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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

State of the art, gaps, and prospects in fusion materials theory and modelling

Advancing the theory and simulation of materials for fusion applications remains a key component of global roadmaps aimed at delivering much-needed fusion power. Especially as the drive for commercial application increases, prototypes must be designed against radiation damage before the relevant experimental data can be collected and cost reductions that are possible by testing materials in silico become even more important. Here, we summarise the state of the art as it emerged during the 7 th Fusion Materials Theory & Modelling Workshop that took place in 2024, with the aim to highlight present gaps and future directions for the fusion materials modelling community. Of particular interest were the effects of transmutations, chemical complexity with the development of novel alloys and interatomic potentials, advancements in modelling high-dose microstructures, comparison with experimental data and multiscale models for structural assessment relying on high-performance computing and virtual reality.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Structure and function of photosystem I–[FeFe] hydrogenase protein fusions: An all-atom molecular dynamics study

All-atom molecular dynamics (MD) simulation was used to study the solution dynamics and protein protein interactions of protein fusions of photosystem I (PSI) from Thermosynechococcus elongatus and an [FeFe]-hydrogenase (FeFe H 2 ase) from Clostridium pasteurianum , a unique complex capable of photocatalytic hydrogen production. This study involved fusions of these two proteins via dithiol linkers of different length including decanedithiol, octanedithiol, and hexanedithiol, for which experimental data had previously been obtained. Evaluation of root-mean-squared deviations (RMSDs) relative to the respective crystal structures of PSI and the FeFe H 2 ase shows that these fusion complexes approach stable equilibrium conformations during the MD simulations. Investigating protein mobility via root-mean-squared fluctuations (RMSFs) reveals that tethering via the shortest hexanedithiol linker results in increased atomic fluctuations of both PSI and the hydrogenase in these fusion complexes. Furthermore, evaluation of the inter- and intraprotein electron transfer distances in these fusion complexes indicates that the structural changes in the FeFe H 2 ase arising from ligation to PSI via the shortest hexanedithiol linker may hinder electron transport in the hydrogenase, thus providing a molecular level explanation for the observation that the medium-length octanedithiol linker gives the highest hydrogen production rate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Search for the Higgs boson in lepton, tau and jets final states

We present a search for the standard model Higgs boson in final states with an electron or muon and a hadronically decaying tau lepton in association with two or more jets using 9.7 fb –1 of Run II Fermilab Tevatron Collider data collected with the D0 detector. The analysis is sensitive to Higgs boson production via gluon fusion, associated vector boson production, and vector boson fusion, followed by the Higgs boson decay to tau lepton pairs or to W boson pairs. The ratios of 95% C.L. upper limits on the cross section times branching ratio to those predicted by the standard model are obtained for orthogonal subsamples that are enriched in either H → ττ decays or H → WW decays, and for the combination of these subsample limits. As a result, the observed and expected limit ratios for the combined subsample at a Higgs boson mass of 125 GeV are 11.3 and 9.0, respectively.

experiment-HEP↗
DOE OSTI2026

Separation of Hydrogen Using Pd/Ag Membranes: Experimental and Modeling Results with Potential Application to Direct Internal Recycle

Implementation of fusion energy requires processing the deuterium-tritium (D-T) mixture used to fuel the reaction, and separation of hydrogen isotopes from other gases is imperative. Specifically, the separation of hydrogen isotopes from helium is a matter of importance to the fusion fuel cycle community. Initial testing with a palladium-silver (Pd-Ag) membrane indicates that even moderate vacuum (~100 torr permeate pressure) can provide a high degree of separation (>90%) at a high ratio of H 2 to He. Given the presence of He in many fusion systems, a high technology readiness level (TRL) for Q 2 /He (where Q represents any isotope of hydrogen) separations is needed. This study demonstrates the efficacy of H 2 removal from He via permeation and potential applications for direct internal recycle. Modeling will accompany the experimental campaign to generate a predictive capability and quantify the separation performance. Modeling from previous hydrogen permeation studies has demonstrated that the typical Sieverts’ law fails to predict the measured permeation rates at high hydrogen fluxes. Existing models are being refined to integrate the effects of surface phenomena into permeation predictions, which have been expanded to account for mixtures with large ranges of Q 2 concentrations. These data will improve the TRL of permeators as a separation technology for the fusion fuel cycle.

08 HYDROGEN↗
DOE OSTI2019

Ab initio predictions for polarized deuterium-tritium thermonuclear fusion

The fusion of deuterium (D) with tritium (T) is the most promising of the reactions that could power thermonuclear reactors of the future. It may lead to even more efficient energy generation if obtained in a polarized state, that is with the spin of the reactants aligned. Here in this paper, we report first-principles predictions of the polarized DT fusion using nuclear forces from effective field theory. By employing the ab initio no-core shell model with continuum reaction method to solve the quantum mechanical five-nucleon problem, we accurately determine the enhanced fusion rate and angular distribution of the emitted neutron and 4 He. Our calculations demonstrate in detail the small contribution of anisotropies, placing on a firmer footing the understanding of the rate of DT fusion in a polarized plasma. In the future, analogous calculations could be used to obtain accurate values for other, more uncertain thermonuclear reaction data critical to nuclear science applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Rare Higgs Processes at CMS and Precision Timing Detector Studies for HL-LHC CMS Upgrade

This thesis describes the search for two rare Higgs processes. The first analysis describes the CMS Run 2 search for $H$ $\rightarrow$ $\mu$$\mu$ decays, with 137.3 fb$^{-1}$ of data at $\sqrt{s}$ = 13 TeV. The analysis targeted four different Higgs production modes: the gluon fusion (ggH), the vector boson fusion (VBF), the Higgs-strahlung process (VH), and the production in association with a pair of top quarks (ttH). Each category used a dedicated machine learning based classifier to separate the signal from the background processes. A combined fit from all these categories saw a slight excess in the data corresponding to 3.0 standard deviations at $M$$_{H}$ = 125.38 GeV, and gave the first evidence for the Higgs boson decay to second-generation fermions. The best-fit signal strength and the corresponding 68% CL interval was found to be +0.17?????? = 1.19 $_{-0.39}^{+0.41}$ (stat)$_{-0.16}^{+0.17}$(syst) at $M$$_{H}$ = 125.38 GeV. The second analysis describes the CMS Run 2 search for 𝐻𝐻 → 𝑏𝑏𝑏𝑏 with highly boosted Higgs bosons. This analysis used a dedicated jet identification algorithm based on graph neural networks (ParticleNet) to identify boosted H→ bb jets. This search targeted the gluon fusion and the vector boson fusion HH production modes, and put constraints on the allowed values of the various Higgs couplings as: 𝜅𝜆 ∈ [−9.9, 16.9] when 𝜅𝑉 = 1, 𝜅2𝑉 = 1; 𝜅𝑉 ∈ [−1.17, −0.79] ∪ [0.81, 1.18] when 𝜅𝜆 = 1, 𝜅2𝑉 = 1; 𝜅2𝑉 ∈ [0.62, 1.41] when 𝜅𝜆 = 1, 𝜅𝑉 = 1. A scenario with 𝜅2𝑉 = 0 was excluded with a significance of 6.3 standard deviations for the first time, when other H couplings are fixed to their SM values. The combined observed (expected) 95% upper limit on the HH production cross section was found to be 9.9 (5.1) × SM. Finally, this thesis also discusses the planned MIP Timing Detector (MTD) upgrade for CMS at the HL-LHC. The MTD will be a time-of-flight (TOF) detector, designed to provide a precision timing information for charged particles using SiPMs + LYSO scintillating crystals, with a time resolution of ∼30 ps. This thesis describes several R&D tests that have been performed for characterizing the sensor properties (time resolution, light yield, etc.) and optimizing the sensor design geometry. This thesis also contains a description of mock test setups for cooling the sensors, since it is known to be an effective way of mitigating the increased dark current rates in the sensors due to radiation damage.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Search for the Standard Model Higgs boson produced by vector-boson fusion and decaying to bottom quarks in $ \sqrt{s}=8 $ TeV pp collisions with the ATLAS detector

A search with the ATLAS detector is presented for the Standard Model Higgs boson produced by vector-boson fusion and decaying to a pair of bottom quarks, using 20.2 fb -1 of LHC proton-proton collision data at √s=8 TeV. The signal is searched for as a resonance in the invariant mass distribution of a pair of jets containing b-hadrons in vector-boson-fusion candidate events. The yield is measured to be -0.8 ± 2.3 times the Standard Model cross-section for a Higgs boson mass of 125 GeV. The upper limit on the cross-section times the branching ratio is found to be 4.4 times the Standard Model cross-section at the 95% confidence level, consistent with the expected limit value of 5.4 (5.7) in the background-only (Standard Model production) hypothesis.[Figure not available: see fulltext.]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

The next-generation magnetic recoil spectrometer (MRSnext) on OMEGA and NIF for diagnosing ion temperature, yield, areal density, and alpha heating

The next-generation magnetic recoil spectrometer (MRSnext) is being designed to replace the current MRS at the National Ignition Facility and OMEGA for measurements of the neutron spectrum from an inertial confinement fusion implosion. The MRSnext will provide a far-superior performance and faster data turnaround than the current MRS systems, i.e., a 2× and 6× improvement in energy resolution at the NIF and OMEGA, respectively, and 20× improvement in data turnaround time. The substantially improved performance of the MRSnext is enabled by using electromagnets that provide a short focal plane (12–16 cm) and unprecedented flexibility for a wide range of applications. In addition to being able to measure neutron yield, apparent ion temperature, areal density, and plasma-flow velocity over a wide range of yields, the NIF MRSnext will be able to directly, uniquely assess the alpha heating of the fuel ions through measurements of the alpha knock-on tail in the neutron spectrum. The goal is to implement a radiation-hard electronic detection system capable of providing rapid data acquisition and analysis. The development of the MRSnext will also set the foundation for the more advanced, time-resolving MRSt and serve as a testbed for its implementation on the NIF.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Mutation L232H Promotes Chromophore Maturation of EGFP-Based Fluorescent Fusion Proteins

The L232H mutant of the enhanced green fluorescent protein (EGFP) was expressed and crystallized. An X-ray diffraction data set was collected from the crystals to 1.53 Å resolution. An analysis of the three-dimensional structure revealed a stacking interaction between the amino-acid residues Н78 and Н232, which contributes to the fastening of the C-terminal region of the protein in the vicinity of the chromophore and influences chromophore maturation of hybrid fluorescent proteins produced by fusion of the target proteins with the C-terminus of EGFP. This hypothesis was experimentally confirmed by investigating chromophore maturation of the hybrid proteins fused to the N- and C-termini of EGFP and EGFP-L232H.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

How does ion temperature gradient turbulence depend on magnetic geometry? Insights from data and machine learning

Magnetic geometry has a significant effect on the level of turbulent transport in fusion plasmas. Here, we model and analyse this dependence using multiple machine learning methods and a dataset of >200 000 nonlinear gyrokinetic simulations of ion-temperature-gradient turbulence in diverse non-axisymmetric geometries. The dataset is generated using a large collection of both optimised and randomly generated stellarator equilibria. At fixed gradients and other input parameters, the turbulent heat flux varies between geometries by several orders of magnitude. Trends are apparent among the configurations with particularly high or particularly low heat flux. Regression and classification techniques from machine learning are then applied to extract patterns in the dataset. Due to a symmetry of the gyrokinetic equation, the heat flux and regressions thereof should be invariant to translations of the raw features in the parallel coordinate, similar to translation invariance in computer vision applications. Multiple regression models including convolutional neural networks (CNNs) and decision trees can achieve reasonable predictive power for the heat flux in held-out test configurations, with highest accuracy for the CNNs. Using Spearman correlation, sequential feature selection and Shapley values to measure feature importance, it is consistently found that the most important geometric lever on the heat flux is the flux surface compression in regions of bad curvature. The second most important geometric feature relates to the magnitude of geodesic curvature. These two features align remarkably with surrogates that have been proposed based on theory, while the methods here allow a natural extension to more features for increased accuracy. The dataset, released with this publication, may also be used to test other proposed surrogates, and we find that many previously published proxies do correlate well with both the heat flux and stability boundary.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Implementation of a High-Speed Multichannel Data Acquisition System for Magnetic Diagnostics and Plasma Centroid Position Control in ISTTOK

In tokamak and other fusion devices, magnetic control is the main tool that allows to regulate the plasma current, position and shape; it is in charge of actuating the desired plasma current waveform, steering the plasma position to a given set point and maintain the plasma shape close to a prescribed plasma equilibrium. This work describes the application of several physics concepts and computational tools in order to obtain a novel optimal controller for the plasma centroid position, which has been implemented and tested in the real-time plasma control system at the ISTTOK tokamak. A key point for the development of the new control system was the installation of a recently upgraded hardware, that numerically integrates in real-time the magnetic probes signals.

poloidal field coils↗
DOE OSTI2021

The data-driven future of high-energy-density physics

High-energy-density physics is the field of physics concerned with studying matter at extremely high temperatures and densities. Such conditions produce highly nonlinear plasmas, in which several phenomena that can normally be treated independently of one another become strongly coupled. The study of these plasmas is important for our understanding of astrophysics, nuclear fusion and fundamental physics—however, the nonlinearities and strong couplings present in these extreme physical systems makes them very difficult to understand theoretically or to optimize experimentally. Here we argue that machine learning models and data-driven methods are in the process of reshaping our exploration of these extreme systems that have hitherto proved far too nonlinear for human researchers. Furthermore, from a fundamental perspective, our understanding can be improved by the way in which machine learning models can rapidly discover complex interactions in large datasets. From a practical point of view, the newest generation of extreme physics facilities can perform experiments multiple times a second (as opposed to approximately daily), thus moving away from human-based control towards automatic control based on real-time interpretation of diagnostic data and updates of the physics model. To make the most of these emerging opportunities, we suggest proposals for the community in terms of research design, training, best practice and support for synthetic diagnostics and data analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Satellite Earth observation data to identify climate and anthropogenic pressures on Bucharest periurban forests

Satellite Earth observation data in the visible and near-infrared (VNIR) wavelengths represent a useful source of information for forest systems monitoring through derived biogeophysical parameters (vegetation index, leaf area index, canopy cover, fraction of absorbed photosynthetically active radiation, chlorophyll content, net primary production, canopy water stress, etc.). Use of satellite remote sensing data to assess forest spatio-temporal changes due to climatic or anthropogenic stressors is an excellent example of the value of multispectral and multitemporal observations. Fusion technique was applied to time-series multispectral and multitemporal satellite imagery (NOAA AVHRR, MODIS Terra/Aqua, Landsat ETM and IKONOS satellite data) for periurban forest areas Cernica-Branesti, placed in the neighboring of Bucharest town, Romania, over 2002-2014 period.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Exploring the influence of transfer channels on fusion reactions: The case of 40 Ca + 58,64 Ni

Fusion cross sections have been measured in the 40 Ca + 58 Ni and 40 Ca + 64 Ni systems at beam energies ranging from E lab = 104.75 MeV to 153.5 MeV using the Laboratori Nazionali di Legnaro electrostatic deflector. Distributions of barriers have been extracted from the experimental data. Preliminary coupled channel calculations were performed and hints of effects of neutron transfers on the fusion below the barrier in the 40 Ca + 64 Ni are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Fabrication of neutron absorbing metal hydride entrained ceramic matrix shield composites

With significant improvement in High Temperature Superconductors (HTS), several projects are adopting HTS technology for fusion power systems. Compact HTS tokamaks offer potential advantages including lower plant costs, enhanced plasma control, and ultimately lower cost of electricity. However, as compact reactors have a reduced radial build to accommodate shielding, HTS degradation due to radiation damage or heating is a significant and potentially design limiting issue. Shielding must mitigate threats to the superconducting coils: neutron cascade damage, heat deposition and potentially organic insulator damage due x-rays. Unfortunately, there are currently no hi-performance shielding materials to enable the potential performance enhancement offered by HTS. In this work, we present a manufacturing method to fabricate a new class of composite shields that are high performance, high operating temperature, and simultaneously neutron absorbing and neutron moderating. The composite design consists of an entrained metal-hydride phase within a radiation stable MgO ceramic host matrix. We discuss the fabrication, characterization, and thermophysical performance data for a series of down-selected composite materials inspired by future fusion core designs and their operational performance metrics. To our knowledge these materials represent the first ceramic composite shield materials containing significant metal hydrides.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Hybrid Simulation of Low Temperature Plasmas: A Brief Tutorial

Modeling and simulation of low temperature plasmas is widely accepted as a useful tool from both physics and plasma reactor design points of view. Of the modeling approaches, hybrid models strive to combine the predictability of kinetic models with the lower computational burden of fluid models. This work presents a brief tutorial of hybrid plasma modeling and representative simulation results using hybrid models. Whenever possible, these results are compared to kinetic and/or fluid simulations as well as experimental data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Search for supersymmetry using vector boson fusion signatures and missing transverse momentum in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

This paper presents a search for supersymmetric particles in models with highly compressed mass spectra, in events consistent with being produced through vector boson fusion. The search uses 140 fb −1 of proton-proton collision data at $\sqrt{s}$ = 13 TeV collected by the ATLAS experiment at the Large Hadron Collider. Events containing at least two jets with a large gap in pseudorapidity, large missing transverse momentum, and no reconstructed leptons are selected. A boosted decision tree is used to separate events consistent with the production of supersymmetric particles from those due to Standard Model backgrounds. The data are found to be consistent with Standard Model predictions. The results are interpreted using simplified models of R-parity-conserving supersymmetry in which the lightest supersymmetric partner is a bino-like neutralino with a mass similar to that of the lightest chargino and second-to-lightest neutralino, both of which are wino-like. Lower limits at 95% confidence level on the masses of next-to-lightest supersymmetric partners in this simplified model are established between 117 and 120 GeV when the lightest supersymmetric partners are within 1 GeV in mass.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Feature extraction for subtle anomaly detection using semi-supervised learning

The demand for automated and effective monitoring techniques has soared with the increased digitization of industrial monitoring systems. State-of-the-art machine learning methods are effectively detecting abrupt changes in system states. However, these methods lack comparable maturity in detecting subtle changes that may be signs of incipient faults. This manuscript argues that the current anomaly detection methods can be enhanced by exploring weak patterns to enable subtle variation detection. Specifically, the concept of semi-supervised learning is employed, with labels representing knowledge about some anomalous conditions of a system. The basic idea is to extract a candidate set of weak patterns discarded by state-of-the-art baselining algorithms. With few labeled anomalous data, the algorithm selects the weak patterns and allows for their possible fusion using the highest sensitivity to the labeled anomalies. Here, the method’s applicability is demonstrated using a representative pressurized water reactor (PWR) model simulated by Dymola.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗