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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Identification of functional non-coding variants associated with orofacial cleft

Oral facial cleft (OFC) comprises cleft lip with or without cleft palate (CL/P) or cleft palate only. Genome wide association studies (GWAS) of isolated OFC have identified common single nucleotide polymorphisms (SNPs) in many genomic loci where the presumed effector gene (for example, IRF6 in the 1q32 locus) is expressed in embryonic oral epithelium. To identify candidates for functional SNPs at eight such loci we conduct a massively parallel reporter assay in a fetal oral epithelial cell line, revealing SNPs with allele-specific effects on enhancer activity. We filter these SNPs against chromatin-mark evidence of enhancers and test a subset in traditional reporter assays, which support the candidacy of SNPs at loci containing FOXE1, IRF6, MAFB, TFAP2A, and TP63. For two SNPs near IRF6 and one near FOXE1, we engineer the genome of induced pluripotent stem cells, differentiate the cells into embryonic oral epithelium, and discover allele-specific effects on the levels of effector gene expression, and, in two cases, the binding affinity of transcription factors FOXE1 or ETS2. Conditional analyses of GWAS data suggest the two functional SNPs near IRF6 account for the majority of risk for CL/P at this locus. This study connects genetic variation associated with OFC to mechanisms of pathogenesis.

Kumari, Priyanka↗
DOE OSTI2024

Novel ceramic capacitors with ultrahigh energy density and efficiency (Final Technical Report)

Antiferroelectric ceramics are a special class of material that have shown great potential as the dielectric in electrical capacitors due to their high energy- and power-density. During each charge-discharge cycle, the ceramic undergoes transformation to a ferroelectric phase and resumes its antiferroelectric phase. The hysteresis associated with the transitions leads to a mediocre energy efficiency and service lifetime of antiferroelectric capacitors and, hence, their almost absence in commercial products. Under the support of this research project, we first formulated a universal lattice-compatibility theory that included electrostatic polarization energy along with elastic energy and thermal energy to understand the origin of the hysteresis in antiferroelectric oxides. Guided by this compatibility theory, we conducted high-throughput density functional theory (DFT) calculations to assess chemical modifiers and their effect on crystal structures of 400+ PbZrO 3 -based compositions. Down-selected compositions were experimentally validated for their suppressed hysteresis and higher energy efficiency. The verified low-hysteresis compositions were then expanded to an antiferroelectric ceramic library with nearly 500 new compositions (more than 1,500 samples) using high-throughput experiments involving ceramic synthesis and property screening. The large quantity of data generated (theory and experimental) in these tasks were processed by machine-learning techniques and identified trends were fed to the next iteration. In the end, we successfully discovered four compositions with near-zero hysteresis, yielding a world-record energy efficiency of 98.2% at an energy density of 3.0 J/cm 3 . Furthermore, our antiferroelectric ceramic capacitor reaches 79.5 million charge-discharge cycles lifetime, a factor of 80 enhancement over previous antiferroelectric ceramics with large hysteresis. These research accomplishments have not only met the milestones set in the SOPO, but also led to two patent filings, three journal publications (one of them was in Advanced Materials, impact factor 29.4), and nine oral presentations at various venues. Through the course of the project, three postdocs, four Ph.D. students, and one M.S. student were trained. In short, our project established a new methodology in searching next-generation functional ceramics on the fundamental side and discovered several high-efficiency antiferroelectric compositions for capacitors on the applied side. Once fabricated into the multilayer form for commercial applications, these ceramic capacitors can potentially enable the high temperature high power density DC-link capacitors that are critical for the next generation inverters in electric vehicles. The project also significantly contributed to the nation’s workforce development in the STEM fields.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Clustering of DESI galaxies split by thermal Sunyaev-Zeldovich effect

The thermal Sunyaev-Zeldovich (tSZ) effect is associated with galaxy clusters - extremely large and dense structures tracing the dark matter with a higher bias than isolated galaxies. We propose to use the tSZ data to separate galaxies from redshift surveys into distinct subpopulations corresponding to different densities and biases independently of the redshift survey systematics. Leveraging the information from different environments, as in density-split and density-marked clustering, is known to tighten the constraints on cosmological parameters, like $\Omega_m$, $\sigma_8$ and neutrino mass. We use data from the Dark Energy Spectroscopic Instrument (DESI) and the Atacama Cosmology Telescope (ACT) in their region of overlap to demonstrate informative tSZ splitting of Luminous Red Galaxies (LRGs). We discover a significant increase in the large-scale clustering of DESI LRGs corresponding to detections starting from 1-2 sigma in the ACT DR6 + Planck tSZ Compton-$y$ map, below the cluster candidate threshold (4 sigma). We also find that such galaxies have higher line-of-sight coordinate (and velocity) dispersions and a higher number of close neighbors than both the full sample and near-zero tSZ regions. We produce simple simulations of tSZ maps that are intrinsically consistent with galaxy catalogs and do not include systematic effects, and find a similar pattern of large-scale clustering enhancement with tSZ effect significance. Moreover, we observe that this relative bias pattern remains largely unchanged with variations in the galaxy-halo connection model in our simulations. This is promising for future cosmological inference from tSZ-split clustering with semi-analytical models. Thus, we demonstrate that valuable cosmological information is present in the lower signal-to-noise regions of the thermal Sunyaev-Zeldovich map, extending far beyond the individual cluster candidates.

Astronomy data analysis↗
DOE OSTI2025

Orbital inversion and emergent lattice dynamics in infinite layer CaCoO 2

The layered cobaltate CaCoO 2 exhibits a unique herringbone-like structure. Serving as a potential prototype for a new class of complex lattice patterns, we study the properties of CaCoO 2 using X-ray absorption spectroscopy (XAS) and resonant inelastic X-ray scattering (RIXS). Our results reveal a significant inter-plane hybridization between the Ca 4s- and Co 3d- orbitals, leading to an inversion of the textbook orbital occupation of a square planar geometry. Further, our RIXS data reveal a strong low energy mode, with anomalous intensity modulations as a function of momentum transfer close to a quasi-static response. These findings indicate that the newly discovered herringbone structure exhibited in CaCoO 2 may serve as a promising laboratory for the design of materials having strong electronic, orbital and lattice correlations.

Electronic properties and materials↗
DOE OSTI2025

Subharmonic Shapiro steps in depinning dynamics of a two-dimensional solid dusty plasma modulated by one-dimensional nonlinear deformed periodic substrates

Langevin dynamical simulations are performed to investigate the depinning dynamics of a two-dimensional (2D) solid dusty plasma, which is modulated by one-dimensional (1D) nonlinear deformed periodic substrates, and also driven by the combination of the DC and AC forces. As the DC driving force increases gradually, pronounced subharmonic and harmonic Shapiro steps are discovered under the combined modulation of the deformed substrate and the external AC drive. Here, these observed subharmonic and harmonic Shapiro steps are attributed to the dynamic mode locking. The data analysis results indicate that the nonlinear deformed substrate strongly influences these subharmonic Shapiro steps, which can be accurately diagnosed using the fraction of sixfold coordinated particles. Furthermore, the diagnostic of the kinetic temperature clearly indicates the difference between harmonic and subharmonic Shapiro steps, i.e., the particle motion is slightly less synchronized at subharmonic Shapiro steps, caused by the unstable locations of the deformed substrate.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Updating Critical Temperature Calculations for Several Secondary High Explosives

In designing experiments where high explosives (HEs) are heated, it is important to have an understanding of where thermal runaway may occur. This determination is often done by using the Frank-Kamenetskii (FK) equation. For several highly-studied HEs, the parameters necessary for FK calculations are typically referenced from decades-old literature, and more recent experimental data have shown that these values require adjustment. For example, some of the legacy parameters dangerously overpredict the critical temperature by tens of degrees relative to more recent observed values. Herein, we first summarize historical results and highlight the importance of insulation effects when estimating critical temperatures for small samples, which is especially relevant to small-scale aging, compatibility, and characterization experiments. Here, we then present updated FK parameters for several common secondary CHNO HEs like RDX, HMX, PETN, and TATB, as well as the first reported values for 2,6-Diamino-3,5-dinitropyrazine-1-oxide (LLM-105). Our updated parameters produce critical-temperature curves that are consistent with both mm-scale differentical scanning calorimetry (DSC) measurements and cm-scale data from the Lawrence Livermore National Laboratory one-dimensional time-to-explosion (ODTX) experiment. In analyzing the critical temperature versus sample size curves derived from the transcendental FK equation, we discovered that these curves are remarkably well described by a simple power-law function with a universal power of 0.142 and a HE-specific scaling factor.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Ribosome-inactivation by a class of widely distributed C-tail anchored membrane proteins

Ribosome hibernation is a commonly used strategy that protects ribosomes under unfavorable conditions and regulates developmental processes. Multiple ribosome-hibernation factors have been identified in all domains of life, but due to their structural diversity and the lack of a common inactivation mechanism, it is currently unknown how many different hibernation factors exist. Here, we show that the YqjD/ElaB/YgaM paralogs, initially discovered as membrane-bound ribosome binding proteins in E. coli, constitute an abundant class of ribosome-hibernating proteins, which are conserved across all proteobacteria and some other bacterial phyla. Our data demonstrate that they inhibit in vitro protein synthesis by interacting with the 50S ribosomal subunit. In vivo cross-linking combined with mass spectrometry revealed their specific interactions with proteins surrounding the ribosomal tunnel exit and even their penetration into the ribosomal tunnel. Thus, YqjD/ElaB/YgaM inhibit translation by blocking the ribosomal tunnel and thus mimic the activity of antimicrobial peptides and macrolide antibiotics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Nitrogen starvation causes lipid remodeling in Rhodotorula toruloides

Abstract Background The oleaginous yeast Rhodotorula toruloides is a promising chassis organism for the biomanufacturing of value-added bioproducts. It can accumulate lipids at a high fraction of biomass. However, metabolic engineering efforts in this organism have progressed at a slower pace than those in more extensively studied yeasts. Few studies have investigated the lipid accumulation phenotype exhibited by R. toruloides under nitrogen limitation conditions. Consequently, there have been only a few studies exploiting the lipid metabolism for higher product titers. Results We performed a multi-omic investigation of the lipid accumulation phenotype under nitrogen limitation. Specifically, we performed comparative transcriptomic and lipidomic analysis of the oleaginous yeast under nitrogen-sufficient and nitrogen deficient conditions. Clustering analysis of transcriptomic data was used to identify the growth phase where nitrogen-deficient cultures diverged from the baseline conditions. Independently, lipidomic data was used to identify that lipid fractions shifted from mostly phospholipids to mostly storage lipids under the nitrogen-deficient phenotype. Through an integrative lens of transcriptomic and lipidomic analysis, we discovered that R. toruloides undergoes lipid remodeling during nitrogen limitation, wherein the pool of phospholipids gets remodeled to mostly storage lipids. We identify specific mRNAs and pathways that are strongly correlated with an increase in lipid levels, thus identifying putative targets for engineering greater lipid accumulation in R. toruloides . One surprising pathway identified was related to inositol phosphate metabolism, suggesting further inquiry into its role in lipid accumulation. Conclusions Integrative analysis identified the specific biosynthetic pathways that are differentially regulated during lipid remodeling. This insight into the mechanisms of lipid accumulation can lead to the success of future metabolic engineering strategies for overproduction of oleochemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Discovering the Most Severe K-Point Failure Based on Reinforcement Learning: Preprint

Smart devices are essential to ensure the stability of the power grid and resilience to intermittent energy production. However, smart devices can also be the target of cyber adversaries that may exploit false data injection attacks (FDIAs) to induce unstable grid conditions. A practical consideration of FDIA mitigation approaches is addressed here: given a finite available budget, for which smart device should cyber-threat mitigation be deployed first? In this work, this question is answered by identifying the so-called most-sensitive devices, i.e., the devices that, if compromised, can let an adversary induce the most serious grid instabilities. The method proposed utilizes an adversarial reinforcement learning (RL) framework to identify the k-mostsensitive smart devices (here, smart inverters). The adversarial agent can tamper with the compromised inverters' active and reactive operating power setup points, with the goal of maximizing voltage deviations. Numerical results show that the proposed RL method finds the optimal attack scenarios for 1-point failure and the near-optimal solution for the 2-point case. Additionally, the proposed RL method achieves an 8.8 speed-up ratio in running time compared to the brute force method for the 2-point case.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A family portrait of lanmodulin selectivity for enhanced rare-earth separations

Proteins offer a molecular design space to create bespoke ligands for the separation of critical metals like rare earth elements (REs). However, data-intensive approaches to tune metalloprotein selectivity are constrained by the low-throughput nature of existing characterization methods. Here we invented an assay called ‘SpyTag-Catcher Immobilization of Lanmodulin for Assaying Metal-Binding Selectivity’ (SpyCI-LAMBS) to measure metalloprotein selectivity en masse. This 96-format workflow was used to study the selectivity of 621 lanmodulin (LanM) orthologs for 15 REs, revealing eight distinct selectivity profiles based on sequence-to-function analyses. We discovered >200 LanMs with stronger selectivity against low-value LaIII relative to the prototypical LanM. This includes a LanM that can perform a challenging one-stage separation of PrIII from LaIII with up to >99.9 mol% purity and 83% yield. SpyCI-LAMBS is a powerful tool that can rapidly collect high-fidelity selectivity data to inform metal ion separations and machine-learning-assisted metalloprotein design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

ReaxFF Reactive Force Field for Exploring Electronically Switchable Polarization in Zn 1– x Mg x O Ferroelectric Semiconductors

Cation misfit in traditional ferroelectric crystals offers a new material platform that can drive electronic components toward structural miniaturization and high-density integration, enabling deviation from von-Neumann architectures. Here, we explore ferroelectricity in Zn 1–x Mg x O, a nontraditional ferroelectric material with tunable properties. Using data from density-functional theory calculations, we have developed a ReaxFF reactive force field to explore the ferroelectric properties of Zn 1–x Mg x O and reveal the hysteresis behavior. We discover that ferroelectric switching can be observed at a critical thickness of 10 nm with a residual polarization of ~100 μC/cm 2 . Our analysis indicates that an increase in Mg-substitution correlates with a decrease in the coercive field. We also observe a strong temperature dependence of the coercive field in Zn 1–x Mg x O, with values decreasing as the temperature increases. Additionally, we find that the distribution of Mg atoms significantly impacts the coercive field, with a clustered distribution leading to a substantial increase. In particular, a decrease in coercive field values is observed when Mg atoms are randomly distributed, compared to uniform distribution. Furthermore, leveraging tunable hysteresis behavior offered by varied percentages and distribution of Mg-substitution provides valuable insights into the design of next-generation functional devices and will inspire further investigations.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Movement Models to Predict Low‐Altitude Flight of Soaring Birds Using Look‐Ahead Environmental Factors

Advances in fine-scale movement modeling of soaring birds can aid efforts to understand and resolve the impacts of anthropogenic activities on such birds. Soaring birds often rely on underlying terrain and low-altitude updrafts to govern their flights at rotor-swept altitudes (≤ 200 m above ground level), which puts them at risk of collision with wind turbines. We developed a data-driven Markov model at 1-s resolution that predicts the fine-scale flight behavior of golden eagles (Aquila chrysaetos) as a function of ecological covariates at the current location as well as those within an eagle's line of sight. We only considered ecological covariates that are readily available in real-time (ground elevation and wind conditions). Latent factors (age, sex, species, behavioral intent, migratory status) were intentionally left out of the model. We calibrated the model using golden eagle telemetry data collected in two different ecoregions of the United States. Given a starting location, the calibrated model simulates multiple stochastic 3D paths to produce a time-explicit and spatially explicit risk map of turbine collisions. We discovered an empirical relation between the rate of change of heading and the orographic updraft conditions within an eagle's line of sight. Our model performed most effectively when predicting predominantly-soaring flights at rotor-swept altitudes during wind conditions in which turbines are likely to be operational. The calibrated model could be used in concert with automated eagle detection and turbine curtailment technologies. Specifically, once an eagle is detected by those systems, our model could then provide accurate predictions of turbines the eagle is likely to interact with in the near term.

17 WIND ENERGY↗
DOE OSTI2026

Westcott g factors extended to arbitrary neutron energy spectra

Westcott 𝑔 factors are used in Neutron Activation Analysis (NAA) and Prompt Gamma-ray Activation Analysis (PGAA) to evaluate the impact of non-1∕𝑣 behavior in the neutron-capture cross sections of certain nuclei on activation product yields. This non-1∕𝑣 behavior arises from the presence of neutron resonances in the neutron- capture cross sections that overlap with the source neutron spectrum at low (< 5 eV) energies. Historically, Westcott 𝑔 factors that have been cataloged for NAA and PGAA applications are the result of calculations that assume a Maxwellian neutron flux distribution with a given temperature. In this work, we use this approach with updated neutron-capture cross sections from the Evaluated Nuclear Data File, version VIII.1 (ENDF/B-VIII.1) to tabulate Westcott 𝑔 factor values for a broad range of Maxwellian distribution temperatures, comparing the results against currently-available 𝑔 factors from International Atomic Energy Agency tables and other sources. Here, it was discovered during this analysis that the use of guided thermal and cold-neutron beams at certain facilities necessitates an approach for evaluating Westcott 𝑔 factors based on arbitrary non-Maxwellian spectra. In this paper, we present an approach for calculating 𝑔 factors with user-specified neutron spectra, and we demonstrate these methods to obtain Westcott 𝑔-factors for guided- and cold-neutron beams at the Budapest Research Reactor and the Forschungsreaktor München II reactor. As part of this work, open-source software has been developed that can be used to perform these calculations for applications in PGAA and NAA experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

OpenStudio®-MCP [SWR-26-035]

OpenStudio®-MCP is a Model Context Protocol (MCP) server that lets AI assistants perform building energy modeling through natural language. Rather than requiring users to learn the OpenStudio® SDK, EnergyPlus® scripting, or Ruby/Python automation, the server translates conversational requests into sequences of tool calls that create models, design HVAC systems, run simulations, and extract results — all within a single chat session. The server's 124 tools are organized into a skills architecture where each skill encapsulates a domain of building energy modeling (envelope, HVAC, loads, weather, simulation, results) behind typed, LLM-friendly interfaces. High-leverage operations like applying ASHRAE 90.1 baseline systems or generating standards-compliant typical buildings are exposed as single tool calls that internally wire dozens of OpenStudio® objects. Bundled measures from ComStock™ and Openstudio® -common-measures-gem are wrapped with dedicated tools and typed arguments rather than exposed through a generic measure interface, so AI models get consistent, error-resistant recipes without needing to discover measure arguments at runtime. A key design decision is structured results extraction: six SQL-based tools return surgical ~300–1,000 token responses (end-use breakdowns, envelope summaries, HVAC sizing, timeseries data) instead of requiring the AI to parse ~100K-token raw HTML reports, making iterative design exploration practical within context window limits. The codebase is designed as a reference implementation — explicit, well-commented, and modular — so that other simulation engines (EnergyPlus® standalone, TRNSYS, DOE-2) can use it as a template for building their own MCP servers.

Ball, Brian [National Laboratory of the Rockies (N↗
DOE OSTI2025

Tetraquarks in the Born-Oppenheimer approximation

The conventional loosely bound molecule interpretation of the X(3872) is not compatible with the recent LHCb experimental measurement of the ratio of branching fractions $\mathcal{R}$ = Br(X → ψ′γ)/Br(X → ψγ). We systematically determine the entire tetraquark spectrum for J = 0, 1, 2 and refine the calculation of $\mathcal{R}$ in an improved Born-Oppenheimer description of the X(3872) compact tetraquark. This refinement yields a significantly better agreement with experimental data on $\mathcal{R}$ and on the spectroscopy of the states themselves. Extending the diquark-antidiquark paradigm to encompass tetraquarks that are linear super-positions of open charm singlets and color octets, we discover that these exotic resonances manifest as compact shallow bound states of quarks in color force potentials.

Effective Field Theories of QCD↗
DOE OSTI2026

A New Way to Discover Strong Gravitational Lenses: Pairwise Spectroscopic Search from DESI DR1

We present a new method to search for strong gravitational-lensing systems by pairing spectra that are close together on the sky in a spectroscopic survey. We visually inspect 26,621 spectra in the Dark Energy Spectroscopic Instrument (DESI) Data Release 1 that are selected in this way. We further inspect the 11,848 images corresponding to these spectra in the DESI Legacy Imaging Surveys Data Release 10, and obtain 2046 conventional strong gravitational lens candidates, of which 1906 are new. This constitutes the largest sample of lens candidates identified to date in spectroscopic data. Besides the conventional candidates, we identify a new class of systems that we term “dimple lenses.” These systems have a low-mass foreground galaxy as a lens, typically smaller in angular extent and fainter compared with the lensed background source galaxy, producing subtle surface brightness indentations in the latter. We report the discovery of 318 of these “dimple lens” candidates. We suspect that these represent dwarf galaxy lensing. With follow-up observations, they could offer a new avenue to test the cold dark matter model by probing their mass profiles, stellar mass–halo mass relation, and halo mass function for M Halo ≲ 10 13 M ⊙ . Thus, in total, we report 2164 new lens candidates. Our method demonstrates the power of pairwise spectroscopic analysis and provides a pathway complementary to imaging-based and single-spectrum lens searches.

Hsu, Yuan-Ming 許淵明 [National Taiwan University, Ta↗
DOE OSTI2025

Structural constraint integration in a generative model for the discovery of quantum materials

Billions of organic molecules have been computationally generated, yet functional inorganic materials remain scarce due to limited data and structural complexity. Here, in this work, we introduce Structural Constraint Integration in a GENerative model (SCIGEN), a framework that enforces geometric constraints, such as honeycomb and kagome lattices, within diffusion-based generative models to discover stable quantum materials candidates. SCIGEN enables conditional sampling from the original distribution, preserving output validity while guiding structural motifs. This approach generates ten million inorganic compounds with Archimedean and Lieb lattices, over 10% of which pass multistage stability screening. High-throughput density functional theory calculations on 26,000 candidates shows over 95% convergence and 53% structural stability. A graph neural network classifier detects magnetic ordering in 41% of relaxed structures. Furthermore, we synthesize and characterize two predicted materials, TiPd 0.22 Bi 0.88 and Ti 0.5 Pd 1.5 Sb, which display paramagnetic and diamagnetic behaviour, respectively. Our results indicate that SCIGEN provides a scalable path for generating quantum materials guided by lattice geometry.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Feasibility of fusion plasma burn control via real-time, sub-divertor neutral gas isotopic and compositional analysis

The ability to provide fusion burn control without requiring physical access through the first wall and fuel breeding blankets, would be vital for any future, magnetically confined fusion power reactor. A multi-sensor, fusion fuel cycle exhaust, neutral gas analysis system on JET, capable of delivering real time data, and accessing only the sub-divertor region, provides an excellent example of such capability. Optimized for and operated during the deuterium–tritium experimental campaigns 2 and 3 (DTE2, DTE3), it is proving valuable for planning to explore fusion reactor burn control in ITER with a comparable diagnostic system called the Diagnostic Residual Gas Analyzer (DRGA). This paper aims to show feasibility of developing model-based controllers for ITER and next generation, reactor-relevant devices, by building both on the empirical experience in JET-DTE2, and on the already emerging experience on developing such models specifically for ITER. The paper begins with a specific use-case from JET-DTE2, pertaining to the observed sensitivity of the fusion neutron yield on the concentration of isotopic helium-3 ( 3 He), with data from one of the high-performance DT shots exhibited with emphasis on the 3 He measurement via the sub-divertor. Then, a first model is developed and then explored with simulations that aim to discover how well the controllers in the model react to either insufficient levels of 3 He or excessive levels of 3 He. The simulations then explore potential impact from a delay in the measurement (or the response) that would be comparable to the ∼1 s, conductance limited response for the ITER DRGA system, currently in its final design. The simulations show that control is feasible, and that its effectiveness is not significantly impacted by such delay.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗