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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

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

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

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Nested Pebble Bed Blanket (NesPeB)

Recent advances in magnetic confinement fusion technology have attracted billions of dollars of investments in startups from venture capitals and corporations, resulting in the development of devices aiming to demonstrate net energy gain in a self-heated burning plasma, such as SPARC (under construction) and others. However, future fusion power plants must operate in regimes that will require technologies far beyond current experience. According to a National Academies of Science, Engineering, and Medicine report, to have nuclear fusion power plants contributing in a timely manner to the planned reduction of atmospheric carbon dioxide, a pilot plant should be built by 2035, and it should demonstrate fusion power production and the performance of the tritium fuel system (requiring a high enough tritium breeding) by 2040. A recognized key technology gap by [26] is the fusion first wall and blanket since no current blanket concept is considered satisfactory or has been built and proven. The first wall and blanket in magnetic fusion reactors form a vital and complex system, as it must satisfy different functions such as power extraction, tritium breeding, plasma containment, radiation shielding, and safety. The list of design requirements is even longer: high enough tritium production for fusion self-sufficiency, low material activation, decay heat and shutdown dose rates, high thermal efficiency, high-capacity factor, high magnets-divertor-vacuum vessel-first wall life, low corrosion, low cost, and intrinsically safe (requiring minimal licensing). Despite fifty-plus years of research, the first wall and blanket concepts proposed suffer from fundamental technical problems and immaturity (TRL=2-3) that jeopardize the timely delivery of a commercial fusion power plant. A fusion first-wall blanket has never been built nor tested, and a "winning", practical functioning design requires enough engineering margins (high enough tritium breeding considering the uncertainty, etc.), manufacturing simplicity, ease of continuous operation, maintenance, and low cost. A new, groundbreaking blanket concept called "Nested Pebble Bed Blanket" (NesPeB) was developed at ORNL under the successful ARPA-E GAMOW FERMI project (patent application allowed by the USPTO). The NesPeB blanket concept addresses current blanket concepts' shortcomings and technical immaturity, paving the way for accelerated delivery of fusion power plants. NesPeB is based on nested pebbles, which are binary-sized lithium-ceramic pebbles enclosed in "Beryllide" perforated and coated spherical shells, which are also binary-sized, stacked on top of each other, forming a "bed" and cooled by Nitrogen gas also "sweeping" the Helium and Tritium generated by the neutron irradiation of Lithium; the vacuum vessel plasma facing material is Molybdenum-96 and -97 with the first wall cooled by Helium while the divertor armor is made of Tungsten. The simulations of the NesPeB blanket using Fusion Reactors Models Integrator (FERMI) are encouraging as they estimate a tritium breeding ratio (TBR) greater than 1.2 using natural Lithium, acceptable pressure drop, and excellent heat transfer properties. Furthermore, the NesPeB blanket is not limited by magneto-hydro-dynamics (MHD) effects, is designed for online refueling, relies on existing tritium extraction technologies, has a simple construction, and limits the corrosion and chemical reactivity problems. NesPeB has the potential to be transformational and disruptive since it can solve all the main, challenging technical problems of fusion device blankets and accelerate a pilot plant delivery for 10 or more years.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Elevated Inlet Temperature Effects on the Operation of a Rotating Detonation Combustor

This experimental work explores the impact of elevated inlet temperatures on a H2/air operated rotating detonation combustor (RDC) without a nozzle. In practical systems, the temperature of the inlet air would be higher than that found in many laboratory settings. Inlet air pre-heating up to 480 K was accomplished by using an integrated pebble-bed heater. The operation of the RDC was found to switch from a single detonation wave at ambient temperature to two, counter-rotating detonation waves at higher temperatures for some of the conditions tested. In addition, the detonation wave properties (i.e., speed and pressure ratio) were impacted by the elevated inlet temperature. The cause of the observed changes in the operation dynamics was explored by evaluating the existence of secondary waves prior to the operational mode change and the changes in the cycle-averaged inlet Mach number.

Feleo, Alexander↗
DOE OSTI2023

Strongly Heated Turbulent Flow in a Channel with Pin Fins

Large-eddy simulations (LES) were performed to study the turbulent flow in a channel of height H with a staggered array of pin fins with diameter D = H/2 as a function of heating loads that are relevant to the cooling of turbine blades and vanes. The following three heating loads were investigated—wall-to-coolant temperatures of Tw/Tc = 1.01, 2.0, and 4.0 - where the Reynolds number at the channel inlet was 10,000 and the back pressure at the channel outlet was 1 bar. For the LES, two different subgrid-scale models—the dynamic kinetic energy model (DKEM) and the wall-adapting local eddy-viscosity model (WALE)—were examined and compared. This study was validated by comparing with data from direct numerical simulation and experimental measurements. The results obtained show high heating loads to create wall jets next to all heated surfaces that significantly alter the structure of the turbulent flow. Results generated on effects of heat loads on the mean and fluctuating components of velocity and temperature, turbulent kinetic energy, the anisotropy of the Reynolds stresses, and velocity-temperature correlations can be used to improve existing RANS models.

42 ENGINEERING↗
DOE OSTI2023

Applying Physics-Informed Neural Networks to Solve Navier–Stokes Equations for Laminar Flow around a Particle

In recent years, Physics-Informed Neural Networks (PINNs) have drawn great interest among researchers as a tool to solve computational physics problems. Unlike conventional neural networks, which are black-box models that “blindly” establish a correlation between input and output variables using a large quantity of labeled data, PINNs directly embed physical laws (primarily partial differential equations) within the loss function of neural networks. By minimizing the loss function, this approach allows the output variables to automatically satisfy physical equations without the need for labeled data. The Navier–Stokes equation is one of the most classic governing equations in thermal fluid engineering. This study constructs a PINN to solve the Navier–Stokes equations for a 2D incompressible laminar flow problem. Flows passing around a 2D circular particle are chosen as the benchmark case, and an elliptical particle is also examined to enrich the research. The velocity and pressure fields are predicted by the PINNs, and the results are compared with those derived from Computational Fluid Dynamics (CFD). Additionally, the particle drag force coefficient is calculated to quantify the discrepancy in the results of the PINNs as compared to CFD outcomes. The drag coefficient maintained an error within 10% across all test scenarios.

Hu, Beichao (ORCID:0009000163215151)↗
DOE OSTI2019

MAESTROeX: A Massively Parallel Low Mach Number Astrophysical Solver

@e present MAESTROeX, a massively parallel solver for low Mach number astrophysical flows. The underlying low Mach number equation set allows for efficient, long-time integration for highly subsonic flows compared to compressible approaches. MAESTROeX is suitable for modeling full spherical stars as well as well as planar simulations of dynamics within localized regions of a star, and can robustly handle several orders of magnitude of density and pressure stratification. Previously, we have described the development of the predecessor of MAESTROeX, called MAESTRO, in a series of papers. Here, we present a new, greatly simplified temporal integration scheme that retains the same order of accuracy as our previous approaches. We also explore the use of alternative spatial mapping of the one-dimensional base state onto the full Cartesian grid. The code leverages the new AMReX software framework for block-structured adaptive mesh refinement (AMR) applications, allowing for scalability to large fractions of leadership-class machines. Finally, using our previous studies on the convective phase of single-degenerate progenitor models of SNe Ia as a guide, we characterize the performance of the code and validate the new algorithmic features. Like MAESTRO, MAESTROeX is fully open source.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Additively Manufactured Compliant Hybrid Gas Thrust Bearing for Supercritical Carbon Dioxide Turbomachinery: Design and Proof of Concept Testing

The following paper presents a new type of gas lubricated thrust bearing that utilizes additive manufacturing or also known as direct metal laser melting (DMLM) to fabricate the bearing. The motivation for the new bearing concept is derived from the need for highly efficient supercritical carbon dioxide (sCO2) turbomachinery in the mega-watt power range. The paper provides a review of existing gas thrust-bearing technology, outlines the need for the new DMLM concept, and discusses proof-of-concept testing results. The new concept combines hydrostatic pressurization with individual tilting pads that are flexibly mounted using hermetic squeeze film dampers (HSFD) in the bearing-pad support. This paper describes the thrust-bearing concept and discusses the final design approach. Proof-of-concept testing in air for a 6.8 in. (173 mm) outer diameter thrust gas bearing was performed; with thrust loading, up to 1500 lbs (6.67 kN) and a thrust runner speed of 10krpm (91 m/s tip speed). The experiments were performed with a bent shaft resulting in thrust runner axial vibration magnitudes of 2.9 mils (74 μm) p-p and dynamic thrust loads of 270 lbs (1.2 kN) p-p. In addition, force deflection characteristics and stiffness coefficients of the bearing system are presented for an inlet hydrostatic pressure of 380 psi (2.62 MPa). Results at 10 krpm show that the pad support architecture was able to sustain high levels of dynamic misalignment equaling 6 times the nominal film clearance while demonstrating a unit load-carrying capacity of 55 psi (0.34 Mpa). Gas-film force deflection tests portrayed nonlinear behavior like a hardening spring, while the bearing pad support stiffness was measured to be linear and independent of gas film thickness.

Engineering↗
DOE OSTI2025

Multi-scale Interaction Mechanism for Edge-Localized-Mode Suppression in the Tokamak Edge

A central challenge in fusion energy is reconciling the high-confinement mode required for reactor performance with the intense intermittent relaxation events it produces, known as edge-localized modes. These instabilities arise in the steep pressure pedestal at the plasma edge when magnetohydrodynamic thresholds are crossed, inflicting damaging heat loads on reactor components. Here, we show that multiscale interactions between microscopic turbulence and macroscopic magnetohydrodynamic modes provide encouraging prospects for self-organized edge-localized modes regulation. Using direct quantitative measurements of multiscale modes, eddy dynamics, and turbulent flux, we show that small-scale electron drift wave turbulence actively scatters the large-scale peeling-ballooning modes. This scattering decorrelates the pressure and velocity fields of the instability, so arresting its growth. Our modeling and theoretical analysis confirm this suppression mechanism is effective even when conventional linear stability thresholds are exceeded. This work establishes a nonlinear principle for edge-localized modes stability, revealing how ambient micro-turbulence can be leveraged to maintain a macro-stable, high-performance pedestal for future fusion reactors.

experimental nuclear physics↗
DOE OSTI2023

Topological electride phase of sodium at high pressures and temperatures

Sodium, a textbook example of a nearly-free-electron metal, exhibits unforeseen pressure-induced behavior including the stabilization of numerous polymorphs—some possessing extremely complex unit cells—as well as a metal-to-insulator transition to the iconic hP4 phase. However, until recently, most of the experimental and theoretical studies on solid sodium have been restricted to the low-temperature regime. In this work, using ab initio evolutionary structure searches coupled with quasiharmonic calculations, we discover seven new phases of sodium that are more stable than the known hP4 phase at pressure-temperature conditions that were recently attained in ramp-compression experiments. From these, our calculations suggest that P6 3 /m Na is the ground state between ≈250 GPa at 710 K and ≈350 GPa at 1900 K. Electronic structure calculations show that this phase is a topological semimetal with a Dirac nodal surface that is protected by a nonsymmorphic symmetry S 2z and an electride owing to its non-nuclear charge localized within one-dimensional honeycomb channels and zero-dimensional cages. Our results highlight the complexity of dense sodium's free-energy landscape and intricate electronic structure that emerges at finite temperatures and conditions where ionic cores overlap.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Thermodynamically consistent semi-compressible fluids: a variational perspective

This paper presents (Lagrangian) variational formulations for single and multicomponent semi-compressible fluids with both reversible (entropy-conserving) and irreversible (entropy-generating) processes. Semi-compressible fluids are useful in describing low-Mach dynamics, since they are soundproof. These models find wide use in many areas of fluid dynamics, including both geophysical and astrophysical fluid dynamics. Specifically, the Boussinesq, anelastic and pseudoincompressible equations are developed through a unified treatment valid for arbitrary Riemannian manifolds, thermodynamic potentials and geopotentials. By design, these formulations obey the 1st and 2nd laws of thermodynamics, ensuring their thermodynamic consistency. This general approach extends and unifies existing work, and helps clarify the thermodynamics of semi-compressible fluids. To further this goal, evolution equations are presented for a wide range of thermodynamic variables: entropy density s, specific entropy η, buoyancy b, temperature T, potential temperature θ and a generic entropic variable χ; along with a general definition of buoyancy valid for all three semicompressible models and arbitrary geopotentials. Finally, the elliptic equation for the pressure perturbation (the Lagrange multiplier that enforces semi-compressibility) is developed for all three equation sets in the case of reversible dynamics, and for the Boussinesq/anelastic equations in the case of irreversible dynamics; and some discussion is given of the difficulty in formulating it for the pseudoincompressible equations with irreversible dynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Composition and Pressure Effects on Partitioning of Ferrous Iron in Iron-Rich Lower Mantle Heterogeneities

Both seismic observations of dense low shear velocity regions and models of magma ocean crystallization and mantle dynamics support enrichment of iron in Earth’s lowermost mantle. Physical properties of iron-rich lower mantle heterogeneities in the modern Earth depend on distribution of iron between coexisting lower mantle phases (Mg,Fe)O magnesiowüstite, (Mg,Fe)SiO3 bridgmanite, and (Mg,Fe)SiO3 post-perovskite. The partitioning of iron between these phases was investigated in synthetic ferrous-iron-rich olivine compositions (Mg0.55Fe0.45)2SiO4 and (Mg0.28Fe0.72)2SiO4 at lower mantle conditions ranging from 33–128 GPa and 1900–3000 K in the laser-heated diamond anvil cell. The resulting phase assemblages were characterized by a combination of in situ X-ray diffraction and ex situ transmission electron microscopy. The exchange coefficient between bridgmanite and magnesiowüstite decreases with pressure and bulk Fe# and increases with temperature. Thermodynamic modeling determines that incorporation and partitioning of iron in bridgmanite are explained well by excess volume associated with Mg-Fe exchange. Partitioning results are used to model compositions and densities of mantle phase assemblages as a function of pressure, FeO-content and SiO2-content. Unlike average mantle compositions, iron-rich compositions in the mantle exhibit negative dependence of density on SiO2-content at all mantle depths, an important finding for interpretation of deep lower mantle structures.

Dorfman, Susannah M. (ORCID:0000000239689592)↗
DOE OSTI2026

From Weibel seeds to dynamo beyond pair-plasmas

Bridging the spatiotemporal scales of magnetic seed field generation and subsequent dynamo amplification in the weakly collisional intracluster medium presents an extreme numerical challenge. We perform collisionless turbulence simulations with initially unmagnetised electrons that capture both magnetic seed generation via the electron Weibel instability and the ensuing dynamo amplification. Going beyond existing pair-plasma studies, we use an ion-to-electron mass ratio of 100 for which we find electron and ion dynamics are sufficiently decoupled. These simulations are enabled by the 10-moment collisionless fluid solver of Gkeyll, which evolves the full pressure tensor for all species. The electron heat-flux closure regulates pressure isotropisation and effectively sets the magnetic Reynolds number. We investigate how the strength of the closure influences the transition between a regime reminiscent of previous kinetic pair-plasma simulations and a regime exhibiting dynamo behaviour qualitatively similar to magnetohydrodynamics.

astrophysical plasmas↗
DOE OSTI2021

CFD modeling of pre-spark heat release in a boosted direct-injection spark-ignition engine

Accurate predictions of low-temperature heat release (LTHR) are critical for modeling auto-ignition processes in internal combustion engines. While LTHR is typically obscured by deflagration, extremely late ignition phasing can lead to LTHR prior to the spark, a behavior known as pre-spark heat release (PSHR). In this research, PSHR in a boosted direct-injection spark-ignition engine was studied using 3-D computational fluid dynamics (CFD) and detailed chemical kinetics. The turbulent combustion was modeled via a hybrid approach that incorporates the G-equation model for tracking the turbulent flame front, and the well-stirred reactor model with detailed chemistry for assessing the low-temperature reactions in unburnt gas. Simulations were conducted using Co-Optima alkylate and E30 fuels at operating conditions characterized by different PSHR intensities. The predicted in-cylinder pressure and heat release rate were found to agree well with experiments. It was found the estimate of previous-cycle trapped residuals is of utmost importance for capturing PSHR correctly. A simulation best practice was developed which keeps the detailed chemistry solver active throughout the entire simulation, allowing to track the evolution of intermediate species from one cycle to the next. Following the validation, the dynamics of PSHR were analyzed in detail employing the pressure-temperature (P-T) trajectory framework. It was shown that PSHR correlated with the first-stage ignition delay of the fuel, hence showing close relation to the in-cylinder P-T trajectory and the chemical kinetics. Besides, it was indicated that LTHR is a self-limiting process that has the effect of attenuating the thermal stratification in the combustion chamber. Furthermore, it was observed the occurrence of PSHR caused the P-T trajectory of end-gas to overlap with the negative temperature coefficient region of the fuel’s ignition-delay maps. This effect was more significant in the fuel-rich regions where engine knock tendency would be generally higher, with potential implications on knock control and mitigation.

42 ENGINEERING↗
DOE OSTI2025

Multiframe X-ray diffraction on the OMEGA EP laser

A method of measuring multiple temporally resolved powder x-ray diffraction measurements during a single dynamic compression laser experiment has been demonstrated on the OMEGA EP laser. Up to four time-gated snapshots of the x-ray diffraction pattern are collected on an ultrafast x-ray framing camera with a 2θ scattering angle coverage of 48°–65° and 400-ps temporal resolution with the potential for 10°–160° and 200-ps resolution. X-ray diffraction snapshots capture the transformation to a high-pressure β phase in ramp-compressed Zr, constraining the atomic structure and pressure–density equation-of-state in a single shot. Here, this platform will be used to constrain transition pressures, understand the role of kinetics, and verify the existence of hysteresis and metastability on phase transformations at the lattice level under single-shot dynamic compression.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Three-Dimensional CFD Investigation of Pre-Spark Heat Release in a Boosted SI Engine

Low-temperature heat release (LTHR) in spark-ignited internal combustion engines is a critical step toward the occurrence of auto-ignition, which can lead to an undesirable phenomenon known as engine knock. As such, correct predictions of LTHR are of utmost importance to improve the understanding of knock and enable techniques aimed at controlling it. While LTHR is typically obscured by the deflagration following the spark ignition, extremely late ignition timings can lead to LTHR occurrence prior to the spark, i.e., pre-spark heat release (PSHR). In this research, PSHR in a boosted direct-injection SI engine was numerically investigated using three-dimensional computational fluid dynamics (CFD). A hybrid approach was used, based on the G-equation model for representing the turbulent flame front and the multi-zone well-stirred reactor model for tracking the chemical reactions within the unburnt region. A recently developed best practice was also employed which keeps the well-stirred reactor model active throughout the entire simulation. This allowed for correct predictions of the previous cycle trapped residuals which have a considerable effect on the onset of LTHR. Multi-cycle simulations were conducted using Co-Optima alkylate and E30 fuels. The predicted in-cylinder pressure and heat release rate agreed well with the experimental data and served as validation for the CFD model. Following the initial validation, the dynamics of PSHR was discussed and a series of parameters of interest were assessed. First, the effect of exhaust valve temperature was investigated, qualitatively highlighting the importance of boundary conditions uncertainty. Further analyses were carried out on the effects of fuel properties, including laminar flame speed (LFS) and heat of vaporization (HOV). The results indicate that PSHR phasing is slightly advanced with lower LFS as more trapped unburnt fuel is made available for the next cycle. A similar trend was observed with lower HOV as less intense spray cooling led to higher mixture temperatures, i.e., higher mixture reactivity. Finally, a comparison of Co-Optima alkylate and E30 fuels was made using the pressure-temperature trajectory framework. It was shown that the differences between Co-Optima alkylate and E30 in PSHR tendency are correlated with both HOV and chemical effects.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Dynamics of argon metastables in Ar–CH 4 radio frequency capacitively-coupled plasma: real-time monitoring with neural network-augmented broadband optical emission spectroscopy

In moderate-pressure radio frequency (RF) capacitively coupled plasmas generated in argon–methane mixtures, the density of argon metastable atoms (Ar 1 s 5 ) exhibits a non-monotonic dependence on methane (CH 4 ) concentration. Laser-induced fluorescence (LIF) was used to measure and compare local Ar 1 s 5 densities in Ar and Ar–CH 4 plasmas at 2.6 Torr and RF powers of 17–117 W. The addition of 1% CH 4 increases the metastable density, and 2% CH 4 triggers a strong depletion by an order of magnitude, compared to 1% CH 4 case. This non-monotonic behavior demonstrates the sensitivity of metastable populations to small gas admixtures, which is critical for processes where metastables drive precursor dissociation. For real-time monitoring of metastable population, broadband optical emission spectroscopy (OES) is augmented with a feedforward neural network (NN) to predict Ar s1 5 densities from spectral features. When trained on LIF data, the NN replicates the absolute densities and the dynamic trends of Ar 1 s 5 density variation. The NN-augmented broadband OES approach can be used as a simple and cost-effective tool for tracking Ar metastables in Ar-rich plasmas, facilitating industrial-scale optimization.

Yatom, Shurik [Princeton Plasma Physics Laboratory↗
DOE OSTI2024

Counterintuitive Trend of Intrusion Pressure with Temperature in the Hydrophobic Cu 2 (tebpz) MOF

Liquid porosimetry experiments reveal a peculiar trend of the intrusion pressure of water in hydrophobic Cu 2 (3,3',5,5'-tetraethyl-4,4'-bipyrazolate) MOF. At lower temperature (T) range, the intrusion pressure (P i ) increases with T. For higher T values, P i first reaches a maximum and then decreases. This is at odds with the Young–Laplace law, which for systems showing a continuous decrease of contact angle with T predicts a corresponding reduction of the intrusion pressure. Though the Young–Laplace law is not expected to provide quantitative predictions at the subnanoscale of Cu 2 (tebpz) pores, the physical intuition suggests that to a reduction of their hydrophobicity corresponds a reduction of the P i . Molecular dynamics simulations and sychrothron experiments allowed to clarify the mechanism of the peculiar trend of P i with T. At increasing temperatures the vapor density within the MOF’ pores grows significantly, bringing the corresponding partial pressure to ≈5 MPa. This pressure, which is consistent with the shift of P i observed in liquid porosimetry, represents a threshold to be overcame before intrusion takes place. Beyond some value of temperature, the phenomenon of reduction of hydrophobicity (and water surface tension) dominated over the opposite effect of increase of vapor pressure and P i inverts its trend with T.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The effect of microstructure on the dynamic shock response of 1045 steel

Herein, the effect of microstructure on the shock response of 1045 steel is investigated via plate impact experiments and postmortem characterization. Three unique microstructures are explored: ferrite-pearlite, martensite, and ferrite with spheroidal cementite (i.e. spheroidized). Two spall recovery experiments, at approximate peak pressures of 3.2 and 3.5 GPa, are conducted to assess the Hugoniot elastic limit (HEL), spall strength, and damage morphology of the various microstructures. The ferrite-pearlite and martensite microstructures exhibit continuous yielding at both quasi-static and dynamic rates, while the spheroidized condition displays discontinuous yielding. Discontinuous yielding of the spheroidized microstructure is attributed to a combined low initial dislocation density coupled with a low dislocation nucleation rate. The spall strength of ferrite-pearlite is consistently lower than the spheroidized microstructure, attributed to elongated cementite that is more susceptible to cracking than more spherical cementite precipitates. Despite a high density of boundaries, martensite exhibits the highest spall strength. A large percentage of the boundaries within the martensite microstructure are found to be low energy (i.e. Σ3 or low angle), and are thus less susceptible to spall damage. Overall, the high spall strength of martensite is likely linked to traditional strengthening mechanisms that limit dislocation motion.

36 MATERIALS SCIENCE↗