Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “spatial mapping”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Toward a More Complete Optical Census of Active Galactic Nuclei via Spatially Resolved Spectroscopy

While emission line flux ratio diagnostics are the most common technique for identifying active galactic nuclei (AGNs) in optical spectra, applying this approach to single-fiber spectra of galaxies can omit entire subpopulations of AGNs. Here, we use spatially resolved spectroscopy from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey to construct a sample of 10 galaxies where Baldwin–Philips–Terlevich line flux ratio diagnostics classify each galaxy’s central 3" spectrum as LINER or star-forming, while >10% of the spaxels in the galaxy’s MaNGA footprint are classified as Seyfert. We obtain Chandra observations of these 10 galaxies with off-nuclear Seyfert regions to determine whether AGNs are actually present in them. Our main result is that 7–10 (depending on strictness of criteria) of the galaxies host one or more X-ray AGNs, even though none of them were classified as AGNs based on their single-fiber optical spectra. We find that these AGNs were not identified in the single-fiber spectra because they are AGNs in the nuclei of companion galaxies, low-luminosity AGNs, dust-obscured AGNs, and/or flickering AGNs. In summary, we find that off-nuclear AGN signatures may increase the number of known AGNs by a factor of two over what conventional single nuclear fiber spectra identify. Our results show that spatially resolved spectroscopy can be leveraged to reveal a more complete census of AGNs that are traditionally missed by single-fiber spectra.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Developing a Power Plant Suitability Model for the Energy Zones Mapping Tool

This report provides an example of designing, developing, and running a power plant suitability model in the Energy Zones Mapping Tool (EZMT), a public, web-based mapping tool with a large spatial database focused on energy infrastructure, energy resources, and related siting factors. The example focuses on natural gas combined cycle (NGCC) power plants, which have several unique and interesting characteristics. NGCC plants typically provide peaking power to the electrical grid. Such plants can be started or stopped relatively quickly and are often used to supplement base load plants (such as nuclear or coal) during times of peak electrical consumption or to counterbalance lulls in variable power generation (such as wind or solar). Due to these and other factors, NGCC plants have been projected to increase in number under energy planning studies such as Hadley et al. The scope of the Hadley et. al. study is the Eastern Interconnection (EI), the electrical transmission grid serving much of the United States and Canada east of the Rocky Mountains. Results in the study are organized according to 22 Multi-region National—North American Electricity and Environment Model (NEEM) regions within the EI. NGCC plants usually have lower water requirements than other thermoelectric power plants they may replace; therefore, they are expected to have an interesting role in reducing the overall water requirements of energy generation.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Disentangling multiple scattering with deep learning: application to strain mapping from electron diffraction patterns

Abstract A fast, robust pipeline for strain mapping of crystalline materials is important for many technological applications. Scanning electron nanodiffraction allows us to calculate strain maps with high accuracy and spatial resolutions, but this technique is limited when the electron beam undergoes multiple scattering. Deep-learning methods have the potential to invert these complex signals, but require a large number of training examples. We implement a Fourier space, complex-valued deep-neural network, FCU-Net, to invert highly nonlinear electron diffraction patterns into the corresponding quantitative structure factor images. FCU-Net was trained using over 200,000 unique simulated dynamical diffraction patterns from different combinations of crystal structures, orientations, thicknesses, and microscope parameters, which are augmented with experimental artifacts. We evaluated FCU-Net against simulated and experimental datasets, where it substantially outperforms conventional analysis methods. Our code, models, and training library are open-source and may be adapted to different diffraction measurement problems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Layer-resolved magnetic proximity effect in van der Waals heterostructures

Magnetic proximity effects are integral to manipulating spintronic, superconducting, excitonic and topological phenomena in heterostructures. These effects are highly sensitive to the interfacial electronic properties, such as electron wavefunction overlap and band alignment. The recent emergence of magnetic two-dimensional materials opens new possibilities for exploring proximity effects in van der Waals heterostructures. In particular, atomically thin CrI 3 exhibits layered antiferromagnetism, in which adjacent ferromagnetic monolayers are antiferromagnetically coupled. In this paper, we report a layer-resolved magnetic proximity effect in heterostructures formed by monolayer WSe 2 and bi/trilayer CrI 3 . By controlling the individual layer magnetization in CrI 3 with a magnetic field, we show that the spin-dependent charge transfer between WSe 2 and CrI 3 is dominated by the interfacial CrI 3 layer, while the proximity exchange field is highly sensitive to the layered magnetic structure as a whole. In combination with reflective magnetic circular dichroism measurements, these properties allow the use of monolayer WSe 2 as a spatially sensitive magnetic sensor to map out layered antiferromagnetic domain structures at zero magnetic field as well as antiferromagnetic/ferromagnetic domains at finite magnetic fields. Our work reveals a way to control proximity effects and probe interfacial magnetic order via van der Waals engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Unravelling the origin of extended radio emission in narrow-line Seyfert 1 galaxies with the JVLA

Narrow-line Seyfert 1 galaxies (NLS1s) are believed to be active galactic nuclei (AGN) in the early stages of their evolution. Several dozen of them have been found to host relativistic jets, whilst the majority of NLS1s have not even been detected in radio, emphasising the heterogeneity of the class in this band. In this paper, our aim is to determine the predominant source of radio emission in a sample of 44 NLS1s, selected based on their extended kiloparsec-scale radio morphologies at 5.2 GHz. Here, we accomplish this by analysing their spatially resolved radio spectral index maps, centred at 5.2 GHz, as the spectral index carries information about the production mechanisms of the emission. In addition, we utilise several diagnostics based on mid-infrared emission to estimate the star formation activity of their host galaxies. These data are complemented by archival data to draw a more complete picture of each source. We find an extraordinary diversity among our sample. Approximately equal fractions (~10–12 sources) of our sources can be identified as AGN-dominated, composite, and host-dominated. Among the AGN-dominated sources are a few NLS1s with very extended jets, reaching distances of tens of kiloparsecs from the nucleus. One of these, J0814+5609, hosts the most extended jets found in an NLS1 so far. We also identify five NLS1s that could be classified as compact steep-spectrum sources. In addition, one source shows a possible kiloparsec-scale relic that reaches well outside the host galaxy as well as restarted nuclear activity, and one could belong to the sub-class of NLS1s that host relativistic jets that seem to be absorbed at lower radio frequencies (< 10 GHz). We further conclude that, due to the variety seen in NLS1s, simple proxies, such as the star formation diagnostics also employed in this paper and the radio loudness parameter, are not ideal tools for characterising NLS1s. We emphasise the necessity of examining NLS1s as individuals instead of making assumptions based on their classification. When these issues are properly taken into account, NLS1s offer an exceptional environment for studying the interplay between the host galaxy and several AGN-related phenomena, such as jets and outflows.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

BEYONDPLANCK XIII. Intensity foreground sampling, degeneracies, and priors

We present the intensity foreground algorithms and model employed within the BEYONDPLANCK analysis framework. The BEYONDPLANCK analysis is aimed at integrating component separation and instrumental parameter sampling within a global framework, leading to complete end-to-end error propagation in the Planck Low Frequency Instrument (LFI) data analysis. Given the scope of the BEYONDPLANCK analysis, a limited set of data is included in the component separation process, leading to foreground parameter degeneracies. In order to properly constrain the Galactic foreground parameters, we improve upon the previous Commander component separation implementation by adding a suite of algorithmic techniques. These algorithms are designed to improve the stability and computational efficiency for weakly constrained posterior distributions. These are: (1) joint foreground spectral parameter and amplitude sampling, building on ideas from MIRAMARE; (2) component-based monopole determination; (3) joint spectral parameter and monopole sampling; and (4) application of informative spatial priors for component amplitude maps. We find that the only spectral parameter with a significant signal-to-noise ratio using the current BEYONDPLANCK data set is the peak frequency of the anomalous microwave emission component, for which we find $ν$ p = 25.3 ± 0.5 GHz; all others must be constrained through external priors. Future works will be aimed at integrating many more data sets into this analysis, both map and time-ordered based, thereby gradually eliminating the currently observed degeneracies in a controlled manner with respect to both instrumental systematic effects and astrophysical degeneracies. When this happens, the simple LFI-oriented data model employed in the current work will need to be generalized to account for both a richer astrophysical model and additional instrumental effects. This work will be organized within the Open Science-based COSMOGLOBE community effort.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Characterization of a Low-Temperature Plasma (LTP) Ambient Ionization Source Using Temporally Resolved Monochromatic Imaging Spectrometry

The low-temperature plasma (LTP) probe is a common plasma-based source used for ambient desorption–ionization mass spectrometry (MS). While the LTP probe has been characterized in detail with MS, relatively few studies have used optical spectroscopy. In this paper, two-dimensional (2D) imaging at selected wavelengths is used to visualize important species in the LTP plasma jet. First, 2D steady-state images of the LTP plume for N 2 + (391.2 nm), He I (706.5 nm), and N 2 (337.1 nm) emissions were recorded under selected plasma conditions. Second, time-resolved 2D emission maps of radiative species in the LTP plasma jet were recorded through the use of a 200 ns detection gate and varying gate delays with respect to the LTP trigger pulse. Emission from He I, N 2 + , and N 2 in the plasma jet region was found to show a transient behavior (often referred to as plasma bullets) lasting only a few microseconds. The N 2 + and He I maps were highly correlated in spatial and temporal structure. Further, emission from N 2 showed two maxima in time, one before and one after the maximum emission for N 2 + and He I, due to an initial electronic excitation wave and ion–electron recombination, respectively. Third, the interaction of the LTP probe with a sample substrate and an electrically grounded metallic needle was studied. Emission from a fluorophore on the sample substrate showed an initial photon-induced excitation from plasma-generated photons followed by electronic excitation by other plasma species. The presence of a grounded needle near the plasma jet significantly extended the plasma jet lifetime and also generated a long-lived corona discharge on the needle. The effect of LTP operating parameters on emission spectra was correlated with mass-spectral results including reagent-ion signals. Lastly, five movies provide a side-by-side comparison of the temporal behavior of emitting species and insights into the interactions of the emission clouds with a sample surface as well as an external needle. Temporally and spatially resolved imaging provided insights into important processes in the LTP plasma jet, which will help improve analyte ion sampling in LTP–MS.

Chan, George C. -Y.↗
DOE OSTI2021

Immobilization of Uranium in a Wetland 8-km Downstream from an Industrial Source (Report)

A three-day walk-over survey with portable gamma detecting equipment was conducted over a uranium-contaminated wetland located 8-km downstream from a former fuel fabrication facility. 97,000 spectra were collected, individually processed to extract uranium activity data, and then integrated with topographical information (LIDAR) to create maps. These maps reveal that 50 years after being released into the environment, 11% of the uranium is retained in the 9-ha wetland area. Combined with measurement collected closer to the source, it was determined that 94% of the released uranium is presently being held in downstream wetlands. This demonstrates that wetlands can be very effective at immobilizing contaminants for long durations. The survey also showed that previous flyover maps overestimated the size of the contaminated areas by 140% but had the advantage of being completed in orders-of-magnitude fewer labor hours. Depending on project needs, the walk-over technique may be useful to include in tandem with flyover measurements to acquire maps with greater sensitivity and spatial resolution.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Advanced User Interface Capabilities [Slides]

This tutorial will review the data plotting and geometry visualization capabilities in the Fulcrum user interface. This tutorial will help you become familiar with Fulcrum’s 2D plot, and 2D and 3D geometry visualization features. You will learn how to identify plottable data items, compose and export plot and plot data for SCALE plot formats (SDF, Ampx MG/CE, PLT, F71, PTP, SPF, ORIGEN Gamma data, etc.) and visualize, navigate, cut, hide, and export the geometry and spatial data (fission-, dose-map, etc.) overlays in 2D and 3D. No prior experience with SCALE is required. Attendees can follow along using 6.3.0-beta.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Characterization of Rare-Earth Elements in Lignite Coal of the Williston Basin: Past Efforts and Ongoing Work

Rare-earth elements (REEs) have been a subject area of high interest for their unique properties. REEs are crucial materials used in an incredible array of consumer goods, energy system components, and military defense applications. While the United States has one operating REE mine, the product is sent overseas for refining into usable metals making the United States 100% import-reliant on these critical materials. This has led the Federal Government to declare the REE market an issue of national security. The Energy and Environmental Research Center (EERC) under funding provided by the Department of Energy (DOE) has undertaken efforts to determine if the lignite coal found in the Williston Basin has the potential to be an ore body containing sufficient quantities of REEs and Critical Minerals (CM) for extraction and processing. In one such effort, the EERC collected over 400 samples from the Williston Basin lignite coal seams including outcrops as well as active mines. Those efforts have been followed up with ongoing work under the U.S. DOE’s Carbon Ore, Rare Earth and Critical Minerals Initiative (CORE-CM) currently ongoing in the Williston Basin as well as other basins in the United States. This ongoing work in the Williston Basin characterizing REEs in coal has focused on the collection of new sampling and analysis of REEs in coal and building upon previous characterization work. This information is being used to understand the spatial distribution of REEs through mapping and 3D modeling. The goals of these efforts are to better understand the mechanisms for distribution of the REEs in lignite coal as well as their concentration and determine knowledge gaps in characterization and to start to build the database required to understand the potential resource in the Williston Basin.

Feole, Ian K.↗
DOE OSTI2025

Simulation of Creep Deformation and Failure in Graded AM Microstructures

This report describes modeling tools and techniques developed to simulate the long-term material performance of 316H stainless steel manufactured using Laser Powder Bed Fusion (LPBF). A physics-based Crystal Plasticity Finite Element model is used to simulate creep in microstructures and to study the roles of grain morphology, porosity, and texture. We describe our modeling methodology, including an orientation-mapping technique to capture the spatially varying crystallographic orientation that results from the build conditions. Our study of microstructural features shows that AM microstructures produced by LPBF tend to creep faster in the build direction, while texture and grain boundaries strengthen the transverse directions. However, when grain-boundary porosity and the consequent cavity growth are included in the model, the transverse directions begin to creep faster. In examining texture, the results indicate that spatially varying orientation arising from the build conditions increases anisotropy in the material, making it critical to account for orientation gradients in the material to accurately model its mechanical behavior. We also describe a material-model calibration campaign in which we calibrated the constitutive model specifically for LPBF 316H stainless steel at 725℃ for both solution-annealed and as-built conditions. Finally, these tools and techniques are used to model creep in microstructures representing different regions of an LPBF material with graded microstructure, owing to intentional variation in processing conditions. The creep simulation results show good agreement with experimental data across all three microstructures, with future work planned to study rupture in the material.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Signatures of Inflowing Gas in Red Geyser Galaxies Hosting Radio Active Galactic Nuclei

We study cool neutral gas traced by NaD absorption in 140 local ($z$ < 0.1) early-type red geyser galaxies. These galaxies show unique signatures in spatially resolved strong line emission maps that have been interpreted as largescale active galactic nucleus–driven ionized winds. To investigate the possible fuel source for these winds, we examine the abundance and kinematics of cool gas ($T$ ~ 100–1000 K) inferred from Na I D absorption in red geysers and matched control samples drawn from the Sloan Digital Sky Survey IV Mapping Nearby Galaxies at Apache Point Observatory survey. We find that red geysers host greater amounts of NaD-associated material. Substantial cool gas components are detected in more than 50% of red geysers (compared to 25% of the control sample) going up to 78% for radio-detected red geysers. Our key result is that cool gas in red geysers is predominantly infalling. Among our 30 radio-detected red geysers, 86% show receding NaD absorption velocities (with respect to the systemic velocity) between 40 and 50 km s-1 . We verify this result by stacking NaD profiles across each sample, which confirms the presence of infalling NaD velocities within red geysers (~40 km s -1 ) with no velocity offsets detected in the control samples. Interpreting our observations as signatures of inflowing cool neutral clouds, we derive an approximate mass inflow rate of $\dot{M}$ in ~ 0.1$M$ ⊙ yr -1 , similar to that expected from minor merging and internal recycling. In conclusion, some red geysers show much higher rates ($\dot{M}$ in ~ 5$M$ ⊙ yr -1 ), which may indicate an ongoing accretion event.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Connecting Galactic Outflows and Star Formation: Inferences from Hα Maps and Absorption-line Spectroscopy at 1 ≲ z ≲ 1.5

We investigate the connection between galactic outflows and star formation using two independent data sets covering a sample of 22 galaxies between 1 ≲ z ≲ 1.5. The Hubble Space Telescope WFC3/G141 grism provides low spectral resolution, high spatial resolution spectroscopy yielding Hα emission-line maps from which we measure the spatial extent and strength of star formation. In the rest-frame near-UV, Keck/DEIMOS observes Fe ii and Mg ii interstellar absorption lines, which provide constraints on the intensity and velocity of the outflows. We compare outflow properties from individual and composite spectra with the star formation rate (SFR) and SFR surface density (Σ{sub SFR}), as well as the stellar mass and specific SFR (sSFR). The Fe ii and Mg ii equivalent widths (EWs) increase with both SFR and Σ{sub SFR} at ≳3σ significance, while the composite spectra show larger Fe ii EWs and outflow velocities in galaxies with higher SFR, Σ{sub SFR}, and sSFR. Absorption-line profiles of the composite spectra further indicate that the differences between subsamples are driven by outflows rather than the interstellar medium. While these results are consistent with those of previous studies, the use of Hα images makes them the most direct test of the relationship between star formation and outflows at z > 1 to date. Future facilities such as the James Webb Space Telescope and the upcoming Extremely Large Telescopes will extend these direct, Hα-based studies to lower masses and SFRs, probing galactic feedback across orders of magnitude in galaxy properties and augmenting the correlations we find here.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Forest aboveground biomass estimation through integration of sentinel-2 and PALSAR-2 time series: assessing models trained on GEDI and field inventory benchmarks

Accurate and spatially explicit forest Aboveground Biomass (AGB) mapping through remote sensing is critical for quantifying terrestrial carbon stocks and informing effective forest management strategies. However, AGB estimation in dense forests with complex terrain remains challenging due to satellite sensor signal saturation problem (saturation issue occurs in high biomass forests), structural complexity, and limited ground truth for calibration. This study presents a novel framework that integrates multi-temporal Sentinel-2 optical imagery, ALOS PALSAR-2 Synthetic Aperture Radar (SAR) data, and topographic variables with explainable Machine Learning to map AGB across mountainous forests within subtropical and temperate oceanic climate zones of Mexico. We evaluate the effects of temporal granularity and sensor synergy by comparing multiple temporal inputs and sensor configurations (Sentinel-2, PALSAR-2, and their fusion), and assess model performance using two reference datasets: NASA GEDI LiDAR-derived biomass and Mexico’s National Forest and Soil Inventory (INFyS). Our results showed that models trained on INFyS consistently outperformed those trained on GEDI, highlighting limitations in GEDI’s reliability in biomass estimates within this study region. Furthermore, the integration of Sentinel-2 and PALSAR-2 provided improved predictions compared to single-sensor models, particularly when combined with temporally explicit yearly statistics. The best-performing model, which was trained on INFyS data, and considered both Sentinel-2 and PALSAR-2 yearly statistics, as well as topographic variables, achieved an R2 of 0.64, RMSE of 51.10 Mg/ha, and relative RMSE (rRMSE) of 58.69%. Explainable ML analysis identified Sentinel-2 spectral indices and topographic features as key predictors, while PALSAR-2 metrics provided complementary information, partially mitigating saturation effects in high-biomass areas. Specifically, integrating both sensors substantially improved AGB estimation in high biomass forest (≥200 Mg/ha), yielding 98% gains over optical-only model, with resulting estimates exceeding GEDI L4B by 29% and ESA-CCI-BIOMASS by 174%. Terrain-stratified analysis indicated close agreement with GEDI in low-slope areas, with increasing divergence as slope steepness increased, while estimates remained consistently higher than ESA-CCI-BIOMASS across all slope classes. The proposed approach advances multi-sensor fusion and temporal feature engineering for AGB mapping using open-access satellite datasets, providing a scalable and reproducible framework for annual biomass monitoring in topographically complex mountainous forests. The resulting 25 m resolution biomass product has the potential to provide spatially detailed information for forest monitoring and may support applications in carbon accounting and forest management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication.

There is a growing interest in custom spatial accelerators for machine learning applications. These accelerators employ a spatial array of processing elements (PEs) interacting via custom buffer hierarchies and networks-on-chip. The efficiency of these accelerators comes from employing optimized dataflow (i.e., spatial/temporal partitioning of data across the PEs and fine-grained scheduling) strategies to optimize data reuse. The focus of this work is to evaluate these accelerator architectures using a tiled general matrix-matrix multiplication (GEMM) kernel. To do so, we develop a framework that finds optimized mappings (dataflow and tile sizes) for a tiled GEMM for a given spatial accelerator and workload combination, leveraging an analytical cost model for runtime and energy. Finally, our evaluations over five spatial accelerators demonstrate that the tiled GEMM mappings systematically generated by our framework achieve high performance on various GEMM workloads and accelerators.

42 ENGINEERING↗
DOE OSTI2025

Maps of growing season gross primary production and net ecosystem exchange for Council Road Mile Marker 71, Seward Peninsula, Alaska, [2017-2023]

This data archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025a). Murphy et al. (2025a) evaluated whether incorporating observed Arctic vegetation heterogeneity into ELM, the land model of the Department of Energy’s Energy Exascale Earth System Model (E3SM), improved simulations of tundra carbon cycling. The associated model archive can be found at Murphy et al. (2025b). The study focused on the spatial patterns and net landscape-level growing season productivity and carbon uptake. As part of this evaluation, observationally derived maps of average growing season (June–August) net ecosystem exchange (NEE) and gross primary production (GPP) were developed for the same domain. These maps, which form the dataset described here, integrate eddy covariance flux tower, remote sensing, and vegetation community data to provide spatially explicit benchmarks for model evaluation. The maps provide spatially explicit estimates of average growing season NEE and GPP across 13 tundra vegetation communities within the study domain. By combining flux tower observations with Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) hyperspectral imagery and drone-based normalized difference vegetation index (NDVI), these maps capture the heterogeneity of carbon fluxes associated with different Arctic vegetation types. While they represent average seasonal conditions rather than interannual variability, the maps provide a unique dataset for evaluating model performance, comparing vegetation community contributions to landscape-scale carbon cycling, and supporting regional analyses of Arctic carbon dynamics. This data archive contains 5 m resolution maps of vegetation communities, vegetation community average growing season GPP, and vegetation community average growing season NEE (three *.tif files), a User’s Guide (*pdf file), and Table 1 of the User’s Guide displaying vegetation community coverage and average growing season NEE and GPP values (*.csv file).

Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗
DOE OSTI2026

Unsupervised Segmentation and Clustering Workflow for Efficient Processing of 4D-STEM and 5D-STEM Data

Four-dimensional scanning transmission electron microscopy (4D-STEM) enables mapping of diffraction information with nanometer-scale spatial resolution, offering detailed insight into local structure, orientation, and strain. However, as data dimensionality and sampling density increase, particularly for in situ scanning diffraction experiments (5D-STEM), robust segmentation of structurally consistent behavior across sequential measurements becomes essential for efficient and physically meaningful analysis. Here, we introduce a clustering framework that identifies crystallographically distinct domains from 4D-STEM datasets. By using local diffraction-pattern similarity as a metric, the method extracts closed contours delineating spatially contiguous regions. This approach produces cluster-averaged diffraction patterns that improve signal quality while reducing data volume by orders of magnitude, enabling rapid and accurate orientation, phase, and strain mapping. We demonstrate the applicability of this approach to in situ liquid-cell 4D-STEM data of gold nanoparticle growth. Our method provides a scalable and generalizable route for spatially coherent segmentation, data compression, and quantitative structure–strain mapping across diverse 4D-STEM modalities. The full analysis code and example workflows are publicly available to support reproducibility and reuse.

4D-STEM↗
DOE OSTI2024

Quasifragmentation functions in the massive Schwinger model

We introduce the concept of the quark quasifragmentation function (qFF) using an equal-time and spatially boosted form of the Collins-Soper fragmentation function where the out-meson fragment is replaced by the current asymptotic condition. We derive the qFF for a fermion in two-dimensional quantum electrodynamics (QED2) using the Kogut-Susskind Hamiltonian after a mapping onto spin qubits in a spatial lattice with open boundary conditions. This form is suitable for quantum computations. We compute the qFF by exact diagonalization of the spin Hamiltonian. The results are compared to the qFF following from the Drell-Levy-Yan result for QED2, both at strong and weak coupling, and to two-dimensional quantum chromodynamics in the lowest Fock approximation.

Fragmentation functions↗