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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Semiconducting Electrides Derived from Sodalite: A First-Principles Study

Electrides are ionic crystals, with electrons acting as anions occupying well-defined lattice sites. These exotic materials have attracted considerable attention in recent years for potential applications in catalysis, rechargeable batteries, and display technology. Among this class of materials, electride semiconductors can further expand the horizon of potential applications due to the presence of a band gap. However, there are only limited reports on semiconducting electrides, hindering the understanding of their physical and chemical properties. In recent work, we initiated an approach to derive potential electrides via selective removal of symmetric Wyckoff sites of anions from existing complex minerals. Herein, we present a follow-up effort to design semiconducting electrides from parental complex sodalites. Among four candidate compounds, we found that a cubic Ca 4 Al 6 O 12 structure with the I-43m space group symmetry exhibits perfect electron localization at the sodalite cages, with a narrow electronic band gap of 1.8 eV, making it suitable for use in photocatalysis. Analysis of the electronic structures reveals that a lower electronegativity of the surrounding cations drives greater electron localization and promotes the formation of an electride band near the Fermi level. Our work proposes an alternative approach for designing new semiconducting electrides under ambient conditions and offers guidelines for further experimental exploration.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Phase 1 Engagement Summary: Rural Alabama

An Alabama community coalition received technical assistance through the U.S. Department of Energy's Communities Local Energy Action Program (LEAP) to expand awareness of alternative transportation fuels through stakeholder engagement efforts. Phase 1 of the project centered on outreach, relationship-building, and the identification of community priorities. Through two workshops held in October and December 2024, the coalition engaged over 120 stakeholders - including county commissioners, school district representatives, and public and private fleet operators. These sessions included presentations from technical experts and industry partners, as well as a vehicle showcase and structured discussions to assess stakeholder needs and concerns. This report summarizes these efforts and identifies three key priority areas for Phase 2 of the project.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Evidence for large baryonic feedback at low and intermediate redshifts from kinematic Sunyaev-Zel’dovich observations with ACT and DESI photometric galaxies

Recent advances in cosmological observations have provided an unprecedented opportunity to investigate the distribution of baryons relative to the underlying matter. In this work, we show that the gas is more extended than the dark matter, and the amount of baryonic feedback at $z \lesssim 1$ disfavors low-feedback models such as that of state-of-the-art hydrodynamical simulation IllustrisTNG compared with high-feedback models such as that of the original Illustris simulation. This has important implications for bridging the gap between theory and observations and understanding galaxy formation and evolution. Furthermore, a better grasp of the baryon-dark matter link is critical to future cosmological analyses, which are currently impeded by our limited knowledge of baryonic feedback. Here, we measure the kinematic Sunyaev-Zel'dovich (kSZ) effect from the Atacama Cosmology Telescope (ACT), stacked on the luminous red galaxy (LRG) sample of the Dark Energy Spectroscopic Instrument (DESI) imaging survey. This is the first analysis to use photometric redshifts for reconstructing galaxy velocities. Due to the large number of galaxies comprising the DESI imaging survey, this is the highest signal-to-noise stacked kSZ measurement to date: we detect the signal at 13$σ$, finding strong evidence that the gas is more spread out than the dark matter, as well as a preference for larger feedback compared to some commonly used state-of-the-art hydrodynamical simulations. Here, our work opens up the possibility of recalibrating large hydrodynamical simulations using the kSZ effect. In addition, our findings highlight the importance of properly accounting for baryonic feedback with future surveys such as LSST through direct probes such as the kSZ, and shed light on long-standing enigmas in astrophysics, such as the “missing baryon” problem.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Surface analysis insight note: Illustrating the effect of adventitious contamination on Pt photoemission peak intensities

Adventitious carbon contaminations are not only omnipresent and used for charge referencing of XPS spectra but also can alter the apparent presence of the element peaks that span over the large spectral window of binding energies. This Insight note describes the effect of an adventitious contamination layer on Pt and presents, in brief, the approach whereby the component spectra are derived for ion beam cleaned Pt samples that can then utilize linear mathematics to peak fit said spectra thus quantifying the amount of each component including that assigned to the contamination itself of Pt metal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Two-mode bosonic quoctit for high energy physics

In this work, we study a two-mode bosonic encoding of a quoctit inside a non-Abelian group-structured constellation of coherent states. This work is motivated by the importance of non-Abelian symmetry in particle physics and the desire to have transversal non-Abelian logical gates. We use the previously developed 2 T constellation of states used to encode a so-called 2 T qutrit. The fidelity of the 2 T quoctit is benchmarked against other bosonic qudits for different noise models and find it compare favorably when power constraints are considered. This paves the way for the construction of higher-dimensional qudits (e.g., a quicosotetrit with 2 T group structure) in bosonic systems with practical applications in quantum simulations of particle physics.

Kürkçüoglu, Doga Murat [Fermilab] (ORCID:000000031↗
DOE OSTI2023

Enhanced Optical Contrast and Switching in Near‐Infrared Electrochromic Devices by Optimizing Conjugated Polymer Oligo(Ethylene Glycol) Sidechain Content and Gel Electrolyte Composition

Abstract A detailed investigation addressing the effects of functionalizing conjugated polymers with oligo(ethylene glycol) (EG n ) sidechains on the performance and polymer‐electrolyte compatibility of electrochromic devices (ECDs) is reported. The electrochemistry for a series of donor‐acceptor copolymers having near‐infrared (NIR)‐optical absorption, where the donor fragment is 3,4‐ethylenedioxythiophene (EDOT) or an EG n functionalized bithiophene (g2T) and the acceptor fragment is diketopyrrolopyrrole (DPP) functionalized with branched alkyl or EG n sidechains, is extensively probed. ECDs are next fabricated and it is found that EG n sidechain incorporation must be finely balanced to promote polymer‐electrolyte compatibility and provide efficient ion exchange. Proper electrolyte‐cation pairing and polymer structural tuning affords a 2x increase in optical contrast (from 12% to 24%) and >60x reduction in switching time (from 20 to 0.3 s). Atomic force microscopy (AFM)/grazing incidence wide‐angle X‐ray scattering (GIWAXS) characterization of the polymer film morphology/microstructure reveals that an over‐abundance of EG n sidechains generates large polymer crystallites, which can suppress ion exchange. Lastly, time‐of‐flight secondary ion mass spectrometry (ToF‐SIMS) indicates sidechain/electrolyte identity does not influence the electrolyte penetration depth into the films, and EG n sidechain inclusion increases electrolyte cation uptake. The material structural design insight and guidelines regarding the polymer‐electrolyte ion insertion/expulsion dynamics reported here should be of significant utility for developing next‐generation mixed ionic‐electronic conducting materials.

Chemistry↗
DOE OSTI2026

Monolayer Films of Binary Metal Oxide Nanoparticles for Carbon Nanotube Synthesis

Binary metal oxide nanoparticles (biMO-NPs) combining transition and main-group metals with well-organized atomic architectures have unique potential as robust and economical heterogeneous catalysts. Herein, metal oxide nanoparticles (CoAlxOy) using cobalt and aluminum were synthesized, and their structure, morphology, and chemical composition were investigated using various characterization techniques. The biMO-NPs, which had a Gaussian-type size distribution (∼6 nm), were assembled on plain silicon substrates modified chemically with linker molecules bearing suitable end groups. Surface analysis revealed an ordered, uniform, close-packed arrangement of biMO-NPs forming a monolayer architecture with nanoscale thickness (∼12 nm), high surface uniformity, and negligible defects. The nanoparticle monolayer film (NP-MF) was employed as a catalyst to grow carbon nanotube (CNT) forests via the thermal chemical vapor deposition (CVD) method, similar to those grown from catalyst thin films deposited by physical vapor deposition. Structural characterization confirmed the growth of a dense, uniform, high-quality vertically aligned carbon nanotube (VA-CNT) forest with a length of ∼125 µm, which is comparable to the VA-CNTs grown from expensive thin films. Thus, CNT growth was successfully catalyzed by the biMO-NPs, highlighting a simple and inexpensive alternative for catalyst deposition. In this innovative wet-chemistry approach, the catalyst and catalyst support are combined within a single nanoparticle before NP-MF assembly. Interestingly, this approach provides a scalable and cost-effective pathway for CNT growth, eliminating the need for expensive thin deposition techniques.

Regmi, Bishow [University of Cincinnati]↗
DOE OSTI2024

Photoelectrochemical Proton-Coupled Electron Transfer of TiO 2 Thin Films on Silicon

TiO 2 thin films are often used as protective layers on semiconductors for applications in photovoltaics, molecule–semiconductor hybrid photoelectrodes, and more. Experiments reported here show that TiO 2 thin films on silicon are electrochemically and photoelectrochemically reduced in buffered acetonitrile at potentials relevant to photoelectrocatalysis of CO 2 reduction, N 2 reduction, and H 2 evolution. On both n-type Si and irradiated p-type Si, TiO 2 reduction is proton-coupled with a 1e – :1H + stoichiometry, as demonstrated by the Nernstian dependence of the Ti 4+/3+ E 1/2 on the buffer pK a . Experiments were conducted with and without illumination, and a photovoltage of ∼0.6 V was observed across 20 orders of magnitude in proton activity. The 4 nm films are almost stoichiometrically reduced under mild conditions. The reduced films catalytically transfer protons and electrons to hydrogen atom acceptors, based on cyclic voltammogram, bulk electrolysis, and other mechanistic evidence. TiO 2 /Si thus has the potential to photoelectrochemically generate high-energy H atom carriers. Characterization of the TiO 2 films after reduction reveals restructuring with the formation of islands, rendering TiO 2 films as a potentially poor choice as protecting films or catalyst supports under reducing and protic conditions. Altogether, this work demonstrates that atomic layer deposition TiO 2 films on silicon photoelectrodes undergo both chemical and morphological changes upon application of potentials only modestly negative of RHE in these media. While the results should serve as a cautionary tale for researchers aiming to immobilize molecular monolayers on “protective” metal oxides, the robust proton-coupled electron transfer reactivity of the films introduces opportunities for the photoelectrochemical generation of reactive charge-carrying mediators.

Electrodes↗
DOE OSTI2026

Complex-Concentrated Anion Doping Enables Ultra-Stable Lattice Oxygen and Structural Integrity in Lithium-Rich Layered Oxide Cathodes

Lithium- and manganese-rich layered oxides (LMR) stand out as next-generation lithium-ion cathode chemistries, which harness both transition-metal and lattice-oxygen redox processes to deliver exceptional capacity and energy density. However, their full potential is hindered by intrinsic oxygen instability and structural degradation, resulting in pronounced voltage fade and capacity decay. Here, we present a complex-concentrated anion-doping paradigm in which multiple anions, F, Br, and S, are incorporated into the oxygen sublattice to enhance oxygen-redox and structural stability. X-ray absorption spectroscopy and aberration-corrected scanning transmission electron microscopy confirm ultra-stable local oxygen coordination environments during long-term cycling, with detrimental phase transformations and oxygen-loss-induced cavitation dramatically inhibited. Notably, we show that the characteristic LiTM6 transition metal (TM) honeycomb ordering is preserved even after electrochemical cycling. Concurrently, this strategy yields an unprecedented volume change of only 0.63% upon charging to 4.8 V vs. Li+/Li, achieving the first zero-strain LMR cathode. The resulting LMR cathode delivers ultralow voltage fade (1 mV per cycle during the first 100 cycles and becomes negligible in subsequent cycles) and outstanding energy retention (93% after 200 cycles) in a pouch cell configuration. Our complex-concentrated anion-doping concept establishes a broadly applicable strategy for resolving chemo-mechanical failure mechanisms in ceramic intercalation electrodes for next-generation energy storage.

Li-ion batteries↗
DOE OSTI2026

UCB-GLOBES: An open-access mass spectral database of identified and unidentified atmospheric organic compounds

Chemical characterization of atmospheric organic aerosols using gas chromatography with 70 eV electron ionization mass spectrometry (GC/EI-MS) has been used for decades in advancing molecular marker detection and identification, though primarily through suspect screening and/or targeted analyses. To advance non-targeted analyses of environmental samples, we have catalogued approximately 27 000 mass spectra (MS) of the trimethylsilyl derivatives of semi-volatile organic aerosol (OA) analytes in the open-access University of California Berkeley Goldstein Library of Organic Biogenic Environmental Spectra (UCB-GLOBES). Analytes were observed in ambient samples from the U.S. and the Central Amazon and/or laboratory simulations of secondary OA (SOA) formation. These samples are representative of OA under urban and biomass burning influences as well as SOA derived from biogenic precursors (e.g., isoprene, monoterpenes, sesquiterpenes) and biomass burning intermediates. MS are documented in UCB-GLOBES without regard to known chemical identity, annotated with extensive metadata such as sample source/experimental conditions, any structural information gained from MS analyses, and predicted chemical properties such as average carbon oxidation state and carbon number. UCB-GLOBES MS are compatible for importing into the NIST MS Search program, and we have also provided a Jupyter Notebook for MS visualization and comparisons. We demonstrate the utility of UCB-GLOBES through MS reanalyses of prior analytes observed in ambient data, finding a 20 % reduction in the number of analytes assigned to OA source categories reliant solely on time series correlation and an overall 11 % increase in new MS-based OA source categorization for the Southeast U.S. For 1513 analytes observed previously in the Central Amazon, we found 375 MS matches using UCB-GLOBES vs. 136 MS matches during prior analyses, representing a 14 % gain in newly confirmed or newly categorized OA species. While OA from laboratory oxidation experiments in UCB-GLOBES are highly diverse chemically, on average only 29 % of UCB-GLOBES MS have a mass spectral match to another MS entry in UCB-GLOBES and/or in databases of known compounds (i.e. NIST MS Database, Adams Essential Oil, MANE Flavor and Fragrance Company). This indicates that roughly 70 % of UCB-GLOBES MS are unique thus far, not observed more than once among the laboratory oxidation samples and ambient data in UCB-GLOBES MS. Further, only 18 % can be positively identified using these databases or known authentic standards. This points to a large gap between these laboratory simulations and ambient OA. Overall, the UCB-GLOBES database can be utilized for improving confidence in OA source categorization and/or identification, novel chemical marker discovery, tracking chemical diversity, de novo structure and properties prediction, and improving MS search and matching algorithms. This can ultimately inform future research priorities for the chemical characterization of atmospheric organic samples.

Mass spectrometry↗
DOE OSTI2026

Improving the Performance of NEML2 with Modern Graph Compilation Backends

NEML2 vectorizes constitutive-model evaluation for large-scale multiphysics simulation, using PyTorch as its tensor backend so that a batch of material-point updates runs on CPU or GPU through a single implementation. In the two prior reports in this series it was a C++-native library, deployed through TorchScript tracing and just-in-time (JIT) compilation; it has since been rewritten from the ground up into a Python-native library deployed through Ahead-of-Time Inductor (AOTInductor), a modern PyTorch graph-compilation backend. The rewrite is driven by a persistent tension, not a language preference: NEML2 composes constitutive models at runtime from a registry of small, independently-authored pieces, and that flexibility is difficult to reconcile with the compile-time knowledge an efficient GPU kernel needs. This report documents the rewrite and the investment that accompanied it: the AOTInductor export pipeline that turns a Python-authored model into a portable, Python-free compiled artifact loadable from pure C++; the eager and compiled runtimes and the new implicit solver layer built on them; a head-to-head benchmark of legacy JIT against AOTInductor; the physics-model catalog and its worked examples; the developer tooling; and the corresponding overhaul of MOOSE’s NEML2 integration that lets MOOSE consume it. A central objective is to examine whether modern PyTorch graph-compilation backends are effective for MOOSE GPU integration. The benchmark answers directly: AOTInductor outperforms legacy JIT on every GPU scenario measured, by 1.0–4.5×. Modern graph-compilation backends are effective for MOOSE GPU integration, and AOTInductor specifically – not compilation in the abstract – is why.

Hu, Gary (Tianchen) [Argonne National Laboratory (↗
DOE OSTI2026

Impact of Crystalline Phases on Low-Activity Waste Glass Durability: Insights from PCT and VHT

During vitrification of nuclear wastes, slow cooling along the container centerline promotes crystalline phase formation, which can alter residual glass composition and reduce chemical durability. This study investigates the effects of crystalline phases on the chemical durability of low-activity waste (LAW) borosilicate glasses using the product consistency test (PCT) and vapor hydration test (VHT) on container centerline cooled (CCC) samples. A preliminary model (R2 = 0.88) was developed to predict CCC PCT responses based on glass composition, PCT data from quenched glasses, and measured crystal fractions. Using the latest LAW glass dataset, the feasibility of predictive modeling is evaluated, limitations in current data and methods are identified, and challenges for improving model accuracy are discussed to guide future data collection and model development.

borosilicate glass↗
DOE OSTI2024

The S-PLUS Fornax Project (S+FP): A first 12-band glimpse of the Fornax galaxy cluster

ABSTRACT The Fornax galaxy cluster is the richest nearby (D ∼ 20 Mpc) galaxy association in the southern sky. As such, it provides a wealth of opportunities to elucidate on the processes where environment holds a key role in transforming galaxies. Although it has been the focus of many studies, Fornax has never been explored with contiguous homogeneous wide-field imaging in 12 photometric narrow and broad bands like those provided by the Southern Photometric Local Universe Survey (S-PLUS). In this paper, we present the S-PLUS Fornax Project (S+FP) that aims to comprehensively analyse the galaxy content of the Fornax cluster using S-PLUS. Our data set consists of 106 S-PLUS wide-field frames (FoV∼1.4 × 1.4 deg2) observed in five Sloan Digital Sky Survey-like ugriz broad bands and seven narrow bands covering specific spectroscopic features like [O ii], Ca ii H+K, Hδ, G band, Mg b triplet, Hα, and the Ca ii triplet. Based on S-PLUS specific automated photometry, aimed at correctly detecting Fornax galaxies and globular clusters in S-PLUS images, our data set provides the community with catalogues containing homogeneous 12-band photometry for ∼3 × 106 resolved and unresolved objects within a region extending over ∼208 deg2 (∼5 Rvir in RA) around Fornax’ central galaxy, NGC 1399. We further explore the eagle and IllustrisTNG cosmological simulations to identify 45 Fornax-like clusters and generate mock images on all 12 S-PLUS bands of these structures down to galaxies with M⋆ ≥ 108 M⊙. The S+FP data set we put forward in this first paper of a series will enable a variety of studies some of which are briefly presented.

Astronomy & Astrophysics↗
DOE OSTI2026

High-resolution modeling of indoor radon exposure with uncertainty quantification in Utah

Indoor radon accounts for 37% of population-level exposure to ionizing radiation in the United States. However, radon metrics are typically reported at coarse spatial scales, potentially obscuring meaningful local variation. We developed a high-resolution modeling framework to estimate indoor radon concentrations across Utah while explicitly quantifying predictive uncertainty. A total of 19,497 residential radon measurements collected between 2006 and 2017 were combined with environmental and housing characteristics and analyzed using a geospatial neural network that accommodates spatial dependence and nonlinear associations. Predictions were generated on a uniform hexagonal grid at 0.73 km2 resolution (H3 level 8). Out-of-sample predictions aggregated to the H3 level 8 grid showed good agreement with observed concentrations (Pearson r=0.64), while household-level predictions exhibited more moderate agreement (r=0.45). The model produced well-calibrated uncertainty estimates, with 24.1% of held-out observations exceeding the predicted 75th-percentile threshold. Maps of predicted radon concentrations and the probability of exceeding the U.S. EPA action level of 148 Bq/m3 (4 pCi/L) revealed substantial fine-scale spatial heterogeneity that was not apparent in conventional coarse-resolution summaries, with greater local variability observed in densely monitored urban counties than in sparsely sampled regions. High-resolution radon models that explicitly quantify uncertainty provide a useful framework for characterizing the spatial distribution of indoor radon and identifying areas of elevated exceedance risk. These findings highlight the value of fine-scale monitoring data and uncertainty-aware modeling approaches for radon exposure assessment, environmental risk characterization, and radon-related health research.

Wu, Yunhan [ORNL] (ORCID:0000000178842994)↗
DOE OSTI2026

A comparison of wrought and powder metallurgical FeCrAl claddings under simulated LWR accident transients

Iron-chromium-aluminum (FeCrAl) alloys are potential accident tolerant fuel (ATF) cladding candidates for light-water reactors but are difficult to fabricate as thin-walled tubes via conventional cast-and-wrought routes. Powder metallurgy (PM) offers a manufacturing alternative with improved compositional control, but its transient accident performance has not been directly benchmarked against wrought variants. This study evaluates the burst behavior of commercially developed PM-processed FeCrAl alloys, PM-C26M (Fe-12Cr-6Al-2Mo) and the high precipitate density FA-SMT (Fe-22Cr-5Al-3Mo), under simulated light-water reactor accident transient conditions. Burst testing was conducted using the Severe Accident Test Station with heating rates of 5 °C/s and 50 °C/s and internal pressures ranging from 25 MPa to 100 MPa. PM-C26M reproduced wrought C26M burst behavior within 7–37 °C across the stress range, indicating that PM processing does not compromise transient strength. FA-SMT exhibited markedly higher burst temperatures and reduced heating-rate sensitivity, consistent with its engineered precipitate strengthening. FA-SMT rupture exhibited axial "unzipping" rather than the lateral tearing characteristic of PM- and wrought C26M. Post-test EBSD and fractography indicate that this behavior is strongly correlated with strain-gated intergranular void nucleation associated with the dense precipitate architecture of FA-SMT, a response absent in the comparatively clean PM-C26M matrix and consistent with rupture morphologies reported for oxide-dispersion strengthened (ODS) FeCrAl of similar base-matrix chemistry to PM-C26M. These findings highlight the potential of powder metallurgy as a viable fabrication route for ATF claddings from an accident performance standpoint.

Bell, Sam [ORNL] (ORCID:0000000251905657)↗
DOE OSTI2026

Advancing Protein Display on Bacterial Spores through an Extensive Survey of Coat Components

The profound stability of bacterial spores makes them a promising platform for biotechnological applications like biocatalysis, bioremediation, drug delivery, etc. However, though the Bacillus subtilis spore is composed of >40 types of proteins, only ∼12 have been explored as fusion carriers for protein display. Here, we assessed the suitability of 33 spore proteins (SPs) as enzyme display carriers by direct allele tagging at native genomic loci. Of the 33 SPs investigated, 26 formed functional fusions with β-glucuronidase (GUS)─a ∼272 kDa homotetramer. This almost triples the number of SPs assessed for enzyme display and doubles the number of functional fusions documented in the literature. We quantitatively assessed 1) SP promoter activation dynamics, 2) GUS activity on spores, 3) surface availability, and 4) protection from thermal and proteolytic degradation. Multicopy expression and pairwise coexpression of the most promising SP-GUS fusions highlighted the complexity of spore structure/assembly and the difficulty in predicting compatibility between different SP fusions. We also assessed the suitability of engineered spores to degrade PET (polyethylene terephthalate) films and found that surface-exposed SPs were most effective. Beyond the broad survey, a key outcome of our work was the identification of SscA (small spore coat assembly protein A) as an effective spore display carrier. SscA supported enzyme activity at least 4-fold higher than any other SP, including the well-established anchor, CotY. We attribute this to its promoter, which demonstrated early and sustained activation relative to other SPs and its small size (∼3 kDa), which likely minimally interferes with enzyme folding, oligomerization, and activity. Labeling and genetic studies, its hydrophobic nature, and low surface availability suggest that SscA assembles within the inner spore coat, which makes it stabilizing and suitable for many biocatalytic applications. Overall, this work serves as a knowledge base to advance the biotechnological utility of B. subtilis spores.

Bacillus subtilis↗
DOE OSTI2025

Bridging Additive Manufacturing and Electronics Printing in the Age of AI

Printing techniques have been instrumental in developing flexible and stretchable electronics, including organic light-emitting diode displays, organic thin film transistor arrays, electronic skins, organic electrochemical transistors for biosensors and neuromorphic computing, as well as flexible solar cells with low-cost processes such as inkjet printing, ultrasonic nozzle, roll-to-roll coating. The rise of additive manufacturing provides even more opportunities to print electronics in automated and customizable ways. In this work, we will review the current technologies of printing electronics (including printed batteries, supercapacitors, fuel cells, and sensors), especially with 3D printing. In this age of ongoing AI revolution, the application of AI algorithms is discussed in terms of combining them with 3D printing and electronics printing for a future with automated optimization, sustainable design, and customizable and scalable manufacturing.

Chemistry↗
DOE OSTI2026

Deep Learning and Photogrammetric Reconstruction for Automated Crack Detection and Dimensional Measurement in Mining Operations

Surface crack detection and dimensional measurement at active mining sites present significant safety and operational challenges. Manual inspection methods are labor-intensive, spatially incomplete, and expose personnel to hazardous environments, while existing automated approaches have been developed primarily for concrete civil infrastructure and have not been validated on the complex, variable surfaces characteristic of mining environments. This dissertation presents an automated pipeline that integrates deep learning semantic segmentation with Structure-from-Motion photogrammetry to detect surface cracks and measure their aperture, length, and vertical displacement from standard RGB imagery acquired during routine Uncrewed Aerial Vehicle (UAV) survey operations, without requiring additional sensor hardware or manual measurement. The pipeline combines a U-Net architecture with an EfficientNet-B0 encoder, pretrained on the SDNET2018 concrete crack dataset and fine-tuned on a mining-specific dataset spanning laboratory concrete specimens, coal refuse impoundment embankments, and post-blast limestone quarry benches. Photogrammetric reconstruction is performed using COLMAP Structure-from-Motion and Multi-View Stereo, with crack segmentation masks projected into the reconstructed point cloud to enable three-dimensional vertical displacement measurement through local plane fitting and bimodal surface detection. The pipeline was validated across 36 controlled laboratory specimens at three imaging distances and four vertical displacement levels, achieving aperture measurement RMSE of 0.047 cm and R² of 0.954, and vertical displacement RMSE of 0.140 cm and R² of 0.966, against independent caliper measurements. Field application at a coal refuse impoundment in southwestern Pennsylvania detected 71 crack components across the embankment crest, with a dominant longitudinal crack exhibiting aperture values reaching 28 cm and a 95th percentile vertical displacement of 35.53 cm, consistent in magnitude and spatial distribution with simultaneously acquired LiDAR-derived estimates. Application across four post-blast limestone quarry bench datasets in California successfully characterized blast-induced fracture networks at ground sampling distances ranging from 0.59 to 1.23 cm/pixel, with detected crack geometries physically consistent with observable surface conditions at each site. The results demonstrate that deep learning-based crack detection and photogrammetric measurement can be integrated into routine UAV inspection workflows at mining sites, providing repeatable, scalable, and quantitative crack characterization across surface types, crack scales, and displacement magnitudes not previously addressed in the literature. The pipeline requires no dedicated surveying equipment beyond the UAV platforms already deployed at mine sites for survey and monitoring purposes, supporting practical adoption within existing operational workflows.

Crack detection, Dimensional Measurement↗