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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Reaction engineering: a lost (and found) art for a decarbonized future [Slides]

The heart (or, perhaps more appropriately, the stomach) of any chemical manufacturing process is the reactor, where chemical and physical transformations occur under precisely controlled conditions. For traditional industrial processes, the design, optimization and operation of chemical reactors are extremely well developed, drawing upon the principles of chemistry, physics, calculus and economics. However, new-age process concepts proposing to use "exotic" reactors and/or sustainable inputs (e.g., renewable carbon resources, electrons, photons, plasma) face a dearth of well documented reaction engineering principles & design practices that eclipses their rapid adoption. This presentation features two vignettes of (the return of) reaction engineering in sustainable process science, first in the valorization of lignin from biomass, and second in understanding multimodal catalyst deactivation in industrial-scale reactors within the Catofin process for propane dehydrogenation. Overall, this seminar seeks to educate student researchers on practical means of advancing laboratory reactor technologies towards commercial practice.

09 BIOMASS FUELS↗
DOE OSTI2024

Thinking Bayesian for plasma physicists

Bayesian statistics offers a powerful technique for plasma physicists to infer knowledge from the heterogeneous data types encountered. To explain this power, a simple example, Gaussian Process Regression, and the application of Bayesian statistics to inverse problems are explained. The likelihood is the key distribution because it contains the data model, or theoretic predictions, of the desired quantities. By using prior knowledge, the distribution of the inferred quantities of interest based on the data given can be inferred. Because it is a distribution of inferred quantities given the data and not a single prediction, uncertainty quantification is a natural consequence of Bayesian statistics. The benefits of machine learning in developing surrogate models for solving inverse problems are discussed, as well as progress in quantitatively understanding the errors that such a model introduces.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Neutralization of ion beam by electron injection: Accumulation of cold electrons

Ion beam charge neutralization by electron injection is a complex kinetic process. Recent experiments show that the resulting self-potential of the ion beam after neutralization by plasma is much lower than the temperature of plasma electrons [Stepanov et al., Phys. Plasmas 23, 043113 (2016)], indicating that kinetic effects are important and may affect the neutralization of the ion beam. We performed a numerical study of the charge neutralization process of an ion beam making use of a two-dimensional electrostatic particle-in-cell code. The results show that the process of charge neutralization by electron injection is composed of two stages. During the first stage, the self-potential of the beam is higher than the temperature of injected electrons (T e /e) and all injected electrons are captured by the ion beam. During the second stage, hot electrons escape from the ion beam and the beam self-potential (φ) decreases because cold electrons slowly accumulate resulting in the beam self-potential φ to become much lower than Te/e in agreement with previous experimental observations at Princeton Advanced Teststand. We also determined that the resulting φ scales as φ~√T e , in agreement with previous experimental observations from Gabovich's group. In addition, the results show that the transverse position of the electron source has a great impact on ion beam neutralization. A slight shift of the electron source as relevant to the ion thrusters leads to a large increase in the beam self-potential because of an increase in potential energy of injected electrons.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Anisotropic angular scattering models of elastic electron-neutral collisions for Monte Carlo plasma simulations

Many laboratory and industrial plasma applications require accurate modeling techniques to understand the interplay between microscopic and macroscopic processes. A prime example of this interplay is how particle and Monte Carlo (MC) simulation codes describe angular scattering of electrons following elastic scattering events. The forward peaked nature of high energy electron elastic scattering is relatively trivial to accurately describe in plasma simulations. However, for lower energy collisions, which produce near isotropic or backward peaked differential cross sections, there is not a strong consensus among the plasma modeling community on how to best describe these angular scattering trends. Here, in this study, we propose a systematic method to approximate the aforementioned non-trivial angular scattering behavior with a formula that can be readily implemented in particle-in-cell (PIC) and/or MC plasma simulation codes. The present approach is specifically applied to fusion relevant atomic hydrogen and helium, as well as for molecular hydrogen, and results are also applicable to the atomic isotopes and homonuclear molecular isotopologues of these species. Comparisons between the present angular distribution function and benchmark scattering data were used to validate the proposed models. In addition, two-term Boltzmann calculations and PIC direct simulation MC simulations revealed that the proposed angular distribution function is accurate, agreeing very well with benchmark convergent close-coupling scattering calculations, and electron transport measurements. These studies confirmed that the present angular distribution function model can be utilized without the need of renormalization to the momentum transfer cross section (as opposed to using the elastic scattering integrated cross section), which has been suggested by several studies in order to correct for deficient angular scattering models, and to agree with transport measurements. Hence, the present anisotropic angular scattering model can be utilized to accurately model the momentum transfer as well as the electron trajectories of elastic collisions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

MPEX AI Digital Twins

All magnetically confined plasma fusion power plant concepts (Tokamak, Spherical Tokamak, Stellarator, Mirror, ...) must exhaust the heat and plasma from the core confinement region to the material walls. The primary channel for this exhaust is through a plasma divertor which directs plasma along open magnetic field lines to a material target. The Material Plasma Exposure eXperiment (MPEX) illustrated in Figure 1, is a high-power, steady-state linear plasma device designed to produce the plasma material interaction (PMI) conditions of the divertor of future magnetic confinement fusion power plants: energy flux 20MW/m 2 , ion fluence 1031/m 2 , pulse duration 106 sec. These goals of plasma exposure in MPEX are well beyond those achieved in magnetic fusion experimental devices. Successfully achieving these high power steady state conditions for long pulses requires operational control of the heating and particle sources and the plasma flux to the walls and target. The MPEX AI Hot Spot Controller, proposed in this project, will help achieve the operational milestones of MPEX. The MPEX device will begin commissioning at the end of FY26. A smaller proto-MPEX was operated for 14,666 plasma discharges and will resume operation in September of 2025 as proto-MPEX-lite, with reduced capability, to test a new window for the Helicon plasma source. The proto-MPEX data has undergone surrogate modeling with machine learning methods (R. Archibald, 2022 IEEE International Conference on Big Data). This proto-MPEX data will be used to begin development of the AI digital twins described in this white paper. The scientific mission of MPEX is to qualify materials of different composition for use in the high energy and plasma flux conditions of a fusion power plant. The materials exposed in MPEX will in some cases be exposed to high neutron fluxes at other ORNL facilities to measure the changes to their PMI properties. The targets exposed in MPEX will be transported under vacuum to a Surface Analysis Station (SAS). The SAS will be equipped with the following diagnostics: Focused Ion Beam (FIB) for trench milling, 100-400 angstrom resolution scanning electron microscope (SEM), surface mapping x-ray spectrometer, high resolution camera, and a future upgrade to a laser induced breakdown spectroscopy quadruple mass spectrometer (LIBS-QMS). The MPEX experiments will generate diverse pre- and post-exposure measurement data of detailed material properties down to the crystal grain level in 3D for post-exposure assessment of PMI damage (e.g. cracking, melting, erosion and redeposition of the material). Physics models for the PMI, and how the material composition and manufacturing impact its performance under high energy plasma exposure, need to be validated with MPEX data to guide the selection of new candidate materials. Our vision for the MPEX AI Digital Twins project is to supply experimental and physics model simulation data to train Artificial Intelligence (AI) models for data processing, analysis, operational control, PMI and materials simulation to maximize the scientific output of the MPEX device. Ultimately, an AI digital twin of MPEX material assessment metrics for tested and synthetic material types with simulated PMI will be trained by the AI Modeling Teams on the experimental and physics simulation data submitted to the American Science Cloud by this project. A purely empirical search for the best material is inefficient given the finite number of samples that can be tested on MPEX. In order to expand the material properties database for training the MPEX Material Assessment AI Digital Twin, and to gain physics understanding of the PMI processes, physics models of the material properties and PMI processes are required. The physics simulations provide detailed simulation data, like impact angles for plasma ions, sputtering yields, transport of the ionized sputtered target material in the plasma, and redeposition locations. This simulation data expands the measurement data for deeper physics understanding. The experimental data is essential to validate the PMI and material structure simulation models. The validated models can then be used to generate new simulation data of MPEX material assessments for synthetic material compositions that have not been exposed in MPEX. These predictive simulations, plus the whole experimental dataset, will be used to train the MPEX Material Assessment AI Digital Twin allowing a rapid generative AI search for new materials with reduced PMI damage by interpolating the domain of the training set. These new optimum materials can be simulated with the physics codes and/or tested in MPEX. The ability of AI neural networks to interpolate multi-dimensional parameter spaces and generate virtual data is exploited for a more efficient search for optimum materials. The advent of the Transformational AI Models Consortium (TAIMC) is an opportunity to engage with state of the art private and public AI developers to achieve the goals of the AI digital twins and AI accelerated physics models proposed in this project. Our partners at ORNL from the Advance Scientific Computing Research (ASCR) organization will collaborate in accelerating the integrated plasma material interaction simulation framework. This simulation framework will provide a platform for generating simulation data across a range of physical fidelities, including hybrid methods that produce multi-fidelity results. This data will be leveraged for AI model development, both for generation of surrogates and the automation of simulation campaigns. A part of the research below will include collaborative efforts with the TAIMC to (i) adapt data storage approaches to ensure AI-readiness, (ii) provide a protypical exemplar to inform and exercise constructed workflows, and (iii) generate and share data, using the TAIMC unified AI data standard, for foundational models that will be trained from multiple sources across the DOE complex. We will also collaborate with the TAIMC, as well as the planned AI modeling teams, to develop approaches for reducing the cost of data generation. These include tailored multi-fidelity approaches as well as fine-tuning strategies to augment general, large-scale foundational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Collaborative Research: Unravelling the Physics Associated with the Production of Extremely Dense Plasma States of Microscale (Final Report) Nanosecond-pulsed Discharges

The aim of this project is to study and establish the physical mechanisms that contribute to the formation of anomalously dense plasmas in high-pressure nanosecond-pulsed discharges. These discharges have a broad range of applications such as plasma-assisted combustion, plasma flow actuators, biomedical sterilization and exotic materials synthesis. The structure and formation of these discharges, producing high plasma densities of ~10 14 -10 15 cm -3 , are well-studied and understood. Fast-pulsed microscale high-pressure discharges can be driven to even higher densities of > 10 19 cm -3 , approaching warm dense matter conditions. The mechanisms that generate these plasmas have not been understood. Analysis of the warm dense matter state under laboratory conditions is an expensive and non-trivial endeavor. For instance, dense plasmas can be generated by electrical explosions of metal foils and wires. Plasmas generated after the explosion have a short lifetime and often present difficult conditions for diagnostics. Generation of dense plasmas was also achieved during high-voltage nanosecond pulsed discharges when the so-called explosive electron emission is obtained. Unfortunately, this process is very difficult to control for the studies of warm dense matter. In our recent study, we have shown that additional heating of plasma by lasers can further increase the density of plasma and even lead to the fully ionized state. This method, potentially, allows better control of the plasma parameters. In this work, we studied a second stage laser-heated micro-discharge using a self-consistent one-dimensional particle-in-cell Monte Carlo-collision (1D PIC-MCC) model coupled with Maxwell’s equations. We predicted the generation of a fully ionized plasma on the picosecond time scale. However, this model considered the plasma as an ideal gas despite the high pressure and the nearly fully ionized state. The ideal plasma model assumes that the dilute gas approximation is valid, where the inter-particle interactions are negligible. For charged particles this assumption holds as long as the shielded Coulomb potential assumption is valid. For very high plasma densities, this concept breaks down since the Debye sphere surrounding each charged particle no longer contains enough electrons to statistically provide the shielding of the single particle Coulomb interaction potential. At such densities, the plasma can no longer be described as ideal and non-ideal coupling effects need to be considered. In this report, we elucidate our recent work of developing a PIC-MCC model with improvements for non-ideal plasma conditions due to Coulomb coupling at high densities. In particular, we study the interaction of green light radiation and a dense microplasma, and explore the non-ideal plasma effects in this interaction. In this computational model, we implement the two most important non-ideal effects: ionization potential depression (IPD) and enhanced collision cross sections. Our primary goal is to study the physics associated with electromagnetic (EM) wave heating, also called the second-stage wave-heating, and establish the role of plasma non-ideality in this phenomenon. Our secondary goal is to improve the chemistry mechanism of the 1D PIC-MCC model by including a more detailed excited species collision treatment. At high pressures, stepwise ionization from excited species might play an important role in the ionization process. Previously, this ionization mechanism was neglected due to the excitation collision cross section of xenon being smaller than that of ionization. However, a preliminary study showed that the excited species density in the initial microplasma was an order of magnitude higher than the electron density. Therefore, my aim is to determine the significance of this additional ionization pathway to the plasma generation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Spatio-temporal ablation dynamics and plasma chemistry of aluminum induced by temporally modulated ytterbium fiber laser

Here, in this work, we studied single-pulse ablation dynamics of a temporally modulated continuous wave laser-material interaction with Al using in situ multimodal time-resolved diagnostics that describe in detail the associated physical and chemical processes. Time-resolved scattering, emission imaging, and optical emission spectroscopy unveiled a sequence of events spread out across three distinct phases: (i) early phase ablation process, associated with particle generation and liquid Al column formation (<20 μs), (ii) secondary detonation when sufficient ejected material is accumulated over the surface (20-50 μs), and (iii) molten liquid Al pool oscillation on the surface, followed by large droplet ejection from the liquid pool (100-500 μs). Atomic Al and AlO were observed with optical emission spectroscopy at different ratios during the entire lifetime of the event, verifying the formation of oxidized Al vapor upon its interaction with air. Morphological and compositional characterization confirmed surface oxidation and material re-solidification in the form of protrusions produced during the irradiation process. This work provides insights into the complex physical and chemical mechanisms of single-pulse ablation in the sub-millisecond laser pulse regime, which are critically important for parameter optimization in a variety of laser processing, microfabrication, and deposition applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Phase-field approach to cellular blebbing

Bulges in the plasma membrane of cells known as blebs can form spontaneously in a wide range of biological processes, but what controls their shape and stability remains incompletely understood. Here, to address this we introduce a dual phase-field model with coupled order parameters representing the cell cortex and plasma membrane that can quantitatively model blebbing in three dimensions. Simulations and sharp-interface analyses reveal that, depending on whether blebbing occurs by detachment of the plasma membrane or rupture of the actin cortex, blebs can form discontinuously through a saddle-node bifurcation or continuously with increasing cortical tension. The model predictions are in good quantitative agreement with existing experimental data for laser-induced cortex rupture.

Biological and medical sciences↗
DOE OSTI2022

Fully Kinetic Shearing-box Simulations of Magnetorotational Turbulence in 2D and 3D. I. Pair Plasmas

The magnetorotational instability (MRI) is a fundamental mechanism determining the macroscopic dynamics of astrophysical accretion disks. In collisionless accretion flows around supermassive black holes, MRI-driven plasma turbulence cascading to microscopic (i.e., kinetic) scales can result in enhanced angular-momentum transport and redistribution, nonthermal particle acceleration, and a two-temperature state where electrons and ions are heated unequally. However, this microscopic physics cannot be captured with standard magnetohydrodynamic (MHD) approaches typically employed to study the MRI. In this work, we explore the nonlinear development of MRI turbulence in a pair plasma, employing fully kinetic particle-in-cell (PIC) simulations in two and three dimensions. First, we thoroughly study the axisymmetric MRI with 2D simulations, explaining how and why the 2D geometry produces results that differ substantially from 3D MHD expectations. We then perform the largest (to date) 3D simulations, for which we employ a novel shearing-box approach, demonstrating that 3D PIC models can reproduce the mesoscale (i.e., MHD) MRI dynamics in sufficiently large runs. With our fully kinetic simulations, we are able to describe the nonthermal particle acceleration and angular-momentum transport driven by the collisionless MRI. Since these microscopic processes ultimately lead to the emission of potentially measurable radiation in accreting plasmas, our work is of prime importance to understand current and future observations from first principles, beyond the limitations imposed by fluid (MHD) models. While in this first study we focus on pair plasmas for simplicity, our results represent an essential step toward designing more realistic electron–ion simulations, on which we will focus in future work.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

NO formation by N 2 /O 2 plasma catalysis: The impact of surface reactions, gas-phase reactions, and mass transport

Pathways and timescales relevant to facilitate plasma-assisted N 2 -O 2 reactions are assessed by measuring the consumption of plasma-derived N and the formation of NO in the gas phase and over Ag catalytic surfaces. These measurements are enabled by a setup that enables N 2 activation in an atmospheric pressure RF plasma jet, enables O 2 addition in the plasma afterglow, facilitates reactions over an Ag wire catalyst, and allows species density quantification by molecular beam mass spectrometry. Gas-phase reactions consume N but do not form NO with high selectivity. The presence of the non-porous Ag wire catalyst increases the rate of N conversion to NO, though mass transfer processes, not surface reactions, dictate the rate of N consumption. When O 2 concentrations and the ratio of the surface area of the catalyst to the void volume of the reactor are high (3–5 mol% O 2 , 10900 m –1 ), N conversion to NO reaches 100 % selectivity. When both N 2 and O 2 are fed through the plasma jet, gas-phase NO production increases 10×, although plasma and gas-phase processes do not exclusively produce NO. Above a threshold NO density, N cannot diffuse to the catalyst surface faster than it is consumed in the gas phase by reactions with NO. Furthermore, the use of heterogeneous catalysts to enhance plasma-driven N x O y formation and control N x O y product selectivity is limited to cases where diffusive transport of N from the gas phase to the catalyst surface is faster than consumption of N from gas-phase reactions with NO.

Engineering↗
DOE OSTI2023

Anomalous hydrodynamics effective actions from holography

We derive an effective action for charged plasmas with an anomalous (abelian) global current charge current using holography. The holographic description is captured by the dynamics of an Einstein-Maxwell-Chern-Simons theory in an asymptotically AdS spacetime. The ’t Hooft anomaly contribution, which is encoded in the Chern-Simons term, contributes at the Gaussian order in the effective action only in the momentum diffusion sector, where it leads to chiral shear waves. However, as we demonstrate, beyond the Gaussian order, there is non-trivial imprint of the parity-violating anomaly term in sound and charge diffusion dynamics as well.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Deletion of Carboxypeptidase E in β-Cells Disrupts Proinsulin Processing but Does Not Lead to Spontaneous Development of Diabetes in Mice

Carboxypeptidase E (CPE) facilitates the conversion of prohormones into mature hormones and is highly expressed in multiple neuroendocrine tissues. Carriers of CPE mutations have elevated plasma proinsulin and develop severe obesity and hyperglycemia. We aimed to determine whether loss of Cpe in pancreatic β-cells disrupts proinsulin processing and accelerates development of diabetes and obesity in mice. Pancreatic β-cell–specific Cpe knockout mice (βCpeKO; Cpe fl/fl x Ins1 Cre/+ ) lack mature insulin granules and have elevated proinsulin in plasma; however, glucose-and KCl-stimulated insulin secretion in βCpeKO islets remained intact. High-fat diet–fed βCpeKO mice showed weight gain and glucose tolerance comparable with those of Wt littermates. Notably, β-cell area was increased in chow-fed βCpeKO mice and β-cell replication was elevated in βCpeKO islets. Transcriptomic analysis of βCpeKO β-cells revealed elevated glycolysis and Hif1α-target gene expression. On high glucose challenge, β-cells from βCpeKO mice showed reduced mitochondrial membrane potential, increased reactive oxygen species, reduced MafA, and elevated Aldh1a3 transcript levels. Following multiple low-dose streptozotocin injections, βCpeKO mice had accelerated development of hyperglycemia with reduced β-cell insulin and Glut2 expression. In conclusion, these findings suggest that Cpe and proper proinsulin processing are critical in maintaining β-cell function during the development of hyperglycemia.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Plasma Synthesis of Spherical Crystalline and Amorphous Electrolyte Nanopowders for Solid-State Batteries

Here, we demonstrate the theory-guided plasma synthesis of high purity nanocrystalline Li 3.5 Si 0.5 P 0.5 O 4 and fully amorphous Li 2.7 Si 0.7 P 0.3 O 3.17 N 0.22 . The synthesis involves the injection of single or mixed phase precursors directly into a plasma torch. As the material exits the plasma torch, it is quenched into spherical nanocrystalline or amorphous nanopowders. This process has virtually zero Li loss and allows for the inclusion of N, which is not accessible with traditional synthesis methods. Finally, we further demonstrate the ability to sinter the crystalline nanopowder into a dense electrolyte membrane at 800 °C, well below the traditional 1000 °C required for a conventional Li 3.5 Si 0.5 P 0.5 O 4 powder.

25 ENERGY STORAGE↗
DOE OSTI2024

Methods for Color Center Preserving Hydrogen‐Termination of Diamond

Abstract Chemical functionalization of diamond surfaces by hydrogen is an important method for controlling the charge state of near‐surface fluorescent color centers, an essential process in fabricating devices such as diamond field‐effect transistors and chemical sensors, and a required first step for realizing families of more complex terminations through subsequent chemical processing. In all these cases, termination is typically achieved using hydrogen plasma sources that can etch or damage the diamond, as well as deposited materials or embedded color centers. This work explores alternative methods for lower‐damage hydrogenation of diamond surfaces, specifically the annealing of diamond samples in high‐purity, non‐explosive mixtures of nitrogen and hydrogen gas, and the exposure of samples to microwave hydrogen plasmas in the absence of intentional stage heating. The effectiveness of these methods are characterized by x‐ray photoelectron spectroscopy (XPS), and comparison of the results to density‐functional modelling of the surface hydrogenation energetics implicates surface oxygen ligands as the primary factor limiting the termination quality of annealed samples. Finally, photoluminescence (PL) spectroscopy is used to verify that both the annealing and reduced sample temperature plasma methods are non‐destructive to near‐surface ensembles of nitrogen‐vacancy (NV) centers, in stark contrast to plasma treatments that use heated sample stages.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Thermoelectric Performance of the 2D Bi 2 Si 2 Te 6 Semiconductor

Bi 2 Si 2 Te 6 , a 2D compound, is a direct band gap semiconductor with an optical band gap of 0.25 eV, and is a promising thermoelectric material. Single-phase Bi 2 Si 2 Te 6 is prepared by a scalable ball-milling and annealing process and the highly densified polycrystalline samples are prepared by spark plasma sintering. Bi 2 Si 2 Te 6 shows a p-type semiconductor transport behavior and exhibits an intrinsically low lattice thermal conductivity of ~0.48 Wm -1 K -1 (cross-plane) at 573 K. The first-principles density functional theory calculations indicate that such low lattice thermal conductivity is derived from the interactions between acoustic phonons and low-lying optical phonons, local vibrations of Bi, the low Debye temperature and strong anharmonicity result from the unique 2D crystal structure and metavalent bonding of Bi 2 Si 2 Te 6 . The Bi 2 Si 2 Te 6 exhibits an optimal figure of merit ZT of ~0.51 at 623 K, which can be further enhanced by the substitution of Bi with Pb. Pb doping leads to a large increase in power factor S 2 σ, from ~4.0 μWcm -1 K- 2 of Bi 2 Si 2 Te 6 to ~8.0 μWcm -1 K -2 of Bi 1.98 Pb 0.02 Si 2 Te 6 at 775 K, owing to the increase in carrier concentration. Moreover, Pb doping induces a further reduction in the lattice thermal conductivity to ~0.38 Wm -1 K -1 (cross-plane) at 623 K in Bi 1.98 Pb 0.02 Si 2 Te 6 ,. The simultaneous optimization of the power factor and lattice thermal conductivity achieves a peak ZT of ~0.90 at 723 K and a high average ZT of ~0.66 at 400–773 K in Bi 1.98 Pb 0.02 Si 2 Te 6 .

36 MATERIALS SCIENCE↗
DOE OSTI2023

Design and implementation of a prototype infrared video bolometer (IRVB) in MAST Upgrade

A prototype infrared video bolometer (IRVB) was successfully deployed in the Mega Ampere Spherical Tokamak Upgrade (MAST Upgrade or MAST-U), the first deployment of such a diagnostic in a spherical tokamak. The IRVB was designed to study the radiation around the lower x-point, another first in tokamaks, and has the potential to estimate emissivity profiles with spatial resolution beyond what is achievable with resistive bolometry. The system was fully characterized prior to installation on MAST-U, and the results are summarized here. After installation, it was verified that the actual measurement geometry in the tokamak qualitatively matches the design; this is a particularly difficult process for bolometers and was done using specific features of the plasma itself. The installed IRVB measurements are consistent both with observations from other diagnostics, including magnetic reconstruction, visible light cameras, and resistive bolometry, as well as with the IRVB-designed view. Early results show that with conventional divertor geometry and only intrinsic impurities (for example, C and He), the progression of radiative detachment follows a similar path to that observed for large aspect ratio tokamaks: The peak of the radiation moves along the separatrix from the targets to the x-point and high-field side midplane with a toroidally symmetric structure that can eventually lead to strong effects on the core plasma inside the separatrix.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Thermophysical Properties of Ti3SiC2 MAX Phase Composites with SiC Reinforcement

In the present work, dense (∼100%) Ti 3 SiC 2 composites (TSC) are processed along with 20 vol% of SiC reinforcement (TSC20) via spark plasma sintering at 1400°C, 40 MPa, 15 min, and dynamic vacuum environment. Thermal expansion of both the composites increases from RT to 1273 K and linear fitting of data yields coefficient of thermal expansion (CTE) of 9.4 × 10 −6 K −1 for TSC which decreases to 8.3 × 10 −6 K −1 for TSC20. With increase in temperature from RT to 773 K, specific heat for both TSC and TSC20 composites is observed to increase from 598-850 J.kg −1 .K −1 , whereas thermal diffusivity and thermal conductivity values decrease with testing temperature. SiC reinforcement in Ti 3 SiC 2 resulted in improved thermal diffusivity from 12.7 to 18.7 mm 2 .s −1 and thermal conductivity from ∼57 to ∼79 W.m −1 .K −1 at RT. However, with increase in temperature (773 K), thermal diffusivity and conductivity decrease, and values get closer for both TSC and TSC20 composites. Further extrapolation of thermal conductivity data showed cross-over at ∼973 K due to domination of phonon-phonon scattering and thus lower values of thermal conductivity for TSC20 than TSC. Therefore, reduced CTE and higher thermal conductivity of TSC20 make it a viable choice for applications in high temperatures.

36 MATERIALS SCIENCE↗