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DOE OSTI2023

Correlating Tomographic Chemical Inhomogeneity and Low Energy Electronic Structure in Layered Quantum Materials

Photoemission spectroscopy (PES) is a suite of experimental tools to learn about the electronic and chemical structure of materials and surfaces. Normally implemented in a surface-sensitive manner, the research performed under this grant focused on pushing PES into less explored regimes, to reveal bulk electronic structure, to reveal tomographic (layer-resolved) chemistry and electronic structure of layered materials and heterostructures, and to reveal interface phenomena at the junction of two different materials. Standing wave (SW) spectroscopies have also been applied to PdCoO2, a material of interest due to its high conductivity and electron-hydrodynamic tendencies. This material can be modeled as an alternating layered structure consisting of metallic Pd layers and insulating CoO2 layers. Using SW XPS, the total electronic structure has been decomposed into contributions from the two layers, and computations highlighted the different many-body interactions in the two layers (Comm. Phys. 4, 143 (2021)). We have also used hard-x-ray angle-resolved photoemission spectroscopy (ARPES), to investigate LaB6, a technologically important material with widespread application as a cathode material for electron microscopes. We measured the bulk electronic structure of this material and found that the one-step model of photoemission better captured the electronic structure and correlations. This model treats the three steps of the photoemission process—excitation, transport of the photoelectron to the crystal surface, and escape into the vacuum—as a single quantum mechanically coherent process (Phys. Rev. Mater. 5, 055002 (2021)). We also applied x-ray photoelectron spectroscopy, implemented in a near total reflection grazing incidence geometry to elucidate technologically relevant interfaces, such as those between a substrate and photoresist (J. Phys. D: Appl. Phys. 54 464002 (2021)).

36 MATERIALS SCIENCE↗

DOE OSTI2022

Data used in “Enguehard et al. 2022, Machine-Learning Functional Zonation Approach for Characterizing Terrestrial–Aquatic Interfaces: Application to Lake Erie”

The package contains the data layers used in “Enguehard et al. 2022, Machine-Learning Functional Zonation Approach for Characterizing Terrestrial–Aquatic Interfaces: Application to Lake Erie”. Spatial data layers include: topography, wetland vegetation cover, time series of Landsat’s enhanced vegetation index (EVI) between 1990 and 2020. The study aims to characterize coastal wetlands with particular focus on the co-variability between plant dynamics, topography, soil, and other environmental factors. We proposed a functional zonation approach based on machine learning clustering to identify the spatial regions, i.e., zones that capture these co-varied properties. This approach was applied to publicly available datasets along Lake Erie, in the Great Lakes Region

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Numerical framework for integrated additive manufacturing-compression molding (AM-CM) of thermoplastic composites

Additive manufacturing-compression molding (AM-CM) has emerged as a transformative technology in advanced composite manufacturing. Additive manufacturing (AM) offers high design flexibility and the ability to produce complex geometries with precisely aligned fibers in the preferred orientation. Compression molding (CM) enhances composite materials by providing excellent dimensional stability, reduced porosity, high production rates, and a smooth surface finish. Despite these advantages, extensive integrated analysis is required to optimize processing conditions for improved fiber orientation distribution (FOD) and porosity control. Here, this study develops a comprehensive numerical model to simulate the AM-CM manufacturing process. The model isolates the effects of both the AM and CM phases while also capturing their integration. Additionally, it accounts for heat transfer, temperature-dependent viscosity, and fiber orientation in the extruded fiber-filled polymer, accurately representing material behavior during processing. This approach enables the analysis of interactions between deposited beads of complex strand shapes and their interface regions after full compression. Moreover, the model predicts key parameters such as polymer flowability, fiber orientation, and temperature evolution in AM-CM parts. By optimizing processing conditions, it facilitates a controlled and predictable microstructure.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Curvature Memory in Electrically Stimulated Lipid Membranes

Here, we demonstrate, using non-equilibrium molecular dynamics simulations, that lipid membrane capacitance varies with surface charge accumulation linked to membrane shape and curvature changes. Specifically, we show that lipid membranes exhibit a hysteretic response when exposed to oscillatory electric fields. The electromechanical coupling in these membranes leads to hysteretic buckling, in which the membrane can spontaneously buckle in one of two distinct directions along the electric field, even for the same ionic charge accumulation at the water–membrane interface. In this regard, these binary buckled membrane states suggest potential applications in neuromorphic computing. Their bistable nature, characterized by two distinct and stable configurations, could serve as a foundation for implementing memory storage systems and logic operations. Furthermore, we introduce a circuit model that captures these dynamic effects, offering insights into emergent memory effects in electrically stimulated lipid membranes. Finally, this work presents lipid bilayers as dynamic, adaptable elements and suggests a new platform for exploring energy storage, information processing, and memory encoding at the lipid membrane level.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

EXERGETIC: De-Risking Next-Generation Resilient Geothermal Hybrids via At-Scale Evaluation Using Virtual Emulation Digital Twin Environment for Efficient Operation

The DOE-GTO-funded project, award number 5.1.2.12, entitled "EXERGETIC - De-risking Next Generation Resilient Geothermal Hybrids via at-Scale Evaluation Using a Virtual Emulation Digital Twin Environment for Efficient Operation," advances the solution to these challenges by developing and validating a geothermal co-emulation environment implemented at the National Laboratory of the Rockies (NLR)'s Advanced Research on Integrated Energy Systems (ARIES) platform. This framework enables the de-risking of next-generation geothermal and geothermal hybrid systems through high-fidelity modeling, real-time digital emulation, advanced control strategies, and techno-economic assessment. The project focused on geothermal hybrid configurations that integrate geothermal power plants with concentrated solar power and underground thermal energy storage, enabling enhanced efficiency, flexibility, and grid support capabilities. The main goal of this project was the development of a geothermal digital co-emulation environment to demonstrate the technical and economic value of geothermal hybrid systems and their contribution to grid stability and flexibility. The EXERGETIC framework combined physics-based models, controls, and real assets at ARIES, including digital real-time simulators (DRTS), a 20-MW-scale controllable grid interface (CGI), and a 2-MW conventional generator. Detailed transient models were developed for the key subsystems of a hybrid geothermal plant, including parabolic trough solar collectors, reservoir thermal energy storage (RTES), and a binary Organic Rankine Cycle (ORC) power plant. The ORC model explicitly captured thermal inertia and off-design operation and integrated control strategies to dynamically respond to electric load profiles. The models were validated against published experimental and numerical studies, demonstrating strong agreement and confirming the accuracy and robustness of the modeling approach. The resulting digital twin represents geothermal-solar-storage systems at multiple scales (1 MW to 100 MW) and enables realistic emulation of grid-connected operation. The control architecture allows the geothermal resource to provide stable baseload generation, while solar and stored thermal energy supply flexible, dispatchable support during periods of high demand or variable grid conditions. A key contribution of the EXERGETIC project is the demonstration that geothermal hybrid systems can be designed to be active grid assets rather than passive baseload generators. Using the ARIES platform, the digital twin was evaluated under multiple grid scenarios, including load following, voltage support at the distribution level, and frequency response at the transmission level. Results show that hybrid geothermal systems can respond effectively to dynamic grid conditions, providing inertia-like behavior, primary frequency support, and voltage regulation through coordinated control. In addition to the performance and grid services capability analysis of geothermal and hybrid geothermal systems, the EXERGETIC project also focused on scalability and techno-economic analysis of geothermal hybrid plants. In particular, for the scalability analysis, machine-learning (ML)-based surrogate models were trained using data generated from the geothermal digital twin under different grid-connected scenarios and plant capacities. These ML models demonstrated strong interpolation and extrapolation capabilities across plant sizes, accurately reproducing both steady-state and transient responses with very low errors. Regarding the techno-economic analysis, plant performance results were integrated with cost models for hybrid geothermal systems, and the levelized cost of electricity (LCOE) was used as the main economic metric to evaluate system performance across a range of system capacities, solar shares, solar multiples, and storage durations. Results indicate that economies of scale significantly reduce geothermal LCOE as plant capacity increases, with large-scale systems (25-100 MW) achieving substantially lower costs than small plants. Hybridization with solar thermal energy and storage further improves economic performance by increasing capacity utilization and enabling flexible dispatch. In addition, thermal storage plays a critical role in reducing LCOE by maximizing geothermal, solar, and stored energy resources. In summary, the results from this project demonstrate that geothermal hybrid systems represent a promising alternative for increasing the energy conversion efficiency of geothermal technologies, contributing to the preservation of geothermal resources, and supporting the transition of geothermal plants from traditional baseload resources into flexible, resilient, and cost-competitive energy conversion technologies.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

Degradation-related defect level in weathered silicon heterojunction modules characterized by deep level transient spectroscopy

Commercial silicon heterojunction photovoltaic modules, known as amorphous-silicon-based heterojunction with intrinsic thin-film layer (HIT) modules, show average degradation after 10 years in the field. HIT modules weathered outdoors in Colorado and Florida display mostly uniform decreases in intensity when mapped with photoluminescence (PL) imaging compared to a control module. Flash-table-based current-voltage curves show that degradation is dominated by voltage loss. Samples are cored from each of the modules, and deep level transient spectroscopy (DLTS) detects three electron-trap defect states in all modules with activation energies of electron emission from the defects of 0.07, 0.16, and 0.50 eV. DLTS measurements on the weathered modules show an additional deep-level, electron-trap defect state with an activation energy of 0.51 eV and a trap density of approximately 10 12 cm –3 . The capture rate is measured using varying short filling pulse times, and the resulting capture cross section is estimated to be 1.1x10 –16 cm 2 . The development of the weathering-related defect level correlates to decreases in carrier lifetime, PL intensity, and module voltage. Various depths of the space charge region are probed with increments in applied reverse bias and filling-pulse bias. Furthermore, this DLTS depth profiling shows a trend of trap density increasing with less applied reverse bias, suggesting that the weathering-related defect increases carrier recombination toward the interface between the bulk silicon wafer and the junction-forming amorphous-silicon passivation layers.

14 SOLAR ENERGY↗

DOE OSTI2021

Scanning ultrafast electron microscopy reveals photovoltage dynamics at a deeply buried $p^- \mathrm{Si/SiO_2}$ interface

The understanding and control of charge carrier interactions with defects at buried insulator/semiconductor interfaces is essential for achieving optimum performance in modern electronics. In this work, we report on the use of scanning ultrafast electron microscopy (SUEM) to remotely probe the dynamics of excited carriers at a Si surface buried below a thick thermal oxide. Our measurements illustrate a previously unidentified SUEM contrast mechanism, whereby optical modulation of the space-charge field in the semiconductor modulates the electric field in the thick oxide, thus affecting its secondary electron yield. By analyzing the SUEM contrast as a function of time and laser fluence we demonstrate the diffusion mediated capture of excited carriers by interfacial traps.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Thermal conductivity of 3D-printed block-copolymer-inspired structures

This study primarily focuses on examining the impact that geometric structure has on thermal conductivity of multi-phase constructs in different 3D-printed poly(lactic acid), PLA, samples. The investigated structures are inspired by morphologies formed by diblock copolymers: lamellae, hexagonally packed cylinders, and gyroid. This research also investigates how volume percentage and material combination influence the thermal conductivity of these structures. Further, the samples can be tailored to simulate various thermal management structures observed in practical applications, such as thermal interface materials in electronic devices. Thermal conductivity ratio is controlled using air, the least conductive material at 0.026 W/(m K), PLA at 0.136 W/(m K), and thermal paste at 5.11 W/(m K). Different models were tested against thermal conductivity measurements in order to capture the effect of material type (PLA-Air versus PLA-Thermal Paste), volume percentage, structure, and orientation. Simple, effective medium models were good predictions of thermal conductivity in lamellar structures, but it was necessary to develop models for conduction through cylindrical and gyroid structures. Finally, all results were normalized to find a universal model that is independent of structure and material. This approach provides a simple method to predict how to reduce or enhance transport properties and heat management capabilities of 3D printed objects.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Chemical and Structural Insights into Solid Electrolyte Interphase Evolution for Sodium Metal Electrodes

The solid electrolyte interphase (SEI) critically governs the reversibility of sodium metal batteries, through dynamically mediating ion transport and interfacial reactions. However, its kinetic evolution under operating conditions, and how it influences interfacial stability, remains poorly understood. Here, in this study, we reveal that the SEI undergoes coupled chemical and mechanical changes during sodium plating and stripping, leading to spatial and temporal heterogeneity that drives interfacial degradation. Synchrotron operando grazing-incidence wide-angle X-ray scattering and soft X-ray absorption spectroscopy capture the sequential formation and dissolution of inorganic SEI phases (NaF, NaH, NaOH, Na 2 PO 3 F), accompanied by depth-dependent alterations in organic SEI components. Mesoscale modeling connects this evolving SEI heterogeneity to localized current density fluctuations and stress accumulation at the Na interface, identifying pathways to electrically isolated sodium formation. These findings show that SEI instability fundamentally limits reversibility in sodium metal batteries, and that controlling SEI chemistry–mechanics coupling is essential to achieving its durability.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Simulating quantum-classical interfaces via the Lindblad master equation

In hybrid quantum systems, the interface between quantum and classical domains is essential for the generation, control, and measurement of quantum states. Quantum-classical interfaces (QCIs) are ubiquitous in devices such as optical modulators, quantum sensors, and signal processors, where classical signals influence quantum dynamics. In this paper, we employ the Lindblad master equation to simulate the evolution of a quantum system interacting with a classical control system. Our model captures both linear and nonlinear interactions by incorporating first- and second-order susceptibilities, and it quantifies the influence of externally applied control parameters on decoherence and state evolution. As an illustrative example, we analyze an optical modulator and demonstrate how variations in material response and drive conditions affect photon statistics, coherence, and phase-space distributions. In conclusion, the findings offer a path to an all-encompassing model for understanding and optimizing QCIs, with wide-ranging implications for the performance, design, and robustness of next-generation quantum devices.

Quantum engineering↗

DOE OSTI2025

Preliminary Study on Fine-Grained Power and Energy Measurements on Grace Hopper GH200 with Open-Source Performance Tools

The increasing adoption of tightly integrated, heterogeneous architectures, combined with the slowdown of Moore’s law, has made application power and energy-driven optimizations critical to efficiently use high-performance computing systems. This paper introduces a newly developed open-source toolkit that seamlessly integrates the Linux real-time hardware monitoring program hwmon with the Performance Application Programming Interface and the Score-P performance measurement system, thereby enabling fine-grained power and energy measurements for high-performance computing applications. Our primary target platform is the Wombat test bed, which is a system based on the NVIDIA GH200 superchip. The toolkit can capture transient power peaks with high temporal resolution (50 ms) and, thanks to Score-P integration, can map power metrics to specific code regions, thereby providing actionable information on power-intensive operations and inefficiencies. The toolkit also provides a holistic view of both the power and the energy consumption of the entire GH200 superchip by covering all major components: the Grace CPU, the Hopper GPU, and the I/O subsystem. Experiments that use Locally Self-consistent Multiple Scattering, which is an application for first-principles calculations of materials developed at Oak Ridge National Laboratory, have demonstrated the tool’s ability to identify transient power spikes and uncover opportunities for energy-aware optimizations. Additionally, we introduce a Python-based utility for converting Open Trace Format 2 traces to Parquet format, thus enabling advanced data analysis for numerical integration methods applied to power data for accurate energy profiling.

Hernandez Mendoza, Oscar [ORNL] (ORCID:00000002538↗

DOE OSTI2020

Scaling of Imbibition Front Dynamics in Heterogeneous Porous Media

Here we report a quantitative study on the dynamics of countercurrent imbibition in fractured rock samples with the application of CO 2 geosequestration, as the rock matrix is saturated with CO 2 and brine exists in the adjacent microfracture. Direct pore-scale simulations of spontaneous and forced imbibition in a three-dimensional heterogeneous porous matrix enable us to capture the effect of microscopic properties on the imbibition dynamics as these pore-level descriptions are ignored in the existing coarse-grained models. We have established new scaling classes for the propagation of the center of mass of the imbibition front and fluid-fluid interface broadening. It has become evident that the wettability is a major factor which leads to anomalies in these scaling laws. While the governing capillarity under the water-wet condition induces fast roughening dynamics of the interface, the adverse effect of capillary pressure under the intermediate-wet condition leads to a damping effect on the imbibition front fluctuations.

58 GEOSCIENCES↗

DOE OSTI2022

Position Papers for the ASCR Workshop on the Management and Storage of Scientific Data

The purpose of this workshop is to identify priority research directions in the area of data management for high-performance and scientific computing above and beyond HPC’s traditional "the parallel file system is the data-management system" model. Supporting the breadth of the DOE mission, including the explosion of AI uses and the growing needs of experimental and observational science, motivates revisiting our assumptions about data management. There are many facets of this topic to explore including: (1) Interfaces for accessing data that resides on traditional persistent storage as well as memory devices; (2) Storage-system architecture design that supports scientific workflows on varied hierarchical storage and networking devices; (3) Devising metadata management infrastructure to support FAIR principles (Findability, Accessibility, Interoperability, and Reusability); (4) Capturing provenance information about scientific data; (5) Utilizing AI to learn I/O patterns of emerging workloads for efficient data management; (6) Providing data management support for AI and complex workflows; and (7) Understanding the overlap between traditional storage systems and I/O (SSIO) efforts and data management. While the program committee has identified these topics as important areas for discussion, we welcome position papers from the community that propose additional topics of interest for discussion at the workshop. The workshop agenda will include breakout sessions for discussing these and selected topic areas to inform priority research directions for data management for high-performance and scientific computing.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Report for the ASCR Workshop on the Management and Storage of Scientific Data

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Evaluating the tidal energy resource for smooth power output and grid integration in the United States

In comparison to wind and solar energy, tidal resources are predictable with a high degree of certainty. Although tides are inherently variable, their periodicity and predictability create the possibility of providing smooth power output to the grid. By spatially diversifying tidal devices to capture the tidal wave as it propagates through a system, aggregate power becomes smoother. Tidal energy assessments have indicated that energy extraction is viable in several regions around the world, leading to the development and testing of many devices. However, less attention has been given to the interface between energy production and grid integration, particularly in the United States. We evaluate tidal phases for several regions across the United States to determine if there is enough diversity within relatively close distances of one another. By calculating the cross correlations of estimated tidal current velocity time series between representative locations in defined regions, we show three regions in the United States that have the potential to aggregate power output from geographically diversified turbines to generate a smoother, baseload-like power profile.

Preziuso, Danielle C.↗

DOE OSTI2023

Impact of organic solutes on capillary phenomena in water-CO2-quartz systems

Hypothesis: The migration of supercritical CO2 (scCO2) injected into underground reservoirs as part of carbon capture and storage is influenced by organic contamination affecting mineral wettability. Molecular dynamics (MD) simulations of relevant systems that incorporate representative organic solutes allow detailed investigation of changes in fundamental interfacial and capillary properties. Experiments: We use MD simulations to explore the effects of four organic solutes (quinoline, decanoic acid, coronene, sorgoleone) on the wettability of quartz by water in the presence of scCO2. We examine the impacts of polar, alkyl, and aromatic moieties as well as fluid flow velocity at elevated temperatures and pressures. Findings: Organic molecules accumulate at the water-CO2 interface, where they distribute according to their size and functional groups. Certain organics penetrate the adsorbed water film at the quartz-CO2 interface, revealing two modes of hydrogen bonding between polar organic functional group, water, and quartz surface –OH groups. Interfacial energies and contact angles are minimally impacted by organic adsorption at the water-CO2 interface, possibly due to simultaneous CO2 desorption. Non- equilibrium MD simulations reveal that flow-induced redistribution of organic compounds modulates the radii of curvature of the advancing and receding water-CO2 interfaces. Our results indicate that organic adsorption on water surfaces is likely ubiquitous during multi-phase flow in soils and sedimen- tary rocks, with implications for the mobilization and transport of organic compounds.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Quantifying transport and electrocatalytic reaction processes in a gastight rotating cylinder electrode reactor via integration of Computational Fluid Dynamics modeling and experiments

Understanding the complexity of the multiple processes of mass, momentum, charge, and heat transport, and how these affect reaction kinetics at the electrode/electrolyte interface is one of the major challenges in the field of energy and catalysis. The rapid and rational scale-up of electrocatalytic systems to industrial scales require a detailed understanding of nonlinear transport-reaction processes, accessible only through the building of multi-physics models that capture with high fidelity the complexity of real-world devices. The gastight rotating cylinder electrode (RCE) reactor is a promising lab-scale tool that can decouple transport from intrinsic kinetics to generate data for first-principle models useful in the design of industrial, electrochemical reactors. Computational Fluid Dynamics (CFD) studies have previously been used to investigate the bulk flow in RCE reactors for simple corrosion and electroplating processes. However, the quantification of changes in local concentration within the viscous layer where catalysis takes place requires capturing the correct flow conditions inside the hydrodynamic boundary layer near the surface of the electrode. Further, this requires simulations with spatial resolution in the nm and μm scale and temporal resolutions between ms and s scales that are similar to the timescales for reactions on the electrode surface. In this study, experimental electrocatalysis is combined with CFD modeling to elucidate and parameterize the hydrodynamics in a gastight RCE reactor. CFD simulations of the electrochemical ferricyanide reduction reaction under mass transport limited conditions are used to evaluate the validity of the CFD model parameters by comparing calculated dimensionless mass transport descriptors to dimensionless correlations obtained experimentally. Justifications for assumptions and details of the simulation methods used in this study are presented to provide a detailed understanding of the effect that each model parameter has on the ability to accurately simulate electrocatalysis in RCE systems. The simulation methodology reported here is a first step towards the development of multi-scale models for the study of transport dependent electrocatalytic processes, such as the electrochemical transformation of CO 2 to fuels and chemicals.

42 ENGINEERING↗

DOE OSTI2021

Interfacial thermal conductance between multi-layer graphene sheets and solid/liquid octadecane: A molecular dynamics study

Mixtures of paraffin and carbon nanofillers have promising potential for thermal storage, as paraffin (the matrix) possesses high latent heat and the nanofillers compensate for the low thermal conductivity (TC) of paraffin. Understanding thermal transport in these materials is essential for practical applications, as weak thermal transport hinders fast charge/discharge of thermal energy. Here, we use non-equilibrium molecular dynamics (NEMD) simulations to study the interfacial thermal conductance (ITC) between graphene sheets and octadecane (C18H38) matrix under the limiting conditions of the sheets being parallel or perpendicular to the direction of the imposed heat flux. The findings show that the systems containing thin graphene layers exhibit higher values of ITC. This study captures the asymptotic saturation of thermal conductance for the liquid phase of the perpendicular structure. Besides, given the greater number of structured layers of paraffin upon phase change, the ITC for the solid paraffin-graphene system is higher than the conductance of the liquid paraffin-graphene interface. We use the Pearson correlation coefficients of the vibrational power spectrum (VPS) of interfacing materials to explain the orders of magnitude variations of the observed ITC.

25 ENERGY STORAGE↗