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At least 757 records · Page 42

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↗

Temperature Dependent Early-Stage Oxidation Dynamics of Cu(100) Film with Faceted Holes

Fundamental understanding of surface oxidation dynamics is critical for rational corrosion protection and advanced manufacturing of nanostructured oxides. In situ environmental TEM (ETEM) provides high spatial (nano- to atomic- scale) and temporal (< 0.1 s) resolution to investigate the early-stage oxidation/corrosion dynamics of metals and alloys. Thin samples with facets are widely used to enable cross-sectional observation of the oxidation dynamics in ETEM. However, how different facet orientations oxidize under the same conditions, and how these facets change the oxidation process, has not been investigated before. Here, using in situ ETEM, we systematically compare the oxidation dynamics of Cu(001) thin films, with faceted holes exposing {100} and {110} facets at temperatures ranging from 250–600 °C under 0.03 Pa O 2 . Oxidation preference is observed to change, from Cu(110) facets at lower temperatures to Cu(100) facets at ~ 500 °C. Oxide growth mechanisms change from outward growth on Cu 2 O surfaces at low temperatures, to inward growth on Cu-Cu 2 O interfaces at high temperatures. At high temperatures (500–600 °C), a rod-like Cu 2 O morphology is observed, with side facets of ~ {024} and top facets of {100} on Cu(100). This differs from the square-shaped Cu 2 O exposing {110} facets formed on Cu(001) surfaces. Rod-like oxides exhibit directional growth along their lengths with linear growth rates, regardless of rod length and width. This suggests that O from Cu(001) surfaces, rather than Cu(100) facets, serves as an O source for oxide growth. These results show a direct comparison of oxidation at different orientations with temperature, underscoring the temperature dependence of oxidation preference. Our results also suggest future in situ ETEM experiments viewing oxidation corrosion cross-sectionally should be cautious when oxide size is comparable with sample thickness, as the oxidizing mechanism may change due to sample thickness.

36 MATERIALS SCIENCE↗

ADRIANO2 Calorimeter Performance from 2022 Test Beams

A novel high-granularity dual-readout calorimetric technique was developed as part of the T1604 collaboration. The ADRIANO2 Calorimeter Prototype consists of a pair of optically isolated, small sized tiles made of scintillating plastic and lead glass. Čerenkov light from the lead glass are exploited to for high resolution timing measurements, while high granularity from scintillating plastic can be used to probe the spatial component of the particle shower. This setup works for excellent energy resolution and particle detection for REDTOP as it is crucial for a calorimeter to detect the decay products of eta/eta-prime mesons. Measurements were collected on ADRIANO2 between February to December 2022 to evaluate the detector performance at Fermilab’s Test Beam Facility. The key metrics extracted from my analysis are the detector’s efficiency for various tile configuration and light-yield which will then be used as parameters for an upgraded REDTOP monte-carlo simulation campaign. An in-depth analysis of ADRIANO2 performance are detailed in this presentation.

43 PARTICLE ACCELERATORS↗

Simulation of the Impact of Point Defects and Edge Dislocations on X-Ray Diffraction in Hexagonal (Ni,Co) 1+2 x Ti 1– x O 3 Thin Films

In this work, a computer code for simulating high-resolution X-ray diffraction (XRD) data from disordered crystals with arbitrary spatial composition and local lattice parameters is developed. Simulated patterns are compared with the experimental data collected on a single phase, highly crystalline (Ni 0.42 Co 0.58 ) 2.22 Ti 0.39 O 3 solid-solution thin film exhibiting a large number of subsidiary minima. As a case study, the edge dislocations in hexagonal (Ni,Co) 3 O 3 thin films with Burgers vector parallel and perpendicular to the a-axis and c-axis, respectively, are modeled. No peak profiles are assumed and thus issues related to profile fitting are avoided. Both macroscopic features, such as film thickness, and atomic-scale structure, such as dislocations, are simultaneously modeled. Simulations are run on a desktop machine. Commonly applied database-based phase identification routines can result in wrong phase identification, unless intensities are properly modeled. Modeling tools of diffractometer manufacturers are compared with the present approach. An example of how simulated reciprocal lattice patterns can be used to choose relevant measurement geometries in defected thin films is given.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Radiation and heat transport in divergent shock–bubble interactions

Shock–bubble interactions (SBIs) are important across a wide range of physical systems. In inertial confinement fusion, interactions between laser-driven shocks and micro-voids in both ablators and foam targets generate instabilities that are a major obstacle in achieving ignition. Experiments imaging the collapse of such voids at high energy densities (HED) are constrained by spatial and temporal resolution, making simulations a vital tool in understanding these systems. In this study, we benchmark several radiation and thermal transport models in the xRAGE hydrodynamic code against experimental images of a collapsing mesoscale void during the passage of a 300 GPa shock. We also quantitatively examine the role of transport physics in the evolution of the SBI. This allows us to understand the dynamics of the interaction at timescales shorter than experimental imaging framerates. We find that all radiation models examined reproduce empirical shock velocities within experimental error. Radiation transport is found to reduce shock pressures by providing an additional energy pathway in the ablation region, but this effect is small (∼1% of total shock pressure). Employing a flux-limited Spitzer model for heat conduction, we find that flux limiters between 0.03 and 0.10 produce agreement with experimental velocities, suggesting that the system is well-within the Spitzer regime. Higher heat conduction is found to lower temperatures in the ablated plasma and to prevent secondary shocks at the ablation front, resulting in weaker primary shocks. Finally, we confirm that the SBI-driven instabilities observed in the HED regime are baroclinically driven, as in the low energy case.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Distinguishing Elements at the Sub‐Nanometer Scale on the Surface of a High Entropy Alloy

Materials in crystalline form possess translational symmetry (TS) when the unit cell is repeated in real space with long- and short-range orders. The periodic potential in the crystal regulates the electron wave function and results in unique band structures, which further define the physical properties of the materials. Amorphous materials lack TS due to the randomization of distances and arrangements between atoms, causing the electron wave function to lack a well-defined momentum. High entropy materials provide another way to break the TS by randomizing the potential strength at periodic atomic sites. The local elemental distribution has a great impact on physical properties in high entropy materials. It is critical to distinguish elements at the sub-nanometer scale to uncover the correlations between the elemental distribution and the material properties. Here, the use of synchrotron X-ray scanning tunneling microscopy (SX-STM) with sub-nm scale resolution in identifying elements on a high entropy alloy (HEA) surface is demonstrated. By examining the elementally sensitive X-ray absorption spectra with an STM tip to enhance the spatial resolution, the elemental distribution on an HEA's surface at a sub-nm scale is extracted. In conclusion, these results open a pathway towards quantitatively understanding high entropy materials and their material properties.

36 MATERIALS SCIENCE↗

High-resolution in-situ characterization of laser powder bed fusion via transmission X-ray microscopy at X-ray free electron lasers

In this work, we describe the instrumentation used to perform the first operando transmission X-ray microscopy (TXM) and simultaneous X-ray diffraction of laser melting simulating laser powder bed fusion on the XCS instrument at the Linac Coherent Light Source (LCLS) X-ray free-electron laser (XFEL). Our TXM with 40× magnification in the X-ray regime at 11 keV gave spatial resolutions down to 940 nm per line pair, with effective pixel sizes down to 206 nm, image integration times of <100 fs, and frame rates tunable between 2.1 and 119 ns for two probe frames (0.48 GHz to 8.4 MHz). Images were recorded on Zyla and Icarus (UXI) detectors to trade off between spatial resolution and time dynamics. A 1 kW CW IR laser was coupled into the interaction point to conduct pump–probe studies of laser melting and solidification dynamics. Our temporal and spatial resolution with attenuation-based contrast exceeds that currently possible with synchrotron-based high-speed radiography. This system was sensitive to feature velocities of 10–12000 m s −1 but we did not observe any motion in this range in the laser melting of Al6061 alloy. Shockwaves were not observed and hot cracking proceeded at velocities below the detection limits. Pore accumulation was observed between successive shots, indicating that bubble escape mechanisms were not active. With proper experimental design, the spatial resolution, contrast and field of view could be further improved or modified. The increased brightness and narrower bandwidth of the XFEL allowed for this imaging technique and it lays the groundwork for a wide range of operando techniques to study additive manufacturing.

47 OTHER INSTRUMENTATION↗

Extend an innovative HPC-Compatible Multiple Temporal-spatial Resolution Concurrent Finite Element Modeling Approach to Guide Laser Powder Bed Fusion Additive

Laser power bed fusing (PBF) additive manufacturing is a key enabling technology to manufacture highly complex and integrated automotive structures. However, the geometric complexity of PBF-AM technique also leads to highly non-uniform heating and cooling rate in the manufactured part, which may cause flaw formation and produce excessive and nonuniform residual stresses, which increase quality uncertainties and manufacture issues, leading to increases in cost and energy consumption in the form of rejected parts. In this research project, we developed an innovative Multi-Spatial-Temporal-Resolution Finite Element (MUST-FE) method and completed the corresponding high performance computation (HPC) platform-based in-house code, which enables high accuracy prediction of temperature and residual stress fields for component-scale PBF-AM manufacture in efficient computation time. The MUST-FE model is calibrated and validated with a “2D pad” AlSi10Mg experiments by matching the melt pool shape and dimension, and with a “XY-cross” AlSi10Mg experiment by matching the thermal distortion and residual stress. The innovative multi-resolution and concurrent modeling approach adopted in this code ensures accuracy and computational efficiency, which will enable energy-efficient and high-yield, low-cost manufacturing of optimized, qualifiable automotive structures and contribute towards reaching technical targets outlined in AMO’s Program Plan to develop additive manufacturing systems that deliver consistently reliable parts with predictable properties.

36 MATERIALS SCIENCE↗

Fabrication of a Point-Like Transmission Target for Reducing Computed Tomography Imaging Artifacts

In this study, we address the challenge of enhancing image quality and spatial resolution in computed tomography (CT) imaging by introducing simulation and fabrication of high aspect ratio, point-like transmission targets. Utilizing advanced electroplating techniques, traditionally employed in the fabrication of Through Substrate Via (TSV) interconnects for CMOS circuitry, we successfully embed copper targets within silicon substrates. This method allows us to create high-aspect-ratio features specifically designed for X-ray transmission targets, resulting in micro targets that exhibit a volume increase compared to conventional evaporated surface targets. Furthermore, we present simulation results of the X-ray spectrum generated by these targets, demonstrating their potential to significantly improve both image quality and spatial resolution in CT applications. Our findings suggest that leveraging advanced fabrication techniques can open new avenues for the development of enhanced imaging technologies in medical diagnostics and beyond.

47 OTHER INSTRUMENTATION↗

Energy storage emerging: A perspective from the Joint Center for Energy Storage Research

Energy storage is an integral part of modern society. A contemporary example is the lithium (Li)-ion battery, which enabled the launch of the personal electronics revolution in 1991 and the first commercial electric vehicles in 2010. Most recently, Li-ion batteries have expanded into the electricity grid to firm variable renewable generation, increasing the efficiency and effectiveness of transmission and distribution. Important applications continue to emerge including decarbonization of heavy-duty vehicles, rail, maritime shipping, and aviation and the growth of renewable electricity and storage on the grid. This perspective compares energy storage needs and priorities in 2010 with those now and those emerging over the next few decades. The diversity of demands for energy storage requires a diversity of purpose-built batteries designed to meet disparate applications. Advances in the frontier of battery research to achieve transformative performance spanning energy and power density, capacity, charge/discharge times, cost, lifetime, and safety are highlighted, along with strategic research refinements made by the Joint Center for Energy Storage Research (JCESR) and the broader community to accommodate the changing storage needs and priorities. Innovative experimental tools with higher spatial and temporal resolution, in situ and operando characterization, first-principles simulation, high throughput computation, machine learning, and artificial intelligence work collectively to reveal the origins of the electrochemical phenomena that enable new means of energy storage. This knowledge allows a constructionist approach to materials, chemistries, and architectures, where each atom or molecule plays a prescribed role in realizing batteries with unique performance profiles suitable for emergent demands.

Trahey, Lynn↗

“Gray Zone” Simulations Using a Three-Dimensional Planetary Boundary Layer Parameterization in the Weather Research and Forecasting Model

Abstract Generating accurate weather forecasts of planetary boundary layer (PBL) properties is challenging in many geographical regions, oftentimes due to complex topography or horizontal variability in, for example, land characteristics. While recent advances in high-performance computing platforms have led to an increase in the spatial resolution of numerical weather prediction (NWP) models, the horizontal gridcell spacing (Δ x ) of many regional-scale NWP models currently fall within or are beginning to approach the gray zone (i.e., Δ x ≈ 100–1000 m). At these gridcell spacings, three-dimensional (3D) effects are important, as the most energetic turbulent eddies are neither fully parameterized (as in traditional mesoscale simulations) nor fully resolved [as in traditional large-eddy simulations (LES)]. In light of this modeling challenge, we have implemented a 3D PBL parameterization for high-resolution mesoscale simulations using the Weather Research and Forecasting Model. The PBL scheme, which is based on the algebraic model developed by Mellor and Yamada, accounts for the 3D effects of turbulence by calculating explicitly the momentum, heat, and moisture flux divergences in addition to the turbulent kinetic energy. In this study, we present results from idealized simulations in the gray zone that illustrate the benefit of using a fully consistent turbulence closure framework under convective conditions. While the 3D PBL scheme reproduces the evolution of convective features more appropriately than the traditional 1D PBL scheme, we highlight the need to improve the turbulent length scale formulation. Significance Statement The spatial resolution of weather models continues to increase at a rapid rate in accordance with the enhancement of computing power. As a result, smaller-scale atmospheric features become more explicitly resolved. However, most numerical models still ignore the impact of horizontal weather variations on boundary layer flows, which becomes more important at these smaller spatial scales. To address this issue, we have implemented a new modeling approach, using fundamental principles, which accounts for horizontal variability. Our results show that including three-dimensional effects of turbulence is necessary to achieve realistic boundary layer characteristics. This novel technique may be useful for many applications including complex terrain flows, pollutant dispersion, and surface–atmosphere interaction studies.

Juliano, Timothy W.↗

Laboratory-Based Micro-X-ray Computed Tomography of Energy Materials at Idaho National Laboratory

Abstract The Idaho National Laboratory (INL) has implemented laboratory-based micro-X-ray computed tomography in a laboratory equipped for the examination of highly radioactive samples. This capability provides nondestructive three-dimensional volumetric information on samples to inform subsequent traditional destructive examinations as well as real-world inputs for high-fidelity scientific modeling. Samples can be imaged with spatial resolutions ranging from several hundred nm/voxel up to ~ 100 µm/voxel. The best usable spatial resolution achieved to date is 384 nm/voxel with this instrument, while the highest radiological dose rate of a sample imaged is ~ 60 R/h β/γ on contact. Advanced data analysis, including custom tomographic reconstruction and segmentation methods, have also been developed to support this capability. In addition to traditional digital X-ray radiography and tomography, this instrument is also able to visualize in situ tensile and compression testing as well as perform diffraction contrast tomography. This work describes the X-ray computed tomography post-irradiation examination capabilities at INL, as well as detailing a variety of applications this instrument has examined.

36 MATERIALS SCIENCE↗

Non-destructive depth-resolved characterization of residual strain fields in high electron mobility transistors using differential aperture x-ray microscopy

Localized residual stress and elastic strain concentrations in microelectronic devices often affect the electronic performance, resistance to thermomechanical damage, and, likely, radiation tolerance. A primary challenge for the characterization of these concentrations is that they exist over sub-μm length-scales, precluding their characterization by more traditional residual stress measurement techniques. Here, in this study, we demonstrate the use of synchrotron x-ray-based differential aperture x-ray microscopy (DAXM) as a viable, non-destructive means to characterize these stress and strain concentrations in a depth-resolved manner. DAXM is used to map two-dimensional strain fields between the source and the drain in a gallium nitride (GaN) layer within high electron mobility transistors (HEMTs) with sub-μm spatial resolution. Strain fields at various positions in both pristine and irradiated HEMT specimens are presented in addition to a preliminary stress analysis to estimate the distribution of various stress components within the GaN layer. γ-irradiation is found to significantly reduce the lattice plane spacing in the GaN along the sample normal direction, which is attributed to radiation damage in transistor components bonded to the GaN during irradiation.

42 ENGINEERING↗

Gas puff imaging on the TCV tokamak

We present the design and operation of a suite of Gas Puff Imaging (GPI) diagnostic systems installed on the Tokamak à Configuration Variable (TCV) for the study of turbulence in the plasma edge and Scrape-Off-Layer (SOL). These systems provide the unique ability to simultaneously collect poloidal 2D images of plasma dynamics at the outboard midplane, around the X-point, in both the High-Field Side (HFS) and Low-Field Side (LFS) SOL, and in the divertor region. We describe and characterize an innovative control system for deuterium and helium gas injection, which is becoming the default standard for the other gas injections at TCV. Extensive pre-design studies and the different detection systems are presented, including an array of avalanche photodiodes and a high-speed CMOS camera. First results with spatial and time resolutions of up to ≈2 mm and 0.5 µs, respectively, are described, and future upgrades of the GPI diagnostics for TCV are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

LBNF/DUNE Cryostats and Cryogenics Infrastructure for the DUNE Far Detector (Design Report)

DUNE is an international experiment dedicated to addressing some of the questions at the forefront of particle physics and astrophysics, including the mystifying preponderance of matter over antimatter in the early universe. The dual-site experiment will employ an intense neutrino beam focused on both a near detector and a cryogenic far detector. The DUNE far detector implements liquid argon time-projection chamber (LArTPC) technology, and combines many tens-of-kilotons of fiducial mass with sub-centimeter spatial resolution to collect neutrino events and image them with high precision. Given its size, this detector will be implemented as a set of up to four modules, each of which will require its own cryostat that will contain approximately 17.5 metric kilotons of ultra-pure liquid argon (LAr). The cryogenics infrastructure to support the detector modules includes systems to receive, transfer, store, purify, and maintain the LAr. This design report describes the cryostats and the cryogenics infrastructure required for the first two detector modules; this infrastructure is designed to support expansion to up to four far detector modules.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Optimization of scintillated imaging detectors for MeV X-ray radiography

Radiographic imaging at X-ray energies in the MeV range poses a complex problem. Detection of high energy X-rays depends heavily on the ability of the detection material, in this work the scintillator, to attenuate and ultimately stop the X-ray. Attenuation is more readily achieved by increasing material thickness, however thick scintillators are plagued with relatively high internal scattering, leading to an overall decrease in spatial resolution and image quality.

42 ENGINEERING↗

Co-Firing Switchgrass and Waste Coal in A Power Plant: A Techno-Economic and Life Cycle Evaluation for The Ohio River Valley (SWITCH) (Final Technical Report for Ohio State/FE0032204)

Abandoned coal mine lands (AMLs) represent one of the most persistent environmental challenges in the United States. Prior to the enactment of the Surface Mining Control and Reclamation Act (SMCRA) in 1977, coal mining operations were not legally required to reclaim disturbed lands, leaving behind approximately 500,000 AML sites nationwide. These sites pose severe environmental and health risks, including acid mine drainage, soil and water contamination, and spontaneous combustion of waste coal piles. Millions of Americans live within one mile of these AMLs, underscoring the urgency of remediation. Traditional reclamation practices, such as planting cool-season grasses, often fail to fully restore ecological function or leverage the economic potential of these lands. This project addressed these challenges by developing integrated strategies for resource recovery, land reclamation, and sustainable energy production. This project evaluated an integrated strategy to convert this liability into an opportunity by recovering waste coal and co-firing it with switchgrass (Panicum virgatum L.) cultivated on reclaimed or marginal AML areas in existing coal-fired power plants. Switchgrass not only provides a renewable feedstock but also aids in land reclamation and carbon sequestration. 1) Remote Sensing and Machine Learning for Waste Coal Identification Using Sentinel-2 satellite imagery and supervised classification, we applied four machine learning models to detect historical waste coal piles. Random Forest achieved the highest accuracy (precision: 86%, recall: 77%). Time-series analysis revealed gradual vegetation recovery since 1986, indicating natural reclamation processes in historical sites, while active mining areas showed ongoing disturbance. This workflow enables scalable monitoring and prioritization of reclamation efforts. 2) UAS-Based Stockpile Volume Estimation To quantify recoverable waste coal, we evaluated Unmanned Aerial Systems (UAS) equipped with Light Detection and Ranging (LiDAR) and multispectral sensors. Structure-from-Motion (SfM) photogrammetry combined with interpolated Digital Terrain Models (DTMs) achieved strong agreement with LiDAR reference volumes (Root Mean Square Error (RMSE) ≈147 m 3 , Mean Absolute Percentage Error (MAPE) ≈2%). Sensitivity analysis confirmed that spatial resolution significantly influences accuracy, emphasizing the need for high-resolution data for precise volume estimation. This approach offers a scalable, cost-effective, and accurate alternative to conventional ground-based surveys. 3) Switchgrass Cultivation for Bioenergy and Water Quality Improvement We assessed the hydrological and water quality impacts of converting AMLs to switchgrass production areas using the Soil and Water Assessment Tool (SWAT). Results showed that converting 10% of the watershed area into the switchgrass production zone reduced streamflow by 3.1%, total suspended solids by 18.1%, total nitrogen by 7.6%, and total phosphorus by 6.2%, while achieving biomass yields of 8.6–9.2 metric tons per hectare. These findings highlight switchgrass as a dual-benefit strategy for land reclamation and bioenergy feedstock production. 4) Integrated Co-Firing and CCS for Carbon-Negative Power Generation We modeled co-firing scenarios using the Power Plant Flexible Model (PPFM) to evaluate plant efficiency, greenhouse gas (GHG) emissions, and levelized cost of electricity (LCOE). Without carbon capture and storage (CCS), increasing switchgrass co-firing ratios reduced LCOE from $\$$150/MWh at 0% biomass to $\$$110/MWh at full substitution. Under CCS, costs remained higher (~$\$$250/MWh at 0% biomass) but decreased to $\$$200/MWh at 100% biomass, while enabling net-zero or carbon-negative electricity due to switchgrass sequestration benefits. Although CCS introduced efficiency penalties, pairing it with biomass co-firing offset these impacts and maximized climate benefits. Overall, optimizing co-firing ratios between 60-100%, supported by reliable logistics and storage strategies, emerged as a practical pathway to balance affordability, sustainability, and net-zero or negative GHG emissions while promoting productive reuse of AMLs.

01 COAL, LIGNITE, AND PEAT↗

Machine Learning Analysis of Hydrologic Exchange Flows and Transit Time Distributions in a Large Regulated River

Hydrologic exchange between river channels and adjacent subsurface environments is a key process that influences water quality and ecosystem function in river corridors. High-resolution numerical models were often used to resolve the spatial and temporal variations of exchange flows, which are computationally expensive. In this study, we adopt Random Forest (RF) and Extreme Gradient Boosting (XGB) approaches for deriving reduced order models of hydrologic exchange flows and associated transit time distributions, with integrated field observations (e.g., bathymetry) and hydrodynamic simulation data (e.g., river velocity, depth). The setup allows an improved understanding of the influences of various physical, spatial, and temporal factors on the hydrologic exchange flows and transit times. The predictors also contain those derived using hybrid clustering, leveraging our previous work on river corridor system hydromorphic classification. The machine learning-based predictive models are developed and validated along the Columbia River Corridor, and the results show that the top parameters are the thickness of the top geological formation layer, the flow regime, river velocity, and river depth; the RF and XGB models can achieve 70% to 80% accuracy and therefore are effective alternatives to the computational demanding numerical models of exchange flows and transit time distributions. Each machine learning model with its favorable configuration and setup have been evaluated. The transferability of the models to other river reaches and larger scales, which mostly depends on data availability, is also discussed.

97 MATHEMATICS AND COMPUTING↗