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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Non-thermal atmospheric pressure plasma–liquid synthesis of organic acids in aqueous solution from carbon monoxide

This work aims at understanding the conversion of CO to organic acids, namely oxalic acid and formic acid, using non-thermal atmospheric pressure plasma over aqueous solutions. CO exhibited significantly higher conversion to organic acids (more than 15×) compared to CO 2 under the same reaction conditions. The result bolsters a proposed two-step process for CO 2 fixation, whereby CO 2 is first converted to CO, and then CO is converted to organic acids. The organic acids produced from CO are intermediates in the water–gas shift (WGS) reaction of CO in the presence of an aqueous solution to dissolved CO 2 and hydrogen gas. Based on a simple thermodynamic analysis, the organic acid yield was increased by lowering the plasma–liquid reaction temperature using an ice bath to cool the reaction flask. The composition of the organic acids could be varied by changing the pH of the solution. Oxalate was formed in higher concentrations with increasing solution pH above the pK a of the radical species (CO 2 )˙ − . Below the pK a value, formate was the exclusive organic acid formed. The production of formate has a rather weak pH dependence but is enhanced slightly at a basic pH above 10. Furthermore, at basic pH, the effect of electrolyte concentration comes into play. Higher electrolyte concentrations, leading to shorter electrolyte Debye lengths, resulted in lowered organic acid yields. The highest yields of organic acids obtained in our system were 122 mg L −1 for oxalate and 77 mg L −1 for formate at an optimum 1 mM NaOH concentration in the starting solution. This work is a successful pioneering example of CO to organic acids conversion using non-thermal plasmas, which opens the pathway for a promising two-step conversion process of CO 2 to organic acids.

Sudagar, Alcina Johnson [Washington University in ↗
DOE OSTI2026

Multi-Fidelity Bayesian Optimization with Gaussian Processes for Double Shell Inertial Confinement Fusion Target Design

Reliable, secure access to energy is a major focus for national security efforts. One potential route to such energy is through fusion reactions in inertial confinement fusion (ICF) experiments. Such experiments are carried out at facilities such as the National Ignition Facility (NIF) in Livermore, California, where high powered lasers are used to compress a DT fuel-containing target to the necessary high temperature, high pressure conditions. These experiments are limited in number, which creates a heavy dependence on high fidelity predictive physics simulations and analysis performed “pre shot,” or before the experiment occurs. Many of these simulations in higher dimensions (2D and 3D) are computationally expensive, so finding optimal simulation-based designs presents its own challenges. In this work, we present our multi-fidelity Bayesian optimization with Gaussian processes (GPs) for ICF double shell targets, where a 1D surrogate model is used to help find a 2D surrogate model, enabling us to find optimal targets in the higher fidelity (2D), while saving computational cost.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Description of FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment

The urgency to deliver fusion power is growing now more than ever, with increasing pressure for both public programs and private companies to meet milestones timelines and overcome significant remaining technical challenges to ensure growth of a nascent fusion industry in time to meet rapidly growing clean energy demands. With incredible advancements in computation and years of investment in fusion model development and validation, integrated modeling is poised to fill a key role in accelerating the timeline to a fusion pilot plant (FPP). Future fusion pilot plants will operate in regimes far beyond current experience, and device design will rely on physics-based prediction and extrapolation. Many concepts will also rely on simulation to assess safety (shielding, tritium management, materials activation and lifetimes), economics and scalability before the decision to build. Importantly, integrated simulation can be used to reveal and solve the complexities of system integration that may otherwise not be apparent in physical components or models developed in isolation. New experimental test facilities that produce relevant conditions to validate and resolve key technical challenges for various subsystems (materials, blankets, fuel cycle, etc.) have been repeatedly called for by the fusion community but are not yet realized. Integrated modeling has an important role in identifying realistic load conditions (thermal, electromagnetic, plasma, neutron and photon loads, etc.) and defining the components and experiments for these test facilities in order to ensure meaningful validation that sufficiently reduces modeling uncertainties and technical risk for the full integrated reactor. The Fusion REactor Design and Assessment (FREDA) SciDAC project is building a component-based integrated modeling framework & data structure to enable self-consistent, multi-fidelity, iterative optimization workflows for the fusion reactor design process. FREDA aims to shorten the time to viable designs by providing a set of flexible workflows to support the various stages of the design process using an integrated model hierarchy, ranging from the simple analytic descriptions to the highest fidelity, theory-based plasma and engineering modeling developed by the fusion and fission communities. These tools are expected to be needed for timely support of FPP design in the milestone program and in the FIRE collaboratives. The plasma simulation backbone of FREDA is IPS-FASTRAN with newly developed coupled Core-Edge Pedestal-SOL (CESOL) workflows, which is being extended to the far-SOL region up to the plasma facing components. FREDA incorporates the FERMI engineering modeling suite and will enable self-consistent evaluation of the thermal shields, limiters, blanket, magnets, and other surrounding structures with predictions of temperatures, erosion, dpa, activation, tritium generation and transport, creep, corrosion, material degradation, etc. Parametric generation of 3D CAD enables rapid iteration of component geometry in response to plasma and loading specifications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Machine learning assisted prediction of tungsten heavy alloy plasma facing component performance for fusion energy applications

Tungsten and tungsten heavy alloys (WHAs), known for their remarkably high hardness, durability, and corrosion resistance, play a critical role in the thriving development of nuclear fusion reactors in recent years. However, the exploration in tungsten alloys for the nuclear-related applications has been limited by the difficulty of manufacturing and the complexity of experiments to reproduce the environment of nuclear reaction. Therefore, this project aims to utilize nanoscale simulation methods such as density functional theory (DFT) and molecular dynamics (MD) with the help of machine learning techniques to not only understand the mechanisms of tungsten alloys but also allow us to computationally predict their mechanical behaviors under extreme environments. One critical problem of the application of WHAs in nuclear reactors is the surface melting. In the current design of the SPARC reactor, the WHA, W97Ni2.1Fe0.9 or W97NiFe, is chosen to be the first wall components to confine the plasma where the particles are fiercely moving and colliding into each other to create nuclear fusion reaction. This process will generate extremely high heat flux onto these WHA tiles, leaving high surface temperature that could possibly melt the surface of the WHA tiles, As illustrated in Fig. 1(a). a laser experiment previously done illustrates that a rough surface damage would be made after the surface melting where the matrix area mainly composed of nickel and iron as shown in Fig. 1(b), will first melt and then leave vacancies between these tungsten grains. Unfortunately, these kinds of roughness on the first-wall components could be deadly to the plasma inside a Tokmak reactor because the heat that is supposed to dissipate at a designed ratio through the tiles may in turn be excessively absorbed and accumulated on any uneven area of the surface, which will eventually make the whole nuclear reaction fail. In this project, we will introduce a machine learning potential, Allegro, based on DFT calculation and then build a MD model for W-Ni-Fe alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Down-selection of Innovative Fusion Materials

The goal of this proposal is to develop and fundamentally understand the microstructure of refractory multi-component alloys (MCA) as fusion-relevant plasma facing and structural materials, a step to down-select innovative fusion materials prior to the process of advancing their technology readiness level (TRL). Developing materials is paramount to enable fusion as energy source since no existing material is capable of coping with such extreme conditions. We will aim at understanding the role of chemistry and microstructure in these complex multi-component alloys systematically comparing their performance with pure tungsten materials in terms of mechanical properties and manufacturability. Such understanding will open opportunities to optimize MCAs for fusion applications and has a potential of attracting industry partnership.

36 MATERIALS SCIENCE↗
DOE OSTI2026

NanoPSD: A software for automatic detection of Nano-Particle Shape Distribution in electron microscopy images

Accurate quantification of the size and morphology of nanoparticles from electron microscopy (EM) images is essential to understand growth mechanisms, surface reactivity, and functional behavior in nanoscale materials. Manual analysis remains slow, subjective, and difficult to reproduce in large datasets. We introduce NanoPSD (Nano-Particle Shape Distribution), an open-source and fully automated framework for quantitative particle detection and morphology analysis from EM images. NanoPSD integrates adaptive contrast enhancement, polarity-agnostic scale-bar detection, Optical Character Recognition (OCR)-based calibration, and classical segmentation via Otsu thresholding with morphological refinement. Particle contours are used to extract geometric descriptors, including equivalent circular diameter, aspect ratio, circularity, and solidity, enabling automated classification into spherical, rod-like, and aggregate morphologies. The framework supports both single-image and batch processing, generating publication-quality visualizations, LaTeX-ready tables, and structured comma-separated values (CSV) datasets. As a demonstration, we applied NanoPSD to plasma-synthesized nanoparticle samples diagnosed via transmission electron microscopy (TEM). The code produced statistically robust size and morphology distributions spanning a few to tens of nanometers with minimal user supervision. The pipeline demonstrates high reproducibility and scalability, processing large image collections with consistent calibration and output formatting. Its modular design enables seamless integration of future deep-learning-based segmentation models, providing a pathway toward intelligent, data-driven electron microscopy analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A MINi Powder INjector (MINPIN) for the SMART tokamak

Here, this article presents the design and performance characterization of a MINi Powder INjector (MINPIN) developed for boron wall conditioning (boronization) in the SMall Aspect Ratio Tokamak (SMART) at the University of Seville, Spain. SMART studies positive and negative triangularity plasmas within the low aspect ratio range of 1.4 < R/a < 3, with a major radius (R) of 0.40–0.60 m and a minor radius (a) of 0.20–0.33 m. MINPIN, in design, will gravitationally deliver boron (B) powder into the plasma, which ablates and transports the injected material. Mounted on the top of the vessel, the MINPIN will drop controlled amounts of powder using a piezoelectric blade driven by a signal generator that vibrates at a set frequency. The B will then be deposited in a layer on SMART’s stainless steel vacuum vessel walls, and this boronization process reduces the influx of intrinsic wall impurities, such as oxygen, carbon, nitrogen, and iron, which radiate power and cool the plasma. In the laboratory, we calibrated the drop rate for 1–10 mg/s, which will enable controlled boronization coating while achieving efficient powder ablation. We propose MINPIN’s operational scenarios based on the calibrated drop rate and estimated drop duration, assuming the distance from MINPIN to SMART’s plasmas.

Boron powder↗
DOE OSTI2025

Directed energy deposition of functionally graded V-4Cr-4Ti to Fe-9Cr transition for fusion power systems

This study proposes a graded structure via additive manufacturing for divertor and first wall blanket applications in fusion reactors. Materials were selected based on thermodynamic calculations to operate from 1100 °C at the plasma-facing level to 550 °C at the structural steel level. Conventional joining methods often lead to failures due to discrete reaction layers with significant mechanical property differences. Using laser beam-directed energy deposition (LB-DED), this study demonstrates the fabrication of a VCrTi-Gr91 steel functionally graded component through a novel process parameter optimization framework. A systematic approach included powder characterization, single-track depositions, and construction of printability maps. Near full-density specimens of each interlayer were additively manufactured, and a transition from V-based alloys to reduced activation ferritic martensitic steels was achieved. Computational material selection of interlayer alloys and thermodynamic/diffusion kinetics simulations prevented most interface incompatibilities. A brittle intermetallic formed at one interface, causing cracking, which was not predicted by current thermodynamic models. Transition alloy design approach was updated with a more recent database and a mitigation strategy has been proposed to eliminate the formation of deleterious intermetallic phases. Ultimately, LB-DED has proven effective for producing multi-material graded systems for fusion applications, with the demonstrated process parameter optimization framework applicable to various materials.

Additive manufacturing↗
DOE OSTI2025

NewLife Nuclear - An Environmentally and Economically Minded Solution for Fusion Energy Waste Handling

Energy demand is rising as a result of innovative and increasingly more energy intensive processes coming to fruition, particularly through the recent interest in the development of AI data centers as well as manufacturing with the push towards increasing domestic manufacturing interest. Fusion energy can provide virtually limitless energy to support this increase in energy demand. Fusion energy concepts, largely classified as magnetic fusion energy (MFE) and inertial fusion energy (IFE) are being pursued, each having unique challenges to overcome before the successful deployment of electricity to the grid. Achieving fusion ignition on the National Ignition Facility, first in December 2022, and eight times since, has demonstrated the scientific viability of the IFE approach. Meanwhile, MFE test stands continue to improve confinement times, making meaningful strides in progressing towards experimental scientific viability. In each of these approaches, an emphasis is placed on generating more power out of the system than what is required to power the system. An under-researched area applicable to both IFE and MFE is handling activated waste coming out of fusion energy systems, both in the course of normal daily operations, as well as in intermittent periods as structural materials may need to be replaced. In the context of an IFE plant system, commonly discussed plant designs suggest targets are ignited within a chamber at a rate of up to one million targets per day. Between each shot, the chamber housing the ignition event will clear a portion of the chamber – resulting in a mixture of vaporized target gas, target debris, and other materials being expelled from the chamber [source]. Additionally, IFE system concepts typically discuss the modularization of plant designs, which are expected to be replaced periodically as the components degrade over time. This would result in the irradiated chamber structure materials, likely metals and alloys, needing to be removed and safely stored. In MFE plant systems, while targets are not ignited at a repetition rate with the frequent chamber clearing as is expected in IFE plant systems, it is anticipated that portions of the confinement area interfacing with the hot plasma will need to be replaced periodically. In each system, without additional investment and research into alternative processing and recycling methods, the result is storing irradiated materials, and other elements in a safe containment area until they are no longer activated. – resulting in significant waste both economic and environmental.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Polymer-Derived Amorphous Aluminosilicate Nanomembranes for H 2 Purification

Aluminosilicate zeolite membranes with robust microporous crystalline structures are attractive for the molecular separation of H 2 from light gases, but their large-scale fabrication is complicated and costly, hindering their practical applications. Herein, we present polymer-derived amorphous aluminosilicate nanomembranes that combine the exceptional processability of polymers with the superior gas separation properties of aluminosilicates. Specifically, thin-film composite membranes comprising 150 nm polydimethylsiloxane were first treated with oxygen plasma to generate 10 nm polyorganosilica (POSi) on the surface, which were then subjected to few-cycle atomic layer deposition (ALD) using trimethylaluminum as a metal precursor and water vapor as a coreactant. This scalable two-step process yields few-nanometer amorphous aluminosilicates with strong size-sieving ability. For example, three-cycle ALD treatment of POSi increases H 2 /CO 2 selectivity from 39 to 200 and H 2 /CH 4 selectivity from 190 to 500, while decreasing H 2 permeance from 990 to 210 GPU at 150 °C, superior to the state-of-the-art membranes. In conclusion, rapid and scalable manufacturing of amorphous aluminosilicate nanolayers can also be of interest for catalysis and adsorption applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Formation of Organic Compounds Through Meteoritic Atmospheric Shock

This document is a Final Technical Report for DoE award DE-SC0023375 “Formation of Organic Compounds Through Meteoritic Atmospheric Shock”. The document includes a summary of topics studied, specific tasks completed, challenges, and results from the project. The main goal of this project was to investigate the production of organic molecules and/or complex inorganic precursor molecules in a plasma environment reminiscent of the environment surrounding meteoroids during atmospheric entries. The specific hypothesis tested in this project was that meteoroid ablation during the entry and the chemical reactions in the meteoroid plasma tail could have produced significant amounts of organics or precursor inorganics in the Early Earth’s atmosphere. Investigation of these processes is essential in understanding the origins of life on Earth and the search for life beyond our planet. This project was focused on a set of experiments conducted at the Utilizing the DIII-D tokamak in San Diego, CA. The experiments aimed to study the interaction of carbonaceous and silica materials (typically found in meteoroids) with mixtures of hot plasma gases (mimicking atmospheric entry conditions. The material samples and gas mixtures were selected to investigate the synthesis of the organic compound urea – a key ingredient in the origin of life – or one of its precursor, the complex inorganic compound ammonia.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

First look at neutron emission shape characteristics of ignition hotspots at the National Ignition Facility (invited)

The nuclear imaging system has been capturing neutron images of inertial confinement fusion (ICF) driven implosions for over a decade at the National Ignition Facility. This imaging system has evolved from one to three nearly orthogonal lines-of-sight, allowing for the study of three-dimensional shape characteristics of ignition shots. Limited-view tomography algorithms help visualize the burning hotspot in 3D and assess neutron source geometry using Legendre mode parameters. With its neutron, gamma-ray, and x-ray image reconstruction capabilities, NIS has provided critical insight into mechanisms that have limited implosion performance, such as fill tube diameter for ignition-type targets. This comprehensive diagnostic suite opens a window into the shape characteristics of ignition shots and how symmetry affects ICF implosion performance. In more recent ignition shots, neutron yields have visibly increased. Analyzing the shape and size of the reconstructed neutron source has shown an expansion of the burn volume, which is indicative of more efficient alpha heating during the implosion process.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Collaborative Research: Parametric Instabilities of Alfven Waves in Low‐beta Plasmas

Alfven waves are of fundamental importance in magnetized plasmas. This project aims to advance our understanding of the basic physics of the parametric instabilities of Alfven waves using advanced computer simulations. The results will have implications for important processes in the heliosphere involving Alfven waves, such as coronal heating and solar wind heating.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Final Technical Report - Rapid Surface Microanalysis using a Low Temperature Plasma

This project focused on improving our current understanding and scientific knowledge in the area of plasma-surface interactions and plasma assisted material synthesis related to advanced microelectronics and nanotechnology. Current challenges include: controlling the interaction of Low Temperature Plasma (LTP) with a single layer of atoms to manufacture integrated circuits, continued miniaturization of integrated circuits, LTP processing of material surfaces and thin films to enable industrial scale fabrication of advanced microelectronics, synthesis of new materials, nanomaterials, nanotubes, and complex materials, Technology developed in this subtopic is of value to either (i) enable scans of surfaces (~1 sq. cm area) using various microscopies (electron, optical, other) at high resolution (micron or sub-micron resolution) rapidly (hours or days rather than years to complete a high-resolution scan of such a large surface area), or (ii) enable scans of surfaces (~1 sq. cm area) using various microscopies (electron, optical, other) at relatively low resolution rapidly, then apply algorithms to select spots for micron-scale imaging. Sputtering occurs when particles of a solid material are ejected from its surface by energetic particles from a plasma. While the degradation of the solid material and the subsequent deposition of the ejected material onto vulnerable surfaces are the usual subjects of sputtering studies, plasma science has yet to be combined with sputtering to create new diagnostics devices and systems. Small changes in the design of the plasma discharge device make it possible to create broad plasma beams for rapid scanning or small plasma beams to obtain the distribution of ejected elements with micron resolution. In the high-resolution use, the ion flux is extracted from the gas-discharge plasma and focused by a spherical emission surface to micron sizes onto the target specimen, providing very local sputtering and local elemental analysis. We call this “self-focusing”. The radiation from the excited and ionized sputtered atoms is recorded by a spectrometer through a window and fiberglass cable and analyzed with standard software packages used for optical glow discharge spectroscopy. Computer simulations of beam formation were used to verify and optimize the designs to be tested. A prototype was designed, constructed, and used to start experiments of beam formation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Autonomous Aerosol and Plasma Co‐Jet Printing of Metallic Devices at Ambient Temperature

Abstract Additive manufacturing of metallic materials holds the potential to revolutionize the fabrication of functional devices unattainable via traditional methods. Despite recent advancements, printing metallic materials typically requires thermal processing at elevated temperatures to form dense structures with desired properties, which presents a major challenge for direct printing and integration with temperature‐sensitive materials. Herein, a unique co‐jet printing (CJP) method is reported integrating an aerosol jet and a non‐thermal, atmospheric pressure plasma jet to enable concurrent aerosol deposition of metal nanoparticle inks and in situ sintering at ambient temperature. A machine learning algorithm is integrated with the CJP to perform real‐time defect detection and autonomous correction, enhancing the yield of printed films with high electrical conductivity from 44% to 94%. Concurrent printing and sintering eliminate the need for post‐printing processing, reducing the overall manufacturing time by multiple folds depending on product size. CJP enables direct printing of functional devices on a variety of temperature‐sensitive materials including biological materials. Direct printing of hydration sensors on living plant leaves is demonstrated for long‐duration monitoring of hydration level in the plant. The versatile CJP method opens tremendous opportunities to harmoniously integrate abiotic and biotic materials for emerging applications in wearable/implantable devices and biohybrid systems.

Du, Yipu [Department of Aerospace and Mechanical E↗
DOE OSTI2025

An Evaluation of Actinide Reactivity with CO 2 , O 2 , and O 2 /He Gases using Inductively Coupled Plasma Tandem Mass Spectrometry: Application to Simultaneous Measurement of 241 Am/ 241 Pu Ratios in Unseparated Complex Matrices

Accurate actinide measurements are critical within the field of nuclear science. Traditional methods for actinide quantification require time-consuming sample processing prior to analysis. There is a need for rapid analytical techniques that still maintain a high degree of accuracy. In this work, actinide reactivity was assessed for multiple oxygen-containing reaction gases using quadrupole inductively coupled plasma tandem mass spectrometry (Q-ICP-MS/MS) to evaluate actinide analysis in complex sample matrices without analyte-matrix separation. A novel method was developed to measure 241 Am/ 241 Pu in complex sample matrices using O 2 /He reaction gas with no matrix removal or analyte pre-concentration. This inline method reduces matrix-derived polyatomic interferences that complicate traditional ICP-MS analyses by mass-shifting to 241 Am 16 O + and 241 Pu 16 O 2 + , allowing Am and Pu to be mass separated for simultaneous analysis. While mass shifting is efficient, a small portion of Am + (<1.3%) and Pu + (<1.4%) react to from AmO 2 + and PuO + , respectively. Therefore, a mass balance approach was used, in combination with reactivity determined from 242 Pu and 243 Am standard solutions, to correct for residual 241 PuO + and 241 AmO 2 + . The method was validated by measuring 241 Am/ 241 Pu in Pu isotope standards CRM-136 and CRM-137 (separated in March/April 1970 and February 2022, respectively) in both neat solutions and complex matrices containing diluted soil (NIST SRM 2711a, >1000 µg·g -1 ). Method detection limits of 15.9 and 9.6 fg·g -1 were determined for 241 Am and 241 Pu, respectively, and 241 Am/ 241 Pu ratios were measured with accuracies within <3.5%. In conclusion, this work presents the first direct analysis of 241 Am/ 241 Pu in unseparated complex matrices, advancing capabilities for rapid actinide measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Machine learning enhanced predictions of ICRF heating: Overcoming numerical limitations via data curation

In this work, we present the development of robust surrogate models for Ion Cyclotron Range of Frequencies (ICRF) and High-Harmonic Fast Wave (HHFW) heating predictions in fusion plasmas. Building upon our previous efforts to achieve real-time capable models, we identify the cause of the outliers found using TORIC in certain HHFW heating scenarios. The outliers are observed to be spurious ion Bernstein wave (IBW)-like modes caused by a wavelength control algorithm designed to address challenging scenarios with high perpendicular wavenumbers. The effect arises from the modulation in the perpendicular susceptibility, which can induce sign reversal and IBW-like propagation for scenarios featuring normalized ion Larmor radius λ i ≫ 1. We use TORIC with this algorithm disabled to generate a novel HHFW-NSTX database that is free of outliers. Surrogate models trained on this database, including Random Forest Regressor (RFR), Multi-Layer Perceptrons, and Gaussian Process Regressors (GPR), demonstrate the ability to accurately predict HHFW heating profiles, with regression scores of R 2 ∈[0.93−0.99]. Additionally we demonstrate that it is possible to generalize predictions beyond training data by the use of both RFR and GPR models, enabling the prediction of scenarios previously limited to the original model. GPR models also provide uncertainty quantification, offering insights into model confidence. This work introduces a comprehensive Verification, Validation, and Uncertainty Quantification methodology for surrogate modeling, applicable not only to ICRF heating but also to other RF heating challenges and fusion physics problems. Beyond accelerated inference, these models show effective extrapolation capabilities, providing an alternative for addressing numerical challenges.

Artificial neural networks↗
DOE OSTI2026

Adventures in Plasma Chemistry

Plasma chemistry is a remarkably diverse field that spans many areas of fundamental and applied science and industrial technology. Here, over more than a century of study and application, the field has grown in multiple directions and continues to redefine itself and expand its impact. Some promising new directions are identified in quantitative methods, material processing, and applications to living systems.

Graves, D. B. [Princeton Univ., NJ (United States)↗