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Balmer emission measurements in JET-ILW hydrogen, deuterium, tritium and deuterium-tritium low-confinement mode plasmas

Measurements of Balmer-alpha (B-α) and Balmer-gamma (B-γ), where B = H, D, or T isotopes of hydrogen, emission across the low-field side (LFS) divertor in JET ITER-like Wall (ILW), low-confinement mode (L-mode) plasma indicate that the divertor plasma was more strongly detached in deuterium, tritium and deuterium–tritium than in hydrogen plasmas. These measurements are consistent with the lower degree of detachment in hydrogen versus tritium plasmas inferred from Langmuir probes (Groth et al., 2023). The ratio of B-γ to B-α is a suitable indicator of high density/low temperature conditions because B-α emission is dominated by electron impact excitation with a small electron–ion recombination component regardless of electron temperature and density (for conditions in tokamak plasmas) whilst for B-γ the recombination component increases and the excitation component decreases as the electron temperature decreases and the electron density increases. Within the uncertainty of the measurements, the electron density at the low-field side separatrix and the power crossing the separatrix are similar to permit these comparisons. The B-©/B-α ratio is well correlated with the onset of detachment as measured by Langmuir probes (McCracken et al., 1998; Groth et al., 2023). The ratios of B-γ and B-α varied between 0.005 and 0.035 for low-recycling, high-recycling and partially detached conditions, and were 60–70 % higher in partially detached hydrogen than in tritium plasmas. In contrast, the difference between deuterium, tritium and 40–60 % deuterium–tritium is within 10 % and thus within the uncertainties of the measurements. Profiles of the B-α and B-γ emission was measured with two filtered CCDs connected to the visible lost light leg of JET’s mirror link spectroscopy system (Meigs et al., 2010; Lomanowski et al., 2014). Spatially (radial) narrower B-α profiles were measured with increasing isotope mass, while similarly broadened B-γ profiles were measured.

Balmer↗

Expanded method for the determination of burnup in nuclear fuels using multiple neodymium isotopes

Established methods for the determination of burnup in nuclear fuels commonly rely on the measurement of 148Nd in the spent fuel in concert with known fission product yields to determine the atom percent of fissions in the fuel. This isotope of neodymium is used for various reasons, including chemical and radioactive stability, ease of measurement, and low rates of formation and destruction due to neutron flux apart from fission. However, careful calculation of effective cumulative fission yields and correction factors for (n,γ) capture reactions allows for additional stable and long-lived isotopes of neodymium to be used to provide additional independent measurements of burnup, reducing statistical uncertainty. This method was developed and successfully applied to measure the burnup of compacts from the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program. The mean burnup measured using 143Nd, 145Nd, 146Nd, 148Nd, and 150Nd was statistically observed to be the same as that measured using 148Nd alone, but the statistical uncertainty in the measurement was reduced by a factor of 2, providing a tighter confidence interval in the final results.

Helmreich, Grant [ORNL] (ORCID:0000000330464394)↗

Development of uncertainty-aware equation-of-state models: Application to copper

Sophisticated hydrodynamic codes are commonly used to understand and predict events relevant to natural and applied sciences. The degree to which these simulations reflect reality, however, is dependent on how well we understand the materials and underlying physics involved. These research communities need material models that communicate the uncertainty in the physical properties, which at their basest form comes from the uncertainty in the underlying experimental measurements. Additionally, we have constructed a new framework for using both experimental measurements and the associated experimental uncertainties to build equation-of-state models that reflect not only current best measurements but also the accuracy of those measurements. This method had been used to construct an ensemble of equation-of-state models for copper that communicates the experimental uncertainties in the data through the equation-of-state model, which is available for application in any simulation metric of interest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Bayesian uncertainty quantification of tristructural isotropic particle fuel silver release: Decomposing model inadequacy plus experimental noise and parametric uncertainties

Tristructural isotropic (TRISO) particle fuel is one of the most promising fuel concepts enabling high temperature and high burnup reactor operation. One dominant source of radioactivity released from the TRISO particles is silver (Ag), which is subject to a high release fraction and long decay life compared to other fission products. Previous modeling efforts using the fuel performance code BISON indicated nonnegligible uncertainties in modeling the diffusion process of fission products in TRISO compared to the Advanced Gas Reactor experiments. The overall uncertainties observed when modeling the fission product diffusion can result from uncertainties in model parameters, noisy experimental measurements, and deficiencies in the developed models. The three types of underlying uncertainties have not yet been properly quantified in open literature. Here, this paper presents the Bayesian uncertainty quantification (UQ) using massively parallelizable Markov chain Monte Carlo samplers. The uncertainties due to model parameters, model inadequacy, and experimental measurement noise are quantified, with the σ term used to represent the sum of the model inadequacy and measurement noise uncertainties. It is worth noting that this is the first time the σ term is inferred for nuclear fuel experiments, as compared to using prescribed values for uncertainty quantification in previous work. The parallelizable Markov chain Monte Carlo samplers efficiently infer the model parameters and the σ term, giving insight into physical parameters like diffusion coefficients and the combined model discrepancy and measurement noise. A subsequent forward uncertainty quantification (UQ) is also performed based on the calibration results to generate more accurate predictions of the Ag release. The model inadequacy plus experimental noise is the most dominant source of uncertainty compared to the parametric uncertainty. All the UQ analyses presented in this work are based on the second series of the irradiation experiments in the Advanced Gas Reactor program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Verification and Validation Tests of Gamma Library of MC2-3 for Coupled Neutron and Gamma Heating Calculation

For the accurate assessment of the heat generation rate in fast reactors, the gamma library of MC2 -3 and the MC2 -3 + GAMSOR procedure employing the coupled neutron and gamma heating calculation has been thoroughly verified against Monte Carlo results and validated using the ZPPR-15D gamma dose measurement data. NJOY outputs are post-processed in a consistent way with the NJOY procedure to avoid any missing data or double counting of data. Prompt heating for 379 out of 391 isotopes in the gamma library was verified against MCNP6.2 to within 1% relative error in total heating for most isotopes. For both a simple one-dimensional slab problem representing a sodium cooled fast reactor and the Experimental Breeder Reactor II (EBR-II) benchmark problem, the root-mean-square values of assembly power error were less than 0.5% for fuel assemblies, ~1% in blankets and ~1 to ~3% in reflectors compared to MCNP6.2 results. The most plausible cause for the 3% error in a reflector assembly is believed to be the error in the multigroup neutron cross sections for the reflector assembly. For validation, gamma doses measured with thermoluminiscent dosimeters (TLDs) in the ZPPR-15D experiment were calculated using GAMSOR. Due to the uncertainty in the TLD measurement with regards to the energy deposition of photons and neutrons, the validation data leads to a 12.7% uncertainty on the experimental measurement. With this uncertainty bound, the calculated doses all fell within one standard deviation of the measured value. Combined with the accurate calculation of reaction rate distributions and neutron spectrum measurements, these results indicate good agreement for the neutron and gamma heating calculations that were performed.

coupled neutron and gamma heating↗

Uncertainties and Limitations of Experimental Thrust and Pressure Gain Measurements in a Rotating Detonation Combustor

Experimentally measuring the pressure gain through the method of equivalent available pressure is prone to many experimental uncertainties. This study performs a detailed uncertainty analysis of the thrust and pressure gain measurements utilizing data from a H2/air operated rotating detonation combustor with an axial air inlet and a 50% exit constriction. The measured (negative) pressure gain values agree with the results in literature for similar inlet-to-exit area ratios. Specific considerations are given to the uncertainty in thrust measurement introduced by the base drag correction on the inner-body. The assumed unity Mach number utilized in the equivalent available pressure methodology is evaluated experimentally with two different methods using time-averaged measurements at the exhaust plane. A definitive demonstration of gain will be challenging given the assessed uncertainties, but recommendations are given to increase the precision of the equivalent available pressure methodology to estimate pressure gain.

33 ADVANCED PROPULSION SYSTEMS↗

First Application of Mass Measurements with the Rare-RI Ring Reveals the Solar r -Process Abundance Trend at A = 122 and A = 123

The Rare-RI Ring (R3) is a recently commissioned cyclotronlike storage ring mass spectrometer dedicated to mass measurements of exotic nuclei far from stability at Radioactive Isotope Beam Factory (RIBF) in RIKEN. The first application of mass measurement using the R3 mass spectrometer at RIBF is reported. Rare isotopes produced at RIBF— 127 Sn, 126 In, 125 Cd, 124 Ag, 123 Pd—were injected in R3. Masses of 126 In, 125 Cd, and 123 Pd were measured whereby the mass uncertainty of 123 Pd was improved. This is the first reported measurement with a new storage ring mass spectrometry technique realized at a heavy-ion cyclotron and employing individual injection of the preidentified rare nuclei. The latter is essential for the future mass measurements of the rarest isotopes produced at RIBF. The impact of the new 123 Pd result on the solar r-process abundances in a neutron star merger event is investigated by performing reaction network calculations of 20 trajectories with varying electron fraction Y e . It is found that the neutron capture cross section on 123 Pd increases by a factor of 2.2 and β-delayed neutron emission probability, P 1n , of 123 Rh increases by 14%. The neutron capture cross section on 122 Pd decreases by a factor of 2.6 leading to pileup of material at A = 122, thus reproducing the trend of the solar r-process abundances. The trend of the two-neutron separation energies (S 2n ) was investigated for the Pd isotopic chain. The new mass measurement with improved uncertainty excludes large changes of the S 2n value at N = 77. Finally, such large increase of the S 2n values before N = 82 was proposed as an alternative to the quenching of the N = 82 shell gap to reproduce r-process abundances in the mass region of A = 112 – 124.

79 ASTRONOMY AND ASTROPHYSICS↗

Report to NCSP on FY21 DANCE and NEUANCE measurements of 233 U(n, γ)

In order to complete the statistics needed above 10 keV after the experiment performed in December 2020, a production measurement of the 233 U capture cross section, using the thick target (~20 mg) was proposed for the CY21 runcycle. Through collaboration with the DANCE experimental team, we arranged for the NEUANCE array to stay in place in the CY21 run cycle until the 233 U measurement was complete in June-July 2021, further reducing systematic uncertainties in the measurement. The measurement was performed over 10 days with the 20 mg sample, and the 10 mg sample was placed in the beam for 1 day. The rest of the beam time was used to measure radioactive γ sources for energy calibration, and background measurements and tests to define the 233 U windows required during the data taking. The NEUANCE detector placed inside the DANCE cavity is shown.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Demonstrate new plasticity models for doped UO 2 that capture dislocation mechanisms

In light water reactors, fuel vendors are investigating the use of dopants to modify the properties of UO 2 pellets, with the goal of improving pellet-cladding mechanical interactions during operation. Dopants are expected to ‘soften’ the pellets; that is, the doped pellets have higher plastic deformation than conventional UO 2 . This leads to a reduction in the severity of mechanical pellet-cladding interactions, helping to reduce the hoop strain on the cladding. By minimizing the strain exerted by the pellet on the cladding, it is anticipated that cladding performance under accident conditions can be enhanced (i.e., lowering the risk of burst during a LOCA). Dopants such as chromium (Cr) promote grain growth during pellet fabrication, leading to larger grains; therefore, understanding the link between chemistry, microstructure and mechanical deformation (enhanced creep rates) behavior of UO 2 is critical to helping operators further substantiate the benefits of doping UO 2 . Historically, the nuclear energy industry has relied on empirical models to make assessments of performance. Compared to empirical models, mechanistic physics-based models provide benefits, such as, fewer data points for validation and better extrapolation where experimental data is scarce or non-existent. In this report, Bayesian inference techniques have been applied to a previously developed lower length-scale-informed diffusional creep model. The objective is to i) infer lower-length-scale parameter distributions from available experiment and then ii) determine the uncertainties in the measurable quantity (in this case creep rates) after propagating the inferred lower length scale parameter uncertainties. The approach requires many evaluations of the model, which becomes computationally insurmountable; therefore, a neural-network model is trained to data obtained by sampling the full model over the most important parameters. This neural-network is then used in the Bayesian inference approach to determine probability distributions in the parameter values that represent the uncertainty in the model given what is known from the experiments (posterior). A significant reduction compared to conservative initial (prior) uncertainties is achieved through inference against the experimental data, demonstrating the efficacy of this approach. Furthermore, by accounting for uncertainties in the experimental conditions and sample non-stoichiometry, it is possible to resolve apparent discrepancies in experimental measurements within a self-consistent grain boundary (Coble) creep model that is sensitive to chemistry. This work has been written up and submitted to Nuclear Technology for a special issue on accelerated fuel qualification (AFQ). This uncertainty quantification (UQ) work not only improves the diffusional model, while accounting for uncertainty, but also establishes a framework which can readily be applied to the mechanistic models of dislocation deformation developed in this study. The most likely values from the Bayesian analysis are incorporated into our UO 2 diffusional creep model and a lower length scale-informed irradiation UO 2 creep mechanistic model to generate a dataset. This dataset has been provided to our INL collaborators for training an artificial neural network surrogate model, which will be implemented in the BISON fuel performance code to assess how the results differ from those currently obtained using a fully empirical model and that of using the nominal (uncalibrated) atomic scale parameters in our mechanistic model. Plastic deformation (creep and glide) in UO 2 is a complex phenomenon, governed by multiple underlying processes such as local defect concentrations, applied stresses, and microstructural characteristics. Consequently, there is a need for a meso-scale model with polycrystalline resolution capable of extrapolating to large grain sizes applicable to doped UO 2 , where data is limited and the model can help bridge the knowledge gap. By integrating atomistic data into the polycrystal LApx code, it becomes possible to predict dislocation climb and glide plasticity that simple analytical models cannot accurately represent. The application of atomic-scale data within LApx demonstrated the importance of climb and glide mechanisms in reproducing high-stress UO 2 behavior. Behaviors such as this are crucial to capture and implement in BISON, as parts of the fuel pellet can reach temperatures where glide can occur before pellet cracking. This model which captures dislocation based mechanisms for UO 2 is then used to stand up the doped model accounting for larger grain sizes. It was found that larger grain sizes can lead to enhanced deformation rates in the glide regime, and therefore can help with the pellet cladding mechanical interaction. Therefore if the fuel pellet reaches conditions (stress/temperature) where glide is active, the enhanced creep rates for larger grains in the glide regime (doped UO 2 ) can help with pellet cladding mechanical interactions. Plastic deformation in UO 2 involves multiple mechanisms, including diffusional creep, dislocation climb, and glide. This milestone contains two parts: (1) UQ of a pre-existing lower length scale informed mechanistic diffusional creep model, and (2) development of a new LApx based model for dislocation-mediated creep mechanisms in UO 2 , with application to large-grain doped UO 2 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Count Every Trip: Finding the Uncertainty in Energy Estimates Made from Inferred Travel Modes

To properly inform transport policy and infrastructure changes, transportation related metrics need both measured values and uncertainties of those values. Travel monitoring smartphone apps can record people's travel behavior, but trip data quality is limited by sensor errors, user labeling rates and the accuracy of inference algorithms used for travel diary creation. We discuss the use of phone app recorded travel diary data to estimate energy consumption, and propose the use of propagation of variance to find error bars for such estimates. We define energy consumption for one trip as trip length times the energy intensity per distance unit of the travel mode used. We characterize trip length errors with relative error and inferred trip mode errors with confusion matrix columns. The resulting variances of each measurement are then propagated to the final calculated energy consumption. We tested our uncertainty methods on a dataset that used phone app data combined with prompted recall, consisting of 92,234 labeled trips for over 500,000 miles. Accounting for uncertainty using expected energy intensities and variance propagation gives a dataset-wide aggregate energy consumption percent error of about 9%, within one standard deviation from the truth. Future work could involve applying similar methods to other travel diary based metrics.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗

Count Every Trip: Finding the Uncertainty in Energy Estimates Made from Inferred Travel Modes

To properly inform transport policy and infrastructure changes, transportation related metrics need both measured values and uncertainties of those values. Travel monitoring smartphone apps can record people's travel behavior, but trip data quality is limited by sensor errors, user labeling rates and the accuracy of inference algorithms used for travel diary creation. We discuss the use of phone app recorded travel diary data to estimate energy consumption, and propose the use of propagation of variance to find error bars for such estimates. We define energy consumption for one trip as trip length times the energy intensity per distance unit of the travel mode used. We characterize trip length errors with relative error and inferred trip mode errors with confusion matrix columns. The resulting variances of each measurement are then propagated to the final calculated energy consumption. We tested our uncertainty methods on a dataset that used phone app data combined with prompted recall, consisting of 92,234 labeled trips for over 500,000 miles. Accounting for uncertainty using expected energy intensities and variance propagation gives a dataset-wide aggregate energy consumption percent error of about 9%, within one standard deviation from the truth. Future work could involve applying similar methods to other travel diary based metrics.

ADVANCED PROPULSION SYSTEMS↗

Measurement of the muon anomalous precession frequency in runs 2 \& 3 of the Muon $g-2$ Experiment at Fermilab

This dissertation presents a measurement of the muon anomalous precession frequency for the Runs 2 \& 3 data of the E989 Muon $g-2$ Experiment at Fermilab. The muon anomalous precession frequency is one of two key inputs, the other being the magnetic field, used to precisely determine the muon magnetic anomaly, $a_{\mu}$. In April 2021, the E989 collaboration reported its first measurement of $a_{\mu}$ to an unprecedented precision of 460 parts-per-billion (ppb). This result is in agreement with the previous measurement performed by the E821 collaboration at Brookhaven National Laboratory, and the combined experimental value is in tension with the Standard Model prediction at 4.2$\sigma$, a possible hint of new physics. The first result from E989 was based on the Run-1 data, which was collected in 2018 and comprises 6\% of the experiment’s target statistics; the Run-1 result was statistics-limited. The Runs 2 \& 3 data were collected in 2019-2020 and constitute a four-fold increase i n statistics compared to Run-1 and consequently, a factor of two reduction in the measurement’s statistical uncertainty. This reduced statistical uncertainty, as well as continued understanding of systematic effects, will result in an even more precise measurement of $a_{\mu}$ and will help clarify the observed tension between theory and experiment. The precession frequency analysis presented in this dissertation includes a number of improvements compared to Boston University's Run-1 analysis: the implementation of a more robust pileup-subtraction procedure, the implementation of a kernel ratio method, the adoption of the statistically optimal asymmetry-weighted method, and investigations that led to an improved understanding of an outstanding residual slow effect. This dissertation motivates a measurement of the muon magnetic anomaly, describes the experimental principle, gives an overview of the E989 experiment, and presents a precession frequency analysis with full systematic unc ertainty evaluation for the Runs 2 \& 3 data. The combined precession frequency measurement, using the ratio asymmetry-weighted method, has a statistical uncertainty of 201 ppb and a systematic uncertainty of 25 ppb, constituting the most precise determination of the muon anomalous precision frequency to date.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Estimating Travel Energy Consumption Uncertainty Based on Inferred Travel Mode and Sensed Travel Length

To properly inform transport policy and infrastructure changes, transportation related metrics need both measured values and uncertainties of those values. Travel monitoring smartphone apps can record people's travel behavior, but trip data quality is limited by sensor errors, user labeling rates and the accuracy of inference algorithms used for travel diary creation. We discuss the use of phone app recorded travel diary data to estimate energy consumption, and propose the use of propagation of variance to find error bars for such estimates. We define energy consumption for one trip as trip length times the energy intensity per distance unit of the travel mode used. We characterize trip length errors with relative error and inferred trip mode errors with confusion matrix columns. The resulting variances of each measurement are then propagated to the final calculated energy consumption. We tested our uncertainty methods on a dataset that used phone app data combined with prompted recall, consisting of 92,234 labeled trips for over 500,000 miles. Accounting for uncertainty using expected energy intensities and variance propagation gives a dataset-wide aggregate energy consumption percent error of about 8%, within one standard deviation from the truth. Future work could involve applying similar methods to other travel diary based metrics.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

Lattice Relaxations in Bixbyite‐Structured Rare‐Earth Sesquioxides

This report examines atomic relaxations in rare‐earth sesquioxides with the cubic bixbyite crystal structure. In particular, the experimentally determined unit cell atom positions in bixbyite compounds are compared to “ideal” bixbyite atom positions, where the concept of ideality is based on similarities between the bixbyite and fluorite crystal structures. Analyses indicate that all rare‐earth sesquioxide compounds deviate from ideality in similar ways and that there is a trend wherein the magnitudes of these atomic deviations decrease with increasing cationic size. The deviations from an ideal, fluorite‐like structure produce highly distorted coordination polyhedra and variations in metal‐oxygen bond lengths. A modified bond valence sum analysis revealed that the first nearest neighbor cation‐anion bond length variations lead to large (20%) variations in cation‐anion bond strength. This report also provides a qualitative analysis regarding the accuracy of atomic relaxed deviation parameters, based on x‐ray diffraction measurements. The analysis indicates that uncertainties in the accuracy of measured oxygen relaxed deviation parameters in bixbyite sesquioxides are likely much greater than the published uncertainties.

36 MATERIALS SCIENCE↗

Updates to the Regional Seismic Travel Time (RSTT) Model: 2. Path-dependent Travel-time Uncertainty

Abstract The regional seismic travel time (RSTT) model and software were developed to improve travel-time prediction accuracy by accounting for three-dimensional crust and upper mantle structure. Travel-time uncertainty estimates are used in the process of associating seismic phases to events and to accurately calculate location uncertainty bounds (i.e. event location error ellipses). We improve on the current distance-dependent uncertainty parameterization for RSTT using a random effects model to estimate slowness (inverse velocity) uncertainty as a mean squared error for each model parameter. The random effects model separates the error between observed slowness and model predicted slowness into bias and random components. The path-specific travel-time uncertainty is calculated by integrating these mean squared errors along a seismic-phase ray path. We demonstrate that event location error ellipses computed for a 90% coverage ellipse metric (used by the Comprehensive Nuclear-Test-Ban Treaty Organization International Data Centre (IDC)), and using the path-specific travel-time uncertainty approach, are more representative (median 82.5% ellipse percentage) of true location error than error ellipses computed using distance-dependent travel-time uncertainties (median 70.1%). We also demonstrate measurable improvement in location uncertainties using the RSTT method compared to the current station correction approach used at the IDC (median 74.3% coverage ellipse).

58 GEOSCIENCES↗

Measurements of the thermal and ionization state of the intergalactic medium during the cosmic afternoon

We perform the first measurement of the thermal and ionization state of the intergalactic medium (IGM) across 0.9 < z < 1.5 using 301 Ly α absorption lines fitted from 12 archival Hubble Space Telescope Space Telescope Imaging Spectrograph quasar spectra. We employ the machine-learning-based inference method that uses joint Doppler parameter–column density (⁠b-N HI ⁠) distributions obtained from Ly α forest decomposition. Our results show that the Γ HI photoionization rates, ⁠, agree with recent ultraviolet background synthesis models, with log(Γ HI /s -1 ) = $-11.79^{+0.18}_{-0.15}$, $-11.98^{+0.09}_{-0.09}$⁠, and $-12.32^{+0.10}_{-0.12}$⁠, at z = 1.4, 1.2, and 1, respectively. We obtain the IGM temperature at the mean density, T 0 ⁠, and the adiabatic index, γ⁠, as [log(T 0 /K), γ] = $[4.13^{+0.12}_{-0.10}, 1.34^{+0.10}_{-0.15}]$, $[3.79^{+0.11}_{-0.11}, 1.70^{+0.09}_{-0.09}]$, and $[4.12^{+0.15}_{-0.25}, 1.34^{+0.21}_{-0.26}]$ at z = 1.4⁠, 1.2, and 1. Our measurements of T 0 at z = 1.4 and 1.2 are consistent with the trend predicted from previous z < 3 temperature measurements and theoretical expectations, where the IGM cools down after $He\tiny{II}$ reionization in the absence of any non-standard heating. However, our T 0 measurement at z = 1 unexpectedly high IGM temperature. Given the relatively large uncertainty in these measurements, where σ T$_0$ ~ 5000 K, mostly emanating from the limited size of our data set, we cannot conclude whether the IGM cools down as expected. Lastly, we generate mock data sets to test the constraining power of future measurement with larger data sets. The results demonstrate that, with redshift path-length Δz ~ 2 for each redshift bin, three times the current data set, we can constrain the T 0 of IGM within 1500 K, which would be sufficient to constrain the IGM thermal history at z < 1.5 conclusively.

79 ASTRONOMY AND ASTROPHYSICS↗