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DOE OSTI2025

Thermally driven surface phase separation in intermetallic alloys

Intermetallic compounds are widely recognized for their high-temperature phase stability and resistance to composition and structural changes. However, we reveal athermally activated bulk-to-surface mass exchange mechanism that drives surface phase separation, resulting in the formation of surface precipitates with distinct composition andstructure from the bulk matrix. Using the archetypal β-NiAl system, we show that asymmetries in vacancy formation energies between Ni and Al atoms induce preferential Ni segregation to the surface, forming Ni-rich γ'-Ni 3 Al precipitates. By integrating in-situ electron microscopy, synchrotron X-ray absorption spectroscopy and first-principles computational modeling, we establish a direct mechanistic connection between bulk thermal defect dynamics, surface compositional evolution, and phase segregation behavior. This bulk-surface coupling mechanism can be a driver of surface phase separation in multicomponent alloys under thermal stress. In conclusion, these results refine the thermodynamic boundaries of intermetallic stability and provide insights into managingthe performance and durability of intermetallic alloys for demanding high-temperature applications.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Magnetic and dielectric property control in the multivalent nanoscale perovskite Eu 0.5 Ba 0.5 TiO 3

We report nanoscale Eu 0.5 Ba 0.5 TiO 3 , a multiferroic in the bulk and candidate in the search to quantify the electric dipole moment of the electron. Eu 0.5 Ba 0.5 TiO 3 , in the form of nanoparticles and other nanostructures is interesting for nanocomposite integration, biomedical imaging and fundamental research, based upon the prospect of polarizability, f-orbital magnetism and tunable optical/radio luminescence. We developed a [non-hydrolytic]sol–[H 2 O-activated]gel route, derived from in-house metallic Ba (s) /Eu (s) alkoxide precursors and Ti{(OCH(CH 3 ) 2 } 4 . Two distinct nanoscale compounds of Ba:Ti:Eu with the parent perovskite crystal structure were produced, with variable dielectric, magnetic and optical properties, based on altering the oxidizing/reducing conditions. Eu 0.5 Ba 0.5 TiO 3 prepared under air/O 2 atmospheres produced a spherical core–shell nanostructure (30–35 nm), with perovskite Eu 0.5 Ba 0.5 TiO 3 nanocrystal core-insulating oxide shell layer (~3 nm), presumed a pre-pyrochlore layer abundant with Eu 3+ . Fluorescence spectroscopy shows a high intensity 5 D 0 → 7 F 2 transition at 622 nm and strong red fluorescence. The core/shell structure demonstrated excellent capacitive properties: assembly into dielectric thin films gave low conductivity (2133 GΩ mm -1 ) and an extremely stable, low loss permittivity of ε eff ~25 over a wide frequency range (tan δ < 0.01, 100 kHz–2 MHz). Eu 0.5 Ba 0.5 TiO 3 prepared under H 2 /argon produced more irregular shaped nanocrystals (20–25) nm, with a thin film permittivity around 4 times greater ( ε eff 101, tan δ < 0.05, 10 kHz–2 MHz, σ ~59.54 kΩ mm -1 ). Field-cooled magnetization values of 0.025 emu g -1 for EBTO-Air and 0.84 emu g -1 for EBTO-Argon were observed. X-ray photoelectron spectroscopy analysis reveals a complex interplay of Eu II/III /Ti III/IV configurations which contribute to the observed ferroic and fluorescence behavior.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2023

High-bandwidth density silicon photonic resonators for energy-efficient optical interconnects

The growth of artificial intelligence applications demands ever larger and more complex deep learning models, dominating today's—and tomorrow's—data center and high-performance computing systems. While traditional electronics are failing to keep pace with application demands, silicon photonic (SiPh) interconnects have emerged as a necessary technology to support these systems. SiPh-driven wavelength-division multiplexing (WDM) offers a particularly promising path toward supporting incredibly high-aggregate link bandwidth in a compact and efficient form factor. One of the basic building blocks of these integrated WDM interconnects is the SiPh resonator. Their inherent wavelength selectivity and compact footprint allow for efficient data transmission multiplexed across dozens of carrier wavelengths. Used as add-drop (AD) filters, SiPh resonators are critical to constructing integrated tunable wavelength-selective optical circuit switches as well as for demultiplexing the different carrier wavelengths toward independent wavelength-insensitive photodiodes in a dense wavelength-division multiplexing receiver. Resonators in the all-pass (AP) configuration are widespread as well, allowing for wavelength-selective modulation to drive aggregate link bandwidths far beyond the individual channel data rate. Unlike SiPh Mach–Zehnder modulators (MZM), resonant modulators can be driven using low, complementary metal-oxide-semiconductor drive voltages, allowing for tight co-integration between photonic integrated circuits, fabricated with larger process node technologies, and electronic integrated circuits, designed to exploit the advantages of the latest node. To push toward practical peta-scale interconnects, a comprehensive review of SiPh resonators is required, addressing bottlenecks and design constraints at both the architecture and device levels. We first describe the predominant integrated link architectures and identify their limits. We then discuss the device-level design considerations that can be made for both AD and AP configuration resonators to overcome the system level limits with novel resonator device designs. Analytical models and numerical simulation of resonators are validated by experimental measurement of devices fabricated in a commercial 300-mm foundry, showing a clear path toward volume manufacturing. The demonstrated resonant modulators and filters support the feasibility of increasing the aggregate bandwidth of resonator-driven SiPh interconnects into the peta-scale regime.

42 ENGINEERING↗

DOE OSTI2025

X-ray spectroscopy of multi-temperature plasmas using the differential emission measure formalism

We present a theoretical construct that nominally underlies spectroscopic data analysis of multi-temperature plasmas, known as the differential emission measure (DEM). From a data analytic perspective, the DEM formalism is used to derive temperature distributions from line spectra that are formed in the presence of temperature gradients and by time integrations of evolving plasmas. From a modeling perspective, DEMs are convenient intermediaries between radiation hydrodynamics simulations and spectroscopic measurements acquired in the laboratory. The DEM concept and its associated methodologies were originally developed by spectroscopists working with astrophysical data. We borrow from these earlier investigations. In this manuscript, intended primarily as a tutorial, we discuss the basic concepts, but also augment various aspects of the theory by the way of extension and example, including a detailed treatment of various weighting and averaging schemes, intended to mitigate ambiguities that often arise when reporting temperature information. We focus on high-temperature plasmas that are not in local thermodynamic equilibrium and the x-ray spectra that they produce, although the core ideas presented here are applicable to spectroscopy in other energy bands. A few examples involving the derivation and manipulation of model DEMs in simple geometries are provided.

Liedahl, Duane A. [Lawrence Livermore National Lab↗

DOE OSTI2024

Chaotic neural dynamics facilitate probabilistic computations through sampling

Cortical neurons exhibit highly variable responses over trials and time. Theoretical works posit that this variability arises potentially from chaotic network dynamics of recurrently connected neurons. Here, we demonstrate that chaotic neural dynamics, formed through synaptic learning, allow networks to perform sensory cue integration in a sampling-based implementation. We show that the emergent chaotic dynamics provide neural substrates for generating samples not only of a static variable but also of a dynamical trajectory, where generic recurrent networks acquire these abilities with a biologically plausible learning rule through trial and error. Furthermore, the networks generalize their experience in the stimulus-evoked samples to the inference without partial or all sensory information, which suggests a computational role of spontaneous activity as a representation of the priors as well as a tractable biological computation for marginal distributions. These findings suggest that chaotic neural dynamics may serve for the brain function as a Bayesian generative model.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Explicit structure-preserving geometric particle-in-cell algorithm in curvilinear orthogonal coordinate systems and its applications to whole-device 6D kinetic simulations of tokamak physics

Explicit structure-preserving geometric particle-in-cell (PIC) algorithm in curvilinear orthogonal coordinate systems is developed. The work reported represents a further development of the structure-preserving geometric PIC algorithm achieving the goal of practical applications in magnetic fusion research. The algorithm is constructed by discretizing the field theory for the system of charged particles and electromagnetic field using Whitney forms, discrete exterior calculus, and explicit non-canonical symplectic integration. In addition to the truncated infinitely dimensional symplectic structure, the algorithm preserves exactly many important physical symmetries and conservation laws, such as local energy conservation, gauge symmetry and the corresponding local charge conservation. As a result, the algorithm possesses the long-term accuracy and fidelity required for first-principles-based simulations of the multiscale tokamak physics. The algorithm has been implemented in the SymPIC code, which is designed for high-efficiency massively-parallel PIC simulations in modern clusters. The code has been applied to carry out whole-device 6D kinetic simulation studies of tokamak physics. A self-consistent kinetic steady state for fusion plasma in the tokamak geometry is numerically found with a predominately diagonal and anisotropic pressure tensor. The state also admits a steady-state sub-sonic ion flow in the range of 10 km s -1 , agreeing with experimental observations and analytical calculations Kinetic ballooning instability in the self-consistent kinetic steady state is simulated. It is shown that high-n ballooning modes have larger growth rates than low-n global modes, and in the nonlinear phase the modes saturate approximately in 5 ion transit times at the 2% level by the E × B flow generated by the instability. These results are consistent with early and recent electromagnetic gyrokinetic simulations.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

The metallicity’s fundamental dependence on both local and global galactic quantities

ABSTRACT We study the scaling relations between gas-phase metallicity, stellar mass surface density (Σ*), star formation rate surface density (ΣSFR), and molecular gas surface density ($\Sigma _{{\rm H}_2}$) in local star-forming galaxies on scales of a kpc. We employ optical integral field spectroscopy from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, and ALMA data for a subset of MaNGA galaxies. We use partial correlation coefficients and Random Forest regression to determine the relative importance of local and global galactic properties in setting the gas-phase metallicity. We find that the local metallicity depends primarily on Σ* (the resolved mass–metallicity relation, rMZR), and has a secondary anticorrelation with ΣSFR (i.e. a spatially resolved version of the ‘Fundamental Metallicity Relation’, rFMR). We find that $\Sigma _{{\rm H}_2}$ is less important than ΣSFR in determining the local metallicity. This result indicates that gas accretion, resulting in local metallicity dilution and local boosting of star formation, is unlikely to be the primary origin of the rFMR. The local metallicity depends also on the global properties of galaxies. We find a strong dependence on the total stellar mass (M*) and a weaker (inverse) dependence on the total SFR. The global metallicity scaling relations, therefore, do not simply stem out of their resolved counterparts; global properties and processes, such as the global gravitational potential well, galaxy-scale winds and global redistribution/mixing of metals, likely contribute to the local metallicity, in addition to local production and retention.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Exact general solutions for cosmological scalar field evolution in a background-dominated expansion

We derive exact general solutions (as opposed to attractor particular solutions) and corresponding first integrals for the evolution of a scalar field $\phi$ in a universe dominated by a background fluid with equation of state parameter wB. In addition to the previously examined linear [V($\phi$)=V 0 $\phi$] and quadratic [V($\phi$)=V 0 $\phi$ 2 ] potentials, we show that exact solutions exist for the power-law potential V($\phi$)=V 0 $\phi$ n with n=4(1+w B )/(1-w B )+2 and n=2(1+w B )/(1-w B ). These correspond to the potentials V($\phi$)=V 0 $\phi$ 6 and V($\phi$)=V 0 $\phi$ 2 for matter domination and V($\phi$)=V 0 $\phi$ 10 and V($\phi$)=V 0 $\phi$ 4 for radiation domination. The $\phi$ 6 and $\phi$ 10 potentials can yield either oscillatory or nonoscillatory evolution, and we use the first integrals to determine how the initial conditions map onto each form of evolution. The exponential potential yields an exact solution for a stiff/kination (w B =1) background. We use this exact solution to derive an analytic expression for the evolution of the equation of state parameter, $w_\phi$, for this case.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Enhancing Cyber Resilience of Networked Microgrids using Vertical Federated Reinforcement Learning

This paper presents a novel federated reinforcement learning (Fed-RL) methodology to inject sufficient resiliency into the operations of the network of microgrids. We consider adversarial actions to the voltage and power control loop reference signals at the grid forming (GFM) inverters in the microgrids which are essential to integrate renewable resources. Therefore, we formulate a resilient reinforcement learning training setup that uses these adversarial injections to generate episodic trajectories and train the RL agents to alleviate their impact on performance. To circumvent the concerns about data-sharing and privacy for different owners of the microgrids in the networked setting, we bring in the aspects of the federated operation to propose novel Fed-RL algorithms. As the dynamics of each microgrid are coupled due to electrical interlinks, the conventional federated RL approaches using decoupled independent environments are not applicable, which leads us to propose a multi-agent vertically federated variation of actor-critic algorithms, namely federated soft actor-critic (FedSAC). We have performed numerical simulations on an IEEE 123-bus benchmark test feeder with three microgrids by creating a customized simulation setup by encapsulating the microgrid dynamic simulations in GridLAB-D/HELICS co-simulation platform with the OpenAI Gym environment and validated the proposed resilient and secured learning methodology.

Artificial Intelligence (AI), reinforcement learni↗

DOE OSTI2024

QED: A Powerful Query Equivalence Decider for SQL

Checking query equivalence is of great significance in database systems. Prior work in automated query equivalence checking sets the first steps in formally modeling and reasoning about query optimization rules, but only supports a limited number of query features. In this paper, we present Qed, a new framework for query equivalence checking based on bag semantics. Qed uses a new formalism called Q-expressions that models queries using different normal forms for efficient equivalence checking, and models features such as integrity constraints and NULLs in a principled way unlike prior work. Our formalism also allows us to define a new query fragment that encompasses many real-world queries with a complete equivalence checking algorithm, assuming a complete first-order theory solver. Empirically, Qed can verify 299 out of 444 query pairs extracted from the Calcite framework and 979 out of 1287 query pairs extracted from CockroachDB, which is more than 2× the number of cases proven by prior state-of-the-art solver.

Computer Science↗

DOE OSTI2022

Advanced Hydrogen Compressor for Hydrogen Storage Integrated with a Powerplant

This report summarizes work performed by Siemens Energy (SE) to design, build and test an advanced hydrogen compressor stage suitable for use in a hydrogen electrolysis system integrated with a powerplant to achieve energy storage in the form of compressed hydrogen. As hydrogen utilization increases to achieve energy storage and decarbonization of a variety of industries, the need is growing for improved and more cost-effective hydrogen compression technologies. The counter-rotating compression stage concept demonstrated under this contract and presented in this report offers a novel approach to achieve significantly more head rise per stage of compression, resulting in the potential for decreased capital cost and footprint compared to current state of the art centrifugal compression technologies. This report includes details of the design, testing, results, and subsequent validation of aerodynamic performance predictions.

08 HYDROGEN↗

DOE OSTI2022

Applying 3D Geologic Modeling Workflows to the Argillite Reference Case (Rev. 1)

The objective of this short report is to document the application of our 3D geologic modeling workflow to an argillite (shale) host rock. Over the past four years, our team at Los Alamos National Laboratory has developed a geologic modeling workflow that can be applied to generic alluvial basins such as those found in the western United States. In “frontier” or “exploratory” basins where data are sparse, the first steps are to collect, evaluate and integrate available subsurface data into conceptual geologic models. Those models form the basis for constructing the geologic framework model, a 3D geocellular model ideally constrained by seismic and borehole data. To date we have constructed our models using “synthetic” well data derived from conceptual models, without the prospect of validating our workflow using “real” subsurface data. We were tasked to investigate whether our workflow designed for alluvial basin sediments could be applied to other potential repository host rocks. This task also provided the opportunity to work with high-quality subsurface data collected specifically for siting and evaluating a nuclear waste repository. Nagra, the Swiss governmental agency responsible for the disposal of the nation’s radioactive waste, generously provided us with data from two deep boreholes drilled through their argillaceous target formation. The aim of our proof-of-concept demonstration is to evaluate whether geostatistical methods offer a viable approach to property modeling in argillaceous rocks. Nagra provided us with the well data on the condition that we maintain confidentiality with all transferred information and results. Fortunately, Nagra posts numerous technical reports on its public website that describe the subsurface geology in great detail. All of the information and illustrations in this report related to the Swiss repository enterprise are taken from the Nagra public website.

58 GEOSCIENCES↗

DOE OSTI2026

Large Scale Field Demonstration Evaluation Plan

This Evaluation Plan defines practical, commissioning-oriented test protocols for in-field assessment of grid-forming (GFM) inverter-based resources (IBRs) deployed under the UNIFI Consortium Field Demonstration. The demonstration’s overarching objective is to validate multi vendor GFM technologies at impactful unit/plant scale, assess interoperability and grid-service performance, and evaluate the applicability of the UNIFI Specifications for Grid-forming Inverter-based Resources in real utility environments, including integration with operational systems and protection schemes.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Determination of Location-Specific Solidification Cracking Susceptibility for a Mixed Dissimilar Alloy Processed by Wire-Arc Additive Manufacturing

Solidification cracking is a major obstacle when joining dissimilar alloys using additive manufacturing. In this work, location-specific solidification cracking susceptibility has been investigated using an integrated computational materials engineering (ICME) approach for a graded alloy formed by mixing P91 steel and Inconel 740H superalloy. An alloy mixture of 26 wt.% P91 and 74 wt.% Inconel 740H, with high configurational and total entropy, was fabricated using wire arc additive manufacturing. Microstructure characterization revealed intergranular solidification cracks in the FCC matrix, which increased in length along with the enrichment of Nb (~27 to 56 wt.%) and Cu (~87 wt.%) in the middle and top regions. DICTRA simulations to model location-specific solidification cracking susceptibility showed that the top region with the highest cooling rate (270 K/s) has the highest solidification cracking susceptibility in comparison with the middle and bottom regions. This is in good agreement with the experimentally observed varying crack length. From Scheil simulations, it was deduced that enrichment of Nb and Cu affected the solidification range as high as ~77%, in comparison with the matrix composition. The overall solidification cracking susceptibility and freezing range was highest for the 26 wt.% P91 alloy amongst the mixed compositions between P91 steel and 740H superalloy, proving that solidification characteristics play a major role in alloy design for additive manufacturing.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2024

Grid-Forming Inverters: Project Demonstrations and Pilots

Power system operators around the world are pushing the limits of integrating inverter-based resources (IBRs) to very high levels, approaching 100% instantaneous penetration under certain operating conditions. This often applies to smaller power systems with very little or no ac interconnections to other neighboring regions or sometimes to fringes of large balancing areas, such as Denmark or Portugal, within the mainland European power system. These jurisdictions have identified the potential of grid-forming (GFM) technology as a key enabler to support the energy transition with very few or no synchronous generators online. Until recently, practical applications of GFM inverters were limited to microgrids and isolated grids and in smaller grid applications on the order of a few tens of megawatts (MW).

Australia↗

DOE OSTI2022

A scalable, open-source implementation of a large-scale mechanistic model for single cell proliferation and death signaling

Mechanistic models of how single cells respond to different perturbations can help integrate disparate big data sets or predict response to varied drug combinations. However, the construction and simulation of such models have proved challenging. Here, we developed a python-based model creation and simulation pipeline that converts a few structured text files into an SBML standard and is high-performance- and cloud-computing ready. We applied this pipeline to our large-scale, mechanistic pan-cancer signaling model (named SPARCED) and demonstrate it by adding an IFNγ pathway submodel. We then investigated whether a putative crosstalk mechanism could be consistent with experimental observations from the LINCS MCF10A Data Cube that IFNγ acts as an anti-proliferative factor. The analyses suggested this observation can be explained by IFNγ-induced SOCS1 sequestering activated EGF receptors. This work forms a foundational recipe for increased mechanistic model-based data integration on a single-cell level, an important building block for clinically-predictive mechanistic models.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Transferring Liquid Metal to form a Hybrid Solid Electrolyte via a Wettability-Tuning Technology for Lithium-Metal Anodes

Integrating solid-state electrolyte (SSE) into Li-metal anodes has demonstrated great promise to unleash the high energy density of rechargeable Li-metal batteries. However, fabricating a highly cyclable SSE/Li-metal anode remains a major challenge because the densification of the SSE is usually incompatible with the reactive Li metal. Here, a liquid-metal-derived hybrid solid electrolyte (HSE) is proposed, and a facile transfer technology to construct an artificial HSE on the Li metal is reported. By tuning the wettability of the transfer substrates, electron- and ion-conductive liquid metal is sandwiched between electron-insulating and ion-conductive LiF and oxides to form the HSE. The transfer technology renders the HSE continuous, dense, and uniform. The HSE, having high ion transport, electron shut-off, and mechanical strength, makes the composite anode deliver excellent cyclability for over 4000 h at 0.5 mA cm(-2) and 1 mAh cm(-2) in a symmetrical cell. When pairing with LiFePO4 and sulfur cathodes, the HSE-coated Li metal dramatically enhances the performance of full cells. Therefore, this work demonstrates that tuning the interfacial wetting properties provides an alternate approach to build a robust solid electrolyte, which enables highly efficient Li-metal anodes.

li-metal anodes↗

DOE OSTI2021

Leaky Buddies: Cross-Component Covert Channels on Integrated CPU-GPU Systems

Graphics Processing Units (GPUs) are ubiquitous components used across the range of today’s computing plat- forms, from phones and tablets, through personal computers, to high-end server class platforms. With the increasing importance of graphics and video workloads, recent processors are shipped with GPU devices that are integrated on the same chip. Integrated GPUs share some resources with the CPU and as a result, there is a potential for microarchitectural attacks from the GPU to the CPU or vice versa. We consider the potential for covert channel attacks that arise either from shared microarchitectural components (such as caches) or through shared contention domains (e.g., shared buses). We illustrate these two types of channels by developing two reliable covert channel attacks. The first covert channel uses the shared LLC cache in Intel’s integrated GPU architectures. The second is a contention based channel targeting the ring bus connecting the CPU and GPU to the LLC. This is the first demonstrated microarchitectural attack crossing the component boundary (GPU to CPU or vice versa). Cross-component channels introduce a number of new challenges that we had to overcome since they occur across heterogeneous components that use different computation models and are interconnected using asymmetric memory hierarchies. We also exploit GPU parallelism to increase the bandwidth of the communication, even without relying on a common clock. The LLC based channel achieves a bandwidth of 120 kbps with a low error rate of 2%, while the contention based channel delivers up to 400 kbps with a 0.8% error rate. We also demonstrate a proof- of-concept prime-and-probe side channel attack that probes the full LLC from the GPU.

Cyber secruity, high performance comptuing, Hetero↗