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DOE OSTI2024

Flat and Level Analysis Tool (FLAT) for real-time automated segmentation and analysis of concrete slab point clouds

In the United States, the flatness and levelness of concrete floors during construction is traditionally specified by a maximum allowable gap under a 3 meter straightedge. However, the straightedge method is inexact and rarely representative of the entire floor since the technician is free to choose any location on the floor to perform the measurement. In cases requiring a higher degree of precision and repeatability, concrete floor flatness and levelness can be measured using the standard test method ASTM E1155. With the recent introduction of advanced surveying instruments such as robotic theodolites and terrestrial laser scanners (TLS), the means now exist to modernize and expedite the measurement of floor flatness and levelness. This paper details the development and demonstration of a digital tool, named the Flat and Level Analysis Tool (FLAT), to automate and expedite the segmentation and analysis of flatness and levelness from dense point cloud data of concrete floor slabs. Segmentation algorithms were developed using unsupervised machine learning to extract the set of points belonging to the concrete floor slab from a full 360 scan of a construction site. After segmentation, automated analysis algorithms report the results according to the standard method. The developed algorithms were demonstrated on a dense point cloud captured from a concrete slab-on-grade at a construction site. Results show that the digital tool can quickly provide estimates for floor flatness and levelness with minimal human involvement with comparable accuracy to manual methods.

Hayes, Nolan↗

DOE OSTI2025

Deep Point Cloud Building Envelope Segmentation (DeeP-CuBES) using Deep Learning

Building Information Modeling (BIM) plays an important role in building design and construction, particularly for achieving energy-efficient retrofits. Building envelope retrofits using panelized prefabricated system, such as those popularized by the Energiesprong program, need accurate as-built dimensions of facade features (windows, doors, etc.) to achieve the desired thermal and air tightness. Traditionally, building surveying is done manually, resulting in a time-consuming and labor-intensive process. Recently, 3D point clouds from terrestrial LiDAR have been used to automate the generation of as-built dimensions of existing buildings. However, automated BIM using LiDAR relies on solving the point cloud semantic segmentation (PCSS) problem. In this work, we propose a robust pipeline for solving the PCSS problem using deep neural networks, focusing on overcoming challenges posed by imbalanced datasets and complex architectural features. We introduce the first high-density, labeled, and validated building envelope point cloud dataset derived from multiple building scans, specifically curated to tackle challenges in facade-level segmentation. Results from the trained neural networks show that advanced attention-based architectures and incorporating radiometry (light intensity and RGB) features significantly boost segmentation accuracy for windows and doors.

Selvakumar, Balaji [ORNL]↗

DOE OSTI2025

Quality Investigation of Pultruded Carbon Fiber Panels Subjected to Four-Point Flexure via Fiber Optic Sensing

Pultruded carbon fiber-reinforced composites are attractive to the wind energy industry due to the rapid production of highly aligned unidirectional composites with enhanced fiber volume fractions and increased specific strength and stiffness. However, high volume carbon fiber manufacturing remains cost-prohibitive. This study investigates the feasibility of a pultruded low-cost textile carbon fiber-reinforced epoxy composite as a promising material in spar cap production was undertaken based on mechanical response to four-point flexure loading. As spar caps are primarily subjected to flexural loading, large-span four-point flexure was considered, and coupon testing was restricted to tensile modulus and compression strength assessment. High-resolution spatial fiber optic strain sensing was utilized to determine spatial strain distribution during four-point flexure, revealing consistent strain along the length of the part and proved to be an excellent option for process manufacturing quality examination. Additionally, holes with diameters of 2.49 mm, 5.08 mm, and 1.93 mm were drilled through the thickness of full-width parts to determine the feasibility of structural health monitoring of pultruding parts internal to wind blades via fiber optic strain sensing.

Chemistry↗

DOE OSTI2025

Tuning Solvation Dynamics of Electrolytes at Their Eutectic Point Through Halide Identity

Deep eutectic solvents (DESs) are regarded as highly promising solvent systems for redox flow batteries. DESs, composed of choline halides (ChX, X = F − , Cl − , Br − , I − ) and ethylene glycol (EG), exhibit distinct physicochemical properties at their eutectic points, including halide-dependent phase behavior, viscosity, polarity, conductivity, and solvation dynamics. In this study, we investigate the effects of the halide identity on the solvation properties of ChX:EG mixtures at varying mol % of ChX salt content. The solvatochromic polarity based on ET(30) measurements indicates higher polarity for larger halides (I − > Br − ) than for smaller halides (Cl − > F − ), which exhibit larger compensating solvation shells. The ionic conductivity follows the trend of the solvent fluidity (the inverse of the viscosity), namely ChCl > ChBr > ChI > ChF, influenced by the ion mobility and solvodynamic radii. Measurements of the liquidus temperatures (T L ) reveal that the system with ChCl exhibits the deepest eutectic point (at ~20 mol % ChCl), while ChBr and ChI have shallower minima at ~10 mol % ChBr and ~3 mol % ChI, respectively. ChF does not display a eutectic transition but instead appears to readily supercool at salt concentrations above 30 mol % ChF. Consistent with the phase transition measurements, femtosecond transient absorption spectroscopy shows that in the ChCl system, the solvation dynamics become faster with an increasing salt concentration up to ~16.67 mol %, after which the dynamics slow down with further increases in the salt content. The ChF-based system exhibits similar behavior, though with slower dynamics. In contrast, the solvation dynamics of the systems containing ChBr and ChI monotonously slow down with an increasing salt concentration, in agreement with the phase transition measurements, which show that the eutectic points occur at low salt concentrations. These measurements suggest that the solvent composition and, in particular, the identity of the halide anion play a significant role in the solvation behavior of these ethylene-glycol-based DESs, offering a foundation for tuning the DES properties for specific applications.

Biochemistry & Molecular Biology↗

DOE OSTI2024

AEPF: Attention-Enabled Point Fusion for 3D Object Detection

Current state-of-the-art (SOTA) LiDAR-only detectors perform well for 3D object detection tasks, but point cloud data are typically sparse and lacks semantic information. Detailed semantic information obtained from camera images can be added with existing LiDAR-based detectors to create a robust 3D detection pipeline. With two different data types, a major challenge in developing multi-modal sensor fusion networks is to achieve effective data fusion while managing computational resources. With separate 2D and 3D feature extraction backbones, feature fusion can become more challenging as these modes generate different gradients, leading to gradient conflicts and suboptimal convergence during network optimization. To this end, we propose a 3D object detection method, Attention-Enabled Point Fusion (AEPF). AEPF uses images and voxelized point cloud data as inputs and estimates the 3D bounding boxes of object locations as outputs. An attention mechanism is introduced to an existing feature fusion strategy to improve 3D detection accuracy and two variants are proposed. These two variants, AEPF-Small and AEPF-Large, address different needs. AEPF-Small, with a lightweight attention module and fewer parameters, offers fast inference. AEPF-Large, with a more complex attention module and increased parameters, provides higher accuracy than baseline models. Experimental results on the KITTI validation set show that AEPF-Small maintains SOTA 3D detection accuracy while inferencing at higher speeds. AEPF-Large achieves mean average precision scores of 91.13, 79.06, and 76.15 for the car class’s easy, medium, and hard targets, respectively, in the KITTI validation set. Results from ablation experiments are also presented to support the choice of model architecture.

Chemistry↗

DOE OSTI2024

Image Deconvolution and Point-spread Function Reconstruction with STARRED: A Wavelet-based Two-channel Method Optimized for Light-curve Extraction

We present starred, a point-spread function (PSF) reconstruction, two-channel deconvolution, and light-curve extraction method designed for high-precision photometric measurements in imaging time series. An improved resolution of the data is targeted rather than an infinite one, thereby minimizing deconvolution artifacts. In addition, starred performs a joint deconvolution of all available data, accounting for epoch-to-epoch variations of the PSF and decomposing the resulting deconvolved image into a point source and an extended source channel. The output is a high-signal-to-noise-ratio, high-resolution frame combining all data and the photometry of all point sources in the field of view as a function of time. Of note, starred also provides exquisite PSF models for each data frame. We showcase three applications of starred in the context of the imminent LSST survey and of JWST imaging: (i) the extraction of supernovae light curves and the scene representation of their host galaxy; (ii) the extraction of lensed quasar light curves for time-delay cosmography; and (iii) the measurement of the spectral energy distribution of globular clusters in the "Sparkler," a galaxy at redshift z = 1.378 strongly lensed by the galaxy cluster SMACS J0723.3-7327. starred is implemented in jax, leveraging automatic differentiation and graphics processing unit acceleration. This enables the rapid processing of large time-domain data sets, positioning the method as a powerful tool for extracting light curves from the multitude of lensed or unlensed variable and transient objects in the Rubin-LSST data, even when blended with intervening objects.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Cosmology Large Angular Scale Surveyor (CLASS): 90 GHz Telescope Pointing, Beam Profile, Window Function, and Polarization Performance

The Cosmology Large Angular Scale Surveyor (CLASS) is a telescope array that observes the cosmic microwave background (CMB) over ∼75% of the sky from the Atacama Desert, Chile, at frequency bands centered near 40, 90, 150, and 220 GHz. CLASS measures the large angular scale CMB polarization to constrain the tensor-to-scalar ratio and the optical depth to last scattering. This paper presents the optical characterization of the 90 GHz telescope. Observations of the Moon establish the pointing while dedicated observations of Jupiter are used for beam calibration. The standard deviations of the pointing error in azimuth, elevation, and boresight angle are 1$^{'}_.$3, 2$^{'}_.$1, and 2$^{'}_.$0, respectively, over the first 3 yr of observations. This corresponds to a pointing uncertainty ∼7% of the beam’s full width at half-maximum (FWHM). The effective azimuthally symmetrized instrument 1D beam estimated at 90 GHz has an FWHM of 0$^°_.$620 ± 0$^°_.$003 and a solid angle of 138.7 ± 0.6(stats.) ± 1.1(sys.) μsr integrated to a radius of 4°. The corresponding beam window function drops to $b^2_ℓ$ = 0.93, 0.71, 0.14 at ℓ = 30, 100, 300, respectively. Far-sidelobes are studied using detector-centered intensity maps of the Moon and measured to be at a level of 10 −3 or below relative to the peak. The polarization angle of Tau A estimated from preliminary survey maps is 149°.6 ± 0°.2(stats.) in equatorial coordinates. The instrumental temperature-to-polarization (T → P) leakage fraction, inferred from per-detector demodulated Jupiter scan data, has a monopole component at the level of 1.7 × 10 −3 , a dipole component with an amplitude of 4.3 × 10 −3 , with no evidence of quadrupolar leakage.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Supernova pointing capabilities of DUNE

The determination of the direction of a stellar core collapse via its neutrino emission is crucial for the identification of the progenitor for a multimessenger follow-up. A highly effective method of reconstructing supernova directions within the Deep Underground Neutrino Experiment (DUNE) is introduced. The supernova neutrino pointing resolution is studied by simulating and reconstructing electron-neutrino charged-current absorption on Ar 40 and elastic scattering of neutrinos on electrons. Procedures to reconstruct individual interactions, including a newly developed technique called “brems flipping,” as well as the burst direction from an ensemble of interactions are described. Performance of the burst direction reconstruction is evaluated for supernovae happening at a distance of 10 kpc for a specific supernova burst flux model. The pointing resolution is found to be 3.4 degrees at 68% coverage for a perfect interaction-channel classification and a fiducial mass of 40 kton, and 6.6 degrees for a 10 kton fiducial mass respectively. Assuming a 4% rate of charged-current interactions being misidentified as elastic scattering, DUNE’s burst pointing resolution is found to be 4.3 degrees (8.7 degrees) at 68% coverage.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Point containment algorithms for constructive solid geometry with unbounded primitives

Here, we present several algorithms for evaluating point containment in constructive solid geometry (CSG) trees with unbounded primitives. Three algorithms are presented based on postfix, prefix, and infix notations of the CSG binary expression tree. We show that prefix and infix notations enable short-circuiting logic, which reduces the number of primitives that must be checked during point containment. To evaluate the performance of the algorithms, each algorithm was implemented in the OpenMC Monte Carlo particle transport code, which relies on CSG to represent solid bodies through which subatomic particles travel. Two sets of tests were carried out. First, the execution time to generate a rasterized image of a 2D slice of three CSG models of varying complexity was measured. Use of both prefix and infix notations offered significant speedup over the postfix notation that has traditionally been used in particle transport codes, with infix resulting in a 6 x reduction in execution time relative to postfix for a model of a tokamak fusion device. We then measured the execution time of neutron transport simulations of the same three models using each of the algorithms. The results and performance improvements reveal the same trends as for the rasterization test, with a 5.52 x overall speedup using the infix notation relative to the original postfix notation in OpenMC for the tokamak model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Impacts of point defects on shallow doping in cubic boron arsenide: A first principles study

Cubic boron arsenide (BAs) stands out as a promising material for advanced electronics, thanks to its exceptional thermal conductivity and ambipolar mobility. However, effective control of p- and n-type doping in BAs poses a significant challenge, mostly as a result of the influence of defects. In the present study, we employed density functional theory (DFT) to explore the impacts of the common point defects and impurities on p-type doping of Be B and Si As , and on n-type doping of Si B and Se As . We found that the most favorable point defects formed by C, O, and Si are C As , O B O As , Si As , C As Si B , and O B Si As , which have formation energies of less than 1.5 eV. While the O impurity detrimentally affects both p- and n-type dopings, C and Si impurities are harmful for n-type dopings, making n-type doping a potential challenge. Interestingly, the antisite defect pair A s B B As benefits both p- and n-type doping. Finally, the doping limitation analysis presented in this study can potentially pave the way for strategic development in the area of BAs-based electronics.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Point defect energetics in gallium arsenide, a comprehensive density functional theory study

In materials, point defects often control or modify functional properties. To predict the performance of materials intended for application in optoelectronic devices, it is imperative to understand the properties of those point defects. For the first time, all six intrinsic defects of GaAs, a key optoelectronics material, and their charge transition levels are calculated using density functional theory with the HSE06 functional. For comparison, both PBE and r 2 SCAN calculations are also carried out. The HSE06 results are found to be in better agreement with experimental data than previous calculations. In conclusion, the importance of using the exact electron exchange present in hybrid functionals and larger supercells to accurately determine defect levels and ground state defect configurations is demonstrated.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Modeling CO 2 flow through faulted/fractured reservoirs using tEDFM in corner-point grids

The interest in underground CO 2 storage has increased significantly over the last decade because of the rising concern about global warming due to the growing levels of greenhouse gases in the atmosphere. Considering that CO 2 accounts for 80% of these greenhouse gases, carbon capture, utilization, and storage (CCUS) is regarded as one of the most direct approaches to achieving the net zero carbon target. Although CO 2 storage in deep saline aquifers and depleted gas reservoirs has been studied extensively, most studies use commercial simulators that model faults/fractures by simply modifying the transmissibility in the direction perpendicular to the fault surfaces. Here, this work shows that this simplistic approach ignores the accelerated flow in the directions parallel to the fault plane, leading to significantly higher leakage along the fault surface. To accurately model the flow of CO 2 in faulted reservoirs, we present the first transient embedded discrete fracture model for corner-point grids (tEDFM-CPG). By comparing the results of the tEDFM-CPG to high-resolution reference solutions, we show that this approach is accurate and efficient at predicting CO 2 flow in faulted/fractured reservoirs. Finally, this work presents the use of mixed reality (MR) to efficiently observe CO 2 gas migration in the interior of these corner-point grid systems.

25 ENERGY STORAGE↗

DOE OSTI2024

Analysis of heat and mass transfer potential of a dew-point cooling tower in different climatic conditions

In this study, the performance of the Dew-Point Cooling Tower (DPCT) was analyzed for different factors in a variety of climate conditions. For this purpose, a dedicated numerical model describing heat and mass transfer processes was developed and validated. The results of the numerical simulations allowed to analyze the potential of utilizing the heat and mass transfer process with the dew-point phenomenon for water cooling. It was established that the operational parameters that have a high impact on the performance of the DPCT are: inlet water temperature and inlet air humidity ratio. It was also established that DPCT achieves the highest COP and Specific Cooling Capacity for cold subtropical highland climates and that it achieves highest Wet-bulb Effectiveness for monsoon-influenced humid subtropical climates. In conclusion, the regions where all the efficiency factors achieved above-average values included warm, arid, and desert climates.

42 ENGINEERING↗

DOE OSTI2025

Combining four-point bending and corrosion to map stress-dependent corrosion susceptibility of 316H stainless steel in FLiNaK

Understanding the effect of stress on the corrosion of steels in molten salts is important for material screening and safety assessment of molten salt reactors. We present a method that combines four-point bending with corrosion testing, enabling the mapping of corrosion susceptibility as a function of local stress from a single specimen. Guided by finite element analysis, a four-point bending setup was used to bend a 316H stainless-steel bar under controlled elastic stress during a 100-hour exposure in FLiNaK at 700 °C. Post-exposure characterization using scanning electron microscopy and energy-dispersive X-ray spectroscopy revealed a pronounced correlation between stress and corrosion. Regions under tensile stress exhibited significantly deeper attack depths and greater chromium depletion along grain boundaries, whereas compressive zones showed shallower corrosion cracks. The stress effect is attributed to stress concentration under tensile loading, which promotes chromium dissolution and crack propagation. This technique can be readily applied to other structural alloys, enabling quantitative measurement of corrosion susceptibility as a function of local stress.

316H↗

DOE OSTI2026

Revealing the Hidden Third Dimension of Point Defects in Two-Dimensional MXenes

Point defects govern many important functional properties of two-dimensional (2D) materials. However, resolving the three-dimensional (3D) arrangement of these defects in multi-layer 2D materials remains a fundamental challenge, hindering rational defect engineering. Here, we overcome this limitation using an artificial intelligence-guided electron microscopy workflow to map the 3D topology and clustering of atomic vacancies in Ti3C2TX MXene. Our approach reconstructs the 3D coordinates of vacancies across hundreds of thousands of lattice sites, generating robust statistical insight into their distribution that can be correlated with specific synthesis pathways. This large-scale data enables us to classify a hierarchy of defect structures-from isolated vacancies to nanopores-revealing their preferred formation and interaction mechanisms, as corroborated by molecular dynamics simulations. This work provides a generalizable framework for understanding and ultimately controlling point defects across large volumes, paving the way for the rational design of defect-engineered functional 2D materials.

2D materials↗

DOE OSTI2025

Multi-X-point radiation and its dynamics in up/down asymmetry in plasma detachment regimes in Wendelstein 7-X

In Wendelstein 7-X (W7-X), stable plasma detachment in ECRH hydrogen plasmas is routinely achieved with the standard magnetic configuration, containing five magnetic islands in the scrape-off layer (SOL). Plasma detachment induced by intrinsic carbon impurities is characterized by a high radiation fraction (ƒ rad ) with significantly reduced divertor heat load and particle flux. In this work, we present the radiation dynamics during the detached plasma (DP) phase, such as the shift of radiation zones in radial and poloidal directions towards the X-points as ƒ rad increases (∼0.6–0.9), as well as the penetration of the radiation layer into the confinement region in the deep DP phase with ƒ rad approaching unity. In particular, a structure of multi-X-point radiation (multi-XPR) with an up/down asymmetry in the DP phase is highlighted, which is revealed by bolometer tomography and is further confirmed by video diagnostics. The multi-XPR structure forms helical 3D bands aligned with W7-X field periodicity. Field reversal experiments show that the brightest XPR displaces between the upper and lower SOL regions, suggesting the E× B drift effects. This paper presents the multi-XPR structure observed in the W7-X plasma in detail for the first time. A simplified model considering the influence of the poloidal E× B drift ( V d ) on the impurity flow in the SOL shows that the downstream drift toward the target or target shadow region ( V d < 0) decreases the impurity content, while the upstream drift toward the LCFS ( V d > 0) increases the impurity content. On this basis, the poloidal drift potentially leads to an up/down asymmetry of impurity density in the SOL despite the symmetry magnetic topology. The dynamics of the up/down asymmetry in the multi-XPR structure is also related to the magnitude V d /D (normalized to the impurity diffusivity), with an additional effect owing to the radial inward shift of the emission zone. These results provide new insights into impurity-induced detachment dynamics and provide a basis for improving 3D modeling of impurity transport, which typically does not consider drifts.

E × B drift↗

DOE OSTI2025

Describing Point Defect Topology in 2D Energy Materials through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. Here we employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science.

2d materials↗

DOE OSTI2024

Point defects and doping in wurtzite LaN

Wurtzite LaN (wz-LaN) is a semiconducting nitride that has piezoelectric and ferroelectric properties, making it promising for applications in electronics, either as a binary compound or in alloys such as LaAlN. The prospects for wz-LaN in devices are influenced by the properties of point defects and impurities; here, we use first-principles density functional theory with a hybrid functional to calculate their formation energies, as well as their atomic and electronic structures. Among native point defects, we find that nitrogen-related defects, both vacancies ($V^+_N$) and interstitials ($N^-_i$), are energetically most favorable under most relevant chemical potentials and positions of the Fermi level; $V^0_N$ may additionally be observed under N-poor conditions, and $N^0_i$ may be prominent under N-rich conditions. We also investigate the incorporation of oxygen and hydrogen, which will likely be present as unintentional impurities. We find that the $O^+_N$ substitutional species readily forms, but oxygen will not lead to n-type conductivity due to formation of DX centers and compensation by interstitial defects. Similarly, substitutional HN and interstitial H i can compensate both p- and n-type dopants. Our results provide detailed, microscopic guidance for the development of electronic devices based on wz-LaN.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗