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DOE OSTI2022

Hierarchical Materials from High Information Content Macromolecular Building Blocks: Construction, Dynamic Interventions, and Prediction

Hierarchical materials that exhibit order over multiple length scales are ubiquitous in nature. Because hierarchy gives rise to unique properties and functions, many have sought inspiration from nature when designing and fabricating hierarchical matter. More and more, however, nature’s own high-information content building blocks, proteins, peptides, and peptidomimetics, are being coopted to build hierarchy because the information that determines structure, function, and interfacial interactions can be readily encoded in these versatile macromolecules. Here, we take stock of recent progress in the rational design and characterization of hierarchical materials produced from high-information content blocks with a focus on stimuli-responsive and “smart” architectures. We also review advances in the use of computational simulations and data-driven predictions to shed light on how the side chain chemistry and conformational flexibility of macromolecular blocks drive the emergence of order and the acquisition of hierarchy and also on how ionic, solvent, and surface effects influence the outcomes of assembly. Furthermore, continued progress in the above areas will ultimately usher in an era where an understanding of designed interactions, surface effects, and solution conditions can be harnessed to achieve predictive materials synthesis across scale and drive emergent phenomena in the self-assembly and reconfiguration of high-information content building blocks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Precise Colloidal Plasmonic Photocatalysts Constructed by Multistep Photodepositions

Natural photosynthesis relies on a sophisticated charge transfer pathway among multiple components with precise spatial, energetic, and temporal organizations in the aqueous environment. It continues to inspire and challenge the design and fabrication of artificial multicomponent colloidal nanostructures for solar-to-fuel conversion. Herein, we introduce a plasmonic photocatalyst synthesized with colloidal methods with five integrated components including cocatalysts installed in orthogonal locations. The precise deposition of individual inorganic components on an Au/TiO 2 nanodumbell nanostructure is enabled by photoreduction and photo-oxidation, which selectively occurs at the TiO 2 tip sites and Au lateral sites, respectively. Under visible-light irradiation, the photocatalyst exhibited activity of oxygen evolution from water without scavengers. Here, we demonstrate that each component is essential for improving the photocatalytic performance. In addition, mechanistic studies suggest that the photocatalytic reaction requires combining the hot charge carriers derived from exciting both the d-sp interband transition and the localized surface plasmon resonance of Au.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2026

Mountain Basin Controls on the Snow-to-Streamflow Signal: An AIC-Weighted Multiple Linear Regression Framework

A regression-based analysis quantifies how basin characteristics modulate the snow-to-streamflow signal. First, we use the ERA5-Land reanalysis gridded product (European Centre for Medium Range Weather Forecasts reanalysis 5 -Land component) for 4,655 hydrologic unit code - 10 (HUC10) mountain basins across the western United States (US) for water years 1987–2024. Linear regressions are performed for peak snow water equivalent (SWE) and annual streamflow for each mountain basin. Models use ordinary least squares in Python’s statsmodels package. After which, an Akaike Information Criterion (AIC)–weighted ensemble multiple linear regression (MLR) framework with 47 watershed traits is used to predict the linear regression coefficient of determination (r-squared) defining the ability of peak SWE to predict annual streamflow across all mountain basin. Predictor sets are constrained to avoid multicollinearity by excluding models with variance inflation factors (VIF) greater than 5. Mountain basin traits included in the MLR include seasonal climate, topography, vegetation type and structure, and bedrock geology. Accepted models are considered if their AIC is within 2.0 of the model with the minimum AIC, or best model. To compare predictor influence across acceptable models, we computed standardized regression coefficients. To evaluate structural redundancy among models, we constructed binary inclusion vectors for each acceptable model, denoting whether a predictor was present (1) or absent (0). Core predictor variables are defined as occurring in at least 67% of the acceptable models. For this regional analysis, only one model was found acceptable, with higher snow-to-streamflow translation (higher r-squared) occurring in colder mountain basins with higher relative winter precipitation, more snow accumulation and a lower fraction of annual precipitation that falls in the spring and summer. The second component of the data package uses previously published, high-resolution output from an integrated hydrological model of the East River watershed using the U.S. Geological Survey Groundwater and Surface water Flow model (GSFLOW, doi:10.15485/1998576). East River MLR expands upon the approach described above to explore the response of five streamflow metrics—annual streamflow, runoff efficiency, 7-day minimum flow, low-flow duration, and non-perennial stream fraction to snow system indicators including peak SWE, snow-covered area, snow disappearance date, and the fraction of basin area characterized by low-to-no snow, as well as seasonal precipitation and temperature, and annual hydrologic variables representing soil moisture, evapotranspiration (ET), the partitioning of incoming precipitation to evapotranspiration (ET/P), groundwater storage, and groundwater inflow to streams. MLR was done on all water years (P0: 1987-2024) and for each period as determined in the split analysis using pooled regression techniques (P1: 1987-2011 and P2: 2012-2024) to evaluate shifting predictor variable emphasis on streamflow generation. Results indicate that since 2012, peak SWE has lost statistical strength in its prediction of annual streamflow and runoff efficiency, and the indirect influence of spring temperature has emerged as critically important. Low-flow metrics remain largely influenced by soil moisture, vegetation water use and groundwater inflows with summer precipitation becoming a direct influence on minimum summer flow. Together, these data and Python-based analysis tools provide a framework for identifying the key watershed characteristics that control how streamflow responds to snow from year to year. The package also helps quantify uncertainty in statistical models and assess how snow–streamflow relationships vary across regions and over time. This dataset contains comma-separated values files (.csv), text files (.txt), python code files (.py), figure files (.png), and shapefiles (.cpg, .dbf, .prj, .sbn, .sbx, .shp, .xml). Further details on file contents and MLR execution can be found in the readme file and the FLMD files. Work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

FY25 Status Update on A709 Code Case Testing at ANL

This report provides an update on the status of the creep rupture testing on the precipitation-treated (PT) Alloy 709 samples fabricated from the first, the second and the third commercial heats, in support of the first, 100,000-hour Alloy 709 Code Case development under the American Society of Mechanical Engineers (ASME) Section III, Division 5 for high-temperature reactor construction. In Fiscal Year (FY) 25, no new tests were initiated, while 5 previously loaded tests were completed. This report presents an overview of the creep-rupture data gathered at Argonne National Laboratory (ANL) since FY21 that totaled 52 completed tests. Metallographic images showing crack morphologies in some representative samples ruptured in FY25 are also included. Key conclusions include: 1) the creep behavior of the three heats of Alloy 709 can be well described by the Larson-Miller relationship; 2) higher temperatures and larger stresses lead to shorter creep life and higher minimum creep rate; 3) Alloy 709 is overall very ductile under creep; 4) the crack morphologies near fracture surfaces are dependent on material’s grain size and test conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

Constructing Robust Electrode/Electrolyte Interphases to Enable Wide Temperature Applications of Lithium-Ion Batteries

The electrolyte generally dictates the working temperature range of lithium ion batteries (LIBs), thus developing new class of electrolytes (primarily functional additives) in LIBs for wide temperature applications will be quite essential for further development of LIBs for electric vehicle market. In this study, we develop new functional electrolytes containing multiple additives to enable the LIBs to perform well in a wide temperature range from -40°C to 60°C. Importantly, those cells based on the above optimized electrolytes have been proven to behave significantly enhanced discharging performance at -40°C, the long-term cycling stability at 25°C (more than 85% of capacity retention after 1000 cycles at 1C/1C rates in 1 Ah pouch cells), as well as the obviously improved cycling stability at 60°C. These remarkable cell performances originate from the highly conductive, uniform and compact passivating films formed on both anode and cathode surfaces by the synergistic effects of the multiple additives. Our finding on the synergistic benefits originating from certain additive combination in the optimized electrolytes would favorably widen the working temperature range of future high-performance LIBs.

Lithium ion battery, electrolyte, additive, electr↗

DOE OSTI2022

Topological field theory with Haagerup symmetry

Here, we construct a (1 + 1)d topological field theory (TFT) whose topological defect lines (TDLs) realize the transparent Haagerup $\mathscr{H}$ 3 fusion category. This TFT has six vacua, and each of the three non-invertible simple TDLs hosts three defect operators, giving rise to a total of 15 point-like operators. The TFT data, including the three-point coefficients and lasso diagrams, are determined by solving all the sphere four-point crossing equations and torus one-point modular invariance equations. We further verify that the Cardy states furnish a non-negative integer matrix representation under TDL fusion. While many of the constraints we derive are not limited to this particular TFT with six vacua, we leave open the construction of TFTs with two or four vacua. Finally, TFTs realizing the Haagerup $\mathscr{H}$ 1 and $\mathscr{H}$ 2 fusion categories can be obtained by gauging algebra objects. This article makes a modest offering in our pursuit of exotica and the quest for their eventual conformity.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Natural and anthropogenic controls on lake water‐level decline and evaporation‐to‐inflow ratio in the conterminous United States

Abstract Lake water levels are integral to lake function, but hydrologic changes from land and water management may alter lake fluctuations beyond natural ranges. We constructed a conceptual model of multifaceted drivers of lake water levels and evaporation‐to‐inflow ratio (Evap : Inflow). Using a structural equation modeling framework, we tested our model on (1) a national subset of lakes in the conterminous United States with minimal water management to describe natural drivers of lake hydrology and (2) five ecoregional subsets of lakes to explore regional variation in water management effects. Our model fits the national and ecoregional datasets and explained up to 47% of variation in Evap : Inflow, 38% of vertical water level decline, and 79% of horizontal water level decline (littoral exposure). For lakes with minimal water management, Evap : Inflow was related to lake depth ( β = −0.31) and surface inflow ( β = −0.44); vertical decline was related to annual climate (e.g., precipitation β = −0.18) and water management ( β = −0.21); and horizontal decline was largely related to vertical decline ( β = 0.73) and lake morphometry (e.g., depth β = −0.18). Anthropogenic effects varied by ecoregion and likely reflect differences in regional water management and climate. In the West, water management indicators were related to greater vertical decline ( β = 0.38), whereas in the Midwest, these indicators were related to more stable and full lake levels ( β = −0.22) even during drought conditions. National analyses show how human water use interacts with regional climate resulting in contrasting impacts to lake hydrologic variation in the United States.

Fergus, C. Emi↗

DOE OSTI2021

Structure prediction of epitaxial inorganic interfaces by lattice and surface matching with Ogre

We present a new version of the Ogre open source Python package with the capability to perform structure prediction of epitaxial inorganic interfaces by lattice and surface matching. In the lattice matching step, a scan over combinations of substrate and film Miller indices is performed to identify the domain-matched interfaces with the lowest mismatch. Subsequently, surface matching is conducted by Bayesian optimization to find the optimal interfacial distance and in-plane registry between the substrate and the film. For the objective function, a geometric score function is proposed based on the overlap and empty space between atomic spheres at the interface. The score function reproduces the results of density functional theory (DFT) at a fraction of the computational cost. The optimized interfaces are pre-ranked using a score function based on the similarity of the atomic environment at the interface to the bulk environment. Final ranking of the top candidate structures is performed with DFT. Ogre streamlines DFT calculations of interface energies and electronic properties by automating the construction of interface models. The application of Ogre is demonstrated for two interfaces of interest for quantum computing and spintronics, Al/InAs and Fe/InSb.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Structure analysis of supported disordered molybdenum oxides using pair distribution function analysis and automated cluster modelling

Molybdenum oxides and sulfides on various low-cost high-surface-area supports are excellent catalysts for several industrially relevant reactions. The surface layer structure of these materials is, however, difficult to characterize due to small and disordered MoO x domains. Here, it is shown how X-ray total scattering can be applied to gain insights into the structure through differential pair distribution function (d-PDF) analysis, where the scattering signal from the support material is subtracted to obtain structural information on the supported structure. MoO x catalysts supported on alumina nanoparticles and on zeolites are investigated, and it is shown that the structure of the hydrated molybdenum oxide layer is closely related to that of disordered and polydisperse polyoxometalates. By analysing the PDFs with a large number of automatically generated cluster structures, which are constructed in an iterative manner from known polyoxometalate clusters, information is derived on the structural motifs in supported MoO x .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Quantifying CanESM5 and EAMv1 sensitivities to Mt. Pinatubo volcanic forcing for the CMIP6 historical experiment

Large volcanic eruptions reaching the stratosphere have caused marked perturbations to the global climate including cooling at the Earth's surface, changes in large-scale circulation and precipitation patterns and marked temporary reductions in global ocean heat content. Many studies have investigated these effects using climate models; however, uncertainties remain in the modelled response to these eruptions. This is due in part to the diversity of forcing datasets that are used to prescribe the distribution of stratospheric aerosols resulting from these volcanic eruptions, as well as uncertainties in optical property derivations from these datasets. To improve this situation for the sixth phase of the Coupled Model Intercomparison Project (CMIP6), a two-step process was undertaken. First, a combined stratospheric aerosol dataset, the Global Space-based Stratospheric Aerosol Climatology (GloSSAC; 1979–2016), was constructed. Next, GloSSAC, along with information from ice cores and Sun photometers, was used to generate aerosol distributions, characteristics and optical properties to construct a more consistent stratospheric aerosol forcing dataset for models participating in CMIP6. This “version 3” of the stratospheric aerosol forcing has been endorsed for use in all contributing CMIP6 simulations. Recent updates to the underlying GloSSAC from version 1 to version 1.1 affected the 1991–1994 period and necessitated an update to the stratospheric aerosol forcing from version 3 to version 4. As version 3 remains the official CMIP6 input, quantification of the impact on radiative forcing and climate is both relevant and timely for interpreting results from experiments such as the CMIP6 historical simulations. This study uses two models, the Canadian Earth System Model version 5 (CanESM5) and the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1), to estimate the difference in instantaneous radiative forcing in simulated post-Pinatubo climate response when using version 4 instead of version 3. Differences in temperature, precipitation and radiative forcings are generally found to be small compared to internal variability. An exception to this is differences in monthly temperature anomalies near 24 km altitude in the tropics, which can be as large as 3 °C following the eruption of Mt. Pinatubo.

58 GEOSCIENCES↗

DOE OSTI2022

Development of a Flotation Simulator That Can Predict Grade vs. Recovery Curves from Mineral Liberation Data

Flotation is a kinetic process designed to separate mineral fines by control of hydrophobicity. In general, both the recovery and selectivity of a flotation process increase with contact angle. It is difficult, however, to model flotation kinetics using the thermodynamic parameter. In the present work, we consider flotation as heterocoagulation so that the bubble-particle interactions occurring in the pulp phase of a flotation cell can be modeled using the hydrophobic force as a kinetic parameter that can represent the role of contact angles in flotation. Here, the pulp-phase model developed in this manner has been combined with a froth-phase model developed earlier by considering the effect of particles in film thinning kinetics and bubble coarsening (Park et al, 2018). The combined model has been used to develop a flotation simulator that can be used to construct grade vs. recovery curves from feed characteristics (e.g., mineral liberation and particle size) and various operating parameters. The simulator has been tested successfully against a set of bench-scale continuous flotation test results reported in the literature (dos Santos and Galery, 2018).

58 GEOSCIENCES↗

DOE OSTI2026

Design and scale-up of 3D printed bat houses with biomass-derived polymer composites

Biomass (e.g., pine sawdust, especially high–ash content pine sawdust) is commonly disposed of as waste. Combining biomass with polymers to make composite feedstocks for 3D printing has been explored as a method to reduce or repurpose the biomass waste. Although not all biocomposite properties are known, the wood-based polylactic acid (PLA) composite has promising qualities for applications in ecological settings. In this work, pine wood–PLA composite feedstock was used to 3D print supplemental roost structures for endangered tree-roosting bats, which often face a paucity of suitable naturally occurring roosts. This material combination was selected because it is estimated to degrade faster than the synthetic material systems that are used widely in supplemental bat roosting structures to aid in the conservation of tree roosting bats. The layered, rough surface created by the 3D printing process serves as a surface that bats can grip while roosting. Computer-aided design (CAD) models were generated based on natural roost structures, and a full-size bat house was successfully additively manufactured using a pellet-fed large-scale 3D printing system. The 3D printed hexagon exhibited a tensile strength of 22–23 MPa and a Young’s modulus of 3202–3218 MPa in the x-direction. It has been demonstrated that the 3D printed bat house can be installed on a tree in a stable fashion. This successful demonstration of a bat roost manufactured using a bioderived composite should promote its use in other fish and wildlife structures and broader industrial applications such as construction and automobiles.

3D printing↗

DOE OSTI2025

Development of an atomic layer deposition system for deposition of alumina as a hydrogen permeation barrier

Tritium permeation into and through materials poses a critical challenge for the development of nuclear fusion reactors. Minimizing tritium permeation is essential for the safe and efficient use of available fuel supplies. In this work, we present the design, construction, and validation of custom atomic layer deposition (ALD) and deuterium permeation measurement systems aimed at developing thin-film hydrogen permeation barriers. Using the ALD system, we deposited conformal $\mathrm{Al}_{2}\mathrm{O}_{3}$ films on copper foil substrates and characterized their growth behavior, morphology, and composition. ALD growth rates of ∼1.1 Å/cycle were achieved for temperatures between 100 ∘ C and 210 ∘ C. Permeation measurements on bare and alumina coated copper foils revealed a significant reduction in deuterium flux with the addition of a ∼10 nm $\mathrm{Al}_{2}\mathrm{O}_{3}$ layer. While bare copper followed diffusion-limited transport consistent with Sievert’s law, the alumina-coated samples exhibited surface-limited, pore-mediated transport with linear pressure dependence. Arrhenius analysis showed distinct differences in activation energy for the two transport regimes, and permeation reduction factors exceeding an order of magnitude were observed. These results demonstrate the potential of ALD-grown $\mathrm{Al}_{2}\mathrm{O}_{3}$ films as effective hydrogen isotope barriers and provide a foundation for future studies on film optimization and integration into fusion-relevant components.

atomic layer deposition↗

DOE OSTI2026

Dynamic modeling of heat pipe integrated thermal battery latent heat storage system experiment validation

A heat pipe integrated thermal battery system has been constructed to investigate a high-temperature latent heat thermal energy storage technology that takes advantage of near isothermal operation of latent heat storage and heat pipes to potentially enable high-energy isothermal heat storage. A dynamic model constructed in Modelica has been validated, showing errors between 2.5 °C–39.7 °C across 10-h to 47-h simulations against experiment results, showing good prediction capability of experiment output, especially against phase change time. Model calibrations showing vessel heat-up capability of 3 kW and heat pipes combining to provide 600 W each during experiment operation validate experiment circumstances including reduced material loading and reduced power capability. The experiment configuration uses an Al-Mg-Zn eutectic metal as the storage material, heated via heat tape wrapped around the vessel and guide tubes to bring the system to operation range (>400 °C) and to simulate charging heat exchange, respectively, with heat rejection occurring through the surfaces of the material and facilitated via guide tubes with less insulation wrapping. The model is available in the open-source repository HYBRID on Github.

25 - ENERGY STORAGE↗

DOE OSTI2023

Tuning the Interaction between Platinum Single Atoms and Ceria by Zirconia Doping for Efficient Catalytic Ammonia Oxidation

Aiming at the development of an efficient NH 3 oxidation catalyst to eliminate the harmful NH 3 slip from the stationary flue gas denitrification system and diesel exhaust aftertreatment system, a facile ZrO 2 doping strategy was proposed to construct Pt 1 /Ce x Zr 1–x O 2 catalysts with a tunable Pt-CeO 2 interaction strength and Pt–O–Ce coordination environment. According to the results of systematic characterizations, Pt species supported on Ce x Zr 1–x O 2 were mainly in the form of single atoms when x ≥ 0.7, and the strength of the Pt-CeO 2 interaction and the coordination number of Pt–O–Ce bond (CN Pt–O–Ce ) on Pt 1 /Ce x Zr 1–x O 2 showed a volcanic change as a function of the ZrO 2 doping amount. Here, it was proposed that the balance between the reasonable concentration of oxygen defects and limited surface Zr–O x species well accounted for the strongest Pt-CeO 2 interaction and the highest CN Pt–O–Ce on Pt/Ce 0.9 Zr 0.1 O 2 . It was observed that the Pt/Ce 0.9 Zr 0.1 O 2 catalyst exhibited much higher NH 3 oxidation activity than other Pt/Ce x Zr 1–x O 2 catalysts. The mechanism study revealed that the Pt 1 species with the stronger Pt-CeO 2 interaction and higher CN Pt–O–Ce within Pt/Ce 0.9 Zr 0.1 O 2 could better activate NH 3 adsorbed on Lewis acid sites to react with O 2 thus resulting in superior NH 3 oxidation activity. This work provides a new approach for designing highly efficient Pt/CeO 2 based catalysts for low-temperature NH 3 oxidation.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Single-Layer Dititanium Oxide Ti 2 O MOene: Multifunctional Promises for Electride, Anode Materials, and Superconductor

Using the first-principles calculations, we report the existence of the single-layer (SL) dititanium oxide Ti 2 O (labeled as MOene) that constructs a novel family of MXene based on transition-metal oxides. This MOene material strongly contrasts the conventional ones consisting of transition-metal carbides and/or nitrides. SL Ti 2 O has high thermal and dynamical stabilities because of the strong Ti–O ionic bonding interactions. Moreover, this material is an intrinsic electride and exhibits extremely low diffusion barriers of ~12.0 and 6.3 meV for Li and Na diffusion, respectively. When applied as anode materials in lithium-ion batteries and sodium-ion batteries, it possesses a high energy storage capacity (960.23 mAhg –1 ), surpassing the traditional MXenes-based anodes. The superb electrochemical performance stems from the existing anionic electron on Ti 2 O surface. Astonishingly, SL Ti 2 O is also determined to be a superconductor with a superconducting transition temperature (T c ) of ~9.8 K, which originates from the soft-mode of the first acoustic phonon branch and enhanced electron–phonon coupling in the low-frequency region. Furthermore, this soft-mode behaves much softer upon applying a compressive strain of 2%, leading to a higher T c of 11.9 K. Furthermore, our finding broadens the family of MXenes and could facilitate more experimental efforts toward future nanodevices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

PTT System Performance Evaluation in 3-D Imaging of AM Components

Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Because of the geometry of metallic structures of interest for nuclear applications, which consist of planar primitives with no symmetry of revolution, limited options are available for non-destructive evaluation (NDE) either during or post manufacturing. Known material flaws in AM include low density regions consisting of nonsintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. As a solution to NDE of AM, we are developing pulsed thermal tomography (PTT) models and depth inversion algorithms for 3D imaging. PTT has many advantages because the method is non-contact and allows for in-service, NDE of AM nuclear reactor parts. By analyzing transients of surface temperature response due to internal thermal resistances, one can obtain 3D reconstructions of material effusivity using a unique inversion algorithm developed at Argonne. This study investigates the capability of PTT in imaging several AM structures fabricated from Inconel 718 (IN718) feedstock. The AM structures have complex geometry, but do not have calibrated internal defects. The objective is to determine PTT settings, such as the total integration time, for imaging of representative AM structures. A new FLIR X8500sc IR camera with higher spatial resolution (1280x1024 at 181Hz frame rate) was integrated into the PTT laboratory setup. Software tools were developed to ensure compatibility of new camera files with legacy effusivity reconstruction codes. The new camera was used to obtain 3-D reconstructions of IN718 nozzle plate and a particle filter plate. The results demonstrate the capability of PTT in 3- D imaging of complex geometry AM structures. Further, increased resolution imaging is achieved compared to prior results using older FLIR SC4000 IR camera. In addition, preliminary studies were conducted on developing image processing algorithms for automated detection of flaws. Initial demonstrations are shown for segmentation of PTT images of flat bottom hole (FBH) specimens. Imaging of FBH specimens was described in a prior report. Intermediate results demonstrated in this report will be developed further in detection of flaws in AM specimens.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

EVI-LOCATE User Manual

One of the longest stages in the deployment of electric vehicle supply equipment (EVSE) is the initial planning of the infrastructure itself. Engineers and fleet experts from the National Renewable Energy Laboratory (NREL) have supported dozens of charging infrastructure site plans over the past couple decades, including the generation of site schematics, determinations of electric capacity, and estimates for likely costs. As the market for electric vehicles (EVs) has matured, this approach should no longer require a time and personnel intensive process. In order to shorten the time taken to develop site plans and cost estimates, NREL developed a tool that fleet managers, facility managers, electricians, EVSE installers, and members of the public can use to develop initial schematics and ballpark pricing for charging station installations. The Electric Vehicle Infrastructure - Locally Optimized Charger Assessment Tool and Estimator (EVI-LOCATE) provides a structured and consistent way for users to enter information about their planned EVSE project in a relatively simple web-based format. EVI-LOCATE then calculates electrical equipment capacity, wiring runs, and project costs. It produces a site diagram optimized around surface characteristics with differential trenching costs for softscape such as grass compared to hardscape such as asphalt that can be adjusted by users in the tool. It also stores the resulting site plans and costs in a dashboard for access at a later date, including plan revisions if necessary. This document guides users through the EVI-LOCATE screens and associated questions. It contains tip text boxes throughout on how best to interface with the tool and find additional information or context. The appendices contain the assumptions and calculations underpinning the tool. Much of the information for EVI-LOCATE was gathered through industry engagements with EVSE installers, invoices from completed EVSE installations, Gordian's RS Means construction data, and the General Services Administration blanket purchase agreement for EVSE. For a visual tutorial of the tool, users can watch EVI-LOCATE Step-by-Step Video. The tool itself is available at https://evi-locate.nrel.gov.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗