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1,184 records · Page 66

Atomistic insights into the nucleation and growth of platinum on palladium nanocrystals

Abstract Despite the large number of reports on colloidal nanocrystals, very little is known about the mechanistic details in terms of nucleation and growth at the atomistic level. Taking bimetallic core-shell nanocrystals as an example, here we integrate in situ liquid-cell transmission electron microscopy with first-principles calculations to shed light on the atomistic details involved in the nucleation and growth of Pt on Pd cubic seeds. We elucidate the roles played by key synthesis parameters, including capping agent and precursor concentration, in controlling the nucleation site, diffusion path, and growth pattern of the Pt atoms. When the faces of a cubic seed are capped by Br − , Pt atoms preferentially nucleate from corners and then diffuse to edges and faces for the creation of a uniform shell. The diffusion does not occur until the Pt deposited at the corner has reached a threshold thickness. At a high concentration of the precursor, self-nucleation takes place and the Pt clusters then randomly attach to the surface of a seed for the formation of a non-uniform shell. These atomistic insights offer a general guideline for the rational synthesis of nanocrystals with diverse compositions, structures, shapes, and related properties.

36 MATERIALS SCIENCE↗

Providing Experimental Infrastructure for Accelerating Advanced Reactor Demonstrations through the National Reactor Innovation Center

A suite of experimental infrastructure projects has been developed by the National Reactor Innovation Center to accelerate advanced reactor demonstrations and facilitate their development, addressing crucial gaps in data, materials characterization, and modeling. First, the Molten Salt Thermophysical Examination Capability (MSTEC) provides a specialized platform for post-irradiation characterization of molten salt reactor fuel, coolant salts, and structural materials, essential for supporting the design and operation of advanced reactors and future commercial molten salt reactor development and licensing. The Virtual Test Bed (VTB) complements these efforts by leveraging advanced modeling and simulation tools to evaluate reactor performance and safety. Serving as a library of reference models, the VTB offers a database of multiphysics reactor models, facilitating rapid safety evaluations and includes continuous software quality assurance, crucial for accelerating deployment while maintaining reliability. Additionally, the Helium Component Test Facility (HeCTF) addresses the need for high-temperature helium-cooled reactor component testing. As the first-of-its-kind facility in the United States, HeCTF emulates high-temperature gas reactor conditions, reducing time and cost associated with component validation, thereby accelerating reactor development. Finally, In-cell Thermal Creep Frames provide a unique solution for obtaining thermal creep data from irradiated materials, critical for materials qualification and licensing. Developed by the National Reactor Innovation Center, these compact frames enable the examination of previously irradiated materials, overcoming traditional limitations and enhancing the understanding of mechanical properties crucial for reactor development. Collectively, these experimental infrastructure projects form a comprehensive framework aimed at expediting advanced reactor demonstrations, fostering innovation, and ensuring the viability of next-generation nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Accelerating Quantum Materials Development with Advances in Transmission Electron Microscopy

Quantum materials are driving a technology revolution in sensing, communication, and computing, while simultaneously testing many core theories of the past century. Materials such as topological insulators, complex oxides, superconductors, quantum dots, color center-hosting semiconductors, and other types of strongly correlated materials can exhibit exotic properties such as edge conductivity, multiferroicity, magnetoresistance, superconductivity, single photon emission, and optical-spin locking. These emergent properties arise and depend strongly on the material’s detailed atomic-scale structure, including atomic defects, dopants, and lattice stacking. In this review, we describe how progress in the field of electron microscopy (EM), including in situ and in operando EM, can accelerate advances in quantum materials and quantum excitations. We begin by describing fundamental EM principles and operation modes. We then discuss various EM methods such as (i) EM spectroscopies, including electron energy loss spectroscopy (EELS), cathodoluminescence (CL), and electron energy gain spectroscopy (EEGS); (ii) four-dimensional scanning transmission electron microscopy (4D-STEM); (iii) dynamic and ultrafast EM (UEM); (iv) complementary ultrafast spectroscopies (UED, XFEL); and (v) atomic electron tomography (AET). We describe how these methods could inform structure–function relations in quantum materials down to the picometer scale and femtosecond time resolution, and how they enable precision positioning of atomic defects and high-resolution manipulation of quantum materials. For each method, we also describe existing limitations to solve open quantum mechanical questions, and how they might be addressed to accelerate progress. Among numerous notable results, our review highlights how EM is enabling identification of the 3D structure of quantum defects; measuring reversible and metastable dynamics of quantum excitations; mapping exciton states and single photon emission; measuring nanoscale thermal transport and coupled excitation dynamics; and measuring the internal electric field and charge density distribution of quantum heterointerfaces- all at the quantum materials’ intrinsic atomic and near atomic-length scale. Finally, we conclude by describing open challenges for the future, including achieving stable sample holders for ultralow temperature (below 10K) atomic-scale spatial resolution, stable spectrometers that enable meV energy resolution, and high-resolution, dynamic mapping of magnetic and spin fields. With atomic manipulation and ultrafast characterization enabled by EM, quantum materials will be poised to integrate into many of the sustainable and energy-efficient technologies needed for the 21st century.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

LumaCam: a novel class of position-sensitive event mode particle detectors using scintillator screens

A new type of position-sensitive detectors is gaining attention in the neutron community. They are scintillator based detectors that detect the scintillation light on an individual photon basis via an image intensifier and a fast image sensor. Their readout operates in event mode i.e. it produces information about individual neutron interactions, reconstructed from the sensor data, thus enabling to achieve superior spatial and temporal resolutions compared to regular detectors. Although the development of current detectors is focused on neutrons, the concept is also applicable to the detection of other particles such as high-energy photons. This document provides a description on how these detectors are built, how they operate, and what their characteristics are. An example of a detector implementation based on a Timepix3 chip is described to illustrate the detector concept. This includes a detailed description of the algorithm that reconstructs the neutron interactions from the sensor data, one of the core components that sets it apart from established scintillator-based imaging detectors. Energy-resolved epithermal neutron radiography was performed at the ISIS EMMA beamline with this detector, illustrating some of the fundamental differences in the data that can be produced with the new type of detector compared to more established types of scintillator based neutron detectors. The term LumaCam is proposed to refer to this new class of position-sensitive event-mode detectors.

47 OTHER INSTRUMENTATION↗

Nickel-rich, volatile depleted iron meteorites: Relationships and formation processes

Ungrouped iron meteorites Tishomingo, Willow Grove, and Chinga, and group IVB iron meteorites, are Ni-rich. Similarities include enrichments of 10–100 × CI for some refractory siderophile elements, and equivalent depletions in more volatile siderophile elements. Superimposed on the overall enrichment/depletion trend, certain siderophile elements (P, W, Fe, Mo) are depleted relative to elements of similar volatility. All three ungrouped irons derive from parent bodies formed in the early Solar System. Willow Grove and Chinga are characterized by cosmic ray exposure corrected 182 W/ 184 W consistent with metal-silicate segregation on their parent bodies within 1–3 Myr of Solar System formation, within the age range determined for segregation of magmatic iron meteorite parent bodies, including group IVB irons. Tishomingo is characterized by a younger model age 4–5 Myr subsequent to Solar System formation, reflecting either late stage melting resulting from 26 Al decay, or an impact resetting. The discovery of stishovite in Tishomingo, indicating exposure to a minimum shock pressure of 8–9 GPa, is consistent with the latter. Stishovite in Tishomingo and chromite included in troilite-daubréelite in IVB irons allows oxygen isotopic composition comparison between these meteorites. Different mass independent oxygen isotopic compositions of IVB irons and Tishomingo indicate genetically distinct parent bodies. By contrast, mass independent Mo isotopic compositions overlap within analytical uncertainties, indicating a similar, carbonaceous chondrite (CC) type genetic heritage. Molybdenum and 183 W isotopic data for Chinga and Willow Grove indicate derivation from CC type parent bodies. Willow Grove shares Mo and 183 W isotopic compositions with the Ni-rich South Byron Trio (SBT) grouplet and the Milton pallasite. These Ni-rich meteorites likely formed in the same general nebular environment as other CC planetesimals, likely the outer Solar System. Highly siderophile element (HSE) abundances of Willow Grove and Tishomingo are similar to some IVB meteorites, consistent with formation by moderate degrees of fractional crystallization from initial metallic melts with low S and P, and modestly fractionated HSE. The comparable HSE abundances of Tishomingo and Willow Grove to some IVB irons, yet substantially higher Ni concentrations, indicate formation on parent bodies with lower bulk HSE abundances or HSE concentration in proportionally smaller volumes of metal. HSE abundances in Chinga are considerably lower than in IVB irons, highly fractionated, and processes responsible for these remain elusive. For IVB irons and these ungrouped irons, high temperature condensation likely dominated the enrichment and depletion of the refractory and volatile siderophile elements, respectively. Parent body degassing may have also played a role. Relative depletion of volatile siderophile elements is not, however, a universal feature of high-Ni meteorites. The SBT and Milton pallasite are Ni-rich, but less depleted in the more volatile siderophile elements. Nickel enrichment was likely driven by oxidation of Fe metal during parent body accretion or core segregation. Oxidation of the Tishomingo and Willow Grove parent bodies may have occurred at ~ IW + 1, indicated by relative Mo and W depletions due to metal/water reaction during differentiation. Late-stage reduction, indicated by the presence of Cr-bearing sulfides in Tishomingo and IVB irons, may have resulted from exhaustion of the oxidant.

36 MATERIALS SCIENCE↗

Data Summary Report for Soil and Slab Sampling at Former Building 175

Lawrence Livermore National Security (LLNS) and the U.S. Department of Energy (DOE) are in the process of returning the area where Building 175 existed to beneficial use for future site development. The completed assessment will help LLNS and DOE to outline project scope and costs associated with the removal, characterization, and disposal of materials generated when the concrete slab for the former building and any associated remaining subsurface structures are demolished. Slab removal under the Transition & Disposition process requires full screening for potential site contamination to determine appropriate future land use. Borehole locations and depths were designed to correctly assess DOE’s future liability for characterizing residual vadose zone contamination. If a residual source area is identified at depth, DOE will need to evaluate the additional cost of future subsurface cleanup (with limited access) due to planned development. This is necessary to leave the location in a “ready-to-build” status. As a result, Phase II sampling requirements may in some cases extend beyond the construction zone required for slab removal to ensure the necessary due diligence. To avoid the potential spread of contamination and/or the creation of an environmental release by impacting the integrity of known contamination areas (e.g., pit within room 102 and the east to west boundary seam), these locations were not sampled for this project. During demolition of the slab, these locations and their underlying soils should be further evaluated. The assessment was conducted in accord with the May 2022 Lawrence Livermore National Laboratory Former Building 175 Assessment Soil Sampling and Analysis Plan / Quality Assurance Plan. Thirty-six, direct-push borings were advanced, along with collecting concrete (where present) and soil samples for laboratory analyses. Thirty-two of the borings were advanced to a depth of 25 feet below ground (bgs), and four borings were advanced to a depth of 55 feet bgs. The concrete slab for former Building 175 ranged from approximately 8 inches to over two feet in thickness. Soils encountered during the investigation consisted primarily of clayey silt, with interbeds of sandy gravel and silty sand to the total depth explored of 55 feet bgs. Field photoionization detector readings – checking for volatile organic compound (VOC) vapors in soils, ranged from zero (0) to a peak of 33 parts per million at 25 feet bgs in boring PC-B175- 028. The cause for the peak reading is unknown, however, no visually discolored or odorous soils were encountered during the assessment and all VOC results were below Lawrence Livermore National Laboratory’s (LLNL’s) Soil Screening and Management Plan (SSMP) soil screening levels (SSL). Groundwater was not encountered during the assessment and is expected to occur at roughly 65 feet bgs in the project area. No metals were detected at concentrations of concern in the concrete core samples collected and analyzed. Low gross alpha and beta activity concentrations were detected in the concrete core samples collected and analyzed. The detected activity concentrations would appear to be from naturally occurring radioactive isotopes, i.e., potassium 40, present in the raw materials used to make concrete and not artificially added. Tritium was not detected above the testing laboratory's Method Detection Limit (MDL) in any of the concrete core samples collected and analyzed. The radioactive isotopes - actinium 228, bismuth 214, lead 212, lead 214, potassium 40, radium 226, radium 228, and thallium 208, were detected at low activity concentrations in the concrete core samples analyzed. Based on the detected activity concentrations, the isotopes would appear to be naturally occurring in the raw materials used to make concrete and not artificially added. Acetone – a common laboratory contaminant, was detected in nine of the soil samples collected and analyzed. Concentrations of two other volatile organic compounds (benzene and tetrachloroethene) were detected in five of the soil samples analyzed. All concentrations were below SSLs. Total petroleum hydrocarbons as diesel range organics were detected at 43.9 milligrams per kilogram (mg/kg) in the 20-foot bgs duplicate sample from boring PC-B175-007. Total petroleum hydrocarbons as motor oil were detected at 7.20 mg/kg in the 15-foot bgs routine sample from boring PC-B175-001, and at 20.7 mg/kg in the 20-foot bgs duplicate sample from boring PC-B175-007. The SSL for diesel-range TPHs is 260 mg/kg. LLNL does not have an SSL for motor oil range TPHs. No indications of a release, e.g., visibly stained, or odorous soil, were present at the boring locations. No samples collected contained polychlorinated biphenyls (PCBs) in concentrations above the laboratory reporting limit. Arsenic was detected above its SSL of 8.51 mg/kg in the 25-foot bgs routine sample collected from boring PC-B175-023. Nickel was detected above its SSL of 86.0 mg/kg in the 10-foot bgs routine sample from boing PC-B175-005, the 20-foot bgs routine sample from boring PC-B175-025, and the 25-foot bgs routine sample from boring PC-B175-034. The detected concentrations, however, were well below ten times (10x) their respective STLCs. Gross alpha and/or gross beta were detected above their respective SSL activity concentrations in three routine soil samples. Retesting (two per sample) of the samples showed that the initial reported activity concentrations were anomalous. Tritium was not detected in any of the routine or duplicate soil samples collected and analyzed during the investigation. The radioactive isotopes - actinium 228, bismuth 212 and 214, lead 212 and 214, potassium 40, radium 224, 226 and 228, thallium 208, thorium 234 and uranium, were detected at low activity concentrations in the soil samples analyzed for radioactive constituents. The detected isotopes and their associated activity concentrations are typical of those naturally occurring in the marine-type sedimentary deposits underlying the Livermore Valley. No radiological controls are necessary for the soil evaluated.

54 ENVIRONMENTAL SCIENCES↗

Behavior of the Fused Quartz Suspended Core Acoustic Waveguide Sensor in Gamma Radiation

Previously, a fused-quartz acoustic waveguide named the suspended core waveguide with tight-field confinement in a small diameter was developed and its sensing potential in harsh environment was demonstrated with the fabricated periodic acoustic fiber Bragg grating. In this paper, the acoustic sensor was exposed to around 70 Gy/h gamma radiation at room temperature for 3550 h at Oak Ridge National Laboratory. For comparisons, a thermocouple and two optical fiber Bragg gratings were tested under the same conditions. The central frequency reading of the acoustic sensor was found to encounter a relatively fast decrease of 0.5 kHz in the first 800 hours. The reading then became stable, centering at 478.5 kHz with a fluctuation of ±0.2 kHz, and responded to small environmental temperature variations less than 1.2 °C. The major effect to the fluctuation was concluded to be radiation-induced material compaction and expansion. For optical fiber Bragg gratings, the same one-directional fast change of readings in the first 500 hours were observed as well. Although the optical gratings were able to track temperature changes, they also showed continuous drifts. The survivability and consistency of the acoustic sensor under long-term gamma radiation could lead to new sensing methods in nuclear applications.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Ordovician-Cambrian Units: Hierarchical Evaluation of Geologic Carbon Storage Resource Estimates

The Indiana Geological and Water Survey (IGWS) led subtask 1.1 to assess the regional distribution and estimate the storage capacity of Ordovician-Cambrian stratigraphic units located within the partnership region. A comprehensive data set of wireline logs and petrophysical information was used to generate these interpretations. These data include core analysis for porosity and permeability, mercury injection capillary pressure (MICP), and existing well data including location and stratigraphic information. This report includes storage resource estimates (SREs) for three potential storage reservoirs(limestone and dolostone from the Upper Ordovician Trenton Limestone/Black River Group and equivalent units, the Middle Ordovician St. Peter Sandstone, and primary target reservoir rocks of the Lower Ordovician and Upper Cambrian Knox Supergroup and equivalent units) calculated using six methodologies: (1) a fixed value of porosity of 10 percent in all units evaluated; (2) a unique average porosity (per well) from wireline-derived porosity (neutron, sonic, and/or density porosity for each unit); (3) porosity values from core analysis; (4) a depth-dependent porosity model (Knox Supergroup only); (5) porosity based on a model based on petrophysical facies; and (6) SREs using National Energy Technology Laboratory’s CO2 Storage prospeCtive Resource Estimation Excel aNalysis (CO2-SCREEN beta V2). All methods used the same values for thickness for each unit. However, the areal extent of each assessment was limited by the data available for each method. Estimated volumes were calculated in 1-by-1 kilometer grid cells and summarized as county and total stratigraphic unit volumes. The resultant SREs mass are displayed using boxplots, which allow for comparing data statistics (mean values and variability) between methods. Differences observed in SRE results from the six methods are mainly attributable to differences in the data and conceptual models used to interpret or estimate porosity in each method. Based on this systematic variability between methods, it is inferred that methods 1, 4, and 6 are best used for regional-scale reconnaissance estimates of storage capacity while methods 2, 3, and 5 are more appropriate for local scales where more data is required. All estimates are data-density dependent and different methods require different amounts of data for reasonable assessments. ArcMap 10.5.1 software was used to portray SREs to help visualize spatial variance of estimates for each methodology, and more importantly, to highlight those areas having the greatest total storage potential estimates.

01 COAL, LIGNITE, AND PEAT↗

CHESS 2025: Discrete-return LiDAR point clouds from NEON AOP surveys

This dataset provides Level 1 (L1) discrete-return light detection and ranging (LiDAR) point cloud data collected for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). These data were acquired to enable characterization of vegetation structure and other three-dimensional features of the land surface, and to evaluate structural changes that may have occurred between a prior LiDAR acquisition in 2018 and the 2025 overflight. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. LiDAR data were acquired using the Optech Galaxy Prime Airborne LiDAR Terrain Mapper onboard the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP). These are the primary unclassified discrete-return LiDAR data delivered by NEON and are provided per flightline as LASzip (LAZ) 1.4 Format 6 files. Data were processed following the workflow described in the NEON L0-to-L1 Discrete Return LiDAR Algorithm Theoretical Basis Document (Krause and Goulden 2022). Each record in the unclassified point clouds represents a geolocated laser target/return recorded by the LiDAR system, with values for X, Y, Z position and return intensity. All point coordinates are provided in meters. Horizontal coordinates are referenced in Universal Transverse Mercator (UTM) zone 13N and the World Geodetic System (WGS) 1984 ensemble datum. Elevations are referenced to Geoid12A. Flight metadata describing flightline boundaries and positional uncertainty by point are also included. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also 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.

2018 NEON and 2025 CHESS Campaigns↗

Recursive Use of the Short-Time Fast Fourier Transform for Signature Analysis in Continuous Processes

Although a nuclear reactor is a hostile environment for sensing and electrical communications, the reactor core is amenable to acoustic communication. An acoustic measurement infrastructure (AMI) has been installed in the Advanced Test Reactor (ATR) to record acoustic signals that can capture its different operating regimes. AMI uses coolant pumps as continuous signal sources, coolant and structural components as transmission lines, and accelerometers to capture system motion. A recursive signal processing technique based on the short-time fast Fourier transform (STFFT) for continuous processes provides unique signatures for diagnostic and prognostic analyses from the system motion data. Here this article presents a recursive STFFT methodology that processes acoustic signals from continuous industrial processes. The article first discusses the initial STFFT use with simulated data to elucidate the basic principles necessary to understand and interpret the STFFT results from actual pump vibration data. Each repetitive use of the STFFT on pump vibration data using the results from the prior STFFT processing will generate additional complimentary time-frequency-based signatures. These signatures are generated by the coolant pumps operating under different process conditions. After each use of the STFFT, the resulting signatures provide exemplary examples of the diversity and intuitive nature of recursively using the STFFT. This article focuses on recursively using the STFFT to provide numerous complimentary and diverse signatures that will ultimately be inputs for machine learning algorithms that provide predictive data analytics. The intuitive nature of the information and signatures from recursive STFFT processing will also bring intuitive interpretation capabilities to machine learning and predictive data analytic techniques.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

AI-Enabled Discovery and Physics-Based Optimization of Energy Efficient Processing Strategies for Advanced Turbine Alloys (Final Technical Report)

In this project, the multi-organizational team of academic and industrial researchers from the University of Kentucky an aerospace and energy generation OEM partner has leveraged novel Digital Process Twin (DPT) models of process/structure interactions (i.e., process-induced surface integrity) to advance a paradigm of fully integrated computational materials engineering (ICME). Using efficient process models as the core of a digital process simulator for a reinforcement learning algorithm, the team has integrated industrial data and metrics of structure/performance/energy relationships and manufacturing-related energy metrics to optimize dynamic processing parameters for significantly improved life-cycle energy efficiency of advanced γ-TiAl low-pressure turbine (LPT) alloys, as indicated by a set of design relevant parameters (e.g., residual stresses and scrap rate). The key objective and anticipated outcome of the project was at least a 10% reduction in life-cycle embodied energy for a recently developed, γ-TiAl low-pressure turbine (LPT) alloy and nickel-based superalloy Inconel 718, through the adoption of the proposed AI-enabled process optimization approach. The final project outcomes significantly exceeded this original target, realizing manufacturing-related energy efficiency improvements of more than 130% for TiAl and up to 80% for Inconel 718. Rather than following the prevailing and highly inefficient empirical paradigm, the proposed study demonstrated the feasibility of adopting a digital, physics-based process design and optimization paradigm. The recurring need for manual intervention, rework, reinspection causes significant production bottlenecks and unnecessary expense associated with delivering the requisite component quality. The OEM partner, and turbine industry in general, expect to reap significant cost and resource savings if an AI-optimized set of parameters can be applied to specific machining operations. The technical scope of the proposed project involved the paving of a realistic path towards model-based and AI-enabled Integrated Computational Materials Engineering (ICME), and away from inefficient empirical process optimization and legacy manufacturing practices, which are no longer able to efficiently process novel high-performance turbine alloy materials. The project team will address the fundamental knowledge gap that currently exists within the ICME paradigm with respect to the process/structure/performance/energy impacts of finishing processes. While significant resources have been devoted to the ‘early stages’ of manufacturing, such as alloy design, primary and secondary processing, finishing processes have not been adequately integrated within ICME. To provide an actionable path towards model-based finishing process design (e.g., machining, burnishing, grinding, polishing), we will employ a novel AI-enabled process optimization paradigm, based on a computationally efficient, physics-based process simulator. Through limited experimental work to calibrate and validate our process simulator model via an advanced in-situ characterization technique and process optimization via reinforcement learning, the project will seek to demonstrate a viable alternative to the inefficient ‘legacy’ processing strategies, empirical testing and broad scope machining learning approaches, all of which fail to adequately consider complex process physics. The project team has identified an intermetallic γ-TiAl LPT alloy, which is currently being used as part of the OEM partner’s advanced gas turbine designs. This particular alloy poses significant manufacturing challenges during finishing operations, which limit the degree to which the current turbine design can be manufactured in an energy- and cost-efficient manner. Empirical testing and numerical modeling efforts to optimize processing parameters for γ-TiAl have not been able to resolve these manufacturing challenges, so the proposed physics-based AI-enabled optimization technology would offer a truly novel and transformative capability. The multi-organizational team of academic and industry experts from the UKY and the OEM partner will work together closely to demonstrate the analytical and experimental critical function and characteristic proof of concept of this novel approach.

20 FOSSIL-FUELED POWER PLANTS↗

Developing Upscaling Approach for Swarming Hydraulic Fractures Observed at Hydraulic Fracturing Test Site through Multiscale Simulations

We show that this work aims to address a challenge posed by recent observations of tightly spaced hydraulic fractures in core samples from the hydraulic fracturing test site (HFTS) in the Middle Wolfcamp Formation. Many fractures in retrieved cores have subfoot spacing, which is at odds with conventional models in which usually one hydraulic fracture is initiated per cluster. Models assuming a single fracture at each cluster, although a common practice, often predict excessive fracture propagation that is inconsistent with microseismic observation. Here, we aim to develop a numerical approach to effectively account for densely spaced hydraulic fractures in field-scale simulations. Because it is impractical to explicitly model all aforementioned fractures, we develop a new upscaling law that enables existing simulation tools to predict reservoir response to fracture swarms. The upscaling law is derived based on an energy equivalence argument and validated through multiscale simulations using a high-fidelity code, GEOS. The swarming fractures are first modeled with a spacing that is much smaller than the cluster spacing; these fractures are then approximated by an upscaled, single fracture based on the proposed upscaling law. The upscaled fracture is shown to successfully match the energy input rate and produce the total fracture aperture and average propagation length of the explicitly simulated swarm. Afterward, the upscaling approach is further implemented in 3D field-scale simulations and validated against the HFTS microseismic data of a horizontal well. Our results show that hydraulic fracture swarming can significantly affect fracture propagation behaviors compared with the propagation of single fractures as assumed by conventional modeling approaches. Under the considered situations, the conventional treatment yields fast propagation speed that far exceeds that indicated by the microseismic data. We also illustrate that this discrepancy can be reduced readily through the implementation of the upscaling law. Our results demonstrate the importance of accounting for the fracture swarming effect in field-scale simulations and the efficacy of this approach to enable realistic predictions of reservoir responses to fracture swarms, without the need to model tightly spaced fractures individually.

02 PETROLEUM↗

CHESS 2025: Waveform LiDAR data from NEON AOP surveys

This dataset provides Level 1 (L1) full-waveform light detection and ranging (LiDAR) data collected for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). These data were acquired to enable characterization of vegetation structure and other three-dimensional features of the land surface, and to evaluate structural changes that may have occurred between a prior LiDAR acquisition in 2018 and the 2025 overflight. Waveform LiDAR data can provide more detailed information about objects on the ground than discrete point clouds typically do, and they are often used for granular target segmentation and characterization of subcanopy vegetation. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. LiDAR data were acquired using the Optech Galaxy Prime Airborne LiDAR Terrain Mapper onboard the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP). These are the primary waveform LiDAR data delivered by NEON and are provided per flightline in compressed Pulsewaves format, an open-source binary file standard. A Pulsewaves object comprises a two files: a pulse (.pls) file, which stores the geographic origin, outgoing vector, and metadata for every laser pulse emitted by the scanner, and a wave file (.wvs), which stores the sequential amplitude samples of the outgoing pulse and the returning signals. The files are published here in their compressed forms (.plz, .wvz). All waveform data were processed following the theoretical workflow described in the NEON L0-to-L1 Waveform LiDAR Algorithm Theoretical Basis Document (Krause and Goulden 2022a); however, the Pulsewaves output format differs from a legacy format described in that document. Waveform amplitude samples are recorded at 1 nanosecond intervals. All coordinates are provided in meters. Horizontal coordinates are referenced in Universal Transverse Mercator (UTM) zone 13N and the World Geodetic System (WGS) 1984 ensemble datum. Elevations are referenced to Geoid12A. Waveform data for the UPTA survey area were collected without incident and the published records are complete. However, both the ALMO and CRBU collections experienced issues that resulted in incomplete data for those areas. On collection day 2018-06-16 a hardware failure caused the waveform digitizer to lose data from the eastern edge of the ALMO site (Figure 22). The waveform data for flightlines 2–20 could not be extracted from the digitizer, and the data proved unrecoverable. As a result, a portion of the site does not have coverage with waveform data. Although no hardware failure was observed during collection over the CRBU area, final waveform files generated by vendor software contained only ~25% of the expected number of return pulses. After discovery, NEON initiated troubleshooting with the vendor. The root cause of the data ablation had not been identified at the time of publication. Additional data will be published in an update to this package if further recovery proves successful. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also 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.

2018 NEON and 2025 CHESS Campaigns↗

Shake loss intensities in x-ray photoelectron spectroscopy: Theory, experiment, and atomic composition accuracy for MgO and related compounds

The relative intensities of XPS core levels, scaled by their photoionization cross sections, are regularly used to determine sample atomic composition. Cross sections, however, give the intensity to all possible final states for the core ionizations, not just to the main peak. This includes all intrinsic satellite structure (shake states and, for open shell systems, the different ionic multiplets). In practice, for solids, this is usually experimentally impossible to determine accurately because such a satellite structure sits on the inelastically scattered electron background and cannot be easily separated. Therefore, usually, only the intensity of the main peak is used. This limits the ultimate possible accuracy of XPS composition determination. The purpose of the present paper is to examine the contributions that a theoretical analysis of losses of intensity can make to improve quantitation. For an MgO single crystal, we show that the correct stoichiometry of 1:1 can be recovered using the theoretical analysis of the experimental MgO peak ratio intensities. For materials with a sufficient bandgap for the XPS main peaks to be separated from the scattered background, the intensity of main peaks can often be accurately determined. Thus, if one uses theory to calculate that fraction of the total intensity lost from a main peak into all its satellite structure, the intensity of just main peaks could then be used to more accurately determine relative atom % composition. This work tests this approach using a single crystal MgO (50% Mg, 50% O) standard. Ab initio electronic structure theory of representative MgO clusters is used to determine Hartree–Fock wave functions for the ground state and final ionized states corresponding to the main Mg 2p and O1s XPS peaks of the oxide. The sudden approximation, SA, is used to determine the fractional losses from these main peaks to shake satellites, which is found to be greater for O1s than Mg2p. This results in predicted “apparent composition” for stoichiometric MgO of 55.2% Mg, 44.8% O instead of the true 50% Mg, 50% O. Equivalent theory for CaO results in a predicted apparent Ca value of 53.4%. Experimentally, using Mg2s or 2p intensity ratio to O1s, we find values between 52.2% and 56.0% Mg using two crystals and four different instrument electron pass energies. The average value of the measurements is 54.5% Mg when corrected for the presence of an adventitious carbon overlayer and slight surface hydroxide. Though this agreement with theory may be somewhat fortuitous, given the potential experimental errors, which are fully discussed, it is similar to that in our earlier study on LiF. We also present preliminary experimental data on Mg(OH) 2 and MgSO 4 , which show a similar trend of apparently higher than 50% Mg, but we have no theory values. We are not yet able to experimentally test for validation of the difference between apparent composition for MgO (55.2% Mg) and CaO (53.4% Ca), owing to significant carbonate formation at the surface of the single crystal CaO. Here, an important conclusion is that the theoretical determination of shake losses, obtained with ab initio wavefunctions and the SA, is likely to be a useful way to calibrate the accuracy and reliability of compositions obtained from XPS intensities and merits further study.

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