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DOE OSTI2013

Spatial consistency of Chinook salmon redd distribution within and among years in the Cowlitz River, Washington

We investigated the spawning patterns of Chinook salmon Oncorhynchus tshawytscha on the lower Cowlitz River, Washington (USA) using a unique set of fine- and coarse-scale 35 temporal and spatial data collected during bi-weekly aerial surveys conducted in 1991-2009 (500 m to 28 km resolution) and 2008-2009 (100-500 m resolution). Redd locations were mapped from a helicopter during 2008 and 2009 with a hand-held global positioning system (GPS) synchronized with in-flight audio recordings. We examined spatial patterns of Chinook salmon redd reoccupation among and within years in relation to segment-scale geomorphic features. Chinook salmon spawned in the same sections each year with little variation among years. On a coarse scale, five years (1993, 1998, 2000, 2002, and 2009) were compared for reoccupation. Redd locations were highly correlated among years resulting in a minimum correlation coefficient of 0.90 (adjusted P = 0.002). Comparisons on a fine scale (500 m) between 2008 and 2009 also revealed a high degree of consistency among redd locations (P < 0.001). On a finer temporal scale, we observed that salmon spawned in the same sections during the first and last week (2008: P < 0.02; and 2009: P < 0.001). Redds were clustered in both 2008 and 2009 (P < 0.001). Regression analysis with a generalized linear model at the 500-m scale indicated that river kilometer and channel bifurcation were positively associated with redd density, whereas sinuosity was negatively associated with redd density. Collecting data on specific redd locations with a GPS during aerial surveys was logistically feasible and cost effective and greatly enhanced the spatial precision of Chinook salmon spawning surveys.

habitat management↗

DOE OSTI2021

Half-life of 67 Cu

The half-life of 67 Cu was determined through serial gamma-ray spectrometry measurements of the dominant gamma emission (E γ : 184.6 keV; branching ratio: 48.7%) produced following β- decay. Data were collected consecutively for 1000 s per measurement, with a total of 3063 measurements over the duration of 36 days. The incidence rate for the 184.6 keV gamma-ray was determined from the spectral peak area and duration of each measurement. This rate was then corrected to account for detector dead-time, radioactive decay during each acquisition and drift in the computer clock in comparison to NIST nuclear clock. Least-squares regression analysis was performed to determine the half-life of 67 Cu. The result was 61.761 ± 0.004 h, which is the highest precision measurement to date, and marks a 24-fold precision improvement over the current Nuclear Data Sheets value.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Recent evolution of risk analyses in atomic bomb survivor studies: new methods and applications

Abstract Several decades ago a dramatic leap forward occurred in the development and application of statistical methods for modeling radiation risk at the Radiation Effects Research Foundation (RERF). Poisson regression analysis for grouped person-year cohort data and the linear excess relative risk model were introduced, and subsequently a devoted software system, Epicure® (https://www.hirosoft.com), was developed by researchers at RERF and at the U.S. National Cancer Institute. Numerous advancements in understanding radiation effects on humans were made possible with these methods, which are still the state-of-the-art for risk assessment at RERF and have remained part of the standard toolbox for radiation—and other environmental—epidemiological studies worldwide. Nevertheless, as our understanding of radiation risk has increased, so have the breadth and depth of questions that require answers based on emerging data that are not amenable to these conventional methods. This overview briefly recounts the conventional methods and then describes our recent diversification into the use or development of new statistical approaches to meet the challenges of burgeoning biological data and emerging mechanistic information. We briefly discuss the development and application of new methods, current and planned, that are part of the RERF Statistics Department’s role in supporting institution-wide research, especially in our collaborations involving the Life Span Study, Adult Health Study, and First-generation Offspring Clinical Study. Some approaches to modeling and assessing radiation risk with newer methods mentioned herein have already been published, while some are still in development or are only beginning at the proposal stage.

Oncology↗

DOE OSTI2022

Association of optical, ultraviolet, and soft X-ray excess emissions in AGNs

Soft X-ray emission (0.5–2.0 keV) plays a pivotal role in regulating the optical and ultraviolet (UV) emission in the active galactic nuclei (AGNs). We collected a sample of 1811 AGNs from the SDSS database and obtained various parameters of Balmer lines, optical continuum, Mg ii line & UV continuum and studied their dependencies on soft X-ray luminosity. Based on the linear regression analysis, we found that FWHM$_{\rm {Mg\,\,\small {II}}}$ ∝ FWHM$_{\text{H}\beta }^{0.554}$ suggesting that UV emission is arising from a region relatively outside the broad-line region (BLR) associated to the Hβ emission and found a strong correlation between optical and UV luminosities (L$_{\rm {Mg\,\,\small {II}}}$ ∝ $L_{\rm {H}\beta }^{0.822}$). It was noticed that the dependency of optical continuum luminosities on soft excess changes with the redshift (L X ∝ L$^{0.596}_{5100\, \mathring{\rm A}}$ for z < 0.5 and L X ∝ L$^{0.429}_{5100\, \mathring{\rm A}}$ for z > 0.5). The full width at half-maximum components of Hβ and Mg II core components were found to be virialized and is not affected by the soft excess emission whereas the wings of Mg II display a dependency. We estimated a relation viz. L X ∝L$^{0.520}_{3000\, \mathring{\rm A}}$ FWHM$^{0.525}_{\rm {Mg\,\,\small {II}}}$ and found to be well in agreement with a proposed physical scenario. All the derived relations were used to understand the intermodulating association of the BLR and disc in the AGNs.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Mass variance from archival X-ray properties of Dark Energy Survey Year-1 galaxy clusters

ABSTRACT Using archival X-ray observations and a lognormal population model, we estimate constraints on the intrinsic scatter in halo mass at fixed optical richness for a galaxy cluster sample identified in Dark Energy Survey Year-One (DES-Y1) data with the redMaPPer algorithm. We examine the scaling behaviour of X-ray temperatures, TX, with optical richness, λRM, for clusters in the redshift range 0.2 < z < 0.7. X-ray temperatures are obtained from Chandra and XMM observations for 58 and 110 redMaPPer systems, respectively. Despite non-uniform sky coverage, the TX measurements are $\gt 50{{\ \rm per\ cent}}$ complete for clusters with λRM > 130. Regression analysis on the two samples produces consistent posterior scaling parameters, from which we derive a combined constraint on the residual scatter, $\sigma _{\ln T \, |\, \lambda }= 0.275 \pm 0.019$. Joined with constraints for TX scaling with halo mass from the Weighing the Giants program and richness–temperature covariance estimates from the LoCuSS sample, we derive the richness-conditioned scatter in mass, $\sigma _{\ln M \, |\, \lambda }= 0.30 \pm 0.04\, _{({\rm stat})} \pm 0.09\, _{({\rm sys})}$, at an optical richness of approximately 100. Uncertainties in external parameters, particularly the slope and variance of the TX–mass relation and the covariance of TX and λRM at fixed mass, dominate the systematic error. The $95{{\ \rm per\ cent}}$ confidence region from joint sample analysis is relatively broad, $\sigma _{\ln M \, |\, \lambda }\in [0.14, \, 0.55]$, or a factor 10 in variance.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Reconstruction of beam parameters and betatron radiation spectra measured with a Compton spectrometer

The photon flux resulting from high-energy electron beam interactions with high-field systems, such as those found in the upcoming FACET-II experiments at the SLAC National Accelerator Laboratory, yields deep insight into the electron beam’s underlying dynamics during the interaction. However, extracting this information is an intricate process. To demonstrate how to approach this challenge using modern methods, this paper utilizes simulated data that models plasma wakefield acceleration-derived betatron radiation in experiments to determine reliable methods of reconstructing key beam and beam-plasma interaction properties. For betatron radiation measurements, translating the observed 200⁢ keV to 30⁢ MeV photon double-differential energy-angle spectra obtained from an advanced Compton spectrometer requires testing multiple methods to optimize the pipeline from its response to incident electron beam information. The paper compares maximum likelihood estimation and machine learning to refine the translation of photon spectra into precise electron beam metrics, such as spot size, energy, and emittance, enhancing the understanding of beam behavior within these dense, high-field environments. We also introduce machine learning and the expected maximization algorithm to reconstruct the primary photon spectrum, employing a multilayer neural network for regression analysis of the energy and angle spectra. With appropriate modifications, the advanced methods reproduce relevant incident beam parameters with high accuracy, even for beam sizes in the <10 μ⁢m range. This capacity is critical to understanding intense beam propagation and its optimization in plasma.

Beam code development & simulation techniques↗

DOE OSTI2023

Tuning the magnetic properties of the CrMnFeCoNi Cantor alloy

Magnetic properties of more than 20 Cantor alloy samples of varying composition were investigated over a temperature range of 5 K to 300 K and in fields of up to 70 kOe using magnetometry and muon spin relaxation. Two transitions are identified: a spin-glass-like transition that appears between 55K and 190K, depending on composition, and a ferrimagnetic transition that occurs at approximately 43K in multiple samples with widely varying compositions. The magnetic signatures at 43K are remarkably insensitive to chemical composition. A modified Curie-Weiss model was used to fit the susceptibility data and to extract the net effective magnetic moment for each sample. The resulting values for the net effective moment were either diminished with increasing Cr or Mn concentrations or enhanced with decreasing Fe, Co, or Ni concentrations. Beyond a sufficiently large effective moment, the magnetic ground state transitions from ferrimagnetism to ferromagnetism. The effective magnetic moments, together with the corresponding compositions, are used in a global linear regression analysis to extract element-specific effective magnetic moments, which are compared to the values obtained by ab initio based density functional theory calculations. Finally, these moments provide the information necessary to controllably tune the magnetic properties of Cantor alloy variants.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Leveraging AMI data for distribution system model calibration and situational awareness

The many new distributed energy resources being installed at the distribution system level require increased visibility into system operations that will be enabled by distribution system state estimation (DSSE) and situational awareness applications. Reliable and accurate DSSE requires both robust methods for managing the big data provided by smart meters and quality distribution system models. This paper presents intelligent methods for detecting and dealing with missing or inaccurate smart meter data, as well as the ways to process the data for different applications. It also presents an efficient and flexible parameter estimation method based on the voltage drop equation and regression analysis to enhance distribution system model accuracy. Finally, it presents a 3-D graphical user interface for advanced visualization of the system state and events. Moreover, we demonstrate this paper for a university distribution network with the state-of-the-art real-time and historical smart meter data infrastructure.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2016

Hotspots of uncertainty in land-use and land-cover change projections: A global-scale model comparison

Model-based global projections of future land use and land cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socio-economic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g. boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process as well as improving the allocation mechanisms of LULC change models remain important challenges. Furthermore, current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Clusters of COVID ‐19 in long‐term care hospitals and facilities in Japan from 16 January to 9 May 2020

Aim To clarify the association of cluster number and size of coronavirus disease 2019 (COVID‐19) in long‐term care (LTC) hospitals/facilities, general medical/welfare facilities and non‐medical/welfare facilities with morbidity and mortality in 47 prefectures during 16 January to 9 May 2020 in Japan. Methods Information on COVID‐19 clusters ( n ≥2), and morbidity and mortality of COVID‐19 was collected. Results A total of 381 clusters with 3786 infected cases were collected, accounting for 23.9% of 15 852 cumulated cases on 9 May 2020. Although the cluster number (/10 7 subjects) in LTC hospitals/facilities was significantly smaller compared with those in the other two groups, the cluster size in LTC hospitals/facilities was significantly larger than that in non‐medical/welfare facilities. Cluster numbers in general medical/welfare facilities and in non‐medical/welfare facilities were significantly positively correlated with morbidity (/10 5 ), indicating relatively early identification of clusters in these facilities. Unlike in these facilities, cluster size in LTC hospitals/facilities was significantly positively correlated with morbidity, indicating that clusters in LTC hospitals/facilities were finally identified after already having grown to a large size in areas where infection was prevalent. Multivariate logistic regression analysis showed that both cluster number and cluster size only in LTC hospitals/facilities were independently associated with higher mortality (≥median 0.64/10 5 subjects) after adjustment. Conclusions Preventive efforts against COVID‐19 outbreaks even at the early phase of the epidemic are critically important in LTC hospitals/facilities, as both the larger number and size of clusters only in LTC hospitals/facilities were independently linked to higher mortality in prefectures in Japan. Geriatr Gerontol Int 2020; 20: 715–719 .

Iritani, Osamu↗

DOE OSTI2022

Thermophysical modeling of raw glaze liquidus temperature and viscosity

Raw glazes, which do not contain pre-melted glass frits, are widely used due to their low cost. The natural variability of the mineral compositions used in raw glazes affects their viscosity during firing. Molten glaze viscosity plays an important role in determining the final surface quality; therefore, it is important to determine how raw glaze composition and firing conditions affect viscosity. Thermophysical modeling provides a way to evaluate the liquidus temperature and viscosity of molten glazes as a function of composition and oxygen activity. Equilibrium phase volume fraction and composition of 242 raw glaze recipes were evaluated under oxidizing and reducing conditions. Undissolved or precipitation of solid phases explain the secondary flux transition from anti-fluxing to fluxing near the liquidus temperature. The liquidus temperature and viscosity of iron glazes decrease as a function of increasing iron content under a reducing atmosphere. The empirical probability distribution of molten glaze viscosity follows a lognormal distribution, with lead glazes having significantly lower viscosity compared with glazes without lead. Here, the peak firing temperature viscosity of lead-free glazes is near the working point of glass. Multiple linear regression analysis shows that the peak firing temperature viscosity and liquidus temperature significantly predict the viscosity factor.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Experimental Investigation of Electric Contact Resistance in Spark Plasma Sintering Tooling Setup

An experimental investigation on electric contact resistance in the tooling utilized in spark plasma sintering (SPS) is conducted. Two different SPS regimes are operated without the presence of processed powder to obtain the punch–punch (horizontal) and punch–die (vertical) contact resistance assessments separately. The processing temperature and applied pressure are considered to be the main factors that affect the contact resistance. These effects are analyzed by performing experiments at a maximum temperature of 1600°C with constant heating rate of 100°C/min. The applied pressure is ranging from 20 to 60 MPa and a 1 min holding time‐step is used to ensure stable measurements. It is shown that the contact resistance goes down as the temperature ramps up. An increase in the pressure leads to a decrease in the contact resistance. The mechanisms that cause these variations in the contact resistance are discussed. The dependence of assessed contact resistance of the utilized SPS system on the processing temperature and applied pressure is analytically described based on the regression analysis of the collected experimental data. A finite‐element simulation based on the obtained experimental results evidences that the electric contact resistance dominates the temperature evolution. The obtained results are of significant importance for modeling and optimization of SPS processes.

Wei, Xialu↗

DOE OSTI2018

Oxidation effects on spark plasma sintering of molybdenum nanopowders

Surface-oxidized molybdenum nanopowders are compacted by spark plasma sintering (SPS). The oxide impurity behavior is analyzed under various sintering temperatures. The densification mechanism of the nanopowders with a melted oxide phase is identified in situ by regression analysis of the experimental data on the temperature-dependent porosity change and on the SPS multistep pressure dilatometry. To increase the density of the compacted pellets, the nanopowders with the oxide phase are consolidated by SPS using the two in situ oxide removal methods: carbothermic reduction and particle surface cleaning by the electric current flow through the powders. Finally, the advantages and disadvantages of these methods in terms of the density, grain size, and mechanical properties of the final products are discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Modeling of Supercritical CO2 Shell-and-Tube Heat Exchangers Under Extreme Conditions. Part I: Correlation Development

Abstract High-temperature supercritical CO2 Brayton cycles are promising possibilities for future stationary power generation and hybrid electric propulsion applications. Heat exchangers are critical components in supercritical CO2 thermal cycles and require accurate correlations and comprehensive performance modeling under extreme temperatures and pressures. In this paper (Part I), new Colburn and friction factor correlations are developed to quantify shell-side heat transfer and friction characteristics of flow within heat exchangers in the shell-and-tube configuration. Using experimental and computational fluid dynamics (CFD) data sets from existing literature, multivariate regression analysis is conducted to achieve correlations that capture the effect of multiple critical geometric parameters. These correlations offer superior accuracy and versatility as compared to previous studies and predict the thermohydraulic performance of about 90% of the existing experimental and CFD data within ±15%. Supplementary thermohydraulic performance data are acquired from CFD simulations with supercritical CO2 as working fluid to validate the developed correlations and demonstrate its capability to be applied to supercrtical CO2 heat exchangers.

Engineering↗

DOE OSTI2018

Comparison of Equivalence Ratio Transients on Combustion Instability in Single-Nozzle and Multi-Nozzle Combustors

Low-emissions gas turbine combustion, achieved through the use of lean, premixed fueling strategies, is susceptible to combustion instability. The driving mechanism for this instability arises from fluctuations of pressure, fuel/air flow rate, and heat release rate. If these fluctuations are relatively in-phase, the combustion system will evolve to a self-excited state. The self-excited instability frequency and amplitude depend mainly on the operating condition and the geometry of the combustor. In this study, we consider the onset and decay of self-excited instabilities, resulting from transients in fuel/air ratio, in both single-nozzle and multi-nozzle combustors. In particular, we examine the differences in the instability onset and decay processes between these two flame configurations, as most gas turbine combustors have multiple nozzles, but most gas turbine combustor experiments utilize a single-nozzle. A nonlinear logistic regression analysis is applied to study the timescales of the decay and onset transients. Variations in the equivalence ratio change the heat release rate distribution inside the combustor, which is captured using chemiluminescence imaging. The normalized Rayleigh index, which shows the spatial distribution of the instability driving, is calculated to analyze the driving strength in different regions of the flame. Comparisons between the single- and multi-nozzle flame transients, including both center and outer flames for the multi-nozzle combustor, suggest that both confinement from the wall and flame-flame interaction are crucial to determining flame dynamics as the equivalence ratio transient changes the heat release rate distribution near corner recirculation zone and flame shear layers.

Chen, Xiaoling↗

DOE OSTI2014

TU-F-18A-04: Use of An Image-Based Material-Decomposition Algorithm for Multi-Energy CT to Determine Basis Material Densities

Purpose: Published methods for image-based material decomposition with multi-energy CT images have required the assumption of volume conservation or accurate knowledge of the x-ray spectra and detector response. The purpose of this work was to develop an image-based material-decomposition algorithm that can overcome these limitations. Methods: An image-based material decomposition algorithm was developed that requires only mass conservation (rather than volume conservation). With this method, using multi-energy CT measurements made with n=4 energy bins, the mass density of each basis material and of the mixture can be determined without knowledge of the tube spectra and detector response. A digital phantom containing 12 samples of mixtures from water, calcium, iron, and iodine was used in the simulation (Siemens DRASIM). The calibration was performed by using pure materials at each energy bin. The accuracy of the technique was evaluated in noise-free and noisy data under the assumption of an ideal photon-counting detector. Results: Basis material densities can be estimated accurately by either theoretic calculation or calibration with known pure materials. The calibration approach requires no prior information about the spectra and detector response. Regression analysis of theoretical values versus estimated values results in excellent agreement for both noise-free and noisy data. For the calibration approach, the R-square values are 0.9960+/−0.0025 and 0.9476+/−0.0363 for noise-free and noisy data, respectively. Conclusion: From multi-energy CT images with n=4 energy bins, the developed image-based material decomposition method accurately estimated 4 basis material density (3 without k-edge and 1 with in the range of the simulated energy bins) even without any prior information about spectra and detector response. This method is applicable to mixtures of solutions and dissolvable materials, where volume conservation assumptions do not apply. CHM receives research support from NIH and Siemens Healthcare.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2014

TU-F-18A-05: An X-Ray Fluorescence Technique for Energy Calibration of Photon-Counting Detectors

Purpose: To investigate the feasibility of energy response calibration of a Si strip photon-counting detector by using the x-ray fluorescence technique. Methods: X-ray fluorescence was generated by using a pencil beam from a tungsten anode x-ray tube with 2 mm Al filtration. Spectra were acquired at 90° from the primary beam direction with an energy-resolved photon-counting detector based on Si strips. The distances from the source to target and the target to detector were approximately 19 and 11 cm, respectively. Four different materials, containing Ag, I, Ba, and Gd, were placed in small plastic aliquots with a diameter of approximately 0.7 cm for x-ray fluorescence measurements. Linear regression analysis was performed to derive the gain and offset values for the correlation between the measured fluorescence peak center and the known energies for materials. The energy resolution was derived from the full width at half maximum (FWHM) of the fluorescence peaks. In addition, the angular dependence of the recorded fluorescence spectra was studied at 30°, 60°, and 120°. Results: Strong fluorescence signals of all four target materials were recorded with the investigated geometry for the Si strip detector. The recorded pulse height was calibrated with respect to photon energy and the gain and offset values were calculated to be 7.0 mV/keV and −69.3 mV, respectively. Negligible variation in energy calibration was observed among the four energy thresholds. The variation among different pixels was estimated to be approximately 1 keV. The energy resolution of the detector was estimated to be 7.9% within the investigated energy range. Conclusion: The performance of a spectral imaging system using energy-resolved photon-counting detectors is very dependent on the energy calibration of the detector. The proposed x-ray fluorescence technique provides an accurate and efficient way to calibrate the energy response of a photon-counting detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2014

Characterization of energy response for photon-counting detectors using x-ray fluorescence

Purpose: To investigate the feasibility of characterizing a Si strip photon-counting detector using x-ray fluorescence. Methods: X-ray fluorescence was generated by using a pencil beam from a tungsten anode x-ray tube with 2 mm Al filtration. Spectra were acquired at 90° from the primary beam direction with an energy-resolved photon-counting detector based on an edge illuminated Si strip detector. The distances from the source to target and the target to detector were approximately 19 and 11 cm, respectively. Four different materials, containing silver (Ag), iodine (I), barium (Ba), and gadolinium (Gd), were placed in small plastic containers with a diameter of approximately 0.7 cm for x-ray fluorescence measurements. Linear regression analysis was performed to derive the gain and offset values for the correlation between the measured fluorescence peak center and the known fluorescence energies. The energy resolutions and charge-sharing fractions were also obtained from analytical fittings of the recorded fluorescence spectra. An analytical model, which employed four parameters that can be determined from the fluorescence calibration, was used to estimate the detector response function. Results: Strong fluorescence signals of all four target materials were recorded with the investigated geometry for the Si strip detector. The average gain and offset of all pixels for detector energy calibration were determined to be 6.95 mV/keV and −66.33 mV, respectively. The detector’s energy resolution remained at approximately 2.7 keV for low energies, and increased slightly at 45 keV. The average charge-sharing fraction was estimated to be 36% within the investigated energy range of 20–45 keV. The simulated detector output based on the proposed response function agreed well with the experimental measurement. Conclusions: The performance of a spectral imaging system using energy-resolved photon-counting detectors is very dependent on the energy calibration of the detector. The proposed x-ray fluorescence technique offers an accurate and efficient way to calibrate the energy response of a photon-counting detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗