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

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Synthesis of Correct Digital Controller Models from Specifications by Model Transformation (21-0320)

The design of high consequence controllers (in weapons systems, autonomy, etc.) that do what they are supposed to do is a significant challenge. Testing simply does not come close to meeting the requirements for assurance. Today circuit designers at Sandia (and elsewhere) typically capture the core behavior of their components using state models in tools such as STATEFLOW. They then check that their models meet certain requirements (e.g. “The system bus must not deadlock” or “both traffic lights at an intersection must not be green at the same time”) using tools called model checkers. If the model checker returns “yes” then the property is guaranteed to be satisfied by the model. However, there are several drawbacks to this industry practice: (1) there is a lot of detail to get right, this is particularly challenging when there are multiple components requiring complex coordination (2) any errors returned by the model checker have to be traced back through the design and fixed, necessitating rework, (3) there are severe scalability problems with this approach, particularly when dealing with concurrency. All this places high demands on the designers who now face not only an accelerated schedule but also controllers of increasing complexity. This report describes a new and fundamentally different approach to the construction of safety-critical digital controllers. Instead of directly constructing a complete model and then trying to verify it, the designer can start with an initial abstract (think “sketch”) model plus the requirements, from which a correct concrete model is automatically synthesized. There is no need for post-hoc verification of required functional properties. Having tool to carry this out will significantly impact the nation’s ability to ensure the safety of high-consequence digital systems. The approach has been implemented in a prototype tool, along with a suite of examples, including ones that reflect actual problems faced by designers. Our approach operates on a variant of Statecharts developed at Sandia called Qspecs. Statecharts are a widely used formalism for developing concurrent reactive systems, supporting scalability through allowing state models containing composite states, which are the serial or parallel composition of substates which can themselves contain statecharts. Statecharts enable an incremental style of development, in which states are progressively refined to incorporate greater detail in an incremental model of software development. Our approach formulates a set of constraints from the structure of the models and the requirements and propagates these constraints to a fixpoint. The solution to the constraints is an inductive invariant along with guards on the transitions. We also show how our approach extends to implementation refinement, decomposition, composition, and elaboration. We currently handle safety requirements written in LTL (Linear Temporal Logic)

42 ENGINEERING↗
DOE OSTI2025

Investigation of 31 P levels near the proton threshold with nuclear resonance fluorescence and the impact on the 30 Si (𝑝,𝛾)⁢ 31 P thermonuclear rate

We investigated the nuclear structure of 31 P near the proton threshold using nuclear resonance fluorescence (NRF) to refine the properties of key resonances in the 30 Si (𝑝,𝛾)⁢ 31 P reaction, which is critical for nucleosynthesis in stellar environments. Excitation energies and spin-parities were determined for several states, including two unobserved resonances at 𝐸 𝑟 = 18.7keV and 𝐸 𝑟 = 50.5keV. The angular correlation analysis enabled the first unambiguous determination of the orbital angular momentum transfer for these states. These results provide a significant update to the 30 Si (𝑝,𝛾)⁢ 31 P thermonuclear reaction rate, with direct implications for models of nucleosynthesis in globular clusters and other astrophysical sites. The revised rate is substantially lower than previous estimates at temperatures below 200 MK, affecting predictions for silicon isotopic abundances in stellar environments. Furthermore, our work demonstrates the power of NRF in constraining nuclear properties, and provides a framework for future studies of low-energy resonances relevant to astrophysical reaction rates.

20 ≤ A ≤ 38↗
DOE OSTI2026

matsim-agents v1.0

matsim-agents is a multi-agent AI framework for atomistic materials simulation and discovery. It orchestrates large language models (LLMs), machine-learned interatomic potentials (MLIPs), and DFT codes into a single agentic loop running on laptops and DOE leadership-class supercomputers. MULTI-AGENT ORCHESTRATION A LangGraph state machine with three nodes: a Planner that converts a natural-language research objective into structured tasks; an Executor that dispatches atomistic tools and loops until the queue is empty; and an Analyst that summarizes results into a human-readable report. State is checkpointed after every step and human-in-the-loop gates can be inserted at any edge. HYPOTHESIS-DRIVEN DISCOVERY CHAT An interactive REPL (matsim-agents chat) that couples LLM dialogue with atomistic simulation. Chemical formulas are automatically detected in conversation turns and trigger a full crystal-phase exploration: structure generation → relaxation → stability scoring → result injection back into the conversation, creating a closed hypothesis-refinement loop. CRYSTAL PHASE ENUMERATION Given a composition, the phase explorer enumerates prototypes by stoichiometry: elemental (fcc/bcc/hcp/sc/diamond), binary 1:1 (rocksalt/CsCl/zincblende/ wurtzite/fluorite/rutile), ternary 1:1:3 (cubic perovskite), ternary 1:2:4 (perovskite + spinel), quaternary 1:1:2:6 (Fm-3m double perovskite). 2-D prototypes (graphene, h-BN, MoS2 2H/1T) and multilayer stacking are also supported via --include-2d and --num-layers. SUPERCELL GENERATION AND SITE DECORATION Auto-tiling to a minimum atom count (--min-atoms), explicit NxNxN tiling (--supercell), symmetry-distinct site decorations (--n-orderings), and isotropic lattice-scale sweeps (--lattice-scales) for volume bracketing. MLFF RELAXATION AND STABILITY SCORING HydraGNN (multi-headed GNN) drives structure relaxation via ASE with FIRE, BFGS, or BFGSLineSearch. Stability output: delta-E/atom ranking across phases and a max-residual-force dynamical-stability proxy. Other MLIPs (MACE, NequIP, Orb) can be plugged in through the same interface. DFT BACKENDS Quantum ESPRESSO pw.x and VASP 6.6 are first-class labellers. Both have validated GPU builds and SLURM/PBS launchers for three DOE platforms: Frontier (AMD MI250X, ROCm), Aurora (Intel PVC, oneAPI), Perlmutter (NVIDIA A100, CUDA). QE produces ~100 binaries (pw.x, ph.x, epw.x, ...). VASP supports scf, relax, vc-relax, and vc-relax-shape run types. ACTIVE-LEARNING LOOP matsim-agents al run CONFIG.yaml drives an iterative HydraGNN-DFT loop: MD generates candidates → ensemble/MC-dropout uncertainty selects the most informative → DFT labels them in parallel inside one allocation → dataset grows → HydraGNN retrains → repeat. DFT backend is a single YAML toggle (dft.backend: vasp | qe). LLM-generated seed structures are supported (no curated POSCAR library needed). Config uses ${VAR}, ${VAR:-default}, ${VAR:?msg} shell-style substitution for cross-user/cross-site portability. LLM BACKENDS Ollama (local, default), vLLM (HPC multi-GPU serving), OpenAI, Anthropic, HuggingFace Transformers+Accelerate. Selected at runtime via flag or env var with no code changes. HPC PORTABILITY Same Python entry points run on Frontier (ROCm 7.2), Aurora (oneAPI), and Perlmutter (CUDA 12). DFT and ML stacks are never co-loaded in the same shell; they couple through the scheduler and filesystem. Advanced multi-node launchers (serve, discovery-chat, single-relaxation, active-learning, QE warm-start) are provided for all three platforms. CODABENCH COMPETITION BUNDLE A self-contained benchmark: 159 atomistic test structures across 11 material classes, 5 tasks (formation energy, forces, ML relaxation, AI-DFT relaxation, phase stability ranking), public/private leaderboard split (30/70), and four ready-to-run baselines: MACE-MP-0, HydraGNN, UMA, AllScAIP.

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗
DOE OSTI2024

Nanoscale structural correlations in a model cuprate superconductor

Understanding the extent and role of inhomogeneity is a pivotal challenge in the physics of cuprate superconductors. While it is known that structural and electronic inhomogeneity is prevalent in the cuprates, it has proven difficult to disentangle compound-specific features from universally relevant effects. Here, in this study, we combine advanced neutron and x-ray diffuse scattering with numerical modeling to obtain insight into bulk structural correlations in HgBa 2 ⁢ CuO 4+δ . This cuprate exhibits a high optimal transition temperature of nearly 100 K, pristine charge-transport behavior, and a simple average crystal structure without long-range structural instabilities, and is therefore uniquely suited for investigations of intrinsic inhomogeneity. We uncover diffuse reciprocal-space patterns that correspond to prominent nanoscale correlations of atomic displacements perpendicular to the CuO 2 planes. The real-space nature of the correlations is revealed through three-dimensional pair distribution function analysis and complementary numerical refinement. We find that relative displacements of ionic and CuO 2 layers play a crucial role, and that the structural inhomogeneity is not directly caused by the presence of conventional point defects. The observed correlations are therefore intrinsic to HgBa 2 ⁢ CuO 4+δ , and thus likely important for the physics of cuprates more broadly. It is possible that the structural correlations are closely related to the unusual superconducting fluctuations and Mott-localization in these complex oxides. As advances in scattering techniques yield increasingly comprehensive data, the experimental and analysis tools developed here for large volumes of diffuse scattering data can be expected to aid future investigations of a wide range of materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

An experimental and computational investigation of the structure and spectroscopic signatures of α -UO 3

α-UO 3 is a common intermediate compound found in the nuclear fuel cycle, yet the exact crystal structure of this material has long been debated. Inconsistent computational and experimental data in previous works has led to varying conclusions between authors. Furthermore, to ensure the validity of our results in this work, the structural and spectroscopic signatures of pure phase α-UO 3 are investigated using powder X-ray diffraction and optical vibrational spectroscopy (infrared and Raman). Rietveld refinement of powder X-ray diffraction data on pure phase α-UO 3 collected in this work allows us to propose an alteration to the currently accepted C2mm structure (a = 3.9705 Å, b = 6.8553 Å, c = 4.15955 Å, α = β = γ = 90°) for α-UO 3 with no uranyl [UO 2 2+ ] bonds. Raman spectra collected using two excitation wavelengths (two instruments using 532 nm and one 785 nm) are presented, and differences with recently published results are discussed. Infrared spectra from two instruments used here agree well with recently published results, but the spectral range encompassed in our data extends past what has been reported with modern techniques. Additionally, we provide tentative vibrational mode assignments based on density functional perturbation theory calculations and resulting phonon eigenvector visualizations. Unexpected features in the optical vibrational spectra of α-UO 3 are explained by unique features in the structure we present.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2026

Distributed Quantum-Enhanced Optimization: A Topographical Preconditioning Approach for High-Dimensional Search

Optimization problems become fundamentally challenging as the number of variables increases. Because the volume of the search space grows exponentially, classical algorithms frequently fail to locate the global minimum of non-convex functions. While quantum optimization offers a potential alternative, mapping continuous problems onto near-term quantum hardware introduces severe scaling limits and barren plateaus. To bridge this gap, we propose the Distributed Quantum-Enhanced Optimization (D-QEO) framework. Instead of forcing the quantum processor to find the exact minimum, we use it simply as a topographical preconditioner. The QPU maps the landscape to locate the most promising basin of attraction, generating high-quality seed points for a classical GPU-accelerated solver to refine. To make this approach viable for utility-scale problems, we exploit the mathematical structure of separable functions. This allows us to cut a 50-qubit (i.e., $2^{50}$) global search space into independent and manageable sub-spaces using 5-qubit subcircuits. By executing these fragments concurrently with CUDA-Q, we completely bypass the overhead of cross-register entanglement and classical tensor knitting for separable functions. Benchmarks on the 10-dimensional Rastrigin and Ackley functions show that D-QEO prevents the exponential failure rates observed in purely classical algorithms. Furthermore, this quantum warm-start significantly reduces the number of classical BFGS iterations required to converge, providing a highly practical blueprint for utilizing near-term quantum resources in complex global search.

Soos, Dominik [Old Dominion U.]↗
DOE OSTI2025

Shifting and tilting towards enhanced piezoelectricity in high-temperature ceramics: an average structure study of (1 − x )BiFe 2/8 Ti 3/8 Mg 3/8 O 3 – x PbTiO 3 through X-ray and neutron diffraction

A comprehensive report is provided of the average structure of a high Curie temperature ferroelectric ceramic, (1 − x)BiFe 2/8 Ti 3/8 Mg 3/8 O 3 –xPbTiO 3 (BFTM–xPT) when x = 0.25–0.375 at room temperature. Both neutron and synchrotron X-ray powder diffraction data were collected and combined Rietveld refinements were completed. These data revealed that, of the compositions studied, BFTM–xPT crystallizes as mixed phase material. At x = 0.25–0.275, the average structure of each phase is best described by space groups R3c and Cc. At 0.30 ≥ x ≥ 0.35, a morphotropic phase boundary is present and is best modelled by space groups P4mm and Cc, where space group Cc is the dominant phase. As the concentration of PbTiO 3 increases, the amount of octahedral tilting decreases and x = 0.375 exhibits a loss of octahedral tilting and crystallizes in space groups P4mm and Cm. In conclusion, an updated phase diagram at room temperature of this novel system is given and structural intricacies responsible for its piezoelectric properties are revealed.

high Curie temperature↗
DOE OSTI2025

Sensitive detection of structural dynamics using a statistical framework for comparative crystallography

Chemical and conformational changes are crucial to protein function and its pharmacological control. X-ray crystallography can reveal these changes in atomic detail, but standard analysis methods, which refine separate datasets, often overlook differences that are subtle or arise in only a subset of molecules. Direct comparison of crystallographic datasets is, in principle, more powerful, but systematic errors (“scales”) often mask changes in the crystallographic observables (“structure factors”). Machine learning algorithms that jointly estimate scales and structure factors can address this limitation. Here, we augment this approach with multivariate, structured priors derived from crystallographic theory, implemented in the variational deep learning framework Careless. Doing so strongly improves the detection of protein dynamics, element-specific anomalous signals, and the binding of drug candidates, offering a robust approach to comparative crystallography and, potentially, to detection of protein dynamics by other structure determination methods.

Hekstra, Doeke R. [Harvard Univ., Cambridge, MA (U↗
DOE OSTI2025

d -Electron Heavy Fermion Behavior in a Near-Room-Temperature Polar Metallic Ferrimagnet: A Case of Mn 5 SiC

Polycrystalline Mn 5 SiC was synthesized by using a high-temperature solid-state method. Mn 5 SiC adopts a polar space group (Cmc2 1 ) with six crystallographic Mn sites confirmed by X-ray and neutron diffraction, transmission electron microscopy, and second harmonic generation experiments. The complex crystal structure features edge-sharing trigonal prisms and icosahedra, as well as face/edge-sharing pentagonal prisms. Magnetic measurements indicate ferrimagnetic ordering with a transition temperature of 284 K. The ferrimagnetic structure (magnetic space group Cm’c’2 1 ) was further identified by powder neutron diffraction, where collinear Mn spins align along the crystallographic c-axis. The refined magnetic moment for each crystallographic Mn site at 4 K is 1.8(2), −2.42(9), −1.72(8), 0.51(6), 0.50(4), and 1.7(2) μ B . Density functional theory calculations confirm both the metallic behavior and the ferrimagnetic structure observed experimentally and further provide insight into the observed Mn moment dependence across crystallographic sites. The resistivity and specific heat measurements and density functional theory calculations reveal a substantially large Kadowaki–Woods ratio of 5 × 10 –5 μΩ·cm/(mJ/mol) 2 and a many-body renormalization factor of 5.5, indicating the unusual heavy Fermion behavior in such an itinerant magnetic metal.

Messegee, Zachary T. [George Mason University, Fai↗
DOE OSTI2025

Influences of shock imprinting on mix in a 3D-printed porous media

Mixing of materials in porous media can cause a significant impact on fusion yield as previously demonstrated by the National Ignition Facility (NIF) MARBLE Campaign. Initially, the reactants are separated, with deuterium in the lattice struts and a tritium gas fill in the voids. Lattice parameters such as the strut thickness and relative pitch, provide a control for the mix parameters in the experiment. Los Alamos National Laboratory’s (LANL) BOSQUE project looks to better understand how the mix of the reactants and shell materials impact the fusion burn and resultant yield on various laser platforms. xRAGE’s Eulerian hydrodynamics and adaptive mesh refinement (AMR) provide the unique ability to study the impacts of multiscale features of complex lattice structures. This modeling provides the ability to measure shock front variations as the wave progress’ through a given media. Initial conditions of the lattice are essential to accurately model mix and burn measured by experiment. By varying the initial orientation and densities of these lattice regions the early time dynamics of how the shock is launched into the system is changed and advocates for the study of resulting effects. In this work, we will study the sensitivities of shock effects in varying 3D printed geometric systems and how these shocks alter the structure and mix in the lattice. We will discuss both preliminary experimental results and simulations to help plan and constrain future experiments where we will study the impact of different lattice geometries and lattice bulk densities. This work concludes with the relative impacts of lattice geometries on shock speeds at different bulk densities and the resultant mix widths due to those shock interactions. We see agreement with theory at the higher end of our bulk density study, however, as we approach lower bulk density systems the dynamics of these interactions begin to change.

2 Photon Polymerization↗
DOE OSTI2024

Assessment of effective elastic constants of U-10Mo fuel: A multiscale modeling and homogenization study

The significant microstructural changes that U-Mo fuel undergoes during operation degrades its mechanical properties and structural integrity. Microstructural evolution entails the formation, evolution, and redistribution of porosity in conjunction with grain refinement. In the present paper, we employ numerical approaches to assess the impact of the various microstructural features—grains, nanoscale intragranular fission gas bubbles, and mesoscale intergranular voids—on the degradation of elastic constants. Phase-field microstructure models are combined with the asymptotic expansion homogenization technique in order to derive the effective elastic constants as a function of porosity and fission density. Here the results are verified and compared against theoretical bounds. Using this approach, elastic degradation in operating nuclear fuels can be quantified when the distributions of microstructural features are known.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Co nanoclusters derived from zinc-trimesic acid fiber for efficient levulinic acid hydrogenation

The hydrogenation of levulinic acid (LA) to γ-valerolactone (GVL) is significant for producing chemicals and fuels from renewable resources, a promising direction in biomass refining. Currently, non-precious metal catalysts suffer from low activity due to a single electronic structure, which is incapable of effectively activating both CO in LA and H 2 . Herein we report in situ fabricated Co nanoclusters within positive and metallic Co sites on N-doped carbon, which can simultaneously activate LA's CO and H 2 , enhancing the activity and selectivity for GVL production. Urea-assisted Co dispersion coupled with variation of pyrolysis temperature, Co nanoclusters were formed via direct conversion of Co-containing zinc trimesic acid fibers. The resulting Co nanoclusters possess dual active sites of Co-N x and metallic Co, with adjustable electronic structures. Under the reaction conditions of 200 °C and 4.5 MPa H 2 for 4 h, LA was completely converted, achieving 95 % yield of GVL. The outstanding catalytic activity is attributed to the Co-N x and metallic Co active sites, which facilitate the activation of CO and H 2 , respectively. In conclusion, this research provides a new concept for converting N-free metal-organic frameworks into non-precious metal nanoclusters, offering valuable insights for designing high-performance non-precious metal catalysts for biomass-derived chemical and fuel production.

Co nanoclusters↗
DOE OSTI2025

Modeling the Interaction of Laser-Produced Proton Beams with Matter

A major goal of this project is to significantly increase our understanding of isochoric heating of matter using laser produced proton beams, and the associated high energy density (HED) and warm dense matter (WDM) regimes generated. This will benefit research fields such as planetary science, fusion energy, plasma physics, and material science. For example, it will enhance our understanding of WDM properties of iron and silica under conditions encountered in planetary interiors and diagnostic components in fusion devices exposed to high fluxes of energetic plasma ions. The project is motivated by recent experiments that irradiated Si targets with proton beams generated by the 20 TW-laser at the SLAC MEC end-station. The HED/WDM states are probed using the 50 fs hard X-rays available in the 3rd harmonic of the LCLS. As part of this project, results from the phase contrast X-ray imaging, which shows the generation of compression waves that produces rear surface spallation, are compared with results from the 3D multi-physics multi- material code, PISALE, that combines Arbitrary Lagrangian-Eulerian (ALE) hydrodynamics with Adaptive Mesh Refinement (AMR). This comparison required modifications to several physics models in the PISALE (Pacific Island Structured-AMR with ALE) code. An important aspect of this project is the continued training of graduate students in HED physics and in conducting complex multiphysics simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Deployable UHV Pump

This project presents an external motorized actuation system for a deployable ultra-high vacuum (UHV) pump, enabling internal motion without compromising vacuum conditions. All active components remain external due to environmental and space constraints. A motor-driven mechanical feedthrough transfers motion into the pump, supported by a modular, adjustable mounting system that maintains alignment and integrates with existing hardware. CAD modeling and iterative design were used to refine geometry and ensure proper fit. The final design reliably transfers motion while maintaining alignment and structural integrity. Its adjustability improves installation and maintenance, demonstrating a practical solution for actuation in UHV systems.

Remington, Austin [Northern Illinois U.]↗
DOE OSTI2024

New insights into supradense matter from dissecting scaled stellar structure equations

The strong-field gravity in general relativity (GR) realized in neutron stars (NSs) renders the equation of state (EOS) P(ε) of supradense neutron star matter to be essentially nonlinear and refines the upper bound for Φ ≡ P/ε to be much smaller than the special relativity (SR) requirement with linear EOSs, where P and ε are respectively the pressure and energy density of the system considered. Specifically, a tight bound Φ ≲ 0.374 is obtained by perturbatively anatomizing the intrinsic structures of the scaled Tolman–Oppenheimer–Volkoff (TOV) equations without using any input nuclear EOS. New insights gained from this novel analysis provide EOS-model-independent constraints on the properties (e.g., density profiles of the sound speed squared s 2 = dP/dε and trace anomaly Δ = 1/3 – Φ) of cold supradense matter in NS cores. Using the gravity-matter duality in theories describing NSs, we investigate the impact of gravity on supradense matter EOS in NSs. In particular, we show that the NS mass M NS , radius R, and compactness ξ ≡ M NS /R scale with certain combinations of its central pressure and energy density (encapsulating its central EOS). Thus, observational data on these properties of NSs can straightforwardly constrain NS central EOSs without relying on any specific nuclear EOS model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

A general flame aerosol route to high-entropy nanoceramics

High-entropy ceramics are an emerging class of materials with fascinating characteristics. However, elemental immiscibility and crystal complexity limit the development of a general synthesis strategy, and common methods yield bulk materials. Here, we introduce a transformative non-equilibrium flame aerosol technique for synthesizing high-entropy nanoceramics. This scalable, one-step process enables the production of high-entropy oxide nanoceramics with an unprecedented diversity of crystal structures, including fluorite-phase materials that integrate up to 22 distinct cation elements. The method’s capacity for entropic stabilization and grain refinement significantly improves the thermal stability of these nanostructures. In a representative application, a Pt-(MgCoNiCuZn)O high-entropy single-atom catalyst showed superior activity and long-term stability, maintaining constant CO 2 conversion over 670 h and dramatically outperforming conventional catalysts. Finally, the general approach opens a vast composition and structure space for the creation of high-entropy oxide nanomaterials for application across diverse fields, including catalysis, energy storage, sensing, and thermal management.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Accelerating the Structure Exploration of Diverse Bi–Pt Nanoclusters via Physics‐Informed Machine Learning Potential and Particle Swarm Optimization

Bimetallic Bi–Pt nanoclusters exhibit diverse structural motifs, including core-shell, Janus, and mixed alloy configurations, due to the unique bonding characteristics between Bi and Pt atoms. Using density functional theory refinements from ChIMES physically machine-learned potential and CALYPSO particle swarm optimization global searches, 34 Bi20-Pt20 nanoclusters are systematically classified. The results reveal that Bi atoms predominantly occupy surface sites, driven by charge transfer effects. Cohesive energy trends alone prove insufficient for structure differentiation, necessitating a data-driven approach employing principal component analysis and K-means clustering. Furthermore, vibrational, electronic, and infrared spectral analyses provide additional insights into structure-property relationships. The findings offer an original framework for the automated classification and analysis of bimetallic nanoclusters, enhancing the understanding of their stability and functional properties.

bimetallic nanoparticles↗
DOE OSTI2025

STILGAR End-of-Project Report

The Subsurface Tunnel Imaging LeveraGed by Analysis of Rayleigh wave ellipticity (STILGAR) project demonstrated an integrated geophysical approach for detecting, locating, and characterizing underground structural changes using dense seismic arrays and advanced inversion techniques. Field campaigns were conducted at two operational mines—the Redmond salt mine (Utah) and Graymont Pleasant Gap limestone mine (Pennsylvania)—providing real-world testbeds for monitoring anthropogenic subsurface activity. At the Redmond salt mine, seismic interferometry combined with back-projection inversion successfully identified continuous, low-amplitude signals from mining operations. The approach differentiated stationary from migrating anthropogenic sources, captured daily operational cycles, and validated the potential of passive seismic monitoring for remote detection of underground activity. At the Graymont Pleasant Gap mine, two dense seismic deployments in the spring and fall of 2023 generated over 4 TB of high-resolution data. Key outcomes included the relocation of 199 underground and 8 surface explosions with accuracies within tens of meters and the development of a 3D P-wave velocity model using the triple-difference tomography algorithm (tomoTD) that resolved major structural features such as the mine entrance, low-velocity tunnels, and roof-collapse areas. Ambient noise cross-correlation and back-projection analyses revealed persistent sources linked to ongoing mining activity, whereas horizontal-to-vertical spectral ratio (HVSR) and ellipticity studies confirmed stable site responses across seasons and identified soil thickness trends consistent with regional erosional and depositional processes. Checkerboard and sensitivity tests further validated the robustness of the tomographic results. Overall, the findings emphasize that although significant progress has been made in subsurface imaging, further work is needed to enhance the detection and localization of underground structures. Accurate imaging requires higher frequencies, yet anthropogenic sources tend to dominate the seismic record at those frequencies, and high-frequency surface waves are affected by higher modes that complicate interpretation. The improved detection and localization of human-induced signals enabled detailed temporal and spatial mapping of daily mine operations, demonstrating the feasibility of continuous anthropogenic source monitoring. Sensitivity to signals from nontraditional sources, such as fan operations, highlights the broader applicability of this approach to other industrial environments in which continuous and impulsive signals are present. The field campaigns produced a substantial volume of high-quality seismic data, supporting the development and testing of new methods for seismic source characterization and subsurface imaging. Future deployments should include sensors capable of recording lower frequencies to probe deeper structures, increase bandwidth to enhance resolution and sensitivity to both shallow and deep targets, and collect additional large-scale datasets to refine imaging and source characterization techniques. Moreover, conducting 3D modeling studies of seismic wavefields at higher frequencies will provide a better understanding of wave scattering and cavity–wavefield interactions in complex underground environments. In conclusion, the STILGAR project demonstrated that integrated seismic monitoring can effectively characterize underground operations, capturing both natural and anthropogenic signals. The approaches developed provide a foundation for improved detection, localization, and imaging of subsurface structures and are directly transferable to broader industrial monitoring applications.

58 GEOSCIENCES↗