearly show the interannual increase in freshwater content, but without satellite or Ice‐Tethered Profiler measurements, it is not possible to resolve the seasonal cycle of freshwater content, which in fact is larger than the year‐to‐year variability, or the more subtle interannual variations.

Arctic Ocean↗

FastML Science Benchmarks: Accelerating Real-Time Scientific Edge Machine Learning

Applications of machine learning (ML) are growing by the day for many unique and challenging scientific applications. However, a crucial challenge facing these applications is their need for ultra low-latency and on-detector ML capabilities. Given the slowdown in Moore's law and Dennard scaling, coupled with the rapid advances in scientific instrumentation that is resulting in growing data rates, there is a need for ultra-fast ML at the extreme edge. Fast ML at the edge is essential for reducing and filtering scientific data in real-time to accelerate science experimentation and enable more profound insights. To accelerate real-time scientific edge ML hardware and software solutions, we need well-constrained benchmark tasks with enough specifications to be generically applicable and accessible. These benchmarks can guide the design of future edge ML hardware for scientific applications capable of meeting the nanosecond and microsecond level latency requirements. To this end, we present an initial set of scientific ML benchmarks, covering a variety of ML and embedded system techniques.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Structural Simluation Toolkit (SST) v.12.0

The Structural Simulation Toolkit (SST) was developed to explore innovations in highly concurrent computing systems where the instruction set architecture (ISA), micro-architecture, and memory interact with the programming model and communications system. The package provides a fully modular design for extensive exploration of an individual system parameter as well as a parallel simulation environment based on message passing interface (MPI) which enable a high level of performance as well as the ability to look at large systems. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Rodrigues, ArunF.↗

Endless Dirac nodal lines in kagome-metal Ni3In2S2

Abstract Topological semimetals are a frontier of quantum materials. In multiband electronic systems, topological band crossings can form closed curves, known as nodal lines. In the presence of spin–orbit coupling and/or symmetry-breaking operations, topological nodal lines can break into Dirac/Weyl nodes and give rise to interesting transport properties, such as the chiral anomaly and giant anomalous Hall effect. Recently, the time-reversal symmetry-breaking induced Weyl fermions are observed in a kagome-metal Co 3 Sn 2 S 2 , triggering interests in nodal-line excitations in multiband kagome systems. Here, using first-principles calculations and symmetry-based indicator theories, we find six endless nodal lines along the stacking direction of kagome layers and two nodal rings in the kagome plane in nonmagnetic Ni 3 In 2 S 2 . The linear dipsersive electronic structure, confirmed by angle-resolved photoemission spectroscopy, induces large magnetoresistance up to 2000% at 9 T. Our results establish a diverse topological landscape of multiband kagome metals.

36 MATERIALS SCIENCE↗

ORNL_AISD_NiNb

This dataset describes the nickel-niobium solid solution binary alloy, where the two constituent elements nickel (Ni) and niobium (Nb) are randomly placed on an underlying crystal lattice. This dataset for nickel-niobium (Ni-Nb) alloys available includes the formation energy and bulk modulus for each crystal structure. Each atomic sample has a disordered phase which is obtained starting from an initial regular crystal structure of type body-centered cubic (BCC), face-centered cubic (FCC), or hexagonal compact packed (HCP). The geometry optimization ensures that all the alloy samples reached the equilibrium with negative formation energy. We perform geometry optimizations using the LAMMPS simulation package [1], a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. We utilized the embedded atom model (EAM) potential for Ni and Nb developed in a previous study [2]. The potential could describe behaviors of the liquid and solid phases of Ni-Nb alloy. The structural factors and angular distributions of three atoms are well-matched with X-ray and ab initio-based molecular dynamics data. We prepared the three different crystals with different initial lattice parameters (3.52 Ã… for FCC, 3.32 Ã… for BCC, and 3.5 Ã… for HCP). We performed energy minimization in two steps. Firstly, we minimized the structures with an isotropic unit cell to minimize the side effects from our arbitrary lattice parameters for all other compositions. Then, we applied geometry optimization with a triclinic (non-orthogonal) unit cell to fully minimize the stress components to calculate the elastic constants. In this procedure, we chose 10,000 as the maximum number of allowable steps aimed at obtaining fully relaxed atomic geometries. The dataset consists of three sets of crystal structures. The first set contains 46,086 irregular crystal structures, each of them with 54 atoms, obtained through optimization starting from a regular BCC crystal structure. The second set contains 24,543 irregular crystal structures, each of them with 32 atoms, obtained through optimization starting from a regular FCC crystal structure. The third set contains 39,303 irregular crystal structures, each of them with 48 atoms, obtained through optimization starting from a regular HCP crystal structure. The atomic configurations within each set span the possible compositional range. The three sets have been unified in a global dataset, which is extremely heterogeneous in terms of crystal structures, lattice volumes, and atomic configurations. Organization of files inside the dataset: the dataset contains three subdirectories called • BCC_opt • FCC_opt • HCP_opt based on the type of initial regular structure used to start the geometry optimization. Inside each of these folders, every atomic structure is identified by a string “A_B_Câ€, where A denotes the number of Nb in the system, B denotes index of structure with a given Nb number, and C denotes the total number of structures generated with a given Nb number. For each optimized crystal structure identified by the unique string of characters “A_B_Câ€, three files are provided: • A_B_C_opt.xyz: The optimized geometries in xyz format • A_B_C_opt.cfg: The optimized geometries in cfg format. It includes cell information and atomic energy, and forces calculated from LAMMPS. • A_B_C.elastic: Raw data of 21 elastic constants from LAMMPS output. • A_B_C.bulk: Calculated upper and lower bounds of bulk modulus and averaged one based on Voigt-Reuss-Hill approach from *.elastic. References: [1] A. P. Thompson, H. M. Aktulga, R. Berger, D. S. Bolintineanu, W. M. Brown, P. S. Crozier, P. J. in 't Veld, A. Kohlmeyer, S. G. Moore, T. D. Nguyen, R. Shan, M. J. Stevens, J. Tranchida, C. Trott, and S. J. Plimpton. LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales. Comp. Phys. Comm., 271:108171, 2022. [2] Y Zhang, R Ashcraft, MI Mendelev, CZ Wang, and KF Kelton. Experimental and molecular dynamics simulation study of structure of liquid and amorphous ni62nb38 alloy. The Journal of chemical physics, 145(20):204505, 2016.

36 MATERIALS SCIENCE↗

Phased plan for the implementation of the time-resolving magnetic recoil spectrometer on the National Ignition Facility (NIF)

The time-resolving magnetic recoil spectrometer (MRSt) is a transformative diagnostic that will be used to measure the time-resolved neutron spectrum from an inertial confinement fusion implosion at the National Ignition Facility (NIF). It uses a CD foil on the outside of the hohlraum to convert fusion neutrons to recoil deuterons. An ion-optical system positioned outside the NIF target chamber energy-disperses and focuses forward-scattered deuterons. A pulse-dilation drift tube (PDDT) subsequently dilates, un-skews, and detects the signal. While the foil and ion-optical system have been designed, the PDDT requires more development before it can be implemented. Therefore, a phased plan is presented that first uses the foil and ion-optical systems with detectors that can be implemented immediately—namely CR-39 and hDISC streak cameras. These detectors will allow the MRSt to be commissioned in an intermediate stage and begin collecting data on a reduced timescale, while the PDDT is developed in parallel. A CR-39 detector will be used in phase 1 for the measurement of the time-integrated neutron spectra with excellent energy-resolution, necessary for the energy calibration of the system. Streak cameras will be used in phase 2 for measurement of the time-resolved spectrum with limited spectral coverage, which is sufficient to diagnose the time-resolved ion temperature. Simulations are presented that predict the performance of the streak camera detector, indicating that it will achieve excellent burn history measurements at current yields, and good time-resolved ion-temperature measurements at yields above 3 × 10 17 . The PDDT will be used for optimal efficiency and resolution in phase 3.

47 OTHER INSTRUMENTATION↗

Enabling Floating Offshore VAWT Design by Coupling OWENS and OpenFAST

Vertical-axis wind turbines (VAWTs) have a long history, with a wide variety of turbine archetypes that have been designed and tested since the 1970s. While few utility-scale VAWTs currently exist, the placement of the generator near the turbine base could make VAWTs advantageous over tradition horizontal-axis wind turbines for floating offshore wind applications via reduced platform costs and improved scaling potential. However, there are currently few numerical design and analysis tools available for VAWTs. One existing engineering toolset for aero-hydro-servo-elastic simulation of VAWTs is the Offshore Wind ENergy Simulator (OWENS), but its current modeling capability for floating systems is non-standard and not ideal. This article describes how OWENS has been coupled to several OpenFAST modules to update and improve modeling of floating offshore VAWTs and discusses the verification of these new capabilities and features. The results of the coupled OWENS verification test agree well with a parallel OpenFAST simulation, validating the new modeling and simulation capabilities in OWENS for floating VAWT applications. These developments will enable the design and optimization of floating offshore VAWTs in the future.

17 WIND ENERGY↗

Shaping the Future of Self-Driving Autonomous Laboratories Workshop

The "Shaping the Future of Self-Driving Autonomous Laboratories" workshop, held in Denver on November 7-8, 2024, brought together leading experts from materials science and computing to address the growing need to revolutionize scientific research through AI-driven autonomous laboratories. The workshop identified critical challenges, including the integration of heterogeneous data, development of AI systems that understand fundamental physical principles, and comprehensive safety protocols. Key recommendations emerged around developing universal laboratory equipment interfaces, implementing automated metadata collection systems, and creating hybrid AI approaches that combine data-driven learning with scientific principles. The workshop emphasized maintaining human oversight while leveraging automation, transforming scientific education to prepare the next generation of researchers, and establishing a national consortium leveraging DOE facilities as anchors for broader collaboration with academia and industry. Participants stressed the urgency of addressing the growing disconnect between human decision-making timescales and modern instrumentation capabilities, highlighting the need for strategic automation while preserving essential human insight and oversight in the research process.

36 MATERIALS SCIENCE↗

Direct Air Capture and Electromicrobial Production (DAC-EMP) (Final Technical Report for ARPA-E Project)

The collaborative effort of UC Berkeley and GE Vernova (formerly GE Research) aimed to develop an integrated, three-step process to directly capture and convert carbon dioxide (CO 2 ) from ambient air into butanol, a platform molecule for diesel and jet fuels. This new process is intended to address the unmet need for carbon-neutral drop-in substitutes for fossil gasoline, which would substantially reduce the carbon footprint of the transportation sector without requiring significant changes to the nation’s transportation infrastructure. The U.S. alone consumes ~120 billion gallons of gasoline per year, and the use of fossil fuels in transportation accounts for ~30% of U.S. greenhouse gas emissions, a major contribution to the ongoing climate crisis. A successful replacement fuel must therefore be produced in a process that has low carbon emissions over its life cycle while demonstrating both scalability and economic competitiveness. The proposed system is tailorable to a wide range of applications and can establish a viable approach for direct capture and conversion of CO 2 to value-added products with much lower land use compared to a biotechnological process relying on corn-derived glucose.

09 BIOMASS FUELS↗

A2SD: Accelerating Scientific Innovation Through Autonomous Discovery Systems

The 2025 Advancing Autonomous Scientific Discovery (A2SD) workshop convened researchers from academia, national laboratories, and industry to explore the transformative role of autonomy in scientific discovery. The workshop highlighted a convergence of artificial intelligence, robotics, and computational workflows into autonomous systems capable of accelerating the scientific process. Presentations and discussions spanned autonomous experimentation, intelligent workflow orchestration, digital twins, and agent-based systems for managing complex research ecosystems. Key challenges discussed included interoperability across heterogeneous infrastructures, near real-time data management under FAIR principles, reproducibility, and the integration of human oversight. The workshop also emphasized the need for modular software interfaces, federated learning models, and education initiatives to support a next-generation scientific workforce.

Taufer, Michela [University of Tennessee, Knoxvill↗

BioSiting Tool (BioSiting) v2

The BioSiting Tool provides a geospatial interface for analyzing bioeconomy resources and infrastructure across the continental U.S. The tool integrates empirical and modeled data from a broad range of sources. Bioeconomy resources mapped in the tool include agricultural residues, forest residues, municipal solid waste streams, food waste, manure, fats, oils and greases and potential yields of energy crops. Infrastructure mapped in the tool includes biorefineries, material recovery facilities, anaerobic digesters, wastewater treatment plants, combustion plants, district energy systems, crude oil pipelines, petroleum pipelines, natural gas pipelines, railways and freight terminals. Additional data layers include environmental justice indicators at the census tract level and carbon dioxide geologic storage potential. Users can select a location on the map, define a buffer radius in kilometers and generate an inventory of all bioecomony resources within the buffer zone. Data from the tool can be downloaded from individual buffer zones, or at the state or national level.

Huntington, Tyler↗

Computed Tomography Scanning and Petrophysical Measurements of Oriskany Core across Eastern Ohio

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) in Morgantown, West Virginia were used to characterize core material from three Ohio wells. These wells are listed below along with their American Petroleum Institute (API) and Ohio Geological Survey (OGS) identification numbers: - New York Central System 1 well (API 34085200170000, OGS Core 855) - Herren Well (API 34099201650000, OGS Core 2914) - Garvin-King Well (API 34121215610000, OGS Core 2939) The primary impetus of this work was to capture a detailed digital representation of the available core from all three wells. The collaboration between the U.S. Department of Energy’s (DOE) NETL and the Ohio Department of Natural Resources, Division of Geological Survey enables other research entities to access information about this potential carbon storage location and its surrounding formations.

58 GEOSCIENCES↗

Implications of rootless geothermal models: Missing processes, parameter compensation, and imposter convection

Numerical models of geothermal systems commonly capture only the top of a reservoir. Deeper areas of the reservoir are simplified to a boundary at the base of the model domain. Commonly, the basal boundary is given either a heat source or a source of mass and enthalpy. Here we developed and present simple numerical experiments which demonstrate that these approaches do not produce the correct model behavior in comparison to a model that captures the entire convecting domain with a heat flux only. We describe a variety of incorrect types of model behavior that arise directly from the choice of boundary condition, independent of the specific parameterization of the model. Heat sources are sensitive to the thickness of the domain and parameters take unphysical values to compensate for the reduced height. The combined mass/heat boundary can produce temperatures that show similarities to circulating geothermal systems, but with incorrect fluid flow and a strong boundary layer focused at the base of the simulated clay cap. These errors likely cause parameters to adjust their values to compensate for the incorrect physics. We highlight these issues and show an example from a developed reservoir model. Initial calibrations to natural state temperature were unsuitable for history matching. The 3D model required parameter adjustments to achieve a more realistic production model. Appropriate mitigation measures should be considered to reduce parameter compensation and improve decision-support models.

15 GEOTHERMAL ENERGY↗