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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.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Comparison of Shadowgraphy and X-Ray Phase Contrast Methods for Characterizing a DT Ice Layer in an Inertial Confinement Fusion Target

Shadowgraphy and x-ray phase contrast (XPC) imaging are two techniques that are used for characterizing the deuterium-tritium ice layer in Inertial Confinement Fusion targets. Each technique has limitations that affect how accurately they can characterize small crystalline defects and measure the ice-thickness non-uniformities that may be only a few micrometers in height. The concern is that shadowgraphy may be overly sensitive to the shape and depth of defects in the surface and insufficiently sensitive to the shape of longer-wavelength roughness, while x-ray phase contrast may be too insensitive to defects in the ice surface. Multiple ice layers with different thicknesses (40 to 63 μm), thickness uniformities (peak-valley variations that range from <2- to 12 μm), and crystal defects were analyzed using shadowgraphy and x-ray phase contrast techniques. The results from each method agree when the ice layer is uniformly thick and the crystal lacks defects. That agreement worsens as the number of defects in the surface of the ice layer increases and the roughness that is determined from a shadowgram image of the target’s limb is greater than can be justified by the number of defects that are seen in the target’s front and rear surfaces. The XPC technique is considerably less sensitive to surface defects, in part due to the poorer dynamic range and image resolution compared to shadowgraphy. Localized regions of the ice layer that are thicker or thinner than the average thickness of the layer are reported by shadowgraphy to be smaller in height and footprint (by up to 30%) than by XPC. As a result, the two techniques report different ice layer thicknesses that can vary by up to 10%. Shadowgraphy results from two caustics that trace different paths through the target, and, in theory, image the same ice-vapor surface (but reflect from either the vapor or ice side of the interface) did not consistently characterize the size or shape of ice features to be the same magnitude. Here, the XPC technique provides the best assessment of low-mode (l < 7) roughness in the ice layer. Shadowgraphy results using the strongest caustic is best for detecting the presence of grooves in the ice, though not for quantifying the size of them. If multiple grooves are present it is best to discard and reform the ice layer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Designing and defining dynamic protein cage nanoassemblies in solution

Central challenges in the design of large and dynamic macromolecular assemblies for synthetic biology lie in developing effective methods for testing design strategies and their outcomes, including comprehensive assessments of solution behavior. Here, we created and validated an advanced design of a 600-kDa protein homododecamer that self-assembles into a symmetric tetrahedral cage. The monomeric unit is composed of a trimerizing apex-forming domain genetically linked to an edge-forming dimerizing domain. Enhancing the crystallographic results, high-throughput small-angle x-ray scattering (SAXS) comprehensively contrasted our modifications under diverse solution conditions. To generate a phase diagram associating structure and assembly, we developed force plots that measure dissimilarity among multiple SAXS data sets. These new tools, which provided effective feedback on experimental constructs relative to design, have general applicability in analyzing the solution behavior of heterogeneous nanosystems and have been made available as a web-based application. Specifically, our results probed the influence of solution conditions and symmetry on stability and structural adaptability, identifying the dimeric interface as the weak point in the assembly. Force plots comparing SAXS data sets further reveal more complex and controllable behavior in solution than captured by our crystal structures. Lastly, these methods for objectively and comprehensively comparing SAXS profiles for systems critically affected by solvent conditions and structural heterogeneity provide an enabling technology for advancing the design and bioengineering of nanoscale biological materials.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

High-Throughput Microfluidics Platform for Intracellular Delivery and Sampling of Biomolecules from Live Cells

Nondestructive cell membrane permeabilization systems enable the intracellular delivery of exogenous biomolecules for cell engineering tasks as well as the temporal sampling of cytosolic contents from live cells for the analysis of dynamic processes. Here, in this paper, we report a microwell array format live-cell analysis device (LCAD) that can perform localized-electroporation induced membrane permeabilization, for cellular delivery or sampling, and directly interfaces with surface-based biosensors for analyzing the extracted contents. We demonstrate the capabilities of the LCAD via an automated high-throughput workflow for multimodal analysis of live-cell dynamics, consisting of quantitative measurements of enzyme activity using self-assembled monolayers for MALDI mass spectrometry (SAMDI) and deep-learning enhanced imaging and analysis. By combining a fabrication protocol that enables robust assembly and operation of multilayer devices with embedded gold electrodes and an automated imaging workflow, we successfully deliver functional molecules (plasmid and siRNA) into live cells at multiple time-points and track their effect on gene expression and cell morphology temporally. Furthermore, we report sampling performance enhancements, achieving saturation levels of protein tyrosine phosphatase activity measured from as few as 60 cells, and demonstrate control over the amount of sampled contents by optimization of electroporation parameters using a lumped model. Lastly, we investigate the implications of cell morphology on electroporation-induced sampling of fluorescent molecules using a deep-learning enhanced image analysis workflow.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Development of CFD Flow Analysis for Nuclear Facility Ventilation Systems

Understanding and modeling of particulate transport has importance related to safety in ventilated environments that contain hot cells, gloveboxes, and fume hoods. In particular, good modeling of the airflow in these spaces is required to understand areas of stagnation where particles drop out of the free stream and accumulate. This accumulation of particulate can cause either contamination and/or higher than acceptable local dose levels. It is known that multiple sites across the DOE complex take credit for hot cells, gloveboxes, and/or hoods in their safety basis for providing a defense-in-depth benefit for both onsite and offsite releases. By providing confinement of radioactive materials, such features serve to reduce direct doses to facility workers and mitigate the consequences to the environment due to an uncontrolled release. Each of these features has access points that interface with the personnel space. Understanding how air flow behaves at these access points is of great interest to those performing hazard analysis. Computational Fluid Dynamics (CFD) can be used to analyze and model the flows in hot cells and glove boxes as a way to confirm operation. While CFD capability continues to advance, there are still important modeling assumptions that are left to the analyst's discretion. These are most notably the choice of the turbulence models, mesh structure, and wall boundary condition assumptions used in the model. In this work, we apply CFD in modeling airflow through an occupiable work area of the Alpha Gamma Hot Cell Facility (AGHCF) at Argonne National Laboratory (ANL). This modeling is then compared to field test data to both inform and verify the modeling assumptions. Based on the results of field tests, modeling assumptions and boundary conditions are refined and the process is repeated until the results are found to be reliable with a high level of confidence.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Advanced Modes of Electrostatic and Kelvin Probe Force Microscopy for Energy Applications

Since their invention over three decades ago, electrostatic and Kelvin probe force microscopies (EFM and KPFM) have become primary tools for the characterization of electrical phenomena on the nanometer scale, with multiple applications for ferroelectrics, photovoltaics, batteries, and fuel cells among a myriad of other energy-related materials. Meanwhile, the techniques have undergone remarkable advances in terms of resolution, sensitivity, and informational content (e.g., dynamic information). In this chapter, we review the operational principles behind classical EFM/KPFM, including the various excitation/detection schemes, while also highlighting potential cross-talk and instrumental issues. Beyond classical approaches, we will describe more recent advances involving open loop detection, multifrequency/multidimensional excitation, and time-resolved methods. Finally, potential pathways for the further development of EFM/KPFM at the solid-liquid interface are discussed.

Checa, Marti↗
DOE OSTI2026

Interfacial Inversion of Stealth Surfactants

Amphiphilic macromolecular surfactants segregate to liquid–liquid interfaces, thereby reducing the interfacial tension and free energy. Here, we investigated “stealth surfactants” in the form of core–shell bottlebrush polymers comprised of pH-responsive diblock copolymer side chains forming a hydrophilic core and a hydrophobic shell, enabling solubility in oil. At liquid–liquid interfaces, these polymers undergo a structural “inversion”, with hydrophilic blocks segregating into the aqueous phase and hydrophobic blocks residing in the oil phase. The reconfiguration kinetics and surfactant properties are influenced by multiple factors, including the molecular weights of the backbone and side chain components, the hydrophilic-to-hydrophobic balance of the side chains, and the pH of the aqueous phase. An observed nonmonotonic dependence of interfacial tension with time is attributed to a progressive structural inversion, where the projected area of the macromolecule onto the interface decreases. To validate this inversion hypothesis, interfacial properties were characterized by sum-frequency generation vibrational spectroscopy, which revealed configurational changes of the core–shell bottlebrush polymers at the fluid interface and revealed a pH-dependent interfacial coverage. Coarse-grained molecular dynamics simulations supported these experimental findings, showing that the pH-responsive core and hydrophobic shell assume a time-averaged configuration with orientations parallel and perpendicular to the plane of the interface, respectively. These findings open routes to design multistimuli-responsive polymeric surfactants and compatibilizers, expanding their potential applications in advanced interfacial systems.

Stealth surfactants↗
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 OSTI2021

Microstructural impacts on ionic conductivity of oxide solid electrolytes from a combined atomistic-mesoscale approach

Abstract Although multiple oxide-based solid electrolyte materials with intrinsically high ionic conductivities have emerged, practical processing and synthesis routes introduce grain boundaries and other interfaces that can perturb primary conduction channels. To directly probe these effects, we demonstrate an efficient and general mesoscopic computational method capable of predicting effective ionic conductivity through a complex polycrystalline oxide-based solid electrolyte microstructure without relying on simplified equivalent circuit description. We parameterize the framework for Li 7- x La 3 Zr 2 O 12 (LLZO) garnet solid electrolyte by combining synthetic microstructures from phase-field simulations with diffusivities from molecular dynamics simulations of ordered and disordered systems. Systematically designed simulations reveal an interdependence between atomistic and mesoscopic microstructural impacts on the effective ionic conductivity of polycrystalline LLZO, quantified by newly defined metrics that characterize the complex ionic transport mechanism. Our results provide fundamental understanding of the physical origins of the reported variability in ionic conductivities based on an extensive analysis of literature data, while simultaneously outlining practical design guidance for achieving desired ionic transport properties based on conditions for which sensitivity to microstructural features is highest. Additional implications of our results are discussed, including a possible connection between ion conduction behavior and dendrite formation.

25 ENERGY STORAGE↗
DOE OSTI2017

Self-Excited, Multi-kHz Dynamics in a Linear, Semi-Bounded Detonation Channel

A linear, semi-bounded detonation channel was studied to characterize the injection, mixing, and ignition process in a two dimensional analog of a rotating detonation wave combustor (RDWC). The linear channel was developed to provide large optical accessibility in support of high-fidelity diagnostics. The canonical geometry was also chosen to support the generation of future numerical validation. A high degree of modularity was designed into the combustor to allow for testing multiple injector con figurations, and for reconfiguring the high-frequency instrumentation and optical window locations. Initial experiments have shown the presence of self-excited, multi-kHz combustion waves that bear the distinct characteristics of detonation waves. High-frequency pressure data details the dynamic response to detonation propagation in the combustor. The role of manifold-chamber coupling is investigated as the mechanism behind the formation of self-excited detonation waves in the combustor. We explore the formation of the waves using Schlieren imaging techniques and examine the structures present within the reaction zone and the interface between reactants and products. Companion computations were carried out using an in-house CFD solver GEMS(General Equations and Mesh Solver) to develop understanding of the structure and dynamics of the flow, flame, and their coupled interactions.

Schwinn, Kyle S.↗
DOE OSTI2017

Multiple Supersonic Phase Fronts Launched at a Complex-Oxide Heterointerface

Selective optical excitation of a substrate lattice can drive phase changes across heterointerfaces. This phenomenon is a nonequilibrium analogue of static strain control in heterostructures and may lead to new applications in optically controlled phase change devices. Here, we make use of time-resolved nonresonant and resonant x-ray diffraction to clarify the underlying physics and to separate different microscopic degrees of freedom in space and time. We also measure the dynamics of the lattice and that of the charge disproportionation in NdNiO 3 , when an insulator-metal transition is driven by coherent lattice distortions in the LaAlO 3 substrate. We find that charge redistribution propagates at supersonic speeds from the interface into the NdNiO 3 film, followed by a sonic lattice wave. Our results establish a hierarchy of events for ultrafast control at complex-oxide heterointerfaces, when combined with measurements of magnetic disordering and of the metal-insulator transition.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Persistence of Methionine Side Chain Mobility at Low Temperatures in a Nine‐Residue Low Complexity Peptide, as Probed by 2 H Solid‐State NMR

Abstract Methionine side chains are flexible entities which play important roles in defining hydrophobic interfaces. We utilize deuterium static solid‐state NMR to assess rotameric inter‐conversions and other dynamic modes of the methionine in the context of a nine‐residue random‐coil peptide (RC9) with the low‐complexity sequence GGKGMGFGL. The measurements in the temperature range of 313 to 161 K demonstrate that the rotameric interconversions in the hydrated solid powder state persist to temperatures below 200 K. Removal of solvation significantly reduces the rate of the rotameric motions. We employed 2 H NMR line shape analysis, longitudinal and rotation frame relaxation, and chemical exchange saturation transfer methods and found that the combination of multiple techniques creates a significantly more refined model in comparison with a single technique. Further, we compare the most essential features of the dynamics in RC9 to two different methionine‐containing systems, characterized previously. Namely, the M35 of hydrated amyloid‐β 1–40 in the three‐fold symmetric polymorph as well as Fluorenylmethyloxycarbonyl (FMOC)‐methionine amino acid with the bulky hydrophobic group. The comparison suggests that the driving force for the enhanced methionine side chain mobility in RC9 is the thermodynamic factor stemming from distributions of rotameric populations, rather than the increase in the rate constant.

Vugmeyster, Liliya↗
DOE OSTI2025

Achieving the hydrogen shot: Interrogating ionomer interfaces

The aim of this study is to enable the hydrogen economy and decarbonize various sectors in our environment that requires less expensive and more durable water electrolyzers, which can meet the Hydrogen-Shot target. The key is to improve the ionomer interfaces in low-temperature water electrolyzers as rapidly as possible, but to do so, it requires a systematic and holistic campaign combining both experiments and theory. In this perspective, we discuss the issues of electrolyzers and needs for translational science. We then present the approach that the Energy EarthShot Research Center: Center for Ionomer-based Water Electrolysis is taking in hopes of inspiring the community with this approach that can be leveraged to multiple problems and technologies.Graphical abstractHighlightsOne way to achieve the Hydrogen-Shot goal of low-cost, clean hydrogen, is advancing research and development on the interfaces of water electrolyzers for both performance and lifetime. The Center for Ionomer-based Water Electrolysis is exploring new techniques and strategies to not only interrogate interfacial phenomena in water electrolyzers to increase efficiency and durability, but also a new paradigm related to synergistic, cojoined experimental and theoretical research.DiscussionCatalyst\ionomer interfaces are complex and not fully understood, but through investigating different interfaces and utilizing digital and physical twins, we can elucidate key mechanisms and understanding.Understanding the dynamic double layer in electrochemical systems that use solid electrolytes is crucial to identifying and mitigating the controlling phenomena to enable increased performance and durability at the technology level.Studying the time and length scales of interfacial changes can be a powerful tool to understand reaction mechanisms and changes in the electrolyzer performance and durability.

Fornaciari, Julie C↗
DOE OSTI2024

Dynamics of self-hybridized exciton–polaritons in 2D halide perovskites

Abstract Excitons, bound electron–hole pairs, in two-dimensional hybrid organic inorganic perovskites (2D HOIPs) are capable of forming hybrid light-matter states known as exciton-polaritons (E–Ps) when the excitonic medium is confined in an optical cavity. In the case of 2D HOIPs, they can self-hybridize into E–Ps at specific thicknesses of the HOIP crystals that form a resonant optical cavity with the excitons. However, the fundamental properties of these self-hybridized E–Ps in 2D HOIPs, including their role in ultrafast energy and/or charge transfer at interfaces, remain unclear. Here, we demonstrate that >0.5 µm thick 2D HOIP crystals on Au substrates are capable of supporting multiple-orders of self-hybridized E–P modes. These E–Ps have high Q factors (>100) and modulate the optical dispersion for the crystal to enhance sub-gap absorption and emission. Through varying excitation energy and ultrafast measurements, we also confirm energy transfer from higher energy E–Ps to lower energy E–Ps. Finally, we also demonstrate that E–Ps are capable of charge transport and transfer at interfaces. Our findings provide new insights into charge and energy transfer in E–Ps opening new opportunities towards their manipulation for polaritonic devices.

42 ENGINEERING↗
DOE OSTI2018

Linking energy-cyber-physical systems with occupancy prediction and interpretation through WiFi probe-based ensemble classification

With the rapid advances in sensing and digital technologies, cyber-physical systems are regarded as the most viable platforms for improving building design and management. Researchers investigated the possibility of integrating energy management systems with cyber-physical systems to form energy-cyber-physical systems in order to promote building energy management. However, minimizing energy consumption while fulfilling building functions for energy-cyber-physical systems is challenging due to the dynamics of building occupants. As occupant behavior is a major source of uncertainty for energy management, ignoring it often results in both energy waste caused by overheating and overcooling as well as discomfort due to insufficient thermal and ventilation services. To mitigate such uncertainties, this study proposes an occupancy-linked energy-cyber-physical system that incorporates WiFi probe-based occupancy detection. The proposed framework utilizes ensemble classification algorithms to extract three forms of occupancy information. It creates a data interface to link energy management systems and cyber-physical systems and allows for automated occupancy detection and interpretation by assembling multiple weak classifiers for WiFi signals. A validation experiment in a large office room was conducted to examine the performance of the proposed occupancy-linked energy-cyber-physical systems. The experiment and simulation results suggest that, with a proper classifier and occupancy data type, the proposed model can potentially save about 26.4% of energy consumption in cooling and ventilation demands.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Numerical assessment of triply periodic minimal surfaces for direct air capture of carbon dioxide

Direct air capture (DAC) systems often consist of packing material wetted by a capture fluid that reacts with CO 2 in the airstream. The efficiency of the contactor is determined by a complex relationship of fluid dynamics, heat and mass transfer, contactor geometry, and chemical properties. The efficiency of the contactor must be balanced with other factors, primarily pressure drop through the system. Triply periodic minimal surfaces (TPMS) are a class of differential surfaces that have been explored in multiple engineering applications and have been shown to exhibit excellent performance when used in heat exchangers. Their tortuous path provides a high surface-to-volume ratio and favorable trade-off between contact area and pressure drop. In this work, a gyroid-type TPMS contactor was evaluated using computational fluid dynamics for a variety of geometric parameters to explore the potential benefit of TPMS shapes for DAC applications. A thin-film model was employed to model the flow and distribution of the capture solvent, allowing efficient simulations of TPMS structures at scale by eliminating the need for a computationally intensive interface capturing method. A liquid-gas mass transfer model was implemented in the commercial software STAR-CCM+ and used to predict the CO 2 capture efficiency and study the trade-off between capture performance and pressure drop through analysis of capture rates, mass transfer coefficients, and other relevant variables. TPMS contactors with a variety of geometric parameters and two capture solvent options were investigated to determine the effect of design choices on the operational performance of DAC systems. In conclusion, results showed that while contactor geometry is the dominant factor in efficiency and pressure drop, the physiochemical properties of the solvent are an important secondary influence on the contactor performance.

CFD↗
DOE OSTI2016

Numerical modeling of heterogeneous asperity distributions controlling the growth of shear rupture on a frictional fault

Copyright 2016 ARMA, American Rock Mechanics Association. A better understanding of the strength distributions and the seismic response of asperities failing within a cohesive (or breakdown) region of the growing shear rupture is important in many engineering disciplines, such as, hydraulic fracture and induced seismicity. In the laboratory, a fault is experimentally modeled by a 400 mm × 80 mm × 12 mm PMMA slider sheared across a large PMMA base plate. A pressure-sensitive film was employed to localize and size, and measure normal stress upon contact junctions. Moments prior to rapid sliding, multiple discrete and localized dynamic events (or foreshocks) were observed at a section of the fault that exhibited a sparse to dense transition in asperity distribution. Experiments showed that foreshocks occurred as the crack (rupture front) moved into the resistive patch of densely distributed asperities. We use the results of pressure sensitive film asperity measurements to develop a heterogeneous finite element (FE) model that studies the effect of asperities within the cohesive region have on the expanding shear crack. Slip accumulated heterogeneously during the loading cycle due to the non-uniform distribution of asperities. We study the constitutive behavior of a frictional interface where local slip is determined by the asperities and their ability to communicate elastically. A foreshock (Mw -7.4) was simulated in a quasi-static manner by instantaneoulsy removing an asperity contact during the loading cycle. The foreshock increased shear stress perturbations to neighboring regions up to distances of ~ 10 to 15 source radii.

Selvadurai, PA↗
DOE OSTI2025

Deep potential molecular dynamics simulations of low-temperature plasma-surface interactions

Machine learning approaches to potential generation for molecular dynamics (MD) simulations of low-temperature plasma-surface interactions could greatly extend the range of chemical systems that can be modeled. Empirical potentials are difficult to generalize to complex combinations of multiple elements with interactions that might include covalent, ionic, and metallic bonds. This work demonstrates that a specific machine learning approach, Deep Potential Molecular Dynamics (DeepMD), can generate potentials that provide a good model of plasma etching in the Si-Cl-Ar system. Comparisons are made between MD results using DeepMD models and empirical potentials, as well as experimental measurements. Pure Si properties predicted by the DeepMD model are in reasonable agreement with experimental results. Simulations of Si bombardment by Ar + ions demonstrate the ability of the DeepMD method to predict sputtering yields as well as the depth of the amorphous-crystalline interface. Etch yields as a function of flux ratio and ion energy for simultaneous Cl 2 and Ar + impacts are in good agreement with previous simulation results and experiment. Predictions of etch yields and etch products during plasma-assisted atomic layer etching of Si-Cl 2 -Ar are shown to be in good agreement with MD predictions using empirical potentials and with experiment. Finally, good agreement was also seen with measurements for the spontaneous etching of Si by Cl atoms at 300 K. Further, the demonstration that DeepMD can reproduce results from MD simulations using empirical potentials is a necessary condition to future efforts to extend the method to a much wider range of systems for which empirical potentials may be difficult or impossible to obtain.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Update on ORNL TRANSFORM Tool: Simulating Multi-Module Advanced Reactor with End-to-End I&C

The Small Modular Reactor (SMR) Dynamic System Modeling Tool project is in the fourth year of development. The project is designed to support collaborative modeling and study of various advanced SMR (non-light water cooled reactor) concepts, including the use of multiple coupled reactors at a single site. The focus of this report is the development of a steam generator and drum system model that includes the complex dynamics of typical steam drum systems, the development of instrumentation and controls for the steam generator with drum system model, and the development of multi-reactor module models that reflect the full power reactor innovative small module design concept. The objective of the project is to provide a common simulation environment and baseline modeling resources to facilitate rapid development of dynamic advanced reactor models; ensure consistency among research products within the Instrumentation, Controls, and Human-Machine Interface technical area; and leverage cross-cutting capabilities while minimizing duplication of effort. The combined simulation environment and suite of models are identified as the TRANSFORM tool. The critical elements of this effort include (1) defining a standardized, common simulation environment that can be applied throughout the Advanced Reactors Technology program; (2) developing a library of baseline component modules that can be assembled into full plant models using available geometry, design, and thermal-hydraulic data; (3) defining modeling conventions for interconnecting component models; and (4) establishing user interfaces and support tools to facilitate simulation development (i.e., configuration and parameterization), execution, and results display and capture.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗